Transmit Antenna Selection Research Articles

Secrecy Analysis of Transmit Antenna Selection with Hybrid GSC/SC in AF-MIMO Relay Systems

Secrecy Analysis of Transmit Antenna Selection with Hybrid GSC/SC in AF-MIMO Relay Systems

Performance Analysis of Antenna-relay Selection in CNOMA Systems under Practical Impairments

Selection strategies prove to be a valuable approach in mitigating complexity associated with antenna selection (AS) and relay selection (RS), optimizing signal transmission through a streamlined number of antennas/relays, and enhancing overall system performance. This paper offers a comprehensive analysis, deriving closed-form expressions for the outage probability (OP) and throughput in proposed scenarios that leverage the best relay selection (BRS) and transmit antenna selection (TAS) protocol for cooperative non-orthogonal multiple access (CNOMA), along with partial relay selection (PRS) and TAS protocol for CNOMA. The study extends to Rayleigh fading channels, considering practical impairments such as successful interference cancellation (SIC) error, channel estimation error (CEE), and feedback delay error. In comparing the proposed system to conventional CNOMA, our findings highlight the substantial impact of SIC, CEE, and feedback delay imperfections on the performance of both proposed scenarios. Notably, the application of BRS-based TAS protocol outperforms PRS-based TAS in terms of OP and throughput. The close alignment between analytical, asymptotic, and simulation results attests to the credibility of conducted analysis.

Security-reliability trade-off analysis for transmit antenna selection in cognitive ambient backscatter communications

Massive deployment of IoT devices raises the need for energy-efficient spectrum-efficient low-cost communications. Ambient backscatter communication (AmBC) technology provides a promising solution to achieve that. Moreover, incorporating AmBC with cognitive radio networks (CRNs) achieves better spectrum efficiency; however, this comes with performance drawbacks. In this work, we investigate the security and reliability performance of an underlay CRN with AmBC, where the backscattering device (BD) exploits the radio frequency (RF) signals of the secondary transmitter (ST), and both the ST and the BD share a common receiver. Different from previous work, we consider an ST with multiple antenna. The ST employs a transmit antenna selection (TAS) scheme to enhance the ST performance and overcome the performance degradation caused by the BD interference. TAS exploits multiple antenna diversity with lower hardware complexity and power consumption. Considering the Nakagami-m fading model, closed-form expressions are derived for the outage probability (OP) and intercept probability (IP) of both the ST and the BD transmissions at the legitimate receiver and the eavesdropper. Moreover, the asymptotic behavior of OPs and IPs is also investigated in the high signal-to-noise ratio regime and the high main-to-eavesdropper ratio regime, respectively. Monte Carlo simulations are performed to validate the derived closed-form expressions. Numerical results show that employing TAS enhances the ST and BD reliability performance by percentages up to 98% and 80%, respectively, at high primary user interference threshold values. Moreover, it results in a better security-reliability trade-off for the ST and the BD.

Evaluating the effectiveness of various diversity and combining techniques on an RF-FSO link

Abstract Diversity and combining is one of the robust techniques to mitigate multi-path fading in RF links and turbulence-induced scintillation in FSO links. This article evaluates the effect of different diversity and combining techniques on outage and BER performance of decode and forward RF-FSO link. We have utilized diversity and combining techniques over source to relay RF link and/or relay to destination FSO link. The selection combining, transmit antenna selection, maximal ratio combining, and maximum ratio transmission schemes are considered. The Monte-Carlo simulation results of outage probability and bit error rate are compared by considering different parameters affecting link quality like the strength of atmospheric turbulence, pointing error, FSO link detection scheme, RF link fading strength, diversity order, etc. It is found that configurations like SIMO-SISO, MISO-SISO, SISO-SIMO, and SISO-MISO, where diversity is applied in either source to relay link or relay to destination link, are improving the overall link performance provided that diversity is applied at the link experiencing stronger fading compared to another link. The link configurations SIMO-MISO or MISO-SIMO also improve the link performance and it can achieve BER of 10−5 at less than 15 dB SNR in favourable link conditions.

Joint Transmit and Receive Antenna Selection in MIMO-NOMA-Based Uplink Satellite Networks

Joint Transmit and Receive Antenna Selection in MIMO-NOMA-Based Uplink Satellite Networks

Transmit antenna selection in M-MIMO system using metaheuristic aided model

Massive MIMO (M-MIMO) devices are the key tool to meet the performance stards established for 5G-wireless communication. However, more Radio Frequency (RF) chains needed in base station (BS) with a huge count of transmitting antennas, involve expensive hardware and computing complexities. In order to decrease the RF chains needed in BS, this work intended to use the optimal transmit antenna selection (TAS) strategy. This strategy is gaining a lot of interest since the optimization algorithm aids in the ability to enhance the system performance considerably the efficiency and secrecy rate. This work proposes a novel Coati Adopted Pelican Optimization (CA-PO) for choosing the optimal TA by considering efficiency as well as secrecy rate. In addition, the CA-PO algorithm makes the decision on which antenna to be elected. At last, the supremacy of CA-PO-based TAS is proven from the analysis regarding secrecy rate and EE analysis. Accordingly, the proposed CA-PO method for MF for set up 2 has attained a higher EE of 0.976; whereas, the DMOA, COA, MRFO, POA and BEA techniques have got a relatively lower EE of 0.968.

Transmit antenna selection for millimeter-wave communications using multi-RIS with imperfect transceiver hardware

Transmit antenna selection for millimeter-wave communications using multi-RIS with imperfect transceiver hardware

Performance analysis of transmit antenna selection and maximum‐ratio combining in overlay networks powered by harvested energy

AbstractWe aim to improve both the energy harvesting efficiency and communication reliability of overlay networks powered by harvested energy. To this end, multiple antennas are considered to collect energy efficiently and perform reliable decoding by selecting the transmitting antenna and applying maximum‐ratio combining. To further improve communication reliability, nonorthogonal multiple access (NOMA)‐relied decoding is applied to the secondary receiver. For performance evaluation, exact formulas for the secondary/primary outage probability are derived in a closed form. The evaluation results show that the proposed method substantially outperforms a baseline without the NOMA‐relied decoding in all the system settings. The performance of the proposed method is determined by multiple specifications and optimized by allocating the times for energy harvesting and information processing.

Modeling and Analysis of Physical Layer Security of OTFS Systems Under Transmit Antenna Selection and Passive Eavesdropping

Modeling and Analysis of Physical Layer Security of OTFS Systems Under Transmit Antenna Selection and Passive Eavesdropping

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.

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

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.

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.

Robust precoder design with transmit antenna selection for overlay cognitive radio massive MIMO system

Massive MIMO systems were utilized in overlay Cognitive Radio (CR) networks to allow simultaneous primary and secondary data transmission while enhancing the spectral efficiency. However, the precoder design of a massive MIMO system especially in the overlay CR paradigm usually has a trade-off between achieved data rate and complexity. In this paper, the precoder design for overlay Cognitive Radio (CR) massive MIMO system is introduced, where a two-stage precoder that accommodates Transmit Antenna Selection (TAS) is proposed for the Secondary Base Station (SBS). The unselected antennas in the cognitive base station are proposed to be utilized to relay the data of the Primary Users (PUs) to maximize the network sum rate. The proposed precoder design for primary data aims to cancel the interference inflicted on Secondary Users (SUs) as a result of relaying the primary data. Moreover, a fast algorithm is proposed which aims to select and distribute the SBS antennas for primary and secondary data transmission to achieve better data and convergence rates, this algorithm is called Transmit Antenna Selection and Distribution (TASD). Simulation results show that the proposed precoders' design and the TASD algorithm enhance the total system sum rate (primary and secondary rates) compared to the conventional TAS (where the unselected antennas were not used to relay PUs' data). This enhancement was achieved by relaying primary data without affecting the rate of SUs. As a result, the computational time of the TASD algorithm is reduced by 52% compared to the full array case while the total sum rate of the algorithm is only 3% less than the full array scenario. Furthermore, the results in case of using a practical correlated channel proved the robustness of the proposed TASD algorithm, as it achieved nearly the same results compared to uncorrelated channels.

Optimal Antenna Selection and Beamforming for an IRS Assisted System

An intelligent reflecting surface (IRS) is a cost and energy-efficient solution to improve wireless system performance. Transmit antenna selection (AS) harnesses the benefits of multiple antennas with a smaller number of radio frequency (RF) chains. We focus on joint optimization of antenna subset and transmit beamforming at the transmitter (Tx) and passive beamforming at the IRS to maximize the receive signal power. We derive a closed-form optimal AS rule for a Tx and receiver (Rx) equipped with single RF chain each and ideal IRS. We analyze its performance with a correlated channel model and then extend it to non-ideal IRS. We also propose a simpler rule that significantly reduces the number of computations and pilots. For an Rx that performs maximal ratio combining, we propose a manifold optimization algorithm and a low-complexity selection rule. For a Tx with multiple RF chains, we propose a subset selection algorithm that yields a locally optimal solution and an alternating optimization algorithm that reduces complexity. Our simulations study the impact of estimation errors, discrete phase shifts, and channel correlation on the proposed selection rules, which perform better than the existing AS rules. They also show that the proposed low-complexity rules are near-optimal.

Symbol error probability of mmWave communications with transmit antenna selection and RISs under the impacts of hardware impairments

SummaryIn practice, hardware impairments (HIs) often exist in wireless devices, especially in low‐cost device systems. However, previous reports usually ignored HIs due to the computational complexity in mathematical derivations, particularly in millimeter‐wave (mmWave) communications. This article proposes the usage of transmit antenna selection (TAS) and multiple reconfigurable intelligent surfaces (RISs) to address HIs in mmWave communications. In particular, TAS is utilized at the source to increase the received signal power at the destination and reduce the effects of HIs. Multiple channel gains from RISs are combined with the classical source‐destination channel gain at the destination. The symbol error probability (SEP) expression of the mmWave communications with TAS and RISs under the effects of HIs (shortened as the TAS‐RISs‐HIs communications) is formulated over Nakagami‐ channels and verified through Monte Carlo simulations. The effects of HIs on the SEP of TAS‐RISs‐HIs communications are demonstrated through numerical illustrations. Specifically, the SEP of the TAS‐RISs‐HIs communications is significantly higher than the SEP of the ideal hardware communications with TAS and RISs, especially in the high transmit power regime. As a result, ignoring HIs when evaluating the SEP of the mmWave communications can result in some inappropriate conclusions. Moreover, the joint and separate advantages of TAS and RISs are thoroughly analyzed when comparing the SEPs in the cases with and without TAS, with and without RISs.

Intelligent Transmit Antenna Selection Schemes for High-Rate Fully Generalized Spatial Modulation

The sixth-generation (6G) network is supposed to transmit significantly more data at much quicker rates than existing networks while meeting severe energy efficiency (EE) targets. The high-rate spatial modulation (SM) methods can be used to deal with these design metrics. SM uses transmit antenna selection (TAS) practices to improve the EE of the network. Although it is computationally intensive, free distance optimized TAS (FD-TAS) is the best for performing the average bit error rate (ABER). The present investigation aims to examine the effectiveness of various machine learning (ML)-assisted TAS practices, such as support vector machine (SVM), naïve Bayes (NB), K-nearest neighbor (KNN), and decision tree (DT), to the small-scale multiple-input multiple-output (MIMO)-based fully generalized spatial modulation (FGSM) system. To the best of our knowledge, there is no ML-based antenna selection schemes for high-rate FGSM. SVM-based TAS schemes achieve ∼71.1% classification accuracy, outperforming all other approaches. The ABER performance of each scheme is evaluated using a higher constellation order, along with various transmit antennas to achieve the target ABER of 10−5. By employing SVM for TAS, FGSM can achieve a minimal gain of ∼2.2 dB over FGSM without TAS (FGSM-NTAS). All TAS strategies based on ML perform better than FGSM-NTAS.

Transmit antenna selection for multi-user VASM systems: Simplicity and fairness

Variable Active Antenna Spatial Modulation (VASM) systems have been shown to offer higher spectral efficiency and greater flexibility than conventional spatial modulation systems. In VASM systems, since a part of the information is carried on the indices of activated antennas, the transmit antenna selection (TAS) problem significantly impacts the systems’ quality. In this article, we propose two new TAS methods for multi-user VASM systems, namely, Hi-TAS and ObO-TAS. Specifically, Hi-TAS aims to reduce the system’s computational complexity, which is a hierarchical combination of two popular TAS methods, i.e., channel gain-based TAS (CG-TAS) and Euclidean distance-based TAS (ED-TAS). Meanwhile, the ObO-TAS alternately chooses each transmit antenna one by one for every user to ensure fairness among them. In addition, we propose the idea of reusable TAs to improve the quality of the system. The calculation and simulation results show that the proposed Hi-TAS has a computational complexity of only 7.74% compared to ED-TAS while achieving better average bit error rate performance for the system than ED-TAS. The proposed ObO-TAS also demonstrates the advantage of ensuring fairness among users, namely that the difference in bit error rate among users is very small compared to other TAS methods.

Hybrid optimization assisted transmit antenna selection for massive MIMO technology

Hybrid optimization assisted transmit antenna selection for massive MIMO technology

Transmit Antenna Selection for Sum-Rate Maximization with Multiclass Scalable Gaussian Process Classification

Antenna selection techniques are extensively applied to reduce hardware cost and power consumption in multiple-input multiple-output (MIMO) systems. This paper proposed a low-cost antenna selection method for system sum-rate maximization based on multiclass scalable Gaussian process classification (SGPC) which is capable to perform analytical inference and is scalable for massive data. Simulation results show that the average sum-rate obtained by SGPC is 1. 9 bps/Hz more than that obtained by conventional optimization driven user-centric antenna selection (UCAS) algorithm and 1 bps/Hz more than that obtained by the up-to-date learning scheme based on a deep neural network (DNN) when signal-to-noise ratio (SNR) is 10 dB, the number of total antennas at BS is 6, the number of selected antennas is 4, and the number of single-antenna users is 4. The superiority of SGPC over UCAS and DNN is more obvious as SNR, the number of selected antennas, or the number of users increases.