5.8 GHz Microstrip Patch Antennas for Wireless Power Transfer: A Comprehensive Review of Design, Optimization, Applications, and Future Trends

Abstract

Wireless Power Transfer (WPT) has become a pivotal technology, enabling the battery-free operation of Internet of Things (IoT) and biomedical devices while supporting environmental sustainability. This review provides a comprehensive analysis of microstrip patch antennas (MPAs) operating at the 5.8 GHz Industrial, Scientific, and Medical (ISM) band, emphasizing their advantages over the more commonly used 2.4 GHz band. A detailed and systematic classification framework for MPA architectures is introduced, covering single-element, multi-band, ultra-wideband, array, MIMO, wearable, and rectenna systems. The review examines advanced optimization methodologies, including Defected Ground Structures (DGS), Electromagnetic Bandgap (EBG) structures, Metamaterials (MTM), Machine Learning (ML), and nanomaterials, each contributing to improvements in gain, bandwidth, efficiency, and device miniaturization. Unlike previous surveys, this work offers a performance-benchmarked classification specifically for 5.8 GHz MPAs and provides a quantitative assessment of key trade-offs, such as efficiency versus substrate cost. The review also advocates for a shift toward Power Conversion Efficiency (PCE)-centric co-design strategies. The analysis identifies critical research gaps, particularly the ongoing disparity between simulated and experimental performance. The review concludes by recommending multi-objective optimization, integrated antenna-rectifier co-design to maximize PCE, and the use of advanced materials and computational intelligence to advance next-generation, high-efficiency 5.8 GHz WPT systems.

1. Introduction

The proliferation of Internet of Things (IoT) devices and biomedical sensors has increased the demand for self-sustaining power systems that operate independently of conventional batteries. Wireless Power Transfer (WPT) and Radio Frequency (RF) Energy Harvesting (EH) technologies have thus emerged as essential solutions for powering sensors and wearable devices. A critical consideration for these applications is the selection of suitable operational frequencies. Although the 2.4 GHz Industrial, Scientific, and Medical (ISM) band is commonly used, the 5.8 GHz band (5.725–5.875 GHz) offers notable advantages for WPT systems. The 5.8 GHz band supports higher data transmission rates than the 2.4 GHz band, reduces interference from Wi-Fi and Bluetooth signals, and enables more compact antennas due to its shorter wavelength. The relevant ISM frequency ranges are illustrated in Figure 1 [1,2]. Achieving optimal WPT efficiency at this frequency requires careful optimization of the receiving antenna design. Microstrip patch antennas (MPAs) are particularly suitable for this application due to their low-profile structure, ease of fabrication, and compatibility with printed circuit boards (PCBs). However, conventional 5.8 GHz MPAs are limited by narrow bandwidth and low gain, necessitating advanced optimization techniques to improve performance.

This review provides a critical overview of key developments and emerging trends in the design of 5.8 GHz MPAs for Wireless Power Transfer (WPT) systems. It synthesizes recent advancements in antenna architectures and optimization strategies, emphasizing the evolution from fundamental single-element designs to advanced array and Multiple-Input Multiple-Output (MIMO) systems. The discussion highlights methods for enhancing antenna performance through compact structures, as well as the integration of novel classification frameworks to connect disparate research domains. Unique challenges in translating virtual testing results to physical hardware are examined, and the review identifies quantitative trade-offs and optimization opportunities, particularly within the 5.8 GHz ISM band. Special attention is paid to emerging themes, including the use of Defected Ground Structures (DGS), Electromagnetic Bandgap (EBG) structures, and metamaterials, as well as the incorporation of machine learning, design automation, and nanomaterials for next-generation flexible rectenna systems. Finally, the review outlines critical research gaps and provides recommendations for advancing wireless power system development.

This review paper is organized to facilitate a comprehensive and critical understanding of recent advancements in 5.8 GHz microstrip patch antenna (MPA) technology for Wireless Power Transfer (WPT) systems. Section 2 introduces the foundational aspects of 5.8 GHz MPAs, including core design principles, the specific challenges of operating in the 5.8 GHz band, and a rigorous evaluation of various feeding techniques. Section 3 presents a systematic classification and comparative analysis of MPA architectures, including single-element, wearable, array, and Multiple-Input Multiple-Output (MIMO) configurations, with an emphasis on their relevance and optimization for WPT applications. Section 4 provides a detailed examination of state-of-the-art optimization strategies, focusing on the implementation of Defected Ground Structures (DGS), Metamaterials (MTM), and Electromagnetic Bandgap (EBG) structures, and critically assesses their influence on antenna performance metrics. Section 5 explores the integration of advanced computational methods, such as machine learning algorithms and the utilization of nanomaterials, with a particular focus on rectenna integration and the principal parameters governing Power Conversion efficiency (PCE) in 5.8 GHz WPT systems. Finally, Section 6 synthesizes the key findings of the review, identifies prevailing research gaps, and articulates potential avenues for future research and innovation in MPA design and WPT system development.

2. Fundamentals of 5.8 GHz MPAs

2.1. Design Principles

Microstrip patch antennas (MPAs) represent a predominant class of antennas that fulfill a range of stringent performance criteria, rendering them highly suitable for integration into portable, wearable, and implantable biomedical devices. Their inherently lightweight, low-profile configuration facilitates seamless integration across diverse platforms, while their ease of fabrication and cost-effectiveness further enhance their applicability. Additionally, MPAs can be readily integrated into array structures or microwave-printed circuits, enabling advanced system functionalities. Notably, one of the most compelling applications of MPAs is their use in wireless power harvesting systems, where they offer a promising alternative to conventional batteries for medical devices [3].

2.2. Design Challenges at 5.8 GHz Antenna

Antenna design at 5.8 GHz, commonly used in ISM, Wi-Fi, IoT, and Wireless Power Transfer, presents multiple technical challenges. The most critical challenges are achieving wide bandwidth, high efficiency, compact size, and robust performance in real-world environments.

Table 1. Summary of key 5.8 GHz antenna design challenges and solutions.

Ref.	Challenge	Description	Common Solutions	Trade-Offs/Limitations
[4,5]	Bandwidth	The range of frequencies within which an antenna operates at its highest efficiency.	Slots, fractals, SIW, EBG, arrays	Complexity, matching issues
[6,7,8]	Miniaturization	The process of reducing an antenna’s physical size	Fractals, Metamaterials, DGS	Lower gain/efficiency
[9,10]	Efficiency/Gain	Efficiency measures the ability to transmit and receive RF signals, and gain describes how much power is transmitted in the direction of peak radiation compared to an isotropic source.	EBG, AMC, arrays, matching techniques	Increased size, design complexity
[6,11]	Multi-band	An antenna that is specifically designed to operate across many frequency bands.	Stubs, slots, reconfigurable elements	Size, complexity, cost
[12]	Cost/Fabrication	Achieving high performance with low cost.	FR-4, simple geometries	Higher losses, lower performance

summarizes these challenges and their associated performance metrics.

A comprehensive understanding of three fundamental propagation parameters—namely, path loss, penetration depth in lossy media, and conductors—is essential for the effective design of 5.8 GHz antennas and wireless systems. These parameters, summarized in

Table 2. Key propagation and material parameters at 5.8 GHz for WPT system design.

Ref.	Parameter	Description	Typical Value/Behavior at 5.8 GHz
[13,14,15]	Path Loss	Signal attenuation in (dB) over distance and obstacles	High, especially in indoor/urban environments with obstacles. Critical for link budget calculation.
[16,17]	Penetration Depth in Lossy Dielectrics (e.g., human tissue)	Depth at which power density drops to 1/e (~37%) of its surface value. The system operates under the attenuation constant δ = 1/α, which depends on frequency, permittivity (ε), and conductivity (σ).	Order of millimeters in biological tissue (e.g., muscle: ~7.5 mm, skin: ~8 mm, Fat/Bone: 35 mm). Crucial for assessing power delivery depth in biomedical WPT/WBAN and for evaluating on-body antenna performance detuning.
[16,17]	Skin Depth in Conductors (e.g., copper)	Depth at which current density falls to 1/e of its surface value: $\mathsf{\delta }=\sqrt{{\displaystyle \frac{2}{\omega \mu \mathsf{\sigma }}}}$	For high-conductivity metals: micrometer scale. For copper (σ ≈ 5.8 × 107 S/m), δ ≈ 0.87 μm. This dictates the minimum effective conductor thickness and is a primary factor in calculating ohmic losses in microstrip traces and antenna metallization, especially critical for thin-film and printed electronics.

, are critical for evaluating power transfer efficiency and signal integrity along various transmission paths. Accurate assessment of these factors is particularly important for link budget calculations in WPT systems intended for deployment in complex environments, such as biological tissues or densely cluttered settings.

It is essential to clearly differentiate between penetration depth in lossy dielectrics—such as biological tissues—and skin depth in conductive materials. At 5.8 GHz, the penetration depth in biological tissue typically extends to the millimeter scale, which has important implications for power transfer through biological media. In contrast, the skin depth in high-conductivity materials, such as copper, is on the order of micrometers, significantly influencing conductor losses, particularly in thin-film antenna traces. Recognizing these distinctions is critical for optimizing antenna design and ensuring efficient wireless power transfer in diverse application environments.

2.3. Feeding Techniques Comparison

Feeding techniques are essential for determining the bandwidth and isolation of 5.8 GHz Wireless Power Transfer (WPT) systems, as summarized in

Table 3. Comparison of several feeding methods.

Characteristics	Microstrip Feed Line	Co-Axial Feed	Aperture Coupled Feed Line	Proximity Coupled Feed	CPW
Spurious feed radiation	More	More	Less	Minimum	More
Reliability	Better	Poor	Good	Good	Good
Ease of fabrication	Easy	Difficult	Difficult	Difficult	Easy
Impedance matching	Easy	Easy	Easy	Easy	Easy
Typical FBW for Resonant Patch	2–3%	2–3%	3–5%	13–15%	40%
Polarization	Poor	Poor	Good	Poor	Good

[18,19]. To facilitate consistent comparison among the antenna designs reviewed, bandwidth values in subsequent performance tables (Tables 4–10) are reported as Fractional Bandwidth (FBW) in percentage, unless otherwise specified. For multi-band or ultra-wideband antenna configurations, FBW is specifically calculated for the 5.8 GHz frequency band under investigation.

3. Comprehensive Analysis of MPA Architectures

Antennas can be systematically classified according to operational frequency range and structural complexity. This review presents a comprehensive taxonomy of microstrip patch antenna (MPA) structures, as illustrated in Figure 2, encompassing designs from fundamental single-element configurations to advanced rectenna systems. The analysis begins with the most basic configuration: the single-element, single-frequency antenna.

3.1. Single-Element Designs

Recent literature primarily examines the performance of single-element antennas operating at a single resonance within the 5.8 GHz ISM band. Table 4 summarizes key performance trade-offs: replacing lossy FR-4 substrates [20] with Rogers RT5880 [21] significantly increases efficiency (from 57% to 85%), but also increases material costs.

Table 4. A single-element antenna with a single resonance frequency.

Ref.	Tech.	G (dBi)	FBW (%)	η (%)	Substrate εr	Dimension	Anorm	hnorm
[9]	NA	3.93	9.48	86.2	FR4/(4.3)	35 × 50 × 1.6	2.03	0.0545
[20]	Slotting	1.27	4.31	57	FR-4/(4.3)	35 × 50 × 1.6	2.03	0.0545
[21]	Shorting Vias	5	1.55	85	Rogers5880/(2.2)	30 × 24 × 0.787	0.48	0.0202
[22]	MTM (Tx)	11.34	1.72	NA	R4730JXR/(3)	105 × 105 × 1.52	9.40	0.0444
[12]	Inset, Notch, Slot	3.97	4.31	59	FR-4/(4.3)	25.5 × 23 × 1.6	0.68	0.0545
[23]	Double E-shape	7.63	2.17	NA	RT5880/(2.2)	70 × 75 × 1.575	3.47	0.0405
[24]	NA	9.33	4.95	NA	RO4350/(3.66)	60 × 60 × 1.524	3.64	0.0485
[25]	NA	4	79.31	95.9	FR4/(4.3)	22 × 22 × 1.5	0.56	0.0511
[26]	CPW	2.04	4.14	NA	RT5880/(2.2)	25 × 30 × 1.6	0.50	0.0412
[27]	CPW	2	3.45	NA	Polyimide/(3.5)	24 × 22 × 0.07	0.51	0.0022
[28]	EBG	11.2	6.47	NA	FR4/(4.2)	85 × 85 × 0.55	8.24	0.0186
[29]	EBG	11.4	6.03	NA	FR4/(NA)	101 × 98 × 1.6	NA	NA
[30]	CPW	NA	2.76	NA	FR4/(4.4)	30 × 28.4 × 1.6	1.01	0.0551
[31]	NA	0.9	3.45	NA	FR4/(4.3)	85 × 75 × 1.6	7.41	0.0545
[32]	NA	1.49	3.10	NA	FR4/(4.4)	25.5 × 22.5 × 1.6	0.68	0.0551
[33]	DNG MTM Superstrate	3.73	7.07	84	RT5870/(2.33) RT5880/(2.2)	70 × 60 × 1.57 70 × 56 × 0.787	2.98 2.59	0.0418 0.0202
[34]	NA	5.2	2.59	NA	AD 250 (2.5)	38 × 60 × 0.762	1.67	0.0206
[35]	Multi-layer & CPW	6.84	3.10	NA	FR4/(4.4)	∼50 × 96	5.70	NA
[36]	NA	3.2	17.24	NA	FR4/(4.4)	NA	NA	NA
[37]	CPW	4.38	3.79	NA	FR-4/(4.4)	38 × 22 × 1.6	0.99	0.0551
[38]	NA	5.2	3.45	NA	FR4/(4.4)	23.2 × 31 × 1.6	0.85	0.0551
[39]	NA	4.76	3.28	55	FR4/(4.4)	29 × 29 × 1.6	1.00	0.0551
[40]	NA	2.47	15.52	NA	FR4/(4.4)	10.7 × 11 × 1.6	0.14	0.0551
[4]	NA	4.2	38.97		FR4/(4.4)	40 × 40 × 1.6	1.90	0.0551
[41]	NA	5.8	20.17	72.3	FR4/(4.35)	10 × 10 × 1.6	0.12	0.0549
[42]	CPW	NA	70.69	NA	Polyimide/(3.5)	7.8 × 7 × 0.15	0.05	0.0047
[43]	EBG-backed	7.2	7.76	85	RT5880 & Foam/(2.2)	32 × 32 × 3.6	0.68	0.0926
[44]	DGS	4.4	10.00	NA	FR4/(NA)	15 × 10.6 × 1	NA	NA
[45]	DGS	5.81	2.07		FR4/(4.4)	96 × 156.5 × 1.6	17.83	0.0551
[46]	CPW& DGS	1.8	13.79	NA	FR4/(4.4)	15 × 24.5 × 1.6	0.44	0.0551
[47]	Stubs and DGS	4.17	3.45	75	FR4/(4.4)	NA	NA	NA
[48]	NA	4.866	6.90	NA	FR4 (4.3)	21.5 × 25.5 × 1.6	0.64	0.0545
[49]	CPW	8.56	20.69	NA	PTF/(2.1)	60 × 60 × 1.6	2.29	0.0404
[50]	EBG	NA	9.48	NA	Denim/(1.7)	62 × 97 × 0.7	3.26	0.0163
[51]	NA	11.30	3.28	90.85	RT5880/(2.2) RO3010/(10.2)	38 × 60 × 54.2	5.87	2.7513
[52]	SPR	11.85	2.24	NA	Taconic TLY-5/(2.2)	65 × 65 × 0.8	2.79	0.0206
[53]	NA	3.62	15.52	NA	FR4/(4.4)	14.6 × 14.6 × 0.8	0.25	0.0276
[54]	CPW	6.11	0.69	71	TLF-35A/(3.42)	60 × 45 × 1	2.58	0.0309
[55]	CPW	2.97	2.93	63.97	FR4/(4.4)	20 × 18 × 1.6	0.43	0.0551

Table 4. A single-element antenna with a single resonance frequency.

Ref.	Tech.	G (dBi)	FBW (%)	η (%)	Substrate εr	Dimension	Anorm	hnorm
[9]	NA	3.93	9.48	86.2	FR4/(4.3)	35 × 50 × 1.6	2.03	0.0545
[20]	Slotting	1.27	4.31	57	FR-4/(4.3)	35 × 50 × 1.6	2.03	0.0545
[21]	Shorting Vias	5	1.55	85	Rogers5880/(2.2)	30 × 24 × 0.787	0.48	0.0202
[22]	MTM (Tx)	11.34	1.72	NA	R4730JXR/(3)	105 × 105 × 1.52	9.40	0.0444
[12]	Inset, Notch, Slot	3.97	4.31	59	FR-4/(4.3)	25.5 × 23 × 1.6	0.68	0.0545
[23]	Double E-shape	7.63	2.17	NA	RT5880/(2.2)	70 × 75 × 1.575	3.47	0.0405
[24]	NA	9.33	4.95	NA	RO4350/(3.66)	60 × 60 × 1.524	3.64	0.0485
[25]	NA	4	79.31	95.9	FR4/(4.3)	22 × 22 × 1.5	0.56	0.0511
[26]	CPW	2.04	4.14	NA	RT5880/(2.2)	25 × 30 × 1.6	0.50	0.0412
[27]	CPW	2	3.45	NA	Polyimide/(3.5)	24 × 22 × 0.07	0.51	0.0022
[28]	EBG	11.2	6.47	NA	FR4/(4.2)	85 × 85 × 0.55	8.24	0.0186
[29]	EBG	11.4	6.03	NA	FR4/(NA)	101 × 98 × 1.6	NA	NA
[30]	CPW	NA	2.76	NA	FR4/(4.4)	30 × 28.4 × 1.6	1.01	0.0551
[31]	NA	0.9	3.45	NA	FR4/(4.3)	85 × 75 × 1.6	7.41	0.0545
[32]	NA	1.49	3.10	NA	FR4/(4.4)	25.5 × 22.5 × 1.6	0.68	0.0551
[33]	DNG MTM Superstrate	3.73	7.07	84	RT5870/(2.33) RT5880/(2.2)	70 × 60 × 1.57 70 × 56 × 0.787	2.98 2.59	0.0418 0.0202
[34]	NA	5.2	2.59	NA	AD 250 (2.5)	38 × 60 × 0.762	1.67	0.0206
[35]	Multi-layer & CPW	6.84	3.10	NA	FR4/(4.4)	∼50 × 96	5.70	NA
[36]	NA	3.2	17.24	NA	FR4/(4.4)	NA	NA	NA
[37]	CPW	4.38	3.79	NA	FR-4/(4.4)	38 × 22 × 1.6	0.99	0.0551
[38]	NA	5.2	3.45	NA	FR4/(4.4)	23.2 × 31 × 1.6	0.85	0.0551
[39]	NA	4.76	3.28	55	FR4/(4.4)	29 × 29 × 1.6	1.00	0.0551
[40]	NA	2.47	15.52	NA	FR4/(4.4)	10.7 × 11 × 1.6	0.14	0.0551
[4]	NA	4.2	38.97		FR4/(4.4)	40 × 40 × 1.6	1.90	0.0551
[41]	NA	5.8	20.17	72.3	FR4/(4.35)	10 × 10 × 1.6	0.12	0.0549
[42]	CPW	NA	70.69	NA	Polyimide/(3.5)	7.8 × 7 × 0.15	0.05	0.0047
[43]	EBG-backed	7.2	7.76	85	RT5880 & Foam/(2.2)	32 × 32 × 3.6	0.68	0.0926
[44]	DGS	4.4	10.00	NA	FR4/(NA)	15 × 10.6 × 1	NA	NA
[45]	DGS	5.81	2.07		FR4/(4.4)	96 × 156.5 × 1.6	17.83	0.0551
[46]	CPW& DGS	1.8	13.79	NA	FR4/(4.4)	15 × 24.5 × 1.6	0.44	0.0551
[47]	Stubs and DGS	4.17	3.45	75	FR4/(4.4)	NA	NA	NA
[48]	NA	4.866	6.90	NA	FR4 (4.3)	21.5 × 25.5 × 1.6	0.64	0.0545
[49]	CPW	8.56	20.69	NA	PTF/(2.1)	60 × 60 × 1.6	2.29	0.0404
[50]	EBG	NA	9.48	NA	Denim/(1.7)	62 × 97 × 0.7	3.26	0.0163
[51]	NA	11.30	3.28	90.85	RT5880/(2.2) RO3010/(10.2)	38 × 60 × 54.2	5.87	2.7513
[52]	SPR	11.85	2.24	NA	Taconic TLY-5/(2.2)	65 × 65 × 0.8	2.79	0.0206
[53]	NA	3.62	15.52	NA	FR4/(4.4)	14.6 × 14.6 × 0.8	0.25	0.0276
[54]	CPW	6.11	0.69	71	TLF-35A/(3.42)	60 × 45 × 1	2.58	0.0309
[55]	CPW	2.97	2.93	63.97	FR4/(4.4)	20 × 18 × 1.6	0.43	0.0551

Where λ₀ = 5.172 cm is Free-space Wavelength, ${\mathsf{\lambda }}_{\mathrm{g}}={\displaystyle \frac{{\mathsf{\lambda }}_{\mathrm{o}}}{\sqrt{\mathrm{e}\mathrm{f}\mathrm{f}}}}$, and ${\mathsf{\lambda }}_{\mathrm{g}}$ is Guided Wavelength. Normalized Area ${\mathrm{A}}_{\mathrm{n}\mathrm{o}\mathrm{r}\mathrm{m}}={\displaystyle \frac{\mathrm{P}\mathrm{h}\mathrm{y}\mathrm{s}\mathrm{i}\mathrm{c}\mathrm{a}\mathrm{l} \mathrm{A}\mathrm{r}\mathrm{e}\mathrm{a} \left(\mathrm{A}\right)}{\mathrm{s}\mathrm{q}\mathrm{u}\mathrm{a}\mathrm{r}\mathrm{e}\mathrm{d} \mathrm{g}\mathrm{u}\mathrm{i}\mathrm{d}\mathrm{e}\mathrm{d} \mathrm{w}\mathrm{a}\mathrm{v}\mathrm{e}\mathrm{l}\mathrm{e}\mathrm{n}\mathrm{g}\mathrm{t}\mathrm{h} ({\mathsf{\lambda }}_{\mathrm{g}})}}$, and Electrical Thickness ${\mathrm{h}}_{\mathrm{n}\mathrm{o}\mathrm{r}\mathrm{m}}={\displaystyle \frac{\mathrm{s}\mathrm{u}\mathrm{b}\mathrm{s}\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{e} \mathrm{h}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}}{\mathrm{T}\mathrm{h}\mathrm{e} \mathrm{g}\mathrm{u}\mathrm{i}\mathrm{d}\mathrm{e}\mathrm{d} \mathrm{w}\mathrm{a}\mathrm{v}\mathrm{e}\mathrm{l}\mathrm{e}\mathrm{n}\mathrm{g}\mathrm{t}\mathrm{h}}}$.

Incorporating metamaterial loading [22] yields the highest reported gain (11.34 dBi), although this requires a much larger physical footprint. Simulation-based antenna designs are detailed in [6,7,12,23,24,25,26,27,28,29,30,31,32,33,34,35,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82], while measured results from fabricated prototypes are provided in [4,8,9,20,21,22,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,58,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134]. Within the 5.8 GHz ISM band, single-element antennas are utilized in a wide range of applications, including:

• Wireless Local Area Networks (WLAN, Wi-Fi, WiMAX, 5G) [4,6,29,31,33,34,54,58,59,62,66,68,70,73,74,77,83,87,91,92,95,103,104,106,108,111,112,113,114,115,118,120,121,127,133];
• ISM band applications (IoT, RFID, WSN) [7,8,12,21,23,26,32,35,39,40,45,51,53,56,58,60,61,65,67,71,72,75,76,78,79,80,81,94,99,100,101,105,109,110,119,123,126,128,130,131,134];
• Wireless Power Transfer, Energy Harvesting, and Microwave Power Transmission [24,30,37,38,47,48,49,52,63,82,84,96,102,107,116,117,118,119,120,121,122,124,125];
• Medical, Healthcare Monitoring, Wireless Body Area Network (WBAN), and Wearable Electronics [27,41,42,43,46,50,64,69,85,86,88,89,90,93,98];
• Radar and Sensing Systems [22,25,44,129];
• Transportation and Vehicular Systems [9,20,57,97,132].

Analysis of the data presented in Tables 4–10 demonstrates an inherent trade-off between antenna gain and physical size. Designs with gains exceeding 8 dBi generally require a normalized antenna size A_norm > 3, while compact antennas with A_norm < 1 seldom exceed 5 dBi gain due to scaling limitations at 5.8 GHz. This finding highlights that increased design complexity does not always result in proportional performance improvements. The classic constraint is further evident: strategies to enhance gain often reduce bandwidth, and vice versa. Additionally, the data confirm that low-loss, higher-cost substrates such as Rogers consistently outperform more economical materials like FR-4 in terms of efficiency.

Figure 3 presents the design and prototype of a compact, single-resonance antenna optimized for stable performance at its target frequency.

The data in Table 4 show that designs achieving superior efficiency above 80% require low-loss substrates such as Rogers RT5880, whereas cost-effective FR-4 substrates limit efficiency to 55–75%. The use of metamaterials [22] and EBG superstrates [28,29] enables researchers to achieve gain values exceeding 8 dBi, but these designs produce bandwidths of no more than 0.4 GHz. The design process at 5.8 GHz involves essential trade-offs, as designers must choose between maximum gain, efficiency, or bandwidth while working with different substrate materials and varying design complexities.

Critically, analyzing Table 4 requires interpreting the non-obvious trend linking total efficiency ${\mathsf{\eta }}_{\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}}$ to (${\mathrm{h}}_{\mathrm{n}\mathrm{o}\mathrm{r}\mathrm{m}})$. Designs with high electrical thickness (high ${\mathrm{h}}_{\mathrm{n}\mathrm{o}\mathrm{r}\mathrm{m}}$) often exhibit improved gain and bandwidth, but this benefit is offset if surface wave energy is not suppressed, as surface waves are amplified with increasing thickness, thereby degrading (${\mathsf{\eta }}_{\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}}$). This quantitative trade-off demonstrates why techniques such as EBG backing are essential for thicker substrates.

A summary of scientific papers published in recent years is presented in Table 5, focusing on the operation of single antennas at dual-band frequencies within the ISM band (2.45 GHz and 5.8 GHz).

Table 5. A single-element antenna with dual-band frequency.

Ref.	G (dBi)	FBW (%)	η (%)	$\mathbf{Substrate}/{\mathsf{\epsilon }}_{\mathbf{r}}$	Tech	Dimension	Anorm	hnorm
[7]	2.1	2.76	NA	FR-4/(4.4)	(CSRR/SRR), DGS	40.86 × 52.16 × 1.6	2.53	0.0551
[59]	2.08	6.03	64.19	FR4/(4.3)	NA	28 × 26 × 1.4	0.85	0.0477
[60]	3.51	9.98	NA	FR4/(4.3)	NA	26 × 28 × 1.6	0.85	0.0545
[61]	6.49	1.90	NA	RT5880/(2.2)	NA	55.91 × 39.9 × 1.575	1.48	0.0405
[62]	5	17.24	NA	FR4/(4.4)	CPW	50 × 50 × 0.88	2.97	0.0303
[63]	3.04	17.24	NA	FR4/(4.4)	CPW	50 × 50 × 1.6	2.97	0.0551
[64]	5	4.71	59.9	FR-4–PDMS–FR-4 /(4.5,2.65)	DGS	30 × 30 × 2.6	1.09	0.0904
[65]	3.24	4.14	90	RT4003/(3.55)	Pixelated DGS	24.8 × 26 × 1.52	0.66	0.0487
[66]	6.2	3.28	NA	Roger/(2.2)	SIW	48 × 52 × 1.57	1.65	0.0404
[67]	5.48	5.17	NA	FR4/(4.4)	PG	15 × 12 × 1.6	0.21	0.0551
[68]	3.5	32.76	NA	RT5870/(2.33)	CPW	23 × 32 × 0.79	0.51	0.0208
[69]	NA	NA	NA	FR4/(4.2)	NA	56 × 62 × 1.6	3.96	0.0540
[84]	7.3	17.24	NA	FR4/(4.4)	NA	40 × 40 × 1.6	1.90	0.0551
[85]	6.33	3.10	80	FR4/(4.3)	NA	40 × 30 × 1.6	1.39	0.0545
[86]	2.30, 4.95	5.17	97.5,98.3	RT5870/(2.33)	NA	35 × 25 × 0.787	0.61	0.0207
[87]	8.55	9.48	NA	FR-4/(3.4)	MTM	32 × 25 × 1.6	0.76	0.0492
[88]	5.65, 7.39	4.66	57, 63	Felt/(1.2)	Dual-Mode	NA	NA	NA
[89]	3.8, 6.0	2.95	92, 91.7	Rogers/(3)	E-Slot, ML	40 × 41 × 0.5	1.40	0.0146
[90]	1.20, 7.45	13.10	80, 90	F4B/(2.55)	Short Pins	2463 × 5	1.83	0.1364
[91]	2.41, 5.22	8.79	90	FR-4/(4.4)	PG	40 × 24 × 1.6	1.14	0.0551
[92]	3.6, 4.7	7.76	NA	Pyralux Flexible Laminate	Modified IFA	77 × 14 × 0.1	NA	NA
[93]	2.5, 6.9	77.59	76, 93	F4BM220	Hybrid	13 × 13 × 0.1	0.11	NA
[94]	6.8	3.28	80	PLA-printed & copper/(∼2)	SRR & CSRR	70 × 70 × 31	3.01	0.7677
[95]	4.2	2.59	88	FR4/(4.4)	GCPW	15 × 40 × 0.4	0.71	0.0138
[96]	3.96	6.03	69.9	F4B/(2.65)	NA	42.6 × 32.6 × 8	1.07	0.2217
[97]	NA	2.16	NA	FR4/(NA)	NA	34 × 44	NA	NA
[98]	3.7	24.14	47.6	flexible felt/(1.43)	AMC	NA	NA	NA
[99]	8.96	26.90	99	FR4/(NA)	CPW	15 × 30 × 1.6	NA	NA
[100]	3.5	15.34	NA	FR4/(NA)	CPW	29.5 × 29.5 × 1.6	NA	NA
[101]	2.94	6.90	NA	RO4003/(3.55)	DGS	14 × 14 × 1.52	0.19	0.0476
[102]	6.16	5.17	80	RT5880/(2.2)	Pixelated DGS	40 × 28 × 1.575	0.74	0.0405
[103]	2.8	6.90	NA	FR4/(4.4)	DGS	33 × 35 × 1.6	1.37	0.0551
[104]	NA	3.45	NA	FR4/(4.4)	DGS	41 × 44 × 1.6	2.14	0.0551
[105]	5	25.00	NA	FR4/(4.3)	NA	34 × 34 × 1.5	1.34	0.0511
[106]	6.8	18.45	NA	FR4/(4.4)	FSS	40 × 40 × 1.6	1.90	0.0551
[107]	6.27	15.52	98	NA/(12)	DRA	50 × 50 × 3	7.53	0.1647
[108]	4.78	8.62	83.41	FR4/(4.4)	NA	66 × 66 × 1.6	5.17	0.0551
[109]	4.11	2.76	NA	FR4/(4.4)	DGS and Parasitic	23 × 30 × 1.57	0.82	0.0541
[110]	3.22	17.24	NA	RF30/(3.35)	CPW & SIW	28 × 40 × 1.52	1.05	0.0465
[111]	3.1	7.76	NA	FR4/(4.4)	NA	55 × 33 × 1.6	2.15	0.0551
[136]	5.75	5.2	91.4	RT3003/(3)	PIN diode	41 × 44 × 1.52	1.54	0.0444

Table 5. A single-element antenna with dual-band frequency.

Ref.	G (dBi)	FBW (%)	η (%)	$\mathbf{Substrate}/{\mathsf{\epsilon }}_{\mathbf{r}}$	Tech	Dimension	Anorm	hnorm
[7]	2.1	2.76	NA	FR-4/(4.4)	(CSRR/SRR), DGS	40.86 × 52.16 × 1.6	2.53	0.0551
[59]	2.08	6.03	64.19	FR4/(4.3)	NA	28 × 26 × 1.4	0.85	0.0477
[60]	3.51	9.98	NA	FR4/(4.3)	NA	26 × 28 × 1.6	0.85	0.0545
[61]	6.49	1.90	NA	RT5880/(2.2)	NA	55.91 × 39.9 × 1.575	1.48	0.0405
[62]	5	17.24	NA	FR4/(4.4)	CPW	50 × 50 × 0.88	2.97	0.0303
[63]	3.04	17.24	NA	FR4/(4.4)	CPW	50 × 50 × 1.6	2.97	0.0551
[64]	5	4.71	59.9	FR-4–PDMS–FR-4 /(4.5,2.65)	DGS	30 × 30 × 2.6	1.09	0.0904
[65]	3.24	4.14	90	RT4003/(3.55)	Pixelated DGS	24.8 × 26 × 1.52	0.66	0.0487
[66]	6.2	3.28	NA	Roger/(2.2)	SIW	48 × 52 × 1.57	1.65	0.0404
[67]	5.48	5.17	NA	FR4/(4.4)	PG	15 × 12 × 1.6	0.21	0.0551
[68]	3.5	32.76	NA	RT5870/(2.33)	CPW	23 × 32 × 0.79	0.51	0.0208
[69]	NA	NA	NA	FR4/(4.2)	NA	56 × 62 × 1.6	3.96	0.0540
[84]	7.3	17.24	NA	FR4/(4.4)	NA	40 × 40 × 1.6	1.90	0.0551
[85]	6.33	3.10	80	FR4/(4.3)	NA	40 × 30 × 1.6	1.39	0.0545
[86]	2.30, 4.95	5.17	97.5,98.3	RT5870/(2.33)	NA	35 × 25 × 0.787	0.61	0.0207
[87]	8.55	9.48	NA	FR-4/(3.4)	MTM	32 × 25 × 1.6	0.76	0.0492
[88]	5.65, 7.39	4.66	57, 63	Felt/(1.2)	Dual-Mode	NA	NA	NA
[89]	3.8, 6.0	2.95	92, 91.7	Rogers/(3)	E-Slot, ML	40 × 41 × 0.5	1.40	0.0146
[90]	1.20, 7.45	13.10	80, 90	F4B/(2.55)	Short Pins	2463 × 5	1.83	0.1364
[91]	2.41, 5.22	8.79	90	FR-4/(4.4)	PG	40 × 24 × 1.6	1.14	0.0551
[92]	3.6, 4.7	7.76	NA	Pyralux Flexible Laminate	Modified IFA	77 × 14 × 0.1	NA	NA
[93]	2.5, 6.9	77.59	76, 93	F4BM220	Hybrid	13 × 13 × 0.1	0.11	NA
[94]	6.8	3.28	80	PLA-printed & copper/(∼2)	SRR & CSRR	70 × 70 × 31	3.01	0.7677
[95]	4.2	2.59	88	FR4/(4.4)	GCPW	15 × 40 × 0.4	0.71	0.0138
[96]	3.96	6.03	69.9	F4B/(2.65)	NA	42.6 × 32.6 × 8	1.07	0.2217
[97]	NA	2.16	NA	FR4/(NA)	NA	34 × 44	NA	NA
[98]	3.7	24.14	47.6	flexible felt/(1.43)	AMC	NA	NA	NA
[99]	8.96	26.90	99	FR4/(NA)	CPW	15 × 30 × 1.6	NA	NA
[100]	3.5	15.34	NA	FR4/(NA)	CPW	29.5 × 29.5 × 1.6	NA	NA
[101]	2.94	6.90	NA	RO4003/(3.55)	DGS	14 × 14 × 1.52	0.19	0.0476
[102]	6.16	5.17	80	RT5880/(2.2)	Pixelated DGS	40 × 28 × 1.575	0.74	0.0405
[103]	2.8	6.90	NA	FR4/(4.4)	DGS	33 × 35 × 1.6	1.37	0.0551
[104]	NA	3.45	NA	FR4/(4.4)	DGS	41 × 44 × 1.6	2.14	0.0551
[105]	5	25.00	NA	FR4/(4.3)	NA	34 × 34 × 1.5	1.34	0.0511
[106]	6.8	18.45	NA	FR4/(4.4)	FSS	40 × 40 × 1.6	1.90	0.0551
[107]	6.27	15.52	98	NA/(12)	DRA	50 × 50 × 3	7.53	0.1647
[108]	4.78	8.62	83.41	FR4/(4.4)	NA	66 × 66 × 1.6	5.17	0.0551
[109]	4.11	2.76	NA	FR4/(4.4)	DGS and Parasitic	23 × 30 × 1.57	0.82	0.0541
[110]	3.22	17.24	NA	RF30/(3.35)	CPW & SIW	28 × 40 × 1.52	1.05	0.0465
[111]	3.1	7.76	NA	FR4/(4.4)	NA	55 × 33 × 1.6	2.15	0.0551
[136]	5.75	5.2	91.4	RT3003/(3)	PIN diode	41 × 44 × 1.52	1.54	0.0444

The dual-band antenna structure in Figure 4 operates at two separate frequencies, including 5.8 GHz for the support of multiple communication standards.

Table 6 provides an overview of multi-band antennas, showing that techniques such as EBG, DGS, and SRR/CSRR enable operation across multiple bands, with applications in wearable, IoT, and Energy-Harvesting systems. Efficiency and SAR are important metrics for wearable use.

Table 6. A single-element antenna with multi-band frequency.

Ref.	S11 (-) (dB)	G (dBi)	BW (GHz)	η (%)	$\mathbf{Substrate}/{\mathsf{\epsilon }}_{\mathbf{r}}$	Tech.	Dimension	Anorm	hnorm
[6]	22.3	4.35	∼0.8	81	FR4/(4.3)	PG	40 × 15 × 1.6	0.70	0.0545
[70]	∼13	∼1.2	0.6	∼75	FR4/(4.4)	CPW	21 × 21 × 1.6	0.52	0.0551
[71]	36.67	3.947	0.17	NA	FR4/(4.4)	NA	38.429 × 46.86 × 1.6	2.14	0.0551
[72]	∼14.5	NA	∼0.2	NA	FR4/(NA)	DGS	29.6 × 30.5×1.5	NA	NA
[73]	∼27	∼3.4	∼2.4	NA	FR4/(4.4)	CPW	20 × 35 × 1.6	0.83	0.0551
[74]	28.93	3.36	3.76	85.62	FR4/(4.3)	ANN	24 × 33.5 × 1.56	0.93	0.0532
[112]	23	9.64	0.21	NA	FR4/(4.4)	Two Substrate	40 × 42 × 1.6	1.99	0.0551
[113]	∼38	5.14	1.06	90	FR4/(4.4)	Groundless EBG	23.8 × 17.9 × 1	0.51	0.0344
[114]	∼33	3.48	0.49	80.19	FR4/(4.4)	SRR & CSRR	35 × 35 × 1.6	1.45	0.0551
[115]	∼11	2.99	0.09	NA	FR4/(4.3)	DGS	34 × 30 × 1.6	1.18	0.0545
[117]	∼25.5	6.1	6.5	NA	Kappa/(4.38)	CPW	NA	NA	NA
[118]	∼33	4.14	0.1	NA	FR4/(4.4)	DGS	35 × 27.4 × 0.8	1.14	0.0276
[119]	∼37	4.63	∼1.4	88	FR4/(4.4)	NA	32 × 20 × 1.6	0.76	0.0551
[120]	∼34	8.45	2.16	NA	PTFE/(2.4)	NA	49.55 × 46.5 × 1.6	1.63	0.0426

Table 6. A single-element antenna with multi-band frequency.

Ref.	S11 (-) (dB)	G (dBi)	BW (GHz)	η (%)	$\mathbf{Substrate}/{\mathsf{\epsilon }}_{\mathbf{r}}$	Tech.	Dimension	Anorm	hnorm
[6]	22.3	4.35	∼0.8	81	FR4/(4.3)	PG	40 × 15 × 1.6	0.70	0.0545
[70]	∼13	∼1.2	0.6	∼75	FR4/(4.4)	CPW	21 × 21 × 1.6	0.52	0.0551
[71]	36.67	3.947	0.17	NA	FR4/(4.4)	NA	38.429 × 46.86 × 1.6	2.14	0.0551
[72]	∼14.5	NA	∼0.2	NA	FR4/(NA)	DGS	29.6 × 30.5×1.5	NA	NA
[73]	∼27	∼3.4	∼2.4	NA	FR4/(4.4)	CPW	20 × 35 × 1.6	0.83	0.0551
[74]	28.93	3.36	3.76	85.62	FR4/(4.3)	ANN	24 × 33.5 × 1.56	0.93	0.0532
[112]	23	9.64	0.21	NA	FR4/(4.4)	Two Substrate	40 × 42 × 1.6	1.99	0.0551
[113]	∼38	5.14	1.06	90	FR4/(4.4)	Groundless EBG	23.8 × 17.9 × 1	0.51	0.0344
[114]	∼33	3.48	0.49	80.19	FR4/(4.4)	SRR & CSRR	35 × 35 × 1.6	1.45	0.0551
[115]	∼11	2.99	0.09	NA	FR4/(4.3)	DGS	34 × 30 × 1.6	1.18	0.0545
[117]	∼25.5	6.1	6.5	NA	Kappa/(4.38)	CPW	NA	NA	NA
[118]	∼33	4.14	0.1	NA	FR4/(4.4)	DGS	35 × 27.4 × 0.8	1.14	0.0276
[119]	∼37	4.63	∼1.4	88	FR4/(4.4)	NA	32 × 20 × 1.6	0.76	0.0551
[120]	∼34	8.45	2.16	NA	PTFE/(2.4)	NA	49.55 × 46.5 × 1.6	1.63	0.0426

Figure 5 illustrates a multiband antenna that covers 5.8 GHz among several other frequency bands.

3.2. Ultra-Wideband Antenna (UWB)

Table 7 lists UWB antenna designs, demonstrating that CPW feeding and EBG/DGS structures can achieve wide bandwidths (up to several GHz) and high efficiency, making them suitable for high-data-rate and energy-harvesting applications.

The Fractional Bandwidth (FBW) shows the percentage connection between an antenna’s bandwidth and its operating frequency at the center frequency according to Equation (1),

$$FBW\left(\%\right)={\displaystyle \frac{f_h-f_l}{{(f}_h-f_l)/2}}\ast 100.$$

(1)

Table 7. Ultra-wideband antenna at resonance frequency (5.8 GHZ).

Ref.	G (dBi)	BW (GHz) [FBW%]	η (%)	Substrate/εr	Tech.	Dimension	Anorm	hnorm
[75]	5.36	4.5–6.2 [31.8%]	91.62	FR4/(4.4)	CPW	27.34 × 27.34 × 1.6	0.89	0.0551
[76]	4.68	3–7.5 [85.7%]	NA	FR4/(4.4)	CPW	24 × 25 × 1	0.71	0.0344
[77]	NA	2.35–12.9 [138.4%]	96	FR4/(4.3)	NA	32 × 36 × 1.6	1.34	0.0545
[121]	2.53	5–6 [18.2%]	NA	FR4/(4.4)	CPW	24 × 40 × 1.6	1.14	0.0551
[122]	2.32	2–6 [100%]	NA	FR4/(4.4)	CPW	40 × 26 × 1.6	1.23	0.0551
[123]	3.66	NA	93.5	FR4/(4.5)	CPW	25 × 25 × 0.8	0.76	0.0278
[124]	4.7	3.6–13.9 [118.2%]	NA	FR4/(4.4)	CPW	27 × 25 × 1.5	0.80	0.0517
[125]	3.7	3.4–6.3 [58.9%]	NA	FR4/(4.3)	Parasitic Element	20 × 28 × 0.025	0.65	0.0009
[126]	NA	5.7–8 [33.6%]	NA	FR4/(NA)	CPW	20 × 20 × 1.5	NA	NA
[127]	NA	2–9.67 [131.5%]	NA	FR4/(4.4)	EBG on the ground	18 × 21 × 1.6	0.45	0.0551
[128]	3.6	2.3–9.6 [123.5%]	NA	NA/(2.2)	DGS	18 × 15 × 1.6	0.18	0.0412
[129]	14.3	5.5–5.9 [6.0%]	NA	RO4003C/(3.55)	NA	NA	NA	NA
[130]	NA	2–6 [100%]	NA	FR4/(4.4)	Chip-less	21 × 21 × 0.8	0.52	0.0276

Table 7. Ultra-wideband antenna at resonance frequency (5.8 GHZ).

Ref.	G (dBi)	BW (GHz) [FBW%]	η (%)	Substrate/εr	Tech.	Dimension	Anorm	hnorm
[75]	5.36	4.5–6.2 [31.8%]	91.62	FR4/(4.4)	CPW	27.34 × 27.34 × 1.6	0.89	0.0551
[76]	4.68	3–7.5 [85.7%]	NA	FR4/(4.4)	CPW	24 × 25 × 1	0.71	0.0344
[77]	NA	2.35–12.9 [138.4%]	96	FR4/(4.3)	NA	32 × 36 × 1.6	1.34	0.0545
[121]	2.53	5–6 [18.2%]	NA	FR4/(4.4)	CPW	24 × 40 × 1.6	1.14	0.0551
[122]	2.32	2–6 [100%]	NA	FR4/(4.4)	CPW	40 × 26 × 1.6	1.23	0.0551
[123]	3.66	NA	93.5	FR4/(4.5)	CPW	25 × 25 × 0.8	0.76	0.0278
[124]	4.7	3.6–13.9 [118.2%]	NA	FR4/(4.4)	CPW	27 × 25 × 1.5	0.80	0.0517
[125]	3.7	3.4–6.3 [58.9%]	NA	FR4/(4.3)	Parasitic Element	20 × 28 × 0.025	0.65	0.0009
[126]	NA	5.7–8 [33.6%]	NA	FR4/(NA)	CPW	20 × 20 × 1.5	NA	NA
[127]	NA	2–9.67 [131.5%]	NA	FR4/(4.4)	EBG on the ground	18 × 21 × 1.6	0.45	0.0551
[128]	3.6	2.3–9.6 [123.5%]	NA	NA/(2.2)	DGS	18 × 15 × 1.6	0.18	0.0412
[129]	14.3	5.5–5.9 [6.0%]	NA	RO4003C/(3.55)	NA	NA	NA	NA
[130]	NA	2–6 [100%]	NA	FR4/(4.4)	Chip-less	21 × 21 × 0.8	0.52	0.0276

The ultra-wideband antenna in Figure 6 features a design that achieves a very broad impedance bandwidth encompassing the 5.8 GHz band, suitable for high-data-rate and sensing applications.

3.3. Array Antenna

While Table 8 confirms the classical principle that arraying enhances gain (e.g., reaching up to 12.1 dBi [133]), a critical analysis shows that this comes at a cost. The associated increase in physical aperture and system complexity is evident. Furthermore, the data suggest that the total array efficiency can degrade due to increased mutual coupling and feed network losses if careful design is not employed, such as by employing DGS [8] or optimizing element spacing. The results demonstrate that adding elements to the system does not automatically result in maximum WPT performance.

Table 8. Array antenna at resonance frequency (5.8 GHZ).

Ref.	G (dBi)	BW (GHz)	η (%)	Substrate/εr	Tech.	Dimension	Anorm	hnorm
[8]	7.63	0.458	97	RT5880/(2.2)	DGS	50 × 54 × 1.575	1.79	0.0405
[31]	NA	∼0.45	NA	FR4/(4.3)	2 × 1 array	85 × 75 × 1.6	7.41	0.0545
[56]	7.78	0.3	81	FR4/(4.4)	2 × 2 array	49.47 × 47.94	2.81	NA
[57]	12	0.7	NA	RT5880/(2.2)	4 × 4 array	67.67 × 65.52	2.93	NA
[78]	9.915	∼0.15	NA	RT5880/(2.2)	2 × 1 array	30.77 × 59.44 × 1.56	1.21	0.0401
[79]	9.83	∼0.9	NA	RT5880/(2.2)	2 × 1 array	38.77 × 59.44 × 1.6	1.52	0.0412
[80]	8.2	∼0.9	NA	RT5880/(2.2)	2 × 2 array	83 × 71 × 0.287	3.90	0.0074
[81]	3.21	0.21	NA	FR4/(4.4)	NA	75 × 75 × 1.5	6.67	0.0517
[82]	8.9	∼0.1	73.39	FR4/(4.4)	2 × 2	NA	NA	NA
[132]	9.51	0.1353	NA	RT5880/(2.2)	2 × 1 array	70 × 50 × 0.787	2.32	0.0202
[133]	12.1	0.78	NA	FR4/(4.3)	SRR 2 × 1 array	52.5 × 67.1 × 1.48	4.09	0.0504
[134]	4.2	∼0.2	NA	RO3010/(10.2)	2 × 2 array	27 × 36 × 1.28	2.50	0.0650
[137]	4.1	1.5	0.37	RT3003/(3)	2 × 1 array	2.5 × 5 × 0.762	0.01	0.0223

Table 8. Array antenna at resonance frequency (5.8 GHZ).

Ref.	G (dBi)	BW (GHz)	η (%)	Substrate/εr	Tech.	Dimension	Anorm	hnorm
[8]	7.63	0.458	97	RT5880/(2.2)	DGS	50 × 54 × 1.575	1.79	0.0405
[31]	NA	∼0.45	NA	FR4/(4.3)	2 × 1 array	85 × 75 × 1.6	7.41	0.0545
[56]	7.78	0.3	81	FR4/(4.4)	2 × 2 array	49.47 × 47.94	2.81	NA
[57]	12	0.7	NA	RT5880/(2.2)	4 × 4 array	67.67 × 65.52	2.93	NA
[78]	9.915	∼0.15	NA	RT5880/(2.2)	2 × 1 array	30.77 × 59.44 × 1.56	1.21	0.0401
[79]	9.83	∼0.9	NA	RT5880/(2.2)	2 × 1 array	38.77 × 59.44 × 1.6	1.52	0.0412
[80]	8.2	∼0.9	NA	RT5880/(2.2)	2 × 2 array	83 × 71 × 0.287	3.90	0.0074
[81]	3.21	0.21	NA	FR4/(4.4)	NA	75 × 75 × 1.5	6.67	0.0517
[82]	8.9	∼0.1	73.39	FR4/(4.4)	2 × 2	NA	NA	NA
[132]	9.51	0.1353	NA	RT5880/(2.2)	2 × 1 array	70 × 50 × 0.787	2.32	0.0202
[133]	12.1	0.78	NA	FR4/(4.3)	SRR 2 × 1 array	52.5 × 67.1 × 1.48	4.09	0.0504
[134]	4.2	∼0.2	NA	RO3010/(10.2)	2 × 2 array	27 × 36 × 1.28	2.50	0.0650
[137]	4.1	1.5	0.37	RT3003/(3)	2 × 1 array	2.5 × 5 × 0.762	0.01	0.0223

Figure 7 depicts an antenna array configuration designed for operation at 5.8 GHz, combining multiple radiating elements to enhance directivity and gain.

Beamforming networks serve as essential components for power-direction control in WPT links in dynamic environments [138]. Research conducted over the past few years has focused on the 5.8 GHz band to develop beam-steering systems, which now serve as fundamental references for system development. Power transfer efficiency improves with the use of tunable phase shifters in phased-array architectures, enabling electronic beam steering toward mobile receivers [139]. The implementation of beamforming networks requires additional components, which create problems with feed system complexity, power consumption, and system calibration requirements. Discussing these architectures alongside passive arrays provides a more complete picture of the design trade-offs between gain, directivity, adaptability, and system overhead for targeted WPT applications [140,141].

3.4. MIMO Antennas

The rapid expansion of internet platforms and the deployment of 5G technology across industries have increased the demand for wireless systems that deliver high data transfer rates, wide channel bandwidth, substantial diversity, broad coverage, and reliable performance. Implementing Multiple-Input Multiple-Output (MIMO) systems at the 5.8 GHz band poses significant challenges, primarily due to the short wavelength, which intensifies mutual coupling between antenna elements. This mutual coupling can reduce channel capacity and diversity gain, thereby impairing system performance. Recent technological advances, including the use of Metamaterials (MTMs) and Defected Ground Structures (DGS), have improved the management of mutual coupling, resulting in enhanced system isolation and overall efficiency, as summarized in Table 9.

Table 9. MIMO antennas at 5.8 GHz.

Ref.	No. E	DT	II (dB)	EES	G, DG (dBi, dB)	CCL (bits/s/Hz)	ECC	(η) (%)	Substrate εr	Anorm	hnorm
[83]	2 × 2	SMPRG	>12	NA	5.2, ≥10	<0.5	<0.0004	52	FR4 (4.4)	1.71	0.0525
[142]	2	MTM	9	(7 mm)	4, ≥9	<0.05	<0.1	97	FR4 (4.4)	1.93	0.0551
[143]	2	Zigzag (DGS)	37.48	${0.0502\mathsf{\lambda }}_{\mathrm{o}}$	1.5, 9.783	NA	<0.02	NA	PTFE (3.5)	2.44	0.0476
[144]	4 × 4	M-DGS	NA	NA	NA	NA	<0.0001	83	FR4 (4.4)	1.75	0.0276
[145]	1 × 4	array	NA	NA	8–10.9, 10	<0.3	<0.003	97.46	RT5880 (2.2)	0.91	0.0404
[146]	4 × 2	MGS	18	2 mm NA	9.2, NA	NA	<0.02	73.14	Ro4350B (3.66)	10.67	0.0969

Table 9. MIMO antennas at 5.8 GHz.

Ref.	No. E	DT	II (dB)	EES	G, DG (dBi, dB)	CCL (bits/s/Hz)	ECC	(η) (%)	Substrate εr	Anorm	hnorm
[83]	2 × 2	SMPRG	>12	NA	5.2, ≥10	<0.5	<0.0004	52	FR4 (4.4)	1.71	0.0525
[142]	2	MTM	9	(7 mm)	4, ≥9	<0.05	<0.1	97	FR4 (4.4)	1.93	0.0551
[143]	2	Zigzag (DGS)	37.48	${0.0502\mathsf{\lambda }}_{\mathrm{o}}$	1.5, 9.783	NA	<0.02	NA	PTFE (3.5)	2.44	0.0476
[144]	4 × 4	M-DGS	NA	NA	NA	NA	<0.0001	83	FR4 (4.4)	1.75	0.0276
[145]	1 × 4	array	NA	NA	8–10.9, 10	<0.3	<0.003	97.46	RT5880 (2.2)	0.91	0.0404
[146]	4 × 2	MGS	18	2 mm NA	9.2, NA	NA	<0.02	73.14	Ro4350B (3.66)	10.67	0.0969

A thorough evaluation of 5.8 GHz MIMO antenna systems requires consideration of several key parameters, including the number of radiating elements, antenna dimensions, edge-to-edge separation (EES), and the decoupling techniques employed. Critical performance metrics include isolation improvement (II), total efficiency (η), envelope correlation coefficient (ECC), diversity gain (DG), and channel capacity loss (CCL). Table 9 presents a comparative analysis of MIMO antenna designs operating at 5.8 GHz, many of which are underrepresented in the current literature. The Multiple-Input Multiple-Output (MIMO) antenna system in Figure 8 is designed with multiple isolated elements operating at 5.8 GHz to increase channel capacity and link reliability.

Figure 9 illustrates the relationship between gain and physical area, revealing considerable variability in performance. Although increased gain generally correlates with larger apertures, the pronounced dispersion, particularly for designs with A < 2500 mm2, indicates that advanced techniques such as Metamaterials (MTM) and Electromagnetic Bandgap (EBG) structures can address the gain-area trade-off. These methods enable higher gain from compact form factors, which is essential for advancing miniaturized portable Wireless Power Transfer (WPT) devices.

3.5. Critical Synthesis of Architectural Trade-Offs and Performance Metrics

A critical analysis of the data presented in Table 4, Table 5, Table 6, Table 7, Table 8 and Table 9 reveals quantifiable design trade-offs and non-obvious performance trends specific to the 5.8 GHz ISM band. To enable a substrate-agnostic and size-normalized comparison, two key dimensionless parameters are used: the normalized area (A_norm) and the normalized electrical thickness (h_norm). A_norm is defined as the physical area of the antenna divided by the square of the guided wavelength (λg²), whereas h_norm is the substrate height divided by λg. These metrics allow for the assessment of miniaturization and electrical thickness independently of operating frequency and substrate properties.

3.5.1. Key Performance Trade-Offs

This research demonstrates that radiation efficiency (η) strongly depends on the normalized electrical thickness (h_norm) due to an essential non-linear relationship between the two variables. The electrical profile thickness enables designers to create circuits with h_norm values exceeding 0.0015, resulting in improved bandwidth and gain performance. However, this benefit is contingent on effective suppression of surface waves. The EBG-backed design outlined in [43] achieves 85% efficiency at h_norm = 0.0024. The design without EBG, presented in [20], shows a 28% decrease in efficiency because it lacks control over surface-wave losses.

Second, the data establish a clear efficiency–substrate cost relationship. The antennas built on low-loss, high-cost substrates, including Rogers RT5880 (ε_r∼2.2), demonstrate η values greater than 80% according to [21,33,51]. The efficiency of cost-optimized designs on FR-4 (ε_r∼4.4) reaches its maximum between 55% and 96% according to [9,12,20,56,75,77,119], demonstrating a substantial loss of efficiency due to substrate selection. The trade-off between these two factors is evident in Figure 10, which shows the relationship between radiation efficiency and relative substrate cost for the 5.8 GHz MPAs surveyed. The research shows that FR-4 is the best commercial substrate, as its efficiency ranges from 52% to 99%, indicating that designers can achieve high performance with optimized design approaches. The Rogers substrates operate at a minimum 70% efficiency, but rising production costs worsen performance.

The 5.8 GHz frequency band demonstrates its gain–bandwidth trade-off using a specific method. The implementation of high-gain techniques operating above 8 dBi via MTM loading [22] and EBG superstrates [28,29] results in bandwidths that do not exceed 0.4 GHz. UWB designs using CPW feeds [75,76,124] achieve bandwidths exceeding 2 GHz while providing gain levels of 2–5 dBi. The inverse relationship exists in arrays, but the added complexity and increased aperture size help reduce this effect.

The miniaturization process, which uses geometric methods such as DCS and fractals, results in performance deterioration. The research reported in [7,44] presents a small DCS antenna achieving a 4.4 dBi gain with A_norm = 0.18. The MTM design from [22] produces 11.34 dBi gain due to its larger size, resulting in a 6.94 dBi gain boost, but requires a 52 times larger normalized area. The core problem with organizational size and operational effectiveness becomes apparent through this analysis.

3.5.2. Normalized Figures of Merit for Objective Comparison

To provide a fair, substrate-agnostic comparison of the diverse 5.8 GHz MPA designs, we introduce two normalized Figures of Merit (FOMs) that decouple performance from physical scaling and material properties:

FOM₁: Gain per Unit Normalized Area (G/A_norm):

$${\mathrm{F}\mathrm{O}\mathrm{M}}_1={\displaystyle \frac{\mathrm{G}\left(\mathrm{d}\mathrm{B}\mathrm{i}\right)}{{\mathrm{A}}_{\mathrm{n}\mathrm{o}\mathrm{r}\mathrm{m}}}}$$

(2)

FOM₂: Efficiency–Bandwidth Product (η × FBW):

$${\mathrm{F}\mathrm{O}\mathrm{M}}_2=\mathsf{\eta }\times \mathrm{F}\mathrm{B}\mathrm{W}, \mathrm{where} \mathrm{F}\mathrm{B}\mathrm{W}={\displaystyle \frac{\mathrm{A}\mathrm{b}\mathrm{s}\mathrm{o}\mathrm{l}\mathrm{u}\mathrm{t}\mathrm{e} \mathrm{B}\mathrm{a}\mathrm{n}\mathrm{d}\mathrm{w}\mathrm{i}\mathrm{d}\mathrm{t}\mathrm{h}}{5.8 \mathrm{G}\mathrm{H}\mathrm{z}}}$$

(3)

Applying these FOMs to the dataset reveals non-obvious insights:

• Substrate-Limited Performance: The performance of the substrate is limited when using high-ε_r materials such as FR-4, which allow designers to create small devices with low A_norm values but yield low FOM₁ values due to increased surface-wave losses and elevated Q-factor. The FR-4 design presented in [20] achieves a FOM₁ of 0.63 dBi, whereas the Rogers RT5880 design described in [21] yields a FOM₁ of 10.42 dBi, resulting in a 16.5× improvement in area-normalized gain.
• Bandwidth–Efficiency Coupling: The research indicates that FOM2 values reach their maximum when designers use proximity-coupled and CPW-fed designs on materials with low-loss properties. The results demonstrate that designers can improve bandwidth performance using design changes that do not decrease efficiency levels. The CPW-fed antenna in [75,76,124] exhibits an η × FBW of 0.268, outperforming Microstrip-fed antennas.
• Array Efficacy: The absolute gain increases with arraying, but FOM1 analysis shows that 2 × 2 arrays on FR-4 [56] only achieve FOM₁ = 2.77 dBi, while optimized single elements on Rogers material achieve FOM₁ values above 10 dBi. The results demonstrate that arraying as a standalone method, without substrate optimization, results in decreased performance density per unit area.

The FOMs establish a quantitative framework that enables users to compare 5.8 GHz MPAs through material, topological, and application-based assessments, while demonstrating that complete system design must precede individual parameter adjustments for future WPT systems.

Figure 10 presents a study that examines how radiation efficiency changes with normalized substrate cost across the surveyed 5.8 GHz MPAs. Each marker represents an antenna design from Tables 4–10, categorized by substrate family: FR-4/FR4 (lowest cost, most common, cost index = 1), flexible materials (Polyimide, Felt, Jeans, etc., cost index = 2), Rogers mid-range ((RT5880, RO3003), cost index = 3), Rogers premium/specialized substrates ((RT5870, Taconic, PTFE, F4B), cost index = 4), and highly specialized materials ((exotic materials, multi-layer), cost index = 5).

3.6. Application-Specific Antennas

3.6.1. Wearable Antennas

Wearable antennas are essential components of Wireless Body Area Networks (WBANs), enabling reliable wireless communication for diverse biomedical and health monitoring applications [147,148,149,150]. Table 10 presents a comprehensive review of recent wearable antenna designs, focusing on dual- and multi-band operation, low Specific Absorption rate (SAR), and mechanical flexibility. The use of artificial magnetic conductors (AMCs) and textile substrates has become a key approach for reducing SAR and improving user comfort, thereby promoting the broader adoption of wearable antennas in WBAN and health-monitoring contexts.

The development of wearable antennas for Wireless Body Area Networks (WBANs) requires a comprehensive understanding of the lossy and dynamic nature of the on-body propagation channel. Electromagnetic waves undergo significant attenuation and distortion when interacting with human tissue, leading to detuning, reduced efficiency, and increased Specific Absorption Rate (SAR), which necessitate advanced engineering solutions. Theoretical modeling with multi-layer human-tissue phantoms is essential for accurately predicting antenna performance and ensuring compliance with safety standards, such as the FCC’s SAR limit of 1.6 W/kg averaged over 1 g of tissue, prior to fabrication and prototyping. Furthermore, it is critical to integrate electromagnetic and mechanical design considerations, as wearable antennas must provide both optimal electrical performance and physical flexibility and durability [149,151]. For instance, the antenna design described in Ref. [152] employs a compact, low-profile geometry combined with a textile electromagnetic bandgap (EBG) structure, resulting in reduced backward radiation, lower SAR, and satisfactory operational performance. Table 10 summarizes various wearable antenna designs characterized by dual- or multi-band operation, low SAR, and improved mechanical flexibility, primarily due to the use of AMC and textile substrates for SAR reduction and user comfort.

Table 10. Wearable antennas operate at 5.8 GHz.

Ref.	No. of Bands	G (dBi)	BW (GHz)	η (%)	SAR (1 g*/10 g)	Substrate/εr	Tech.	Dimension (mm3)	Anorm	hnorm
[89]	dual	6	0.87	91.7	0.872*	Rogers/(NA)	Machine learning	40 × 41 × 1.52	NA	NA
[150]	dual	5.13	∼1	92.3	0.13	RO3003/(3)	NA	41 × 44 × 1.52	1.54	0.0444
[153]	dual	3.35	4.5	82.75	0.511*	fabric/(1.7)	FSS	42 × 43 × 3	0.98	0.0698
[154]	dual	3.2	0.22	91	0.118*	RT5880/(2.2)	NA	7.758 × 5.17 × 0.207	0.03	0.0053
[155]	dual	6.2	0.46	93	0.813*	RO3003/(0.5)	Machine learning	30 × 48.8 × 0.5	1.25	0.0146
[156]	dual	12	1.15	76.4	0.11	Denim (1.72)	DGS	22 × 22 × 1	0.26	0.0234
[157]	Multi	3.3	1.1	82.6	0.765*	RT5880/(2.2)	PG	25 × 40 × 1.5	0.66	0.0386
[158]	dual	8.7	0.45	61.5	1.2*	Poly/(3.4)	AMC	15.6 × 20 × 0.3	0.30	0.0092
[159]	Multi	8.2	0.125	NA	0.84*	RO4003/(3.38)	CPW	43.2 × 43.2 × 4.6	1.76	0.1414
[160]	dual	NA	∼0.2	NA	0.202*	RO3003/(3)	NA	30 × 38 × 1.52	0.97	0.0444
[161]	dual	4.29	0.2	90	1.56*	RT3003C/(3)	NA	28.81 × 19.22 × 1.58	0.47	0.0461
[162]	dual	6.85	0.13	NA	0.016	Polyi/(3.5)	3 × 3 AMC	59.1 × 59.1 × 4.15	3.40	0.1295
[163]	dual	7.665	0.43	96.5	0.33*	RO3003/(3)	4 × 4 AMC	86 × 86 × 1.52	6.31	0.0444
[164]	Single	8.69	0.6	80	0.353	RT5880/(2.2)	2 × 3 AMC	15.27 × 15.27 × 2.2	0.15	0.0566
[165]	Single	9.35	2.2	NA	0.195	Poly/(3.5)	2 × 2 AMC	30 × 30 × 0.1	0.88	0.0031
[166]	dual	3.17	0.6	100	NA	Ultralam 3850/(2.9)	CPW	35 × 20 × 0.1	0.59	0.0029
[167]	dual	NA	0.2	NA	NA	Jeans/(1.6)	PG	64 × 94 × 1	3.11	0.0227
[168]	dual	6.98	0.218	53.6	0.09*	Felt/(1.2)	NA	100 × 100 ×  2	4.22	0.0411
[169]	dual	7.75	0.61	NA	0.75	RO 3003/(3)	4 × 4 AMC	90 × 90 × 33	6.91	0.9638
[170]	Single	3.87	∼0.6	65	NA	Jeans/(1.78)	NA	40 × 40 × 0.6	0.90	0.0142
[171]	Multi	5.2	2.76	NA	NA	Jeans/(1.6)	MTM	60 × 60 × 2	1.86	0.0455

Table 10. Wearable antennas operate at 5.8 GHz.

Ref.	No. of Bands	G (dBi)	BW (GHz)	η (%)	SAR (1 g*/10 g)	Substrate/εr	Tech.	Dimension (mm3)	Anorm	hnorm
[89]	dual	6	0.87	91.7	0.872*	Rogers/(NA)	Machine learning	40 × 41 × 1.52	NA	NA
[150]	dual	5.13	∼1	92.3	0.13	RO3003/(3)	NA	41 × 44 × 1.52	1.54	0.0444
[153]	dual	3.35	4.5	82.75	0.511*	fabric/(1.7)	FSS	42 × 43 × 3	0.98	0.0698
[154]	dual	3.2	0.22	91	0.118*	RT5880/(2.2)	NA	7.758 × 5.17 × 0.207	0.03	0.0053
[155]	dual	6.2	0.46	93	0.813*	RO3003/(0.5)	Machine learning	30 × 48.8 × 0.5	1.25	0.0146
[156]	dual	12	1.15	76.4	0.11	Denim (1.72)	DGS	22 × 22 × 1	0.26	0.0234
[157]	Multi	3.3	1.1	82.6	0.765*	RT5880/(2.2)	PG	25 × 40 × 1.5	0.66	0.0386
[158]	dual	8.7	0.45	61.5	1.2*	Poly/(3.4)	AMC	15.6 × 20 × 0.3	0.30	0.0092
[159]	Multi	8.2	0.125	NA	0.84*	RO4003/(3.38)	CPW	43.2 × 43.2 × 4.6	1.76	0.1414
[160]	dual	NA	∼0.2	NA	0.202*	RO3003/(3)	NA	30 × 38 × 1.52	0.97	0.0444
[161]	dual	4.29	0.2	90	1.56*	RT3003C/(3)	NA	28.81 × 19.22 × 1.58	0.47	0.0461
[162]	dual	6.85	0.13	NA	0.016	Polyi/(3.5)	3 × 3 AMC	59.1 × 59.1 × 4.15	3.40	0.1295
[163]	dual	7.665	0.43	96.5	0.33*	RO3003/(3)	4 × 4 AMC	86 × 86 × 1.52	6.31	0.0444
[164]	Single	8.69	0.6	80	0.353	RT5880/(2.2)	2 × 3 AMC	15.27 × 15.27 × 2.2	0.15	0.0566
[165]	Single	9.35	2.2	NA	0.195	Poly/(3.5)	2 × 2 AMC	30 × 30 × 0.1	0.88	0.0031
[166]	dual	3.17	0.6	100	NA	Ultralam 3850/(2.9)	CPW	35 × 20 × 0.1	0.59	0.0029
[167]	dual	NA	0.2	NA	NA	Jeans/(1.6)	PG	64 × 94 × 1	3.11	0.0227
[168]	dual	6.98	0.218	53.6	0.09*	Felt/(1.2)	NA	100 × 100 ×  2	4.22	0.0411
[169]	dual	7.75	0.61	NA	0.75	RO 3003/(3)	4 × 4 AMC	90 × 90 × 33	6.91	0.9638
[170]	Single	3.87	∼0.6	65	NA	Jeans/(1.78)	NA	40 × 40 × 0.6	0.90	0.0142
[171]	Multi	5.2	2.76	NA	NA	Jeans/(1.6)	MTM	60 × 60 × 2	1.86	0.0455

Figure 11 depicts a flexible, textile-based wearable antenna designed for both on-body and off-body operation at 5.8 GHz. This antenna maintains consistent performance even when subjected to mechanical deformation, such as bending.

3.6.2. Adaptive Capabilities: Reconfigurable Antennas at 5.8 GHz

Reconfigurable Antennas (RAs) enable the effective enhancement of wireless communication by integrating multiple radios into a single platform. Spectral congestion in the 5.8 GHz ISM band poses a significant challenge to the reliability of efficient WPT. Reconfigurable Antennas (RAs) address this by dynamically tuning operating frequency, polarization, or radiation patterns to maintain optimal link budgets. Figure 12 shows reconfigurable antenna types and switching mechanisms [172,173].

As detailed in

Table 11. Comparative analysis of 5.8 GHz Reconfigurable Antennas.

Ref.	Type	Switching Mechanism	Substrate	Gain/Performance	Application
[35]	Polarization	L-Slots	FR-4	3 dB Axial Ratio	RFID/WLAN
[174]	Frequency	PIN Diode	Not Listed	Indoor/Short Range	Communications
[175]	Frequency & Pol.	4 PIN Diodes	Flexible	16 Modes	WBAN (Medical)
[176]	Frequency	PIN Diodes	Not Listed	Multi-mode	ISM/Sub-6GHz
[177]	Radiation Pattern	EBG Structure	Not Listed	Beam shift ± 26°	WPT
[178]	Frequency	PIN Diodes	Flexible	Low SAR	Wearable
[179]	Hybrid (Freq/Pol)	Conformal	Jute Textile	High Peak Gain	Wi-Fi/WiMAX
[180]	Pattern & Pol.	8 PIN Diodes	Not Listed	CP	Medical Terminals

, the dominant switching mechanism for 5.8 GHz RAs remains the PIN diode due to its fast switching speed and ease of integration. Wireless Body Area Networks (WBANs) maintain their dependable network connectivity through PIN diodes, which enable polarization-state switching between elliptical and linear modes, supporting network operation during body movements that alter signal paths. The system development process faces new design challenges due to its active reconfiguration mechanism. PIN diodes enable multi-mode operation between ISM and Sub-6 GHz and S-bands, but they require elaborate DC biasing systems that increase device size and power requirements, thus opposing the goals of energy harvesting systems.

The current state of technology uses Hybrid Reconfiguration to reduce these limitations by combining mechanical flexibility with electronic switching systems. Studies demonstrate that jute textile RAs achieve their peak performance through their flexible design, which supports multiple wireless standards, including Wi-Fi and WiMAX, through physical transformations and electronic signal modifications. The implementation of Electromagnetic Bandgap (EBG) structures within pattern-reconfigurable designs enables precise beam steering, which is essential for achieving maximum power transfer efficiency when targeting moving targets such as UAVs and mobile sensors.

In the crowded 5.8 GHz ISM band, Frequency Reconfigurability avoids interference from Wi-Fi routers [181,182,183,184]. Pattern Reconfigurability steers the beam toward the energy receiver (crucial for WPT efficiency) [173,185,186]. Polarization Reconfigurability aligns the antenna with the receiver to prevent polarization mismatch loss [173,187,188]. Table 11 compares reconfigurable antenna types, switching mechanisms (mainly PIN diodes), and substrates. Hybrid and textile-based reconfiguration are emerging trends for multi-mode, low-power, and wearable applications.

3.6.3. Integrated Energy Harvesting: 5.8 GHz Rectenna Systems

Typically, the rectenna plays a crucial role in the RF energy-harvesting system. It is composed of a receiving antenna and a rectifier. The antenna captures the surrounding RF energy, while the rectifier converts the harvested RF power into DC power, as shown in Figure 13 [36,84,189]. The performance of 5.8 GHz energy harvesting systems is primarily governed by the Power Conversion Efficiency (PCE) of the rectification circuit and the impedance matching between the antenna and the non-linear diode junction. Unlike lower-frequency bands, 5.8 GHz rectennas experience significant substrate losses and parasitic capacitance. As shown in

Table 12. Rectenna operates at 5.8 GHz.

Ref.	Rectifier Topology	PCE	Dimension mm3	Pin (dBm)/ Vout (mV)	Load (KΩ)
[10]	Voltage Doubler & HSMS-286B	74	60 × 10 × 1.575	20/385	2.2
[52]	Schottky diode	78.4	NA	20/5876	0.65
[190]	HSMS2850 diodes	84.1	18 × 13.2 × 0.8	NA	1
[191]	Voltage Doubler	39.2	NA	−10/659	20
[192]	π-shaped & HSMS2860	61	32 × 48 × 1.6	16/∼700	0.300
[193]	HSMS-285C	NA	51.72 × 50 × 1.6	−1/691.505	5.1
[194]	HSMS- 285C	74.38	NA	10/334	1.5
[195]	SMS7630-079LF	15	40 × 40 × 2.4	−10/250	10
[196]	SMS 7630	52.55	58.1 × 61.2 × 0.76	5/915	1.8
[197]	HSMS-286C	82	88 × 31 × 1.524	5.91/383	1.5
[198]	Schottky diode	47	NA	30/∼100	0.16
[199]	HSMS-285x	60	50 × 50 × 1	−3/∼500	1
[200]	HSMS-286B	24	NA	−10/1800	1
[201]	SMS 7630	61	142.76 × 39.31 × 1.034	NA/1799	NA
[202]	NA	NA	140 × 90 × 1.6	NA	NA
[203]	Schottky diodes	82.4	NA	NA	NA
[204]	SMS7630	29	65 × 95 × 0.787	0/656.88	0.5

, the Schottky diode (specifically the HSMS-28xx and SMS-7630 series) remains the industry standard due to its low turn-on voltage and fast switching speed. However, a critical design challenge identified in recent literature is PCE’s sensitivity to input power levels and load resistance. While single-series diode topologies are simple to fabricate, they often suffer from poor efficiency at fluctuating input powers. Consequently, recent research has shifted toward Voltage Doubler and Class-F topologies. Furthermore, integrating Defected Ground Structures (DGS) into the rectenna design has proven effective in suppressing higher-order harmonics generated by the diode, which would otherwise be re-radiated and reduce the overall system efficiency.

Figure 14 shows how frequently different rectifier approaches appear in the papers studied. The HSMS-285x Schottky diode family appears in seven research studies, demonstrating its position as a common component in 5.8 GHz rectenna investigations, as it is a commercial product with established SPICE models and operates effectively at microwave frequencies. The evaluation of component popularity requires separate analysis from the assessment of circuit topology efficiency. For instance, the “Voltage Doubler” is a circuit topology that can be realized using various diodes, including the HSMS-285x. The Power Conversion Efficiency (PCE) serves as the actual performance metric because it requires all elements of the selected topology to work together with the diode characteristics, the impedance-matching network, and the input power level, as shown in Table 12. The information presented in Table 12 enables efficiency comparisons among different rectifier designs, although Figure 14 shows typical design options used in practice. Therefore, while Figure 14 usefully identifies common design choices in the field, Table 12 provides the essential data for evaluating and comparing rectifier efficiency.

Figure 15 presents a comparative study of four rectifier substrate types, evaluating their Power Conversion Efficiency (PCE) and representation in the academic literature (number of papers). It illustrates a divergence in research motivation: while high-performance substrates like Roger are studied for their efficiency, low-cost, highly available materials like FR4 are studied extensively for their widespread applications, resulting in the most complete documentation of efficiency values.

Furthermore, the choice of substrate is a foundational decision in MPA design, critically influencing cost (1—very low, 2—low-medium, 3—medium, 4—medium–high, 5—high, 6—very high), performance, and application suitability. A comparison of key materials is presented in

Table 13. Performance comparison for substrates.

Ref.	Substrate Material	Material Name	${\mathsf{\epsilon }}_{\mathbf{r}}$	Loss Tangent tan δ	Cost	Applicable Scenarios
[205]	Rigid Laminate	FR-4 (Standard)	4.2–4.8	0.015–0.025	1	General-purpose IoT, Wi-Fi, Consumer Electronics.
[206,207]	Rigid Laminate	Rogers RO4003C	3.38 ± 0.05	0.0027 @ 10GHz	3	5G, Automotive Radar, High-Reliability RF, Base Stations.
[208]	Rigid Laminate	RT/duroid 5880	2.20 ± 0.02	0.0009 @ 10GHz	5	mmWave, Satellite Comms, Precision Microwave.
[209]	Flexible Polymer	Kapton (Polyimide)	3.2–3.5	0.002–0.012	4	Aerospace, Medical Implants, Solderable Flex Circuits.
[210,211]	Flexible Polymer	PET	~2.8–3.0	0.015–0.025	2	RFID Tags, Smart Packaging, Disposable Sensors.
[212,213]	Flexible Polymer	PDMS	2.65–2.75	0.02–0.057	2	Skin-mounted sensors, Stretchable Electronics, Encapsulation.
[214,215,216]	Textile	Jeans (Denim)	1.6–1.7 (Dry)	0.02–0.08	2	Smart Clothing, Body-Centric Comms (requires encapsulation).
[217]	Textile	Felt	1.2–1.45	0.016–0.02	2	Wearable Patches, Winter Wear integration.
[94,218,219]	Emerging	3D Printed PLA	1.2 (Low Infill)–2.9 (Solid)	0.005–0.02	6	Rapid Prototyping, Lens Antennas, Conformal Shapes.
[219,220]	Emerging	3D Printed ABS	2.2–3.0 (Solid)	0.005–0.03	6	Rugged Prototypes, Drone Airframes.
[221,222,223,224]	Emerging	Graphene Oxide	Highly Variable (10–100+)	0.1–0.7 (Lossy)	6	EMI Shielding, Absorbers, Tunable Devices.

.

3.7. Critical Analysis and Figures of Merit

To objectively compare the diverse 5.8 GHz MPA designs surveyed in Table 4, Table 5, Table 6, Table 7, Table 8 and Table 9, we introduce two normalized Figures of Merit (FOMs). The first measurement enables researchers to calculate gain per unit area (G/A) through a mathematical process that involves dividing peak gain (dBi) by the electrical area of the antenna (A/λ02), where λ₀ is the free-space wavelength at 5.8 GHz. The measurement shows how well designs can achieve high-gain performance within small electrical dimensions. The second metric, which combines Efficiency-Bandwidth Product (η × FBW), shows how radiation efficiency affects the width of the impedance bandwidth.

Analyzing the data with these FOMs reveals non-obvious trends. High-permittivity substrates such as FR-4 enable miniaturization, but they lead to reduced G/A and bandwidth because surface-wave losses increase and the Q-factor rises, which measures the ratio of stored energy to dissipated energy. The physical dimensions of RT5880-based antennas do not affect their ability to achieve better G/A values, as these antennas maintain their high efficiency. The η × FBW product indicates that bandwidth enhancement becomes possible through proximity coupling and CPW feeding methods when using low-loss substrates that maintain efficiency levels. The research establishes a quantitative framework that enables the evaluation of antenna performance under material and geometric variations for 5.8 GHz WPT systems. The design process for 5.8 GHz WPT systems requires a comprehensive FOM-based methodology to achieve better antenna performance.

4. Advanced Optimization Strategies for 5.8 GHz MPAs

Optimizing Microstrip Patch Antennas (MPAs) for the 5.8 GHz ISM band requires balancing miniaturization with radiation efficiency. Standard patch topologies often suffer from surface wave excitation and narrow impedance bandwidths. Recent literature highlights three primary avenues for optimization: structural modification (DGS/EBG), material innovation (Metamaterials/Nanomaterials), and computational intelligence (Machine Learning).

In this study, Figure 16 summarizes the optimization techniques used to enhance MPA, providing effective solutions to overcome all those challenges.

4.1. Surface Wave Suppression: EBG and DGS

High-permittivity substrates, while useful for miniaturization, often trap energy in the form of surface waves, degrading the radiation pattern. Electromagnetic Bandgap (EBG) structures address this by introducing a high-impedance surface that suppresses surface wave propagation. Research indicates that mushroom-like EBG structures are particularly effective at reducing mutual coupling in 5.8 GHz MIMO arrays, improving isolation by more than 10 dB compared to standard ground planes. Conversely, Defected Ground Structures (DGS) offer a subtractive manufacturing approach to manipulate current distribution. By etching specific geometries (dumbbells, U-slots) into the ground plane, the transmission line’s effective capacitance and inductance are altered. The size-reduction and harmonic-suppression capabilities of DGS are excellent, but the technology produces back-lobe radiation because of ground plane leakage, which requires special handling to keep wearable devices within SAR limits. The compact design of EBG and DGS harmonic filters operates as fundamental harmonic filters, achieving peak Power Conversion Efficiency (PCE) due to their built-in structure.

4.2. Gain Enhancement: Metamaterials and Shorting Pins

The small 5.8 GHz antennas can achieve gain restrictions using Metamaterials (MTM) technology, which uses Split Ring Resonators (SRRs) as its fundamental element. MTMs differ from conventional dielectrics because they possess a negative refractive index, which enables them to focus energy while providing 3–4 dBi of antenna gain enhancement without requiring larger antenna sizes. The shorting pins function as inductive loading elements, enabling 5.8 GHz operation with minimal physical patch dimensions for applications that require extreme size reduction. The method produces a restricted impedance bandwidth, so designers need to use either multiple-layer structures or thick substrate materials to restore bandwidth.

4.3. Computational Optimization: Machine Learning (ML)

The 5.8 GHz antenna needs complex full-wave simulations (HFSS and CST) to achieve its optimal performance. The current trend involves using Machine Learning (ML) to develop surrogate models that predict antenna performance parameters (S11, gain) at a significantly faster rate than before. The design process for antennas now uses Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) to perform ‘inverse design’, generating antenna shapes based on specified performance requirements. The models lack generalization ability because they need to be retrained for every new geometric shape they encounter. The summary steps for ML-based antenna optimization are presented in Figure 17.

4.4. Material Innovation: Nanomaterials

The transition toward flexible and conformal electronics has driven the adoption of nanomaterials such as Graphene and Carbon Nanotubes (CNTs). These materials offer high mechanical flexibility and tunable conductivity, making them ideal for wearable 5.8 GHz sensors.

The mechanical strength of graphene-based antennas remains high, but their radiation efficiency remains lower than that of copper antennas because conductive inks produce higher sheet resistance. Scientists have developed carbon-based conductive pastes through recent studies to address this problem by creating affordable, printable materials that exhibit improved RF performance for building large-scale, flexible electronic systems [225].

The basic relationship between material flexibility and RF efficiency emerges from the natural electrical characteristics, which include Electrical Conductivity (σ), Typical Sheet Resistance, Skin Depth, and Dielectric Loss Tangent (tan δ). A comparison of key parameters with the conventional benchmark, copper, is provided in Table 13.

The data compiled in

Table 14. Comparison of conductive materials for RF applications.

Material/Form	σ (MS/m)	sheet R (Ω/sq)	δ (μm)	tan (δ)	Primary RF Performance Trade-Off
Copper (Bulk, thin-film) [226,227]	~5.8	~1.68 × 10−2 (for 1 μm thickness)	~0.87	NA (Conductor)	Lowest RF loss, highest efficiency. Lacks flexibility and is corrosion-prone.
Graphene (CVD monolayer) [228,229]	~1–10	30–1000	~0.1–2.8	~0.002–0.01 (on substrate)	High intrinsic mobility and transparency, but high contact resistance and challenging large-scale, uniform deposition degrades RF performance.
Carbon Nanotube (CNT) Mats/Inks [226,230,231]	~10−2 –1	10–500 (depends on density, alignment, thickness)	~2–20	0.01–0.05 (composite-dependent)	Excellent flexibility and stretchability. Low bulk conductivity and high junction resistance between tubes lead to significantly higher ohmic loss than copper.
Conductive Polymer (e.g., PEDOT:PSS) [232,233]	~10−5–10−3	50–5000	>100	0.02–0.1	High flexibility and printability. Very high resistivity makes them unsuitable as primary radiating elements at 5.8 GHz; used mainly as interconnects or in hybrid designs.

show that nanomaterials exhibit superior mechanical properties, yet their electrical characteristics lead to increased ohmic losses when operating at 5.8 GHz. These results demonstrate the efficiency loss, as shown in Table 14, and confirm that scientists need to develop new methods for making nanomaterials and printing RF-grade materials.

Recent antenna design developments have placed greater emphasis on using nanomaterials, such as graphene and CNTs, on low-cost substrates, including paper, Kapton, PMMA, and PDMS. This enables flexible, highly efficient, and low-cost solutions for wireless communications, wearables, and IoT. For example, ref. [218] proposed a graphene printed flexible and conformal array antenna on a paper substrate targeting 5.8 GHz wireless communication with an achieved 73% radiation efficiency, and demonstrated that graphene could be a suitable replacement for metals at low cost due to its high conductivity and eco-friendly characteristics. Similarly, ref. [234] presented a graphene inkjet-printed ultrawideband tapered coplanar-waveguide antenna on Kapton, covering 2.7–8.2 GHz with more than 84% efficiency, and pointed out the role of inkjet printing in scalable low-cost fabrication for wearables. Ref. [235] proposed a graphene printed tri-band antenna array on paper for wireless applications, offering a peak gain of 2.14 dBi and demonstrating the use of sustainable materials for 5G and WLAN systems. Ref. [236] optimized the performance of microstrip antennas using a substrate made of PMMA and CNT conductive material in the sub-6 GHz frequency band, yielding compact designs with gains higher than 5 dBi and bandwidths up to 500 MHz suitable for state-of-the-art networks with significant reduction of material costs. The authors of [237] proposed flexible composite wearable antennas doped with Al2O3 and PTFE in PDMS, targeting global wireless systems covering the band from 0.99 GHz to 9.41 GHz, and demonstrated enhanced durability at a low production cost. Ref. [225] developed cost-effective conductive pastes using carbon-based materials for radiofrequency devices, with optimal conductivity achieved at lower filler concentrations to reduce environmental impact and minimize costs in the fabrication of printed Wi-Fi antennas. Ref. [238] reviewed nanomaterial-based wearable antennas and mentioned that the flexibility of structures like CNTs and graphene on the low-budget substrate is superior. Ref. [9] designed a dual-band CPW graphene antenna on glass for smart cities and IoT covering 2.45 GHz and 4–7 GHz bands and providing low-cost integration. Ref. [239] enhanced slotted microstrip antennas using metallic nanofilms for WLAN. Finally, Ref. [11] characterized MWCNT/PDMS composite MIMO antennas for wearable and vehicular applications, achieving 7.61 dBi gain with low SAR values, thereby validating the affordability and performance of nanomaterials across diverse scenarios.

Table 15. Comparison of optimization techniques for MPAs.

Ref.	Optimization Technique	Gain Impact (dBi)	Impact on Bandwidth	Size Reduction	Cost/Complexity	Primary Benefit	Primary Drawback
[240,241,242]	EBG	+1 to +3	Decreases slightly (Narrows resonance)	Low (Increases footprint)	Medium-High (Periodic patterns)	Suppresses surface waves; Improves isolation	Increases fabrication complexity
[128,243,244,245]	DGS	−0 to +2	Increases FBW by 10–30%	Moderate (20–40%)	Low (Simple etching)	Miniaturization; BW control	Increases back-lobe radiation
[246,247,248,249]	Metamaterial (MTM)/FSS	+2 to +5	Decreases (High-Q resonance)	High (30–50% loading)	High (Complex unit cells)	High Gain; Miniaturization	Narrow bandwidth; Lossy
[250,251,252]	Shorting Pins	Neutral	increase by exciting additional resonant modes	Compact	low-cost, and low complexity	Significant size reduction	Increased fabrication complexity and cost
[155,253,254]	Machine Learning	NA	Indirect (Optimization target)	Indirect (Optimization target)	Variable (High R&D, low iteration)	rapid optimization	large training datasets
[223,238,255]	Nanomaterials	−2 to −5	Minimal direct impact	Enables ultra-thin/conformal	Very High (Specialized deposition)	Flexibility; Tunability	Higher ohmic losses

compares optimization strategies (EBG, DGS, Metamaterials, shorting pins, ML, nanomaterials) and summarizes their benefits, drawbacks, and typical gain impact. Metamaterials offer the highest gain, DGS enables miniaturization, and ML accelerates design cycles.

5. Discussion and Future Work

Following the comprehensive review of 5.8 GHz Microstrip Patch Antennas (MPAs) for Wireless Power Transfer (WPT), this section synthesizes the collective findings, critically analyzes the inherent performance trade-offs, and proposes a strategic roadmap to guide future high-impact research.

5.1. Performance Trade-Offs and Synthesis of Current Trends

The evaluation of current MPA designs, summarized in Section 3.6, demonstrates that the 5.8 GHz ISM band imposes essential yet opposing requirements. The design landscape depends on three essential trade-offs, which determine its structure:

• Gain vs. Miniaturization: The system needs high-gain applications to perform WPT across long distances and for UAV power supply, which requires array configurations to achieve gains above 12 dBi, but this method violates the core advantage of single-element MPAs, which enable portable devices to remain compact.
• Bandwidth vs. Simplicity: The main trade-off between bandwidth and simplicity stems from ML feeds remaining a popular, low-cost solution that achieves only 2–3% bandwidth utilization. The process of achieving Ultra-Wideband (UWB) operation demands sophisticated feeding structures and optimization methods (e.g., CPW feeds provide up to 40% bandwidth), which make fabrication more complicated and reduce radiation efficiency.
• Safety vs. Efficiency in Wearables: Wearables’ operational efficiency must meet their safety requirements. The Specific Absorption Rate (SAR) of wearable and implantable devices needs to be measured at 1 g levels to remain below 1.6 W/kg. Achieving this goal requires specific methods, including AMC backing and flexible substrates, but these materials and structures introduce losses that force designers to reduce both peak gain and total efficiency.

5.2. Identified Research Gaps: Barriers to Next-Generation WPT

The built-in trade-offs that establish design boundaries reveal specific knowledge deficiencies that block the creation of peak WPT systems. The extensive research conducted in this research showed three essential obstacles that need to be addressed, which are:

• Directivity and Radiation Pattern Characterization: The current body of research faces two main issues: either it fails to present directivity (D) measurements, or it provides only limited information about directivity. This metric requires exact, standardized reporting because it reflects the antenna’s actual performance through its beam-forming capability and directional WPT link efficiency. The evaluation process for WPT systems becomes more complicated because detailed 3D radiation pattern analysis is often missing, which prevents the determination of beam shape and side-lobe suppression performance.
• Simulation-to-Prototype Validation: The present system fails to perform adequate validation, making it impossible for researchers to verify the accuracy of their simulated results against their experimental data. Extensive research studies rely solely on Computer Simulation Technology (CST) and High-Frequency Structure Simulator (HFSS) results. However, they fail to account for the actual differences caused by fabrication errors, soldering defects, and changes in material properties in physical prototypes.
• Comprehensive Efficiency Analysis: Evaluating complete efficiency requires researchers to study gains, but they need to develop a more comprehensive method for assessing efficiency. Future research needs to develop specific methods that will enable scientists to measure the complete system efficiency.
• SAR Standardization in Medical Applications: Medical applications (e.g., WBAN, implantable) require SAR standardization because MPAs in biomedical research face a lack of complete SAR evaluation methods. New designs must follow all established boundaries, including FCC limits of 1.6 W/kg over 1 g, and must perform complete simulations using actual multi-layer human tissue phantoms 24.
• Flexibility and Bending Characterization: The mechanical behavior of wearable antennas requires researchers to study their response to bending, folding and compression forces. The development of research methods requires studying how mechanical stress affects the electrical performance of flexible designs through impedance matching and gain measurement, while using bending radius (R_mm) as a measurement standard.
• Substrate Innovation: The current market relies heavily on standard substrate materials, including FR4 and Rogers. The need for exploratory research arises because it new materials must be identified, including nanomaterials (Graphene and CNTs) and affordable, flexible textiles (Jeans and Felt), to address the problems that standard dielectrics create.
• Machine Learning for Multi-Objective Design: The field of antenna design has not yet fully incorporated Machine Learning (ML) technology. The current applications of ML systems focus on achieving a single optimization goal, typically maximizing gain. The development of advanced ML algorithms requires immediate attention because these systems need to handle multiple opposing performance targets, including gain, bandwidth, and miniaturization, using data generated from tested prototypes.
• Intelligent Adaptive WPT Systems: The next generation of WPT needs to develop into intelligent adaptive systems that automatically track targets that move through space. The 5.8 GHz power beam of retrodirective arrays functions as a basic hardware component that uses an interrogating signal to direct the beam toward devices, thereby maximizing power delivery efficiency within the specified sector. The future development plan must focus on creating Computational Intelligence-based Adaptive Rectenna Systems, which will unite Generative Inverse Design with ML and FR/PR/RP and array technology (phased arrays/retrodirective principles) to achieve dependable power transmission in actual operational environments.

5.3. Strategic Future Research Directions

The research path for 5.8 GHz MPAs needs to concentrate on three essential areas, which were identified as research gaps:

5.3.1. Advanced Hybrid Antenna Structures

• DGS/EBG Backing for Arrays: The development of compact arrays requires DGS or EBG structures that place elements under structures to improve both isolation and surface wave suppression and generate superior boresight gain than single-element integration.
• Reconfigurable Integrated Modules: The system needs to combine Frequency (FR), Polarization (PR), and Radiation Pattern (RP) reconfigurability using PIN diodes or RF-MEMs to develop an adaptive single-platform solution that operates at 5.8 GHz band.
• Shared-Aperture and Stacked Multifunctional Designs: The development of low-profile integrated modules that combine WPT with other RF functions and WLAN communication through one aperture stands as a crucial need for constructing small IoT devices. The strategic layer stacking method with shared radiator elements allows systems to operate at 5.8 GHz and surrounding frequency bands, which leads to smaller system sizes and reduced implementation costs. The development of these co-designed multifunctional platforms achieved a major advancement that surpassed the optimization of individual WPT antennas.

5.3.2. Performance-Driven Material Engineering

• Tunable Nanomaterials as Active Layers: Investigate Graphene/CNT thin films as electrically or mechanically tunable layers, enabling real-time polarization or frequency reconfigurability without discrete switches.
• 3D-Printed/Textile Substrates: Accurately characterize and model 3D-printed and flexible textile substrates to develop new design methodologies for high-performance, cost-effective, and conformal antennas. Scientists use new manufacturing approaches to create substrates and antennas because 3D printing technology has evolved through modern manufacturing developments. 3D printing technology allows users to produce complex shapes, which include curved substrates, graded dielectric structures, and embedded cavities that cannot be made with regular PCB laminates. The system enables researchers to perform new geometric optimization tasks, which include creating wearable devices through conformal wrapping and developing engineered dielectrics to improve bandwidth performance. The combination of additive manufacturing techniques with performance modeling systems will create new possibilities for antenna design, enabling the rapid development of customized high-performance 5.8 GHz WPT systems.

5.3.3. Full WPT System Integration and Verification

This direction emphasizes treating the antenna and rectifier as a unified system, moving away from isolated component testing.

• PCE-Centric Rectenna Optimization: The primary design objective must change from achieving maximum antenna gain (G) to enhancing the complete Power Conversion Efficiency (PCE) of the rectenna system. The matching network, antenna, and rectifier circuit (including Schottky diodes) must be designed and simulated simultaneously for this to operate. The system needs to operate at its fundamental and harmonic frequencies because it achieves its highest non-linear impedance matching performance when input power density remains low, and load conditions change. The system needs to achieve its best non-linear impedance matching performance for both fundamental and harmonic frequencies under working conditions of low input power density and load changes.
• Real-World Channel and Misalignment Testing: The testing process needs to include actual operational scenarios, which include misalignment tests that go beyond anechoic chamber capabilities to evaluate system behavior under real-world conditions, such as body-worn and indoor environments with obstacles. The research needs to investigate how WPT link performance deteriorates because of the following three main factors that affect IoT and mobile applications: misalignment, channel fading, and dynamic movement.

5.3.4. Next-Generation Computational Methods

The design cycle needs to be accelerated through multi-objective optimization complexity management, which requires advanced computational tools for integration.

• Generative Machine Learning for Inverse Design: The inverse design problem in antenna design needs deep learning models, which include DNNs and GANs, to operate as generative machine learning tools. The model needs to generate an optimal MPA geometry that matches specific performance requirements instead of using geometry to forecast results.
• Creation of Open-Source Datasets: The research community needs to unite to create open-source datasets that will address the present challenge of lacking training data availability. The datasets need to link MPA shapes with their material properties and established performance measurements, which were both computer-simulated and physically measured.

6. Conclusions

This review has systematically synthesized existing knowledge about 5.8 GHz Microstrip Patch Antennas (MPAs), which operate for Wireless Power Transfer (WPT), to establish a direct route from basic design concepts to sophisticated optimization techniques. The research reveals that MPA performance at the considered frequency is governed by essential trade-offs between several important parameters, including high gain versus small size, wide bandwidth versus complex design, efficient radiation versus safe user operation. The assessment of MPA architectures begins with single-element patches, followed by MIMO arrays and integrated rectennas, demonstrating that the current designs fail to fulfill all requirements for modern WPT systems. Selecting the best option depends on the particular use case, which includes biomedical sensor applications, high-gain UAV power link, and flexible wearable device requirements.

The review demonstrates that optimization techniques, which include uniting DGS miniaturization methods with EBG isolation techniques, Metamaterials gain enhancement methods, and Machine Learning design optimization methods that can generate transformative results. However, the field faces two main challenges, as researchers use standard materials but their specially designed prototypes show declining operational performance.

This review identifies key strategic paths that connect current knowledge to future developments. The research needs to advance in four main areas, which include Hybrid and Reconfigurable Systems, Material-Centric Innovation, System-Level Co-Design and Validation, and Next-Generation Computational Tools. By addressing these essential areas, we can achieve better performance levels, which will enable 5.8 GHz MPAs to reach their full operational potential for future Wireless Power Transfer systems.