Search Results (88)

This paper proposes a novel dual-functional radar-communication (DFRC) framework that integrates unmanned aerial vehicle (UAV) communications into an integrated sensing and communication (ISAC) system, termed the ISAC-UAV architecture. In this system, the UAV’s mobility is leveraged to simultaneously serve multiple single-antenna uplink users (UEs) and perform radar-based sensing tasks. A key challenge stems from the target position uncertainty due to movement, which impairs matched filtering and beamforming, thereby degrading both uplink reception and sensing performance. Moreover, UAV energy consumption associated with mobility must be considered to ensure energy-efficient operation. We aim to jointly maximize radar sensing accuracy and minimize UAV movement energy over multiple time steps, while maintaining reliable uplink communications. To address this multi-objective optimization, we propose a deep reinforcement learning (DRL) framework based on a long short-term memory (LSTM)-enhanced deep deterministic policy gradient (DDPG) network. By leveraging historical target trajectory data, the model improves prediction of target positions, enhancing sensing accuracy. The proposed DRL-based approach enables joint optimization of UAV trajectory and uplink power control over time. Extensive simulations validate that our method significantly improves communication quality and sensing performance, while ensuring energy-efficient UAV operation. Comparative results further confirm the model’s adaptability and robustness in dynamic environments, outperforming existing UAV trajectory planning and resource allocation benchmarks. Full article

Beamforming plays a key role in improving the spectrum utilization efficiency of multi-antenna systems. However, we observe that (i) conventional beam prediction solutions suffer from high model training overhead and computational latency and thus cannot adapt quickly to changing wireless environments, and (ii) deep-learning-based beamforming may face the risk of catastrophic oblivion in dynamically changing environments, which can significantly degrade system performance. Inspired by the above challenges, we propose a continuous-learning-inspired beam prediction model for fast beamforming adaptation in dynamic downlink millimeter-wave (mmWave) communications. More specifically, we develop a meta-empirical replay (MER)-based beam prediction model. It combines empirical replay and optimization-based meta-learning. This approach optimizes the trade-offs between transmission and interference in dynamic environments, enabling effective fast beamforming adaptation. Finally, the high-performance gains brought by the proposed model in dynamic communication environments are verified through simulations. The simulation results show that our proposed model not only maintains a high-performance memory for old tasks but also adapts quickly to new tasks. Full article

A millimeter-wave multi-layer and miniaturized multibeam antenna fed by an E-plane Butler matrix (BM) in substrate integrated waveguide (SIW) technology is proposed. For the beam-forming network (BFN), a folded E-plane 4 × 4 BM is proposed, whose basic components are stacked up along the vertical direction aiming to reduce the horizontal size by more than 75% compared with a single-layer BM. For the radiation portion, an unconventional slot antenna array arranged in a ladder type is adopted. The slot antenna elements are distributed in separate layers, making them more compatible with the presented BM and are arranged in the longitudinal direction to suppress the mutual coupling effect. Furthermore, the BM has been adjusted to accommodate the slot antenna array and obtain further miniaturization. The overall dimension of the designed multibeam antenna, taking the BFN into account, is 12 mm × 45 mm × 2 mm (1.2 λ × 4.5 λ × 0.2 λ), which is preferable for future 6G smartphone applications. The impacts of the air gap in fabrication are also taken into consideration to alleviate the error between simulated model and fabricated prototype. Full article

This paper presents a compact 24 GHz radar with a 4-transmit (4Tx) and 4-receive (4Rx) CMOS radar IC, integrated with a 4 × 4 Tx array and four 1 × 4 receive Rx array antennas, optimized for enhancing small drone detection. By employing the hybrid beamforming technique based on analog beamforming on the transmit side and independent four-channel digital reception, the proposed radar achieves high spatial resolution and robust target tracking. The proposed radar features an elevation scan range of ±45° with an azimuth fan-beam half-power beamwidth (HPBW) of 80° for a comprehensive detection field. Tests with a small drone measuring 20.3 × 15.9 × 7 cm³, positioned at various elevation angles of up to 45° and azimuth angles of up to ±60° at a distance of 4 m from the radar, verified its detection capability and highlighted the radar’s effectiveness in tracking small aerial targets. This architecture emphasizes the advantages of analog beamforming on Tx and multi-channel Rx, addressing the increasing demands for precise drone detection and monitoring in both civilian and defense domains. Full article

Multi-Beam frequency scanning leaky-wave antennas (FBS-LWAs) offer a viable solution for hardware miniaturization in direction-of-arrival (DOA) estimation systems. However, the presence of multiple spatial harmonics results in responses in multiple directions for a given incident source, introducing estimation ambiguity and significantly challenging accurate DOA estimation. Moreover, due to the nonlinear frequency response of the FBS-LWA, its response matrix does not satisfy the Vandermonde structure, which renders common rank-recovery techniques ineffective for processing coherent signals. As a result, the DOA estimation of coherent sources using multi-beam FBS-LWAs remains an open and challenging problem. To address this issue, this paper proposes a novel DOA estimation method for coherent signals based on multi-beam frequency scanning leaky-wave antennas. First, the received signals are transformed into the frequency domain via fast Fourier transform (FFT) to construct the signal data matrix from which the covariance matrix is computed.Then, conventional beamforming (CBF) is employed to obtain an initial estimate of the angle set, which will be further refined by a smaller grid to form a candidate angle set. Finally, a maximum likelihood algorithm based on the stochastic principle (Sto-ML) is used to suppress the interference of the parasitic directions and select the final DOA estimates from the candidate angle set. Simulation results show that the proposed method effectively mitigates the impact of parasitic directions and achieves an accurate DOA estimation of multiple coherent sources, even under both low and medium-to-high signal-to-noise ratio (SNR) conditions. Full article

The capabilities of 6G networks surpass those of existing networks, aiming to enable seamless connectivity between all entities and users at any given time. A critical aspect of achieving enhanced and ubiquitous mobile broadband, as promised by 6G networks, is merging satellite networks with land-based networks, which offers significant potential in terms of coverage area. Advanced routing techniques in next-generation network technologies, particularly when incorporating terrestrial and non-terrestrial networks, are essential for optimizing network efficiency and delivering promised services. However, the dynamic nature of the network, the heterogeneity and complexity of next-generation networks, and the relative distance and mobility of satellite networks all present challenges that traditional routing protocols struggle to address. This paper provides an in-depth analysis of 6G networks, addressing key enablers, technologies, commitments, satellite networks, and routing techniques in the context of 6G and satellite network integration. To ensure 6G fulfills its promises, the paper emphasizes necessary scenarios and investigates potential bottlenecks in routing techniques. Additionally, it explores satellite networks and identifies routing challenges within these systems. The paper highlights routing issues that may arise in the integration of 6G and satellite networks and offers a comprehensive examination of essential approaches, technologies, and visions required for future advancements in this area. 6G and satellite networks are associated with technical terms such as AI/ML, quantum computing, THz communication, beamforming, MIMO technology, ultra-wide band and multi-band antennas, hybrid channel models, and quantum encryption methods. These technologies will be utilized to enhance the performance, security, and sustainability of future networks. Full article

Multi-beam phased array antennas have become essential in modern radar and communication systems, offering high gain, superior directivity, and exceptional agility. However, traditional multi-beam phased array antennas face significant challenges in meeting the growing demand for large, instantaneous bandwidth and compatibility with transmit-and-receive multi-beamforming. To achieve these requirements, we propose a novel transceiver-shared photonic integrated broadband multi-beamforming network architecture based on an extended Blass matrix framework. Combined with wavelength division multiplexing, the architecture enables the separation and decoupling of transmit and receive channels, ensuring the independent synthesis of multiple beams for transmission and receiving. Furthermore, we design and implement a 3 × 3 transceiver-shared photonic integrated broadband multi-beamformer on a standard silicon-on-insulator platform. The proposed multi-beamformer successfully demonstrates broadband multi-beamforming across six independent directions, with transmitted beams at 15°, 30°, and 45° and received beams at 20°, 40°, and 60°, covering both the whole X and Ku bands. Full article

In response to the urgent demands of the Internet of Things for precise indoor target positioning and information interaction, this paper proposes a multi-band analog radio-over-fiber mobile fronthaul system. The objective is to obtain the target’s location in indoor environments while integrating remote beamforming capabilities to achieve wireless access to the targets. Vector signals centered at 3, 4, 5, and 6 GHz for indoor positioning and centered at 30 GHz for wireless access are generated centrally in the distributed unit (DU) and fiber-distributed to the active antenna unit (AAU) in the multi-band analog radio-over-fiber mobile fronthaul system. Target positioning is achieved by radiating electromagnetic waves indoors through four omnidirectional antennas in conjunction with a pre-trained neural network, while high-speed wireless communication is realized through a phased array antenna (PAA) comprising four antenna elements. Remote beamforming for the PAA is implemented through the integration of an optical true time delay pool in the multi-band analog radio-over-fiber mobile fronthaul system. This integration decouples the weight control of beamforming from the AAU, enabling centralized control of beam direction at the DU and thereby reducing the complexity and cost of the AAU. Simulation results show that the average accuracy of localization classification can reach 86.92%, and six discrete beam directions are achieved via the optical true time delay pool. In the optical transmission layer, when the received optical power is 10 dBm, the error vector magnitudes (EVMs) of vector signals in all frequency bands remain below 3%. In the wireless transmission layer, two beam directions were selected for verification. Once the beam is aligned with the target device at maximum gain and the received signal is properly processed, the EVM of millimeter-wave vector signals remains below 11%. Full article

Radio-frequency (RF) microwave wireless power transfer (WPT) offers an efficient means of delivering energy to a wide array of devices over long distances. Previous RF WPT systems faced significant challenges, including complex hardware and control systems, software deficiencies, insufficient rectification power, lack of high-performance substrate materials, and electromagnetic radiation hazards. Addressing these issues, this paper proposes the world’s first watt-level RF WPT system capable of intelligent continuous tracking and occlusion judgment. Our 5.8 GHz band RF WPT system integrates several advanced technologies, such as millimeter-precision lidar, the multi-object image recognition algorithm, the accurate 6-bit continuous beamforming algorithm, a compact 16-channel 32 W high-power transmitting system, a pair of ultra-low axial ratio circularly polarized antenna arrays, ultra-low-loss high-strength ceramic substrates, and a 2.4 W high-power Schottky diode array rectifier achieving a rectification efficiency of $66.8\%$. Additionally, we construct a platform to demonstrate the application of the proposed RF WPT system in battery-free vehicles, achieving unprecedented ${360}^{\circ }$ uninterrupted power supply to the battery-free vehicle. In summary, this system represents the most functionally complete RF WPT system to date, serving as a milestone for several critical fields such as smart living, transportation electrification, and battery-less/free societies. Full article

This paper investigates a multi-antenna, multi-input multi-output (MIMO) dual-functional radar and communication (DFRC) system platform. The system simultaneously detects radar targets and communicates with downlink cellular users. However, the modulated information within the transmitted waveforms may be susceptible to eavesdropping. To ensure the security of information transmission, we introduce non-orthogonal multiple access (NOMA) technology to enhance the security performance of the MIMO-DFRC platform. Initially, we consider a scenario where the channel state information (CSI) of the radar target (eavesdropper) is perfectly known. Using fractional programming (FP) and semidefinite relaxation (SDR) techniques, we maximize the system’s total secrecy rate under the requirements for radar detection performance, communication rate, and system energy, thereby ensuring the security of the system. In the case where the CSI of the radar target (eavesdropper) is unavailable, we propose a robust secure beamforming optimization model. The channel model is represented as a bounded uncertainty set, and by jointly applying first-order Taylor expansion and the S-procedure, we transform the original problem into a tractable one characterized by linear matrix inequalities (LMIs). Numerical results validate the effectiveness and robustness of the proposed approach. Full article

The present study is concerned with the power transfer efficiency enhancement using a combination of the multi-hop node (MHN) and the Intelligent Reflecting Surface (IRS)-based passive beamforming technologies. The primary objective is to ensure a high RF-DC converter power conversion efficiency (PCE) used at the receiving end, which is difficult to achieve due to path loss and multi-path propagation. An electronically tunable reconfigurable reflectarray (RRA) designed to operate at the sub-GHz ISM band (865.5 MHz) is utilized to implement the IRS concept. Both the MHN and RRA were developed and studied in our earlier research. The RRA redirects the reflected power-carrying wave amplified by the MHN toward the intended receiver. It comprises two layers: the RF layer containing tunable phase shifters and the ground plane. Each phase shifter comprises two identical eight-shaped metal patches coupled by a pair of varactor diodes used to achieve the reflection phase tuning. The phase gradient method is used to synthesize the RRA phase profiles, ensuring different desired reflection angles. The RRA prototype, composed of 36 phase shifters, is employed in conjunction with the MHN equipped with two antennas and an amplifier. The RRA parameter optimization is accomplished by randomly varying the varactor diode voltages and measuring the corresponding received power levels until the power reflected in the desired direction is maximized. Two measurement scenarios are examined: power transmission without and with the MHN. In the first scenario, the received power is calculated and measured at several distinct beam steering angles for different distances between the Tx antenna and RRA. The same procedure is applied to different distances between the RRA and MHN in the second scenario. The effect of slight deviations in the operating frequency from the designed one (865.5 MHz) on the RRA performance is also examined. Additionally, the received power levels for both scenarios are estimated via full-wave analysis performed using the full-wave simulation software Ansys HFSS 2023 R1. A Huygens’ surface equivalence principle-based model decomposition method was developed and employed to reduce the CPU time. The calculated results are consistent with the measured ones. However, some discrepancies attributed to the adverse effect of RRA diode biasing lines, manufacturing tolerances, and imperfection of the indoor environment model are observed. Full article

In the multi-user multiple-input-multiple-output (MU-MIMO) beamforming (BF) training defined by the 802.11ay standard, since a single initiator transmits a significant number of action frames to multiple responders, inefficient configuration of the transmit antenna arrays when sending these action frames increases the signaling and latency overheads of MU-MIMO BF training. To configure appropriate transmit antenna arrays for transmitting action frames, the initiator needs to accurately estimate the signal to noise ratios (SNRs) measured at the responders for each configuration of the transmit antenna arrays. In this paper, we propose a two-phase deep learning approach to improve the accuracy of SNR estimation for multiple concurrent beams by reducing the measurement errors of the SNRs for individual single beams when each action frame is transmitted through multiple concurrent beams. Through simulations, we demonstrated that our proposed scheme enabled more responders to successfully receive action frames during MU-MIMO BF training compared to existing schemes. Full article

This article is about better wireless network connectivity. The main goal is to provide wireless service to several use cases and scenarios that may not be adequately covered today. Some of the considered scenarios are home connectivity, street-based infrastructure, emergency situations, disaster areas, special event areas, and remote areas that suffer from problematic/inadequate network and possibly power infrastructure. A target system that we consider for such scenarios is that of an energy-efficient self-backhauled base station (also called a “portable access point—PAP”) that is mounted on a drone to aid/expand the land-based network. For the wireless backhaul link of the PAP, as well as for the fronthaul of the street-mounted base station, we consider newly built multi-active/multi-passive parasitic antenna arrays (MAMPs). These antenna systems lead to increased range/signal strength with low hardware complexity and power needs. This is due to their reduced number of radio frequency chains, which decreases the cost and weight of the base station system. MAMPs can show a performance close to traditional multiple input/multiple output (MIMO) systems that use as many antenna elements as RF chains and to phased arrays. They can produce a directional beam in any desired direction with higher gain and narrow beamwidth by just tuning the load values of the parasitic elements. The MAMP is designed based on radiation conditions which were produced during the research to ensure that the radiation properties of the array were good. Full article

A comprehensive design framework is proposed for optimizing sparse MIMO (multiple-input, multiple-output) arrays to enhance multi-target detection. The framework emphasizes efficient utilization of antenna resources, including strategies for minimizing inter-element mutual coupling and exploring alternative grid-based sparse array (GBSA) configurations by efficiently separating interacting elements. Alternative strategies are explored to enhance angular beamforming metrics, including beamwidth (BW), peak-to-sidelobe ratio (PSLR), and grating lobe limited field of view. Additionally, a set of performance metrics is introduced to evaluate virtual aperture effectiveness and beamwidth loss factors. The framework explores optimization strategies for the partial sharing of antenna elements, specifically tailored for multi-mode radar applications, utilizing the desirability function to enhance performance across various operational modes. A novel machine learning initialization approach is introduced for rapid convergence. Key observations include the potential for peak-to-sidelobe ratio (PSLR) reduction in dense arrays and insights into GBSA feasibility and performance compared to uniform arrays. The study validates the efficacy of the proposed framework through simulated and measured results. The study emphasizes the importance of effective sparse array processing in multi-target scenarios and highlights the advantages of the proposed design framework. The proposed design framework for grid-spaced sparse arrays stands out for its superior efficiency and applicability in processing hardware compared to both uniform and non-uniform arrays. Full article

This paper proposes a novel hybrid beamforming (HBF) structure for gain-aware grouping transmit antennas and users in multiuser multiple-input single-output (MU-MISO) systems. In the conventional HBF structure, all transmit antennas form a beam to each user. In this case, the gain of each antenna varies depending on the location of the base station and each user, and the transmit power after the digital beamformer is allocated to the antenna with the smallest gain. Signals transmitted from antennas with small gains are susceptible to noise and interference. Therefore, this paper proposes an HBF structure in which only the antenna with the highest gain forms the beam for each user. In the proposed scheme, the transmitting antennas are grouped and the beam is formed only by the group of antennas with the highest gain for each user. Simulation results show that the proposed scheme can reduce the number of phase shifters used on the transmit side compared to the conventional HBF scheme while maintaining sum-rate performance when the number of transmit antennas and users are the same. It was also shown that there is a trade-off between the reduction in the number of phase shifters used to form the beam and the improvement in performance as the number of transmit antennas increases. Furthermore, it is shown that when antenna selection is used, although there is a trade-off between the number of phase shifters and performance improvement, the number of phase shifters can be reduced while maintaining performance even when the number of transmit antennas increases. Full article