Search Results (746)

The swift advancement of fifth-generation (5G) wireless technology brings forth a range of enhancements to address the increasing demand for data, the proliferation of smart devices, and the growth of the Internet of Things (IoT). This highly interconnected communication environment necessitates using multiple-input multiple-output (MIMO) systems to achieve adequate channel capacity. In this article, a 2-port MIMO system using two flipped parallel 1 × 2 arrays and a 2-port MIMO system using two opposite 1 × 4 arrays designed and fabricated antennas for 5G wireless communication in the sub-6 GHz band, are presented, overcoming the limitations of previous designs in gain, radiation efficiency and MIMO performance. The designed and fabricated single-element antenna features a circular microstrip patch design based on ROGER 5880 (RT5880) substrate, which has a thickness of 1.57 mm, a permittivity of 2.2, and a tangential loss of 0.0009. The 2-port MIMO of two 1 × 2 arrays and the 2-port MIMO of two 1 × 4 arrays have overall dimensions of 132 × 66 × 1.57 mm³ and 140 × 132 × 1.57 mm³, respectively. The MIMO of two 1 × 2 arrays and MIMO of two 1 × 4 arrays encompass maximum gains of 8.3 dBi and 10.9 dBi, respectively, with maximum radiation efficiency reaching 95% and 97.46%. High MIMO performance outcomes are observed for both the MIMO of two 1 × 2 arrays and the MIMO of two 1 × 4 arrays, with the channel capacity loss (CCL) ˂ 0.4 bit/s/Hz and ˂0.3 bit/s/Hz, respectively, an envelope correlation coefficient (ECC) ˂ 0.006 and ˂0.003, respectively, directivity gain (DG) about 10 dB, and a total active reflection coefficient (TARC) under −10 dB, ensuring impedance matching and effective mutual coupling among neighboring parameters, which confirms their effectiveness for 5G applications. The three fabricated antennas were experimentally tested and implemented using the MIMO Application Framework version 19.5 for 5G systems, demonstrating operational effectiveness in 5G applications. Full article

Traditional 3D millimeter-wave radars lack target height information, leading to identification failures in complex scenarios. Upgrading to 4D millimeter-wave radars enables four-dimensional information perception, enhancing obstacle detection and improving the safety of autonomous driving. Given the high cost-sensitivity of in-vehicle radar systems, single-chip 4D millimeter-wave radar solutions, despite technical challenges in imaging, are of great research value. This study focuses on developing single-chip 4D automotive millimeter-wave radar, covering system architecture design, antenna optimization, signal processing algorithm creation, and performance validation. The maximum measurement error is approximately ±0.2° for azimuth angles within the range of ±30° and around ±0.4° for elevation angles within the range of ±13°. Extensive road testing has demonstrated that the designed radar is capable of reliably measuring dynamic targets such as vehicles, pedestrians, and bicycles, while also accurately detecting static infrastructure like overpasses and traffic signs. Full article

Terahertz (THz) wireless communications can support ultra-high data rates and secure wireless links with miniaturized devices for unmanned aerial vehicle (UAV) communications. In this paper, a three-dimensional (3D) non-stationary geometry-based stochastic channel model (GSCM) is proposed for multiple-input multiple-output (MIMO) communication links between the UAVs in the THz band. The proposed channel model considers not only the 3D scattering and reflection scenarios (i.e., reflection and scattering fading) but also the atmospheric molecule absorption attenuation, arbitrary 3D trajectory, and antenna arrays of both terminals. In addition, the statistical properties of the proposed GSCM (i.e., the time auto-correlation function (T-ACF), space cross-correlation function (S-CCF), and Doppler power spectrum density (DPSD)) are derived and analyzed under several important UAV-related parameters and different carrier frequencies, including millimeter wave (mmWave) and THz bands. Finally, the good agreement between the simulated results and corresponding theoretical ones demonstrates the correctness of the proposed GSCM, and some useful observations are provided for the system design and performance evaluation of UAV-based air-to-air (A2A) THz-MIMO wireless communications. Full article

Massive MIMO has emerged as a key enabler in modern wireless communication, delivering unparalleled spectral efficiency and connectivity. Yet, as antenna arrays become larger, significant obstacles arise in handling channel state information (CSI) feedback and the computational burden. This paper proposes a groundbreaking angular-domain transmission method that transitions from the conventional time–frequency domain to the angular domain. By employing projection-based transforms, akin to the FFT-based OFDMA model that introduced frequency-domain transmission with subcarriers, this technique exploits the inherent sparsity of massive MIMO channels in the angular domain, enabling data flows to be seamlessly mapped onto physical paths or rays. The resulting sparsity reduces signaling overhead and streamlines system complexity, making massive MIMO viable for next-generation networks. Simulation and empirical studies highlight how angular-domain strategies reduce feedback requirements, support Tera-bps data rates, and facilitate scalable designs for ultra-large-scale MIMO. Full article

THz communication stands as a pivotal technology for 6G networks, designed to address the critical challenge of data demands surpassing current microwave and millimeter-wave (mmWave) capabilities. However, realizing Tbps and kilometer-range transmission confronts the “dual attenuation dilemma” comprising severe free-space path loss (FSPL) (>120 dB/km) and atmospheric absorption. This review comprehensively summarizes our group′s advancements in overcoming fundamental challenges of long-distance THz communication. Through systematic photonic–electronic co-optimization, we report key enabling technologies including photonically assisted THz signal generation, polarization-multiplexed multiple-input multiple-output (MIMO) systems with maximal ratio combining (MRC), high-gain antenna–lens configurations, and InP amplifier systems for complex weather resilience. Critical experimental milestones encompass record-breaking 1.0488 Tbps throughput using probabilistically shaped 64QAM (PS-64QAM) in the 330–500 GHz band; 30.2 km D-band transmission (18 Gbps with 543.6 Gbps·km capacity–distance product); a 3 km fog-penetrating link at 312 GHz; and high-sensitivity SIMO-validated 100 Gbps satellite-terrestrial communication beyond 36,000 km. These findings demonstrate THz communication′s viability for 6G networks requiring extreme-capacity backhaul and ultra-long-haul connectivity. Full article

In modern wireless communication systems, achieving high isolation and consistent signal gain is essential for optimizing Multiple-Input Multiple-Output (MIMO) antenna performance. This study presents a metamaterial-integrated smart sensor platform featuring a hexagonal two-element MIMO antenna designed to improve isolation and directive gain. Constructed on an FR4 substrate (1.6 mm thick), the proposed antenna configurations include a base hexagonal patch, an orthogonally oriented two-element system (TEH_OC), and further enhanced variants employing metamaterial arrays as the superstrate and reflector (TEH_OC_MTS and TEH_OC_MTR). The metamaterial structures significantly suppress mutual coupling, yielding superior diversity parameters such as Envelope Correlation Coefficient (ECC), Mean Effective Gain (MEG), and Channel Capacity Loss (CCL). All configurations were fabricated and validated through comprehensive anechoic chamber measurements. The results demonstrate robust isolation and radiation performance across the 3 GHz and 5 GHz bands, making these antennas well-suited for deployment in compact, low-latency smart sensor networks operating in 5G and IoT environments. Full article

Cell-free massive multiple-input multiple-output (CF M-MIMO) is one of the most promising technologies for future wireless communication such as 5G and beyond fifth-generation (B5G) networks. It is a type of network technology that uses a massive number of distributed antennas to serve a large number of users at the same time. It has the ability to provide high spectral efficiency (SE) as well as improved coverage and interference management, compared to traditional cellular networks. However, estimating the channel with high-performance, low-cost computational methods is still a problem. Different algorithms have been developed to address these challenges in channel estimation. One of the high-performance channel estimators is a phase-aware minimum mean square error (MMSE) estimator. This channel estimator has high computational complexity. To address the shortcomings of the existing estimator, this paper proposed an efficient phase-aware element-wise minimum mean square error (PA-EW-MMSE) channel estimator with QR decomposition and a precoding matrix at the user side. The closed form uplink (UL) SE with the phase MMSE and proposed estimators are evaluated using MMSE combining. The energy efficiency and area throughput are also calculated from the SE. The simulation results show that the proposed estimator achieved the best SE, EE, and area throughput performance with a substantial reduction in the complexity of the computation. Full article

Terahertz (THz) communication is regarded as a promising technology for future 6G networks because of its advances in providing a bandwidth that is orders of magnitude wider than current wireless networks. However, the large bandwidth and the large number of antennas in THz massive multiple-input multiple-output (MIMO) systems induce a pronounced beam split effect, leading to a serious array gain loss. To mitigate the beam split effect, this paper considers a delay-phase precoding (DPP) architecture in which a true-time-delay (TTD) network is introduced between radio-frequency (RF) chains and phase shifters (PSs) in the standard hybrid precoding architecture. Then, we propose a fast Riemannian conjugate gradient optimization-based alternating minimization (FRCG-AltMin) algorithm to jointly optimize the digital precoding, analog precoding, and delay matrix, aiming to maximize the spectral efficiency. Different from the existing method, which solves an approximated version of the analog precoding design problem, we adopt an FRCG method to deal with the original problem directly. Simulation results demonstrate that our proposed algorithm can improve the spectral efficiency, and achieve superior performance over the existing algorithm for wideband THz massive MIMO systems with angular spread. Full article

The pervasive scale of networks brought about by smart city applications has created infeasible energy footprints and necessitates the inclusion of sensing sustained operations with minimal human intervention. Consequently, integrated sensing and communication (ISAC) is emerging as a key technology for 6G systems. ISAC systems realize dual functions using shared spectrum, which complicates interference management. This motivates the development of advanced signal processing and multiplexing techniques. In this context, extremely large antenna arrays (ELAAs) have emerged as a promising solution. ELAAs offer substantial gains in spatial resolution, enabling precise beamforming and higher multiplexing gains by operating in the near-field (NF) region. Despite these advantages, the use of ELAAs increases energy consumption and exacerbates carbon emissions. To address this, NF multiple-input multiple-output (NF-MIMO) systems must incorporate sustainable architectures and scalable solutions. This paper provides a comprehensive review of the various methodologies utilized in the design of energy-efficient NF-MIMO-based ISAC systems. It introduces the foundational principles of the latest research while identifying the strengths and limitations of green NF-MIMO-based ISAC systems. Furthermore, this work provides an in-depth analysis of the open challenges associated with these systems. Finally, it offers a detailed overview of emerging opportunities for sustainable designs, encompassing backscatter communication, dynamic spectrum access, fluid antenna systems, reconfigurable intelligent surfaces, and energy harvesting technologies. Full article

This paper describes a compact multi-port sub-6 GHz multiple-input multiple-output (MIMO) antenna system tailored for 5G NR mobile terminals operating in the n77 (3.3–4.2 GHz), n78 (3.3–3.8 GHz), and n79 (4.4–5.0 GHz) frequency bands. The proposed design leverages a shared coupling approach that exploits the smartphone metal frame as the radiating element, facilitating efficient integration within the spatial constraints of modern mobile devices. A two-stage method is used to mitigate the mutual coupling and correlation issues typically encountered when designing compact MIMO configurations. Initially, a four-port structure is used to evaluate broadband impedance and spatial feasibility. Based on the observed limitations in terms of isolation and the envelope correlation coefficient (ECC), the final configuration was reconfigured as an optimized two-port layout with a refined coupling geometry and effective current path control. The fabricated two-port prototype exhibited a measured voltage standing wave ratio below 3:1 across the n78 band on both ports, with the isolation levels attaining –12.4 dB and ECCs below 0.12. The radiation efficiency exceeded −6 dB across the operational band, and the radiation patterns were stable at 3.3, 3.5, and 3.8 GHz, confirming that the system was appropriate for MIMO deployment. The antenna supports asymmetric per-port efficiency targets ranging from −4.5 to −10 dB. These are the realistic layout constraints of commercial smartphones. In summary, this study shows that a metal frame integrated two-port MIMO antenna enables wideband sub-6 GHz operation by meeting the key impedance and system-level performance requirements. Our method can be used to develop a scalable platform assisting future multi-band antenna integration in mass-market 5G smartphones. Full article

With the rapid development of sixth-generation (6G) wireless networks and large-scale multiple-input multiple-output (MIMO) technology, the number of antennas deployed at base stations (BSs) has increased significantly, resulting in a high probability that users are in the near-field region. Note that it is difficult for the traditional far-field plane-wave model to meet the demand for high-precision beamforming in the near-field region. In this paper, we jointly optimize the power and the number of antennas to achieve the maximum energy efficiency for the users located in the near-field region. Particularly, this paper considers the resolution constraint in the formulated optimization problem, which is designed to guarantee that interference between users can be neglected. A low-complexity optimization algorithm is proposed to realize the joint optimization of power and antenna number. Specifically, the near-field resolution constraint is first simplified to a polynomial inequality using the Fresnel approximation. Then the fractional objective of maximizing energy efficiency is transformed into a convex optimization subproblem via the Dinkelbach algorithm, and the power allocation is solved for a fixed number of antennas. Finally, the number of antennas is integrally optimized with monotonicity analysis. The simulation results show that the proposed method can significantly improve the system energy efficiency and reduce the antenna overhead under different resolution thresholds, user angles, and distance configurations, which provides a practical reference for the design of green and low-carbon near-field communication systems. Full article

This paper presents a compact, high-performance metasurface-based leaky-wave MIMO antenna with dimensions of 40 × 30 mm², achieving a gain of 12.5 dBi and a radiation efficiency of 85%. The antenna enables precise control of electromagnetic waves, featuring a flower-like metasurface (MTS) with coffee bean-shaped arrays on substrates of varying permittivity, separated by a cavity layer to enhance coupling. Its dual-port MIMO design boosts data throughput operating in three bands (3.75–5.25 GHz, 6.4–15.4 GHz, and 22.5–30 GHz), while the leaky-wave mechanism supports frequency- or phase-dependent beamsteering without mechanical parts. Ideal for CubeSat communications, its compact size meets CubeSat constraints, and its high gain and efficiency ensure reliable long-distance communication with low power consumption, which is crucial for low Earth orbit operations. Circular polarization (CP) maintains signal integrity despite orientation changes, and MIMO capability supports high data rates for applications such as Earth observations or inter-satellite links. The beamsteering feature allows for dynamic tracking of ground stations or satellites, enhancing mission flexibility and reducing interference. This lightweight, efficient antenna addresses modern CubeSat challenges, providing a robust solution for advanced space communication systems with significant potential to enhance satellite connectivity and data transmission in complex space environments. Full article

This paper presents a compact four-port multiple-input multiple-output (MIMO) antenna for Internet-of-Things (IoT) devices. As electronic IoT devices become smaller, MIMO antennas should also be compact for ease of integration and multi-port operation for a high channel capacity. Instead of using a single-polarized radiator, which increases the antenna size when scaling to a multi-port MIMO array, a dual-polarized radiator is utilized. This helps to achieve multi-port operation with compact size features. To reduce the mutual coupling between the MIMO elements, an I-shaped defected ground structure is inserted into the ground plane. The measured results indicate that the final four-port MIMO antenna with overall dimensions of 0.92 $\lambda$× 0.73 $\lambda$× 0.03 $\lambda$ at 5.5 GHz can achieve an operating bandwidth of about 2.2% with isolation better than 20 dB and a gain higher than 6.0 dBi. Additionally, the proposed method is also applicable to a large-scale MIMO array. Full article

Millimeter-wave (mmWave) MIMO systems have emerged as a key enabling technology for next-generation wireless networks, addressing the growing demand for ultra-high data rates through the utilization of wide bandwidths and large-scale antenna configurations. Beyond communication capabilities, these systems offer inherent advantages for integrated sensing applications, particularly in scenarios requiring precise object detection and localization. The sparse mmWave channel in the beamspace domain allows fewer radio-frequency (RF) chains by selecting dominant beams, boosting both communication efficiency and sensing resolution. However, existing channel estimation methods, such as learned approximate message passing (LAMP) networks, rely on computationally intensive iterations. This becomes particularly problematic in large-scale system deployments, where estimation inaccuracies can severely degrade sensing performance. To address these limitations, we propose a low-complexity channel estimator using a non-iterative reconstruction network (NIRNet) with a learning-based selection matrix (LSM). NIRNet employs a convolutional layer for efficient, non-iterative beamspace channel reconstruction, significantly reducing computational overhead compared to LAMP-based methods, which is vital for real-time sensing. The LSM generates a signal-aware Gaussian measurement matrix, outperforming traditional Bernoulli matrices, while a denoising network enhances accuracy under low SNR conditions, improving sensing resolution. Simulations show the NIRNet-based algorithm achieves a superior normalized mean squared error (NMSE) and an achievable sum rate (ASR) with lower complexity and reduced training overhead. Full article

A detailed statistical analysis of the total active reflection coefficient (TARC) is carried out in this paper for three 4-port MIMO antennas featuring different levels of isolation across its ports. This analysis is very useful to determine the most likely performance of a MIMO antenna in a real communications scenario. The TARC parameter is commonly evaluated for only several combinations of the random phase with which a signal reaches every input port of a MIMO antenna. By contrast, we have evaluated a million combinations to obtain the probability density function of the TARC, using frequency as its parameter. In this way, an expected value of the TARC is obtained for each frequency, as well as a confidence interval ($\Delta C{I}_{\mathrm{TARC}}$) where the TARC values occur with 90% probability. Additionally, we have introduced the term “TARC shadow”, a visual representation of the TARC as a function of the frequency where the probability function is projected into this 2D graphic with different colors to identify the most likely values of the TARC. To demonstrate these concepts, a full TARC evaluation was performed for three 4-port MIMO antennas with increasing isolation of 12.9 dB, 25.4 dB, and 37 dB between elements, and different values of the $S_{nn}$ and $S_{nm}$ parameters, with n and $m=$ 1 to 4. From this study, the importance of the isolation among ports and its comparison with the return losses becomes evident in achieving a MIMO antenna array insensitive to random phase variations occurring in the communication channel. Full article