Antenna Selection Research Articles

Joint Antenna Selection and Beamforming for Area Surveillance With Spatially Distributed Array Radar

Joint Antenna Selection and Beamforming for Area Surveillance With Spatially Distributed Array Radar

Information-Guided Antenna Selection and Activation for Spatial Modulation MIMO Systems

Information-Guided Antenna Selection and Activation for Spatial Modulation MIMO Systems

Analyzing the Performance of TAS/MRC with Decode-and-Forward Relaying for Multihop Transmission over Fisher-Snedecor F Fading Channels

This study comprehensively assesses a decode-and-forward relaying system that employs Transmit Antenna Selection/Maximal Ratio Combining (TAS/MRC) for multi-hop communication across Fisher-Snedecor F fading channels. The study primarily focuses on the average symbol error rate (ASER) and outage probability (OP) while using cross QAM (XQAM) and rectangular quadrature amplitude modulation (RQAM). The proposed MIMO system effectively decreases the hardware complexity and cost of large antennas by implementing Transmit Antenna Selection (TAS) at the source and relay nodes and Maximum Ratio Combining (MRC) diversity at the destination and relays. Analytical formulations for OP (outage probability) and ASER (average symbol error rate) are derived using PDF (Probability Density Function)-based methods. Monte-Carlo simulations further validate these formulas. The investigation indicates that system performance is improved under conditions of lighter shadowing compared to moderate and extreme shadowing settings. Additionally, increasing the hop count amplifies the observed performance. Moreover, when the fading parameter increases, both the OP and ASER decrease. This study comprehensively examines the impact of many parameters, including m, p, L, R, and o, on the behaviour of the system under Fisher-Snedecor F fading. Based on the findings, the combination of shadowing and multipath fading significantly affects the system's performance, with both m and p significantly influencing this. When examining the Signal-to-Noise Ratio (SNR), a comparison between RQAM and XQAM demonstrates that XQAM is superior. The research uncovers crucial information for planning and executing the TAS/MRC-based MIMO multi-hop communication system. This technology possesses the capability to enhance the effectiveness of similar communication systems, as seen by the encouraging advancements in performance, especially in scenarios including signal attenuation.

Joint design of transmit precoding and antenna selection for multi-user multi-target MIMO DFRC

Dual-function radar and communications (DFRC) systems based on multiple-input multiple-output (MIMO) arrays have received considerable attention in recent years due to their excellent ability to alleviate spectrum congestion. The MIMO DFRC systems enable high-resolution detection of multiple targets while communicating with multiple users simultaneously. However, MIMO arrays require numerous radio frequency (RF) units and suffer a strong mutual coupling among antennas, resulting in significant system overhead and performance degradation, respectively. In light of this, this paper investigates the joint optimization of transmit precoding and antenna selection for MIMO DFRC systems, aiming to improve the angular ambiguity function with a guaranteed communication quality of service (QoS) using a small number of antennas. To address the resultant non-convex optimization problem, both the indirect and direct precoding methods are proposed. In the former, the waveform covariance and antenna selection vector are first jointly optimized via a promoted sparsity along the covariance diagonal, followed by the precoding matrix indirectly derived from the optimal covariance. In the latter, the precoding matrix is directly optimized via an imposed group sparsity under the communication QoS and power constraints. Simulation results demonstrate that the proposed sparse MIMO DFRC system with fewer active antennas can achieve comparable dual-functional performance to that of the full array system.

Evaluation of L6 augmentation signal reception characteristics and positioning accuracy of compact and lightweight GNSS antennas

Applications requiring outdoor position estimation, such as unmanned construction and delivery automation, focus on receiving global navigation satellite system (GNSS) correction information from satellites for high-precision positioning. In particular, the delivery of correction information for the Galileo high-accuracy service (HAS) and quasi-zenith satellite system (QZSS) centimeter-level augmentation service (CLAS) is based on a new frequency band called L6. The L6 signal is a new type of GNSS signal, and a GNSS antenna corresponding to the frequency of the L6 signal (1275.46 MHz) is required to receive and decode the correction messages. The reception characteristics of the L6 signal are important for receiving correction information. However, the reception performance of antennas supporting the new L6 signal has not been evaluated. Therefore, in this study, we evaluate the reception characteristics of the L6 signal of a compact and lightweight L6-compatible antenna, and the multipath characteristics, which are the fundamental performance of the antenna that affects high-precision positioning. In a 24-hour static test, each antenna’s signal reception performance and multipath characteristics were evaluated, and significant differences were found in performance among the antennas capable of receiving the L6 signal. Furthermore, in a kinematic test, we evaluated high-accuracy positioning using QZSS CLAS with multiple antennas and showed that centimeter-level positioning using L6 augmentation signals is possible even with compact and lightweight GNSS antennas. These evaluations provide guidelines for antenna selection when high-precision positioning using L6 signals is employed in various applications.

Enhancing rock breakage efficiency by microwave fracturing: A study on antenna selection

Microwave fracturing of rocks prior to mechanical breakage has the potential to significantly enhance rock breakage efficiency while reducing the wear of cutters/bits of mechanical excavators. However, rocks in nature require a vastly different microwave power intensity to be fractured, and they tend to fail in varying patterns under different power intensities. At present, there is no established suggest method for selecting the most suitable microwave antenna to fracture a specific rock in the field. In this study, we compared the technical characteristics of the four open-ended waveguide-based antennas: namely, the horn antenna, the standard waveguide antenna, the converging waveguide antenna, and the dielectric-loaded converging waveguide antenna. Using a 6 kW microwave source and these antennas, we treated four types of hard rocks. We investigated the impact of antenna type on rock fracturing and found that depending on the rock type and antenna used, rocks were typically fractured or weakened in the pattern of cracking, spalling, melting, or a combination thereof. Based on our observations, we have, for the first time, proposed a method for selecting the optimal antenna to fracture rocks with varying microwave fracturability indexes. This paves the way for the commercialization of microwave-assisted mechanical rock breakage.

Antenna Selection for Asymmetrical Uplink and Downlink Transceivers in Massive MIMO Systems

Antenna Selection for Asymmetrical Uplink and Downlink Transceivers in Massive MIMO Systems

Joint Antenna Selection and Multicast Precoding in Spatial Modulation Systems

Joint Antenna Selection and Multicast Precoding in Spatial Modulation Systems

Performance analysis of majority-based transmit antenna selection and maximal ratio combining in MIMO-NOMA networks

Performance analysis of majority-based transmit antenna selection and maximal ratio combining in MIMO-NOMA networks

Antenna Selections Strategies for Massive MIMO Systems With Limited-Resolution ADCs/DACs

In millimeter wave (mmWave) communication systems with massive multiple-input multiple-output (MIMO) architecture, selecting the antennas contributing most from the candidate array to transmit/receive signals is one of the effective solutions to reduce hardware cost and power consumption while maintaining high spectral efficiency. In this paper, for the communication systems where the base station (BS) equipped with massive MIMO antenna array communicates with multiple single-antenna users, the impact of limited-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) on system capacity is investigated, and two antenna selection (AS) algorithms, namely quantization-aware greedy with square maximum-volume (QAG-SMV) and group-selection (GS) schemes, are proposed to enhance system capacity for the uplink and downlink transmission, respectively. Specifically, after the quantization noise caused by limited-resolution ADCs/DACs is converted to independent additive noise, the problem of maximizing system capacity is formulated. Then, two novel AS schemes are proposed to improve system capacity. Simulation results show that the proposed AS algorithms can obtain higher average system capacity, and the computational complexity is reduced as well.

LuMaMi28: Real-Time Millimeter-Wave Multi-User MIMO Systems With Antenna Selection

This paper presents LuMaMi28, a real-time 28GHz multi-user (MU) multiple-input multiple-output (MIMO) testbed. In this testbed, the base station has 16 transceiver chains with a fully-digital beamforming architecture (with different pre-coding algorithms) and simultaneously supports multiple user equipments (UEs) with spatial multiplexing. The UEs are equipped with a beam-switchable antenna array for real-time antenna selection where the one with the highest channel magnitude, out of four pre-defined beams, is selected. For the beam-switchable antenna array, we consider two kinds of UE antennas, with different beam-width and different peak-gain. Based on this testbed, we provide measurement results for millimeter-wave (mmWave) MU-MIMO performance in different real-life scenarios with static and mobile UEs. We explore the potential benefit of the mmWave MU-MIMO systems with antenna selection based on measured channel data, and discuss the performance results through real-time measurements.

Antenna Selection for Reconfigurable Intelligent Surfaces: A Transceiver-Agnostic Passive Beamforming Configuration

Reconfigurable intelligent surface (RIS) is capable of improving the wireless system performance by steering the reflected signal in the desired direction. One of the major challenges is that both the transceiver and RIS have to be jointly optimized, where the optimization problems have to be reformulated for different system models and scenarios. To circumvent this challenge, new low-complexity antenna selection (AS) algorithms for transceiver-agnostic RIS configuration are proposed. Given a multiple-input multiple-output (MIMO) channel, the proposed RIS-AS opts for accurately aligning the RIS both with the transmit antenna (TA) and receive antenna (RA) for the sake of maximizing the MIMO channel’s overall output power. The proposed RIS-AS only has to configure the RIS alone, i.e. without iterations with the transceiver optimization. As a result, the proposed RIS-AS has the compelling benefit that they are generically applicable, regardless of the specific transceiver architecture. Our simulation results confirm that the proposed RIS-AS is capable of supporting any MIMO configuration, regardless of their closed/open-loop, single-/full-RF and multiplexing-/diversity-oriented setups.

Channel Adapted Antenna Augmentation for Improved Wi-Fi Throughput

This paper investigates how the expansion of array size may improve the spatial diversity of state-of-the-art Wi-Fi system and increase its throughput. With comprehensive Wi-Fi measurement studies with augmented antennas, we identify the potential performance gain atop spatial diversity gains from existing technologies like MIMO and beamforming. We propose WINAS, a general Wi-Fi intelligent antenna selection scheme with full system implementation that can be easily integrated with commodity Wi-Fi AP. WINAS provides substantially improved throughput for downlink traffics. Our experimental evaluation suggests that WINAS improves Wi-Fi throughput up to 1.56x, and 1.47x in average, in real user-based evaluation.

Joint design of antenna selection and transmit linear array beamformer for integrated radar and communications

The design of integrated radar-communication (IRC) systems is seen as a promising solution to alleviate the congestion of spectrum resource in recent years. Additionally, with the deployment of large-scaled arrays in base stations, sparse array design via antenna selection has become prominent to reduce system overheads and alleviate mutual coupling effect. In this paper, we propose a joint design of antenna selection and transmit beamformer for IRC systems to realize the dual operations of radar and communications. Specifically, we propose a joint model that achieves a trade-off between minimizing the total number of antennas for IRC and suppressing the peak sidelobe level (PSL) of overall transmit beampattern with well-controlled mainlobe ripples. Unlike the existing schemes that focus on individual beamformer design with varying sparse array configurations, we impose a group sparsity on the beamforming matrix and jointly optimize multiple beamformers to obtain a common sparse array for the constellation of all communication symbols. To solve the resulting non-convex problem, we employ the alternating direction method of multipliers to split the original problem into parallel subproblems which are then solved iteratively. Simulation results illustrate the superiority of the proposed method over the conventional approaches in obtaining a lower PSL using fewer antennas with dual functions.

Adaptive interference mitigation space‐time array reconfiguration by joint selection of antenna and delay tap

AbstractSpace‐time adaptive processing (STAP) array has found extensive use in the global navigation satellite system for interference suppression. Nevertheless, the conventional space‐time array necessitates multiple antennas and time delay taps, resulting in a heavy burden on both hardware and computation resources. Thus, lowering the cost and complexity of STAP becomes a considerable problem demanding prompt solutions. This work designs a space‐time array reconfiguration scheme based on the joint selection strategy of the antenna and delay tap to address this problem. The reconstructed array can induce a high signal to interference plus noise power ratio (SINR) when using fewer antennas and delay taps. The space‐time correlation coefficient (STCC) is first presented to manifest the influence of reconfiguration on output SINR. Then, we formulate the space‐time array reconfiguration mathematical model, aiming to minimise STCC. Two reconfiguration methods are provided to solve the optimal array configuration of antennas and delay taps that can reach the minimum STCC and maximum SINR. The optimal antenna‐delay tap pairs are finally selected to comprise the reconstructed array. Substantial simulation experiments verify that the presented scheme and strategy are effective and reliable in space‐time array reconfiguration.

Adaptive Beamforming with Sidelobe Level Control for Multiband Sparse Linear Array

Multiband antenna arrays have the capability of effectively working in multiple frequency bands and thus significantly simplify the antenna system. To further reduce the system overhead, this paper discusses the joint design of antenna selection and adaptive beamforming for multiband antenna arrays, where the sidelobe level is also controlled so as to alleviate the effect of unknown sporadic interference. Based on the maximum signal-to-interference-plus-noise ratio (SINR) criterion and sidelobe level constraints, the proposed multiband sparse array design is formulated into a nonconvex constrained nonlinear optimization problem with an l0,2-mixed norm regularization. This problem ensures that the same antenna positions are selected at all operating frequencies while the beamformer weights of each frequency are optimized independently. By exploiting the semi-definite relaxation and the reweighted l1,∞-norm approximation, the problem is converted into a series of convex subproblems and is then effectively solved by the proposed iterative reweighted method. Numerical results show that the proposed multiband sparse array significantly reduces the sidelobe levels in all operating frequencies while maintaining the maximum SINR, so it provides superior performance of interference suppression.

Multi-Antenna Jammer-Assisted Secure Short Packet Communications in IoT Networks

In this work, we exploit a multi-antenna cooperative jammer to enable secure short packet communications in Internet of Things (IoT) networks. Specifically, we propose three jamming schemes to combat eavesdropping, i.e., the zero forcing beamforming (ZFB) scheme, null-space artificial noise (NAN) scheme, and transmit antenna selection (TAS) scheme. Assuming Rayleigh fading, we derive new closed-form approximations for the secrecy throughput with finite blocklength coding. To gain further insights, we also analyze the asymptotic performance of the secrecy throughput in the case of infinite blocklength. Furthermore, we investigate the optimization problem in terms of maximizing the secrecy throughput with the latency and reliability constraints to determine the optimal blocklength. Simulation results validate the accuracy of the approximations and evaluate the impact of key parameters such as the jamming power and the number of antennas at the jammer on the secrecy throughput.

FDA antenna selection for localizing targets

In this paper, we propose a joint transmit and receive antenna selection scheme for frequency diverse array (FDA) radar that aims at finding an optimal selection of employed FDA antennas, formed by minimizing the Cramér–Rao lower bound (CRLB) of the target localization problem given the available a priori knowledge of potential target locations. The resulting problem is a non-convex Boolean problem in which the objective function is a quadratic objective function with respect to the optimization variables. To allow for an efficient solution, an iterative relaxed algorithm is proposed, substantially simplifying the resulting minimization. Numerical simulations are provided to demonstrate the effectiveness of the proposed approach.

Joint antenna selection and beamforming for frequency diverse multiple‐input multiple‐output radar in mainlobe spectrum interferences and signal‐dependent interferences coexistence scenarios

AbstractDue to the controllable degrees of freedom of frequency diverse array in the distance dimension, the frequency diverse multiple‐input multiple‐output (FDA‐MIMO) radar can easily deal with mainlobe interference, which is often difficult to solve in traditional phased arrays. Nevertheless, the performance of FDA‐MIMO radar will suffer from degradation in the scenario where spectrum interferences and signal‐dependent interferences coexist. In order to solve this problem, a novel FDA‐MIMO radar framework via antenna switching is proposed. Based on this framework, an effective method for jointly optimising antenna selection and beamforming against spectrum interferences and signal‐dependent interferences is developed. The resulting optimization problem is nonconvex and NP‐hard owing to the integer constraints caused by antenna selection. By relaxing the integer constraints, the original problem can be transformed into a convex optimization form and an iterative reweighting strategy is used to force the obtained solution to satisfy the integer constraints. Simulation examples show that the proposed algorithm has better performance in output signal‐to‐interference‐plus‐noise ratio (SINR) and beampattern radiation performance than the existing competitive methods.

Combining transmit antenna selection and full-duplex aerial relay drone for performance enhancement of multiuser NOMA millimeter-wave communications

In this article, multiple antennas are proposed to utilize the millimeter-wave (MW) communication in a full-duplex aerial relay drone (FD-ARD) multi-user non-orthogonal multiple access (NOMA) system. Notably, the transmit antenna selection (TAS) technique is also incorporated to yield a significant boost in the system performance and a noteworthy reduction in signal processing complexity at the user end. The mathematical formulas of outage probability (OP) and achievable capacity (AC) of the proposed system are derived under the effect of channel and system parameters that are recommended for the fifth generation (5G) standard and the beyond 5G (B5G) proposals. All derived formulas are validated by using Monte-Carlo simulations. Numerical results show that TAS offers a substantial advantage over the scenarios without TAS. This holds even in the presence of several adverse factors, including the attributes of NOMA, the residual self-interference (RSI) stemming from full-duplex (FD) transmissions, the utilization of high carrier frequencies within MW bands, and the elevated altitude of the drone. The OP of systems equipped with TAS remains impressively below 10−11, whereas systems lacking TAS exhibit a substantially higher OP value of 10−4. Furthermore, the AC is notably elevated with the incorporation of TAS, as compared to scenarios where TAS is absent. However, the gap between the performance of the systems with and without TAS becomes insignificant when the RSI is sufficiently high. Consequently, this work can recommend the suitable transmit power corresponding to a specific RSI level and other system requirements to save energy and avoid saturated performance. In addition, the specific effect of high carrier frequencies in MW bands, positions of the drone, numbers of transmit/receive antennas, and RSI levels are deeply investigated to achieve useful insights into the behaviors of the proposed system.