Antenna Subset Selection Research Articles

An antenna subset selection algorithm in distributed MIMO radar for target localization via convolutional neural network

AbstractSince the distributed MIMO radar (DMR) has widely spread transmitters and receivers, it can provide higher target detection probability, as well as superior target tracking and localization performance than the monostatic/bistatic radar systems. An effective radar resource allocation scheme can optimise the DMR system parameter and obtain better system performance. In this paper, a critical but limited system resource is optimised, that is, select a subset of the active radar antennas. In this scenario, the convolutional neural network of the antenna subset selection for target localization (LCNN‐ASS) algorithm in the DMR is proposed based on two free switching policies. The proposed algorithm is immune to the failure of a single policy and selects antenna subsets from the entire sets with a remarkable computational speed. Therefore, the proposed algorithm increases the flexibility of resource scheduling over traditional algorithms. Simulation experiments and performance analysis demonstrate the localization performance and flexibility of the LCNN‐ASS algorithm.

Transmit Antenna Subset Selection in Cooperative SM-MIMO Vehicular System

This paper proposes a transmit antenna subset selection (TASS) in decode-and-forward (DF) cooperative spatial modulation multiple-input multiple-output (CSM-MIMO) vehicular system to enhance the communication performance. Specifically, the first-order autoregressive (FOAR) process is taken to model the time-varying vehicular fading channels. The transmit antenna (TA) subsets at the source and the relay that maximize the minimum squared Euclidean distance (MSED) can be respectively selected, which requires no complete channel state information (CSI). A closed-form analytical average bit error rate (ABER) of the CSM-MIMO vehicular system with the proposed TASS is derived. Numerical results demonstrate the correctness of the analytical ABER performance. The proposed TASS in the CSM-MIMO vehicular system achieves superior ABER performance than the existing CSM-MIMO system and the traditional TASS schemes.

Secure Directional Modulation in RIS-Aided Networks: A Low-Sidelobe Hybrid Beamforming Approach

This letter considers the incorporation of secure directional modulation in reconfigurable intelligent surface (RIS)-aided communication networks. With elaborately selected antenna subsets, secure directional modulation generates randomized signals at undesired directions to assure physical-layer security. One major challenge of introducing RIS is that an additional beam, other than the user-specific beam, is required to align to the RIS. The interplay between the two beams can cause high sidelobe, which is non-trivial to address due to the discrete optimization in antenna subset selection. To tackle this challenge, we propose a novel cross-entropy iterative method to achieve low-sidelobe hybrid beamforming for secure directional modulation in RIS-aided networks. We use maximum sidelobe energy as the objective function to reduce the emission, and deploy Kullback-Leibler divergence as the criterion in the iterative selection of good candidate antenna subsets. Simulation results illustrate that the proposed scheme can reduce the sidelobe energy by 8 dB, and the symbol error rate of the eavesdropper maintains at 0.75 (0.875) for QPSK (8PSK) even when its signal-to-noise ratio increases.

Novel Receive Antenna Selection Scheme for Precoding-Aided Spatial Modulation with Lattice Reduction.

In this paper, a new receive antenna subset (RAS) selection scheme is proposed for precoding-aided spatial modulation (PSM). First, a lattice reduction (LR)-based precoder is employed instead of a conventional zero-forcing (ZF) precoder. It is analytically shown that a full diversity gain can be achieved by the LR-based ZF precoder without RAS selection. Then, an optimal LR-based RAS selection criterion is derived for the over-determined LR-based PSM systems, and a suboptimal selection algorithm is additionally presented. It is also shown that optimal and suboptimal RAS selection algorithms based on LR improve the BER performance of the LR-based PSM system. Further, the overall diversity order of the over-determined LR-based PSM systems with optimal LR-based RAS selection is analyzed. Finally, diversity analysis and simulation results show that the LR-ZF-based PSM system with optimal LR-based RAS selection outperforms the conventional ZF-based PSM system with conventional optimal RAS selection.

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.

Research on 5G Video Security Communication Technology Based on Massive MIMO

Background: The paper aimed at studying a large number of classified and sensitive information transmission security issues brought by 5G mobile communication system. Methods: In this paper, the principle of beamforming and its shortcomings are introduced by combining the large-scale MIMO technology and directional modulation technology, and the directional modulation technology based on antenna subset selection and the hybrid array is introduced to realize the safe transmission target. The results show that large-scale MIMO technology has become a key technology of 5G mobile communication, but the factors such as multipath fading in the actual wireless channel have not been fully considered, and the accurate estimation error of channel state information (CSI) will affect the ideal security level it can achieve. Results: The combined application of massive MIMO technology and directional modulation technology in the 5G system brings security to its communication. Conclusion : Directional modulation technology based on signal modulation has become an important research point of the 5G system because it does not need to consider the eavesdropper's computing power and can achieve the purpose of safe transmission by disturbing the signal constellation in the unexpected direction.

A Random Antenna subset selection jamming method against multistatic radar system

Multistatic radar system (MSRS) is considered an effective scheme to suppress mainlobe jamming, since it has higher spatial resolution enabling jamming cancellation from the spatial domain. To develop electronic countermeasures against MSRS, a low complexity random array subset selection (RASS) jamming method is proposed in this paper. In the RASS jammer, elements of the array antenna are activated randomly, leading to stable mainlobe and random sidelobes, which is different from the traditional jammer that applies the complete antenna array enjoying constant mainlobe and sidelobes. We study the autocorrelation matrix of RASS jamming signals received by radars, and derive its rank, revealing that the rank of jamming subspace is increased thus severely degrading the performance of jamming cancellation. Moreover, we calculate the output jamming to signal-and-noise ratio (JSNR) after the subspace-based jamming suppression methods used in MSRS with the proposed jamming method, which demonstrates that the rank increasing property invalidates such suppression methods. Both simulation and experiment results verify our analytical deduction and exhibit the improved countermeasure performance of our proposed RASS jamming method compared to the traditional jammers.

Efficient Transmit Antenna Subset Selection for Multiuser Space-Time Line Code Systems.

We consider the problem of the efficient transmit antenna subset (TAS) selection for maximizing the signal-to-interference-plus-noise ratio (SINR) of multiuser space–time line code (MU–STLC) systems. The exhaustive search for optimal TAS selection is impractical since the total number of transmit antennas increases. We propose two efficient TAS selection schemes based on the Woodbury formula. The first is to incrementally select active transmit antennas among the available transmit antennas. To reduce the complexity of the incremental selection scheme, the Woodbury formula is employed in the optimization process. The second is to perform the decremental strategy in which the Woodbury formula is also applied to develop the low-complexity TAS selection procedure for the MU–STLC systems. Simulation results show that the proposed incremental and decremental TAS selection algorithms offer better alternatives than the existing greedy TAS selection algorithm for the MU–STLC systems. Furthermore, in terms of bit error rate, the proposed minimum mean square error decremental TAS selection algorithm turns out to outperform the existing greedy algorithm with significantly lower computational complexity. Finally, we analyze the detection SINR penalty experienced from TAS selection and the analytical quantity is shown to be well matched with simulation results.

Hybrid Combining Based on Constant Phase Shifters and Active/Inactive Switches

In this paper, we propose a new hybrid analog and digital combining architecture for millimeter wave (mmWave) multi-user multiple-input multiple-output (MU-MIMO) systems. The proposed structure employs antenna subset selection per radio frequency (RF) chain based on active / inactive switches and uses constant phase shifters (CPS) to control the phases of signals in the RF circuit. In this scheme, for each RF chain, a subset of receive antennas that contribute more to the desired signal power than the interference power is chosen for signal combining in the analog domain, whereas other receive antennas are excluded from signal combining, thereby enhancing sum-rates. Simultaneously, the proposed structure reduces power consumption in the RF circuit by exclusively activating switches that correspond to the antennas selected for each RF chain. We also develop three low-complexity algorithms for per-RF chain antenna subset selection. Finally, through numerical simulation, we show that the proposed structure provides higher spectral efficiency and higher energy efficiency than conventional hybrid analog and digital combining schemes for mmWave MU-MIMO systems.

Energy Efficiency-Oriented Resource Allocation for Massive MIMO Systems with Separated Channel Estimation and Feedback

This paper proposes a dynamic resource allocation scheme to maximize the energy efficiency (EE) for Massive MIMO Systems. The imperfect channel estimation (CE) and feedback are explicitly considered in the EE maximization problem, which aim to optimize the power allocation, the antenna subset selection for transmission, and the pilot assignment. Assuming CE error to be bounded for the complex-constrained Cramer–Rao Bound (CRB), theoretical results show that the lower bound is directly proportional to its number of unconstrained parameters. Utilizing this perspective, a separated and bi-directional estimation is developed to achieve both low CRB and low complexity by exploiting channel and noise spatial separation. Exploiting global optimization procedure, the optimal resource allocation can be transformed into a standard convex optimization problem. This allows us to derive an efficient iterative algorithm for obtaining the optimal solution. Numerical results are provided to demonstrate that the outperformance of the proposed algorithms are superior to existing schemes.

Diversity order of precoding‐aided spatial modulation using receive antenna selection

In this Letter, the authors analyse the diversity order of the precoding-aided spatial modulation (PSM) system with receive antenna subset (RAS) selection. It is shown that when there are N T transmit antennas, N R receive antennas, and N S selected receive antennas, the achievable diversity order is given by N T − N S + 1 N R − N S + 1 , where the product gain of N T − N S + 1 is achieved by the zero-forcing precoding scheme and another of N R − N S + 1 can be attained by the optimal RAS selection algorithm.

Inter-Subset Hamming Distance Maximization for Enhancing the Physical Layer Security of Antenna Subset Modulation

In this article, a novel antenna subset selection technique for enhancing the Physical Layer Randomness (PLR) of Antenna Subset Modulation (ASM) has been proposed. Hamming Distance Optimized Antenna Subset Selection (HD-OASS) minimizes the correlation between the antenna subsets at transmitter by maximizing the hamming distance between the successively used antenna subsets. Unlike previously proposed Randomized Antenna Subset Selection (RASS) and Side-Lobe Level Optimized Antenna Subset Selection (SLL-OASS), in which antenna subsets are randomly selected from the codebook, HD-OASS chooses the antenna subsets having optimally maximized hamming distance. It is shown that SLL-OASS has rather unfavorable effects on encryption strength due to considerable reduction of codebook size. Furthermore, HD-OASS has been shown to outperform RASS and SLL-OASS in terms of encryption strength in the unwanted directions of eavesdropper.

Transmit Antenna Selection for Precoding-Aided Spatial Modulation

This paper examines the impacts of transmit antenna subset (TAS) selection on the biterror-rate (BER) performance of linear precoding-aided spatial modulation (PSM) multiple-input multipleoutput (MIMO) systems. It is analytically shown that decreasing the number of active transmit antennas by TAS selection, which can be used to reduce the number of RF units at the transmitter side, always degrades the BER performance. The expression of a received signal-to-noise ratio (SNR) loss is also derived and its analytical results are shown to be well-matched with simulation results. Furthermore, it is analyzed that when there are NT transmit antennas, NS selected transmit antennas, and NR receive antennas, an achievable diversity order of the zero-forcing (ZF)-based PSM MIMO systems either with optimal TAS selection or without TAS selection can be given as N T -N R +1. To select an optimal TAS based on exhaustive search, an optimization criterion to maximize the received SNR of the selected TAS is employed. In addition, a low-complexity TAS selection scheme is presented using a decremental strategy. It is also observed that the decremental TAS selection algorithm can achieve almost the same BER and achievable rate performance as the optimal one while attaining much lower complexity. Finally, simulation results show that under the identical number of active transmit antennas, the ZF-PSM MIMO system with TAS selection outperforms the conventional ZF-PSM without TAS selection.

Efficient Transmit Antenna Selection for Receive Spatial Modulation-Based Massive MIMO

In this article, two efficient transmit antenna subset (TAS) selection schemes are proposed for receive spatial modulation (RSM)-based massive multiple-input multiple-output. First, an incremental TAS selection algorithm based on the maximization of the received signal-to-noise ratio is presented to select N S active transmit antennas effectively among the available Nτ transmit antennas. Then, to reduce complexity further, the modified TAS selection algorithm performs two consecutive selection stages. The pre-processing stage selects active transmit antennas whose number Np is less than the number of N S of the total transmit antennas to be selected and is equal to or greater than the number N R of the receive antennas. Then the post-processing stage chooses the remaining N S - Np active antennas. In the first stage, a simple norm-based algorithm is employed to reduce the complexity significantly. In the second stage, an incremental selection strategy is performed to find additional transmit antennas. It is demonstrated that the bit error rate and achievable rate of the proposed TAS selection algorithms are close to those of the decremental algorithm. Further, the simulation results show that the proposed TAS selection schemes offer significantly reduced complexity compared to the decremental TAS selection when the difference between the number of selected transmit antennas and the number of total available transmit antennas available is large. Furthermore, the impacts of the channel estimation error on the performance of TAS selection-based RSM systems are examined.

Orthogonality Structure Designs for Generalized Precoding Aided Spatial Modulation

In this letter, we propose an orthogonality structure design (OSD) for the generalized precoding aided spatial modulation (GPSM) to overcome the performance degradation caused by correlated fading channels. To improve the bit error rate (BER) performance of GPSM system, we devise an efficient receive antenna subset selection (RAS) technique relied on the mechanisms of maximizing the equivalent channel gain. To facilitate a better trade-off between performance and computational complexity, we study the peculiarities of the Hermitian matrix which provides an important insight for conceiving orthogonality conditions to the channel matrix of GPSM system. We prove that the performance gain in terms of BER can be attained with the aids of the proposed efficient RAS, and OSD-aided schemes with low-complexity. In particular, our results demonstrate that the OSD-aided scheme is capable of providing significant BER performance improvement for GPSM systems, compared to that of current strategies.

Hybrid mmWave MIMO-OFDM Channel Estimation Based on the Multi-Band Sparse Structure of Channel

This paper presents a hybrid channel estimator for multiple-input multiple-output orthogonal frequency-division multiplexing mmWave systems based on the sparse nature of the angular channel and leveraging the compressed sensing (CS) tools. The angular support is recovered without any discretization by treating the angular channel in a continuous framework which resolves the limited angular resolution of the discrete sparse channel models used in the previous CS-based channel estimators. The power leakage problem is also addressed by modeling the continuous angular channel as a multi-band signal with the bandwidth of each sub-band being proportional to the amount of power leakage caused by the limited antenna array length. The RF combiner is implemented using a network of low-power switches for antenna subset selection based on a multi-coset sampling pattern. Simulation results validate the low reconstruction error and good performance of the proposed channel estimator.

Transmit Antenna Subset Selection in Generalized Spatial Modulation Systems

The existing literature on transmit antenna selection (TAS) aided spatial modulation (SM) systems extensively deals with the Euclidean distance (ED) based TAS owing to its high transmit diversity gain. In this paper, we consider the ED-TAS aided generalized spatial modulation (GSM) system that transmits multiple symbols in each channel use and characterize its attainable diversity gain. Second, we show that the minimum ED of the received constellation does not grow beyond a certain point when the size of the signal set is sufficiently large, which facilitates low-complexity implementations of the ED-TAS aided SM system. Our numerical studies revealed that a signal-to-noise gain of about 8 dB is achievable by employing ED-TAS in the GSM system compared to its counterpart dispensing with ED-TAS.

Analyzing Physical Layer Security of Antenna Subset Modulation as Block Encryption Ciphers

In this paper, a novel framework for analyzing Physical Layer Security (PLS) of Directional Modulation (DM) techniques has been introduced. The proposed framework maps the concepts of PLS techniques to cryptographic techniques, enabling the analysis of DM techniques as block encryption ciphers. The relevance of the proposed framework has been shown by applying it on Antenna Subset Modulation (ASM). After appropriate physical layer mappings, the encryption strength of ASM is analyzed using National Institute of Standards and Technology’s Statistical Test Suite (NIST’s STS). The performance of ASM is benchmarked against strong block encryption cipher of Advanced Encryption Standard (AES) using data types of image, text, and audio. A new metric, namely Physical Layer Randomness (PLR), has been introduced for direct comparison of encryption strength of PLS techniques to that of cryptographic techniques. The analysis shows that Optimized Antenna Subset Selection (OASS) that reduced average Side-Lobe Levels (SLLs) and improved Symbol Error Rate (SER), has rather adverse effects on encryption strength of ASM. Furthermore, it has been found that scrambling the selection of antenna subsets imparts negligible improvement in PLR.

Transmit Antenna Subset Selection for Single and Multiuser Spatial Modulation Systems Operating in Frequency Selective Channels

The extensive study of transmit antenna (TA) subset selection (TAS) in the context of spatial modulation (SM) has recently revealed that significant performance gains are attainable compared to SM systems operating without TAS. However, the existing TAS techniques conceived for SM were studied by considering a frequency-flat channel, which does not represent practical frequency-selective channels. In this paper, we address this open problem by designing TAS schemes for zero-padded single-carrier SM systems. Specifically, we employ a partial successive interference cancellation (SIC) receiver and invoke Euclidean distance based TA subset selection (ED-TAS) for each of the subchannels. Furthermore, we show using a theoretical analysis that the parallel subchannels obtained are nearly identical, which enables us to employ majority logic decision to obtain a single TA subset to be used in all the subchannels. The computational burden is additionally reduced by restricting the number of subchannels over which the ED-TAS technique is invoked. Furthermore, the proposed TAS schemes are extended to the multiuser scenario. The theoretical insights developed are validated using simulation results. Specifically, a signal-to-noise ratio gain as high as 3 dB is observed in the single user scenario and about 1 dB in case of a two-user scenario upon employing our TAS.

Antenna subset selection for massive MIMO systems: A trace-based sequential approach for sum rate maximization

Massive MIMO technology is a promising candidate for the next generation wireless communication systems. The basic idea is to implement a large number of antennas at the base station (BS) of a cell to serve a relatively small number of users. Such an approach brings many benefits in terms of the throughput and energy efficiency. Two major challenges associated with massive MIMO systems are high power consumption and high system complexity. These problems can effectively be dealt with by performing antenna-subset selection at the BS. In this paper, we propose low-complexity antenna-subset selection schemes for both single-cell and multiple-cell cooperative massive MIMO systems for equal-rate zero-forcing beamforming transmission at the BS. These schemes sequentially select an antenna that contributes the most to the overall system sum rate. Simulation results show that our proposed schemes outperform other schemes with similar computational complexities and even surpass some of the higher computational complexity schemes in a massive MIMO setting.