Transmit Antenna Selection Research Articles

Branch-and-Bound Search and Machine Learning-Based Transmit Antenna Selection in MIMOME Channels

The studies on the conventional transmit antenna selection (TAS) in multiple-input, multiple-output, multiple-antenna eavesdropper (MIMOME) channel have been focused on determining the optimal number of transmit antennas or selecting the optimal transmit antenna indices. To maximize the secrecy capacity, we need to develop a novel TAS scheme to simultaneously determine the optimal number of transmit antennas and select the corresponding optimal transmit antenna indices. In this paper, we propose the iterative branch-and-bound search-based TAS (IB-TAS) scheme to determine the optimal transmit antenna set in MIMOME channel. To reduce the computational complexity caused by TAS, we also propose the machine learning-based TAS (ML-TAS) schemes utilizing neural network (NN), support vector machine (SVM), and naive-Bayes (NB). Through the simulation and numerical results, it is demonstrated that the IB-TAS scheme achieves the optimal secrecy capacity. In addition, through comparative analysis of the proposed ML-TAS schemes, it was shown that the NN-based TAS scheme minimizes the computational complexity while minimizing the loss of secrecy capacity compared to other ML-TAS schemes.

Cooperative Mode Switching-Based Cognitive NOMA With Transmit Antenna and User Selection

The paper presents performance analysis of a multiuser Cooperative Non-Orthogonal Multiple Access (CNOMA) network that is underlay to a primary network. A selected secondary Full-Duplex (FD) Near User (NU) cooperates with a selected secondary Far User (FU) by apportioning the Interference Temperature Limit (ITL) with an ITL Apportioning Parameter (ITLAP). This Cooperative Mode (CM) is exercised only when NU meets its own performance criteria, else the network switches to a Non-Cooperative Mode (NCM). The network is therefore made adaptive in such a way that performance of the NU is same as in a network without the FU. Performance of the network is further improved using Maximum Transmit Power-based Transmit Antenna Selection (MTP-TAS), Best NU-Best FU (BNBF) selection, and optimal power allocation, thereby also motivating NOMA even in power-constrained underlay environments where transmit powers are not always high. The selection mechanisms are designed in a way that additional overheads for Channel State Information (CSI) estimation and feedback are not imposed. Analytical expressions for outage probability are presented for both end users, assuming only statistical knowledge of channel gains under the assumption of imperfect Successive Interference Cancellation (SIC) at the NU. Outage minimizing optimal values of the NOMA Power Allocation Parameter (NPAP) and ITLAP are derived that minimize FU outage. Simulations validate the derived expressions, and demonstrate superiority of the proposed scheme over FD NU-based conventional NOMA as well as conventional OMA signalling.

Approaching K-Means for Multiantenna UAV Positioning in Combination With a Max-SIC-Min-Rate Framework to Enable Aerial IoT Networks

In long-range wireless communication networks, the fading channels described in channel state information are strongly related to distance and the path loss exponent and represent a major challenge in delivering the performance required to support emerging applications. Conveniently, multiple antennas and cooperative relays are efficient solutions that can combat fading channels, thereby improving networking capacity and transmission reliability. This study investigated the use of multi-antenna unmanned aerial vehicle (UAV)s as aerial Internet of Things (IoT) relays and employed their direct line-of-sight benefits to assist IoT wireless networks. To improve the outage probability, system throughput, and energy efficiency (EE), we first considered a combination of transmit antenna selection at the transmitter and the selection combining technique at the receiver to determine the best channel from the pre-coding channel matrix. Then, based on a practical model in a three-dimensional earth environment and thanks to the K-means algorithm, we investigated optimal UAV placement to obtain optimal channel state information for the non-orthogonal multiple access (NOMA)-IoT device cluster globally, thereby ensuring the quality of service for the IoT devices. We introduced a max-successive interference cancellation-min-rate framework for non-ordered NOMA devices, thus deriving theoretical expressions in novel closed forms for two independent scenarios: ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> ) Rayleigh and ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii</i> ) Nakagami- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> fading channels. By optimizing the UAV placement, the investigated results applied to the UAV scheme delivered a better performance in a NOMA-IoT network than in a terrestrial relay (TR) scheme. Finally, this study examines a variety of models and presents algorithms for Monte Carlo simulations to verify the theoretical results.

Performance analysis of precoding‐aided differential spatial modulation systems with transmit antenna selection

In this paper, the performance of precoding-aided differential spatial modulation (PDSM) systems with optimal transmit antenna subset (TAS) selection is examined analytically. The average bit error rate (ABER) performance of the optimal TAS selection-based PDSM systems using a zero-forcing (ZF) precoder is evaluated using theoretical upper bound and Monte Carlo simulations. Simulation results validate the analysis and demonstrate a performance penalty < 2.6 dB compared with precoding-aided spatial modulation (PSM) with optimal TAS selection. The performance analysis reveals a transmit diversity gain of for the ZF-based PDSM (ZF-PDSM) systems that employ TAS selection with transmit antennas, selected transmit antennas, and receive antennas. It is also shown that reducing the number of activated transmit antennas via optimal TAS selection in the ZF-PDSM systems degrades ABER performance. In addition, the impacts of channel estimation errors on the performance of the ZF-PDSM system with TAS selection are evaluated, and the performance of this system is compared with that of ZF-based PSM with TAS selection.

A novel massive MIMO strategy for optimal antenna selection via hybrid algorithm

ABSTRACT One of the capable technologies in networking systems is the Multiple-Input Multiple-Output (MIMO) technology as it provides better system capacity and a high Bit Error Rate (BER). Still, the transmit antenna selection remains as the greatest issue. More transmit antennas are necessary to achieve maximum capacity, which leads to increased power consumption. Therefore, for solving these issues in the M-MIMO system, this paper introduces a novel Wolf Adapted Herding algorithm (WA-HA) for selecting the optimal transmit antennas using multi-objective constraints that raise the capacity and Energy Efficiency (EE). The proposed algorithm combines the concept of Elephant Herding Optimization (EHO) and Grey Wolf Optimization (GWO) algorithm and it is referred to as the Wolf Adapted Herding Algorithm (WA-HA). This WA-HA algorithm optimises the number of transmit antennas and hence decides which antenna has to be chosen. Finally, the performance of the adopted method is evaluated over other traditional methods like MV-GSA, SLnO, I-SLnO, EHO and GWO in terms of various metrics like EE and capacity. In particular, the capacity of the proposed WA-HA method for ZF under set-up 1 is 51.02%, 30.61%, 22.44%, 8.163% and 55.10% better than the existing models. Furthermore, the computational time of our model is 10.96%, 26.13%, 14.08%, 13.48% and 10.26% superior to that of the existing models, respectively.

Ultra-Reliable Communication for Critical Machine Type Communication via CRAN-Enabled Multi-Connectivity Diversity Schemes.

This paper focuses on edge-enabled cloud radio access network architecture to achieve ultra-reliable communication, a crucial enabler for supporting mission-critical machine-type communication networks. We propose coordinated multi-point transmission schemes taking advantage of diversity mechanisms in interference-limited downlink cellular networks. The network scenario comprises spatially distributed multiple remote radio heads (RRHs) that may cooperate through silencing, or by using more elaborated diversity strategies such as maximum ratio transmission or transmit antenna selection to serve user equipment in the ultra-reliable operation regime. We derive an exact closed-form expression for the outage probabilities and expected values of signal-to-interference ratio for silencing, transmit antenna selection and maximum ratio transmission schemes. We formulate rate control and energy efficiency under reliability constraints to test the performance and resource usage of the proposed schemes. Furthermore, we study the impact on average system sum throughput with throughput-reliability trade-off under cooperative communication. Extensive numerical analysis shows the feasibility of ultra-reliable communication by implementing diversity schemes with RRHs cooperation.

Performance Analysis of NOMA-Enabled Vehicular Communication Systems With Transmit Antenna Selection Over Double Nakagami-m Fading

In this paper, we investigate the performance of downlink multiple-input-single-output (MISO) non-orthogonal multiple access (NOMA) aided vehicular communication systems. To prepare the background for MISO NOMA-based vehicular systems, we first derive the exact outage probability (OP), average bit error rate (ABER), and ergodic capacity (EC) expressions for the single-input-single-output (SISO) NOMA-based vehicular systems over independent but not necessarily identically distributed (i.ni.d.) double Nakagami- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> fading channels. Furthermore, we propose two transmit antenna selection schemes at multiple-antenna source vehicle for both far user and near user. Based on these antenna selection strategies, we derive the exact expressions for the OP, ABER, and EC, of the MISO NOMA-based vehicular systems over i.ni.d. double Nakagami- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> fading channels. The derived ABER expressions for both SISO and MISO NOMA-enabled vehicular systems can be applicable for various modulation schemes. Moreover, to reveal better insights into the diversity orders of SISO and MISO NOMA-enabled vehicular systems, we present the asymptotic OP analysis in the high signal-to-noise ratio (SNR) regime. The numerical and simulation results corroborate our theoretical and analytical findings, and demonstrate the effects of transmit power, power allocation factor, fading severity parameters, and number of antennas, on the system's performance. We further compare the performance of both systems, and show that the multiple antennas can improve the performance of vehicular systems, which can be further improved significantly with the simultaneous improvement in fading severity parameters.

Security-and-Reliability Trade-off of Energy Harvesting-Based Underlay Relaying Networks with Transmit Antenna Selection and Jamming

Security-and-Reliability Trade-off of Energy Harvesting-Based Underlay Relaying Networks with Transmit Antenna Selection and Jamming

NOMA with optimal transmit antenna selection scheme with self adaptive metaheuristic model

AbstractNonorthogonal multiple access (NOMA) constitutes a promising technique in the fifth‐generation (5G) mobile networks. On the transmitter side, the concurrent usage of multiple antennas needs an appropriate count of parallel Radio Frequency (RF) chains at the front end. Owing to this consequence, it maximizes the power consumption, cost, and system complexity along with maximization in the antenna count. In order to tackle these aforesaid problems, some researchers prefer the Transmit Antenna Selection (TAS) for modeling the transmitter structure simple. The best antenna is selected opportunistically by an efficient TAS technique from multiple antennas and deploys a single RF chain for transmission. In this paper, a novel approach for optimized antenna selection in overlay CR networks using NOMA and SM is proposed via the usage of optimization tactics. To choose the desired respective antenna, this paper introduces a new Mean and Median Fitness Centered Moth flame Optimization (MM‐FCMO), which is the modified Moth Flame Optimization (MFO) Algorithm, which taken the core objectives such as power consumption and Mean Square Error (MSE). The MSE and power consumption of the chosen antennas have to be lower for the system to attain maximum antenna gain with lower noise. Finally, to exhibit that the presented work is much significant than the traditional works, a comparative analysis is made in terms of error minimization and statistical evaluation.

Secure Rate Control and Statistical QoS Provisioning for Cloud-Based IoT Networks

The Internet of Things (IoT) facilitates physical things to detect, interact, and execute activities on-demand, enabling a variety of applications such as smart homes and smart cities. However, it also creates many potential risks related to data security and privacy vulnerabilities on the physical layer of cloud-based Internet of Things (IoT) networks. These can include different types of physical attacks such as interference, eavesdropping, and jamming. As a result, quality-of-service (QoS) provisioning gets difficult for cloud-based IoT. This paper investigates the statistical QoS provisioning of a four-node cloud-based IoT network under security, reliability, and latency constraints by relying on the effective capacity model to offer enhanced QoS for IoT networks. Alice and Bob are legitimate nodes trying to communicate with secrecy in the considered scenario, while an eavesdropper Eve overhears their communication. Meanwhile, a friendly jammer, which emits artificial noise, is used to degrade the wiretap channel. By taking advantage of their multiple antennas, Alice implements transmit antenna selection, while Bob and Eve perform maximum-ratio combining. We further assume that Bob decodes the artificial noise perfectly and thus removes its contribution by implementing perfect successive interference cancellation. A closed-form expression for an alternative formulation of the outage probability, conditioned upon the successful transmission of a message, is obtained by considering adaptive rate allocation in an ON-OFF transmission. The data arriving at Alice’s buffer are modeled by considering four different Markov sources to describe different IoT traffic patterns. Then, the problem of secure throughput maximization is addressed through particle swarm optimization by considering the security, latency, and reliability constraints. Our results evidence the considerable improvements on the delay violation probability by increasing the number of antennas at Bob under strict buffer constraints.

Transmit Antenna Selection for Full-Duplex Spatial Modulation Based on Machine Learning

In this paper, we first derive the channel capacity of the full-duplex spatial modulation (FD-SM) system and its upper and lower bounds. Furthermore, different from the traditional optimization-driven decision, we use the data-driven prediction method to solve the transmit antenna selection (TAS) problem in the FD-SM system. Specifically, two novel TAS methods based on the support vector machine (SVM) and deep neural network (DNN) are proposed for reducing the effect of residual self-interference (RSI) on the FD-SM system performance. In our design, we propose a novel feature extraction method based on the principal component analysis (PCA) to help the proposed classifiers improve training. Our simulation results show that our data-driven TAS schemes can approach the optimal performance achieved by exhaustive search while significantly reducing complexity.

Performance analyses of TAS/Alamouti‐MRC NOMA system with channel estimation error, feedback delay, and imperfect SIC

AbstractIn this article, the performance of a power domain downlink multiple‐input multiple‐output non‐orthogonal multiple access system, where the base station (BS) equipped with three antennas communicates simultaneously with three mobile users equipped with multiple antennas, is analyzed over Nakagami‐m fading channels in the presence of channel estimation error (CEE), feedback delay (FBD), and imperfect successive interference cancellation. In the considered system, the BS applies transmit antenna selection (TAS)/Alamouti‐space‐time block coding (STBC) scheme while mobile users are assumed to adopt maximum‐ratio combining technique in order to take advantage of the combination of transmit and receive diversities. In particular, in order to apply Alamouti‐STBC scheme at the BS, one of the transmit antennas is determined randomly while the other one is selected according to decision of the majority of mobile users. For performance metrics, closed‐form outage probability (OP) and ergodic capacity (EC) expressions derived with the help of moment generating function approach. Moreover, asymptotic analyses are maintained to demonstrate the effects of CEE and FBD in terms of diversity order and array gain. We show that the proposed system provides better OP and EC performance than the system without antenna selection for different users and conditions.

Performance of Transmit Antenna Selection in Multiple Input Multiple Output-Orthogonal Space Time Block Code (MIMO-OSTBC) System Joint with Bose-Chaudhuri-Hocquenghem (BCH)-Turbo Code (TC) in Rayleigh Fading Channel

The Transmit antenna selection (TAS) technique is essential to increase the efficiency of spatial modulation (SM) systems. This TAS is an effective technique for reducing the Multiple Input Multiple Output (MIMO) systems, which can increase the computational difficulty and Bit error rate (BER) by various TAS algorithms. But these selection methods cannot provide code gain, so it is essential to join the external code in TAS to obtain code gain advantages in BER. In some existing work, the improved BER has been perceived by joining Forward Error Correction Code (FEC) and Space Time Block Code (STBC) for MIMO systems provided greater code gain. A multiple TAS-OSTBC technique with new integration of Bose–Chaudhuri–Hocquenghem (BCH)-Turbo code (TC) is proposed in this paper. The TAS-OSTBC system connects with the external BCH code in sequence of internal Turbo code. This combination can provide increasing code gain and the effective advantages of the TAS-OSTBC system. To perform the system analysis Rayleigh channel is utilized. In the case with multiple TAS-OSTBC systems, better performance can provide by this new combination of the BCH-Turbo compared to the conventional Turbo code for the Rayleigh fading.

MIMO-Orthogonal space time block code system joint with BCH-TC in Rayleigh fading channel for performance of transmit antenna selection

Purpose To enhance the performance transmit antenna selection (TAS) of spatial modulation (SM), systems technique needs to be essential. This TAS is an effective technique for reducing the multiple input multiple output (MIMO) systems computational difficulty, and bit error rate (BER) can increase remarkably by various TAS algorithms. But these selection methods cannot provide code gain, so it is essential to join the TAS with external code to obtain cy -ode gain advantages in BER. Design/methodology/approach In this paper, Bose–Chaudhuri–Hocquenghem (BCH)-Turbo code TC is combined with the orthogonal space time block code system. Findings In some existing work, the improved BER has been perceived by joining forward error correction code and space time block code (STBC) for MIMO systems provided greater code gain. The proposed work can provide increasing code gain and the effective advantages of the TAS-OSTBC system. Originality/value To perform the system analysis, Rayleigh channel is used. In the case with multiple TAS-OSTBC systems, better performance can provide by this new joint of the BCH-Turbo compared to the conventional Turbo code for the Rayleigh fading.

Transmit Antenna Selection Methods For Mimo Systems In Wireless Communications

Though MIMO systems improve performance of a wireless communication network by the usage of multiple antennas, demand of distinct set of RF chain (i.e., electronic components required for antenna transmission and reception, in wireless communication) for all the antennas leads to an increase in complexity and cost. Antenna selection technique of MIMO has proved to be a good means to solve this issue. Antenna Selection methods find optimal number of antennas required out of the total antennas present in the MIMO (Multiple Input Multiple Output) system. The selection of antenna can be performed at both ends of the communication network i.e., transmitter or receiver. In this paper, an overview of various Transmit Antenna Selection techniques for various MIMO systems is presented.

Secrecy performance for underlay cognitive multi-relaying MISO-RF/SIMO-FSO networks with outdated CSI

This study evaluates the physical-layer security for an underlay cognitive radio-based radio frequency (RF)–free space optical (FSO) network. In particular, a multi-antenna secondary source (S) communicates with a multi-aperture secondary destination (D) via M (M≥ 1) relays with each equips with both a single antenna and a single aperture in the presence of a N (N≥ 1)-aperture eavesdropper. In addition, a transmit antenna selection scheme is adopted at S with a channel feedback delay, and an equal gain combining protocol is performed at D to combine all the received signals. Moreover, a general Kth relay selection criterion is adopted to select a relay to assist the transmission through a decode-and-forward protocol. Considering the RF links are subject to Nakagami-m fading and the FSO channels are with Gamma–Gamma distributions, the analytical and asymptotic expressions for the lower bound of secrecy outage probability are obtained. Moreover, Monte-Carlo simulations are used to verify those expressions.

Information-Theoretic Security of MIMO Networks Under $\kappa$-$\mu$ Shadowed Fading Channels

This paper investigates the impact of realistic propagation conditions on the achievable secrecy performance of multiple-input multiple-output systems in the presence of an eavesdropper (Eve). Specifically, we concentrate on the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\kappa$</tex-math></inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> shadowed fading model because its physical underpinnings capture a wide range of propagation conditions, while, at the same time, it allows for a much better tractability than other state-of-the-art fading models. By considering transmit antenna selection and maximal ratio combining reception at the legitimate (Bob) and Eve's receiver sides, we study two relevant scenarios: 1) the transmitter knows Bob's channel state information (CSI) but not Eve's CSI, and 2) the transmitter is aware of the CSI of both Bob and Eve channels. For this purpose, we first obtain novel and tractable expressions for the statistics of the maximum of independent and identically distributed (i.i.d.) variates related to the legitimate channel. Based on these results, we derive novel closed-form expressions of the two aforementioned scenarios to assess the secrecy performance of the underlying system. Specifically, for cases: 1) the secrecy outage probability (SOP), the probability of strictly positive secrecy capacity (SPSC), and 2) the average secrecy capacity (ASC). Moreover, we develop analytical asymptotic expressions of the SOP and ASC in the high signal-to-noise ratio regime. In all instances, secrecy performance metrics are characterized in closed-form, without requiring the evaluation of Meijer-G or Fox-H functions. Some useful insights on how the different propagation conditions and the number of antennas impact the secrecy performance are also provided.

Greedy Search-Based Optimal Transmit Antenna Selection for Massive MIMOME Channels

The conventional transmit antenna selection in massive multiple-input multiple-output multiple antenna eavesdropper (MIMOME) channels has been focused on the optimal transmit antenna selection corresponding to a given number of transmit antennas to select. To maximize the secrecy capacity, the antenna selection should be optimized considering the number of transmit antennas to select. In this letter, we propose the greedy search based optimal transmit antenna selection (G-OTAS) algorithm to maximize the secrecy capacity by pursuing the optimal number of transmit antennas in massive MIMOME channels. Throughout the simulation and numerical results, it is demonstrated that the proposed G-OTAS algorithm maximizes the secrecy capacity and effectively reduces the computational complexity compared to those of the reference schemes.

Energy efficient transmit antenna selection scheme for correlation relied beamspace mmWave MIMO system

mmWave communication system that offers high datarate are accompanied by massive number of antennas for high gain transmission. These large array of antennas requires special beamforming schemes and also requires large number of RF chains. Beamspace MIMO is a beamforming architecture that employs large antenna array and supports limited number of RF chains by converting conventional mmWave channel into sparse channel. Multiple antenna array system are susceptible to antenna correlation effect thereby reducing the system capacity. Transmit antenna selection methods considering the effect of antenna correlation provides feasible solution by maximising the system capacity and energy efficiency. In order to improve the energy efficiency of the transmitted signal three new transmit antenna selection schemes are proposed by considering the effects of antenna correlation. The simulation results demonstrate that the proposed methods improve energy efficiency and sum rate.

Adaptive multiple access assists multiple users over multiple‐input‐multiple‐output non‐orthogonal multiple access wireless networks

SummaryThe works in this study examine three scenarios. The scenario (I) as a common scenario with the base station (BS) and users are equipped with multiple antennae over Nakagami‐m fading channels. To improve system performance, the transmit antenna selection (TAS) and maximization of successive interference cancellation (max‐SIC) framework are deployed. A novel cumulative distribute function (CDF) for the scenario (I) is proposed, and the outage probability (OP) in novel closed form can be obtained. It is challenging due to scenario (I) consists of massive users equipped with multiple antennae over Nakagami‐m fading channels. Therefore, this study proposes scenario (II) with a maximum of SIC and minimum of instantaneous bit rate (max‐SIC‐min‐rate) framework for aiding multiple access to reduce the algorithm complexity of the scenario (I). Some adaptive multiple access strategies are proposed as adaptive PA factors, adaptive min–max bit rate threshold, and adaptive Nakagami‐m coefficient are proposed. Finally, the scenario (III) is examined by also applying the max‐SIC‐min‐rate framework as the scenario (II), however, comparing to the adaptive min–max bit rate threshold to investigate the OP, system throughput, and energy‐efficient (EE) performances. The obtained results as shown in the numerical results section confirm that, on one hand, the system performance of the scenario (II) is approximate or better than the scenario (I) at the same transmit power; on another hand, the scenario (III) reaches the system throughput and EE performances better than the other scenarios at the high transmit power. The analysis results are proved and verified by Monte Carlo simulation results.