Transmit Antenna Subset Selection Research Articles

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.

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.

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.

Decoupled Transmit and Receive Antenna Selection for Precoding-Aided Spatial Modulation

This paper proposes an optimal joint transmit and receive antenna subsets (TRASs) selection scheme for linear precoding-aided spatial modulation (PSM) systems. The optimal joint TRASs selection is performed by exhaustively searching, so that it is difficult to analyze an achievable diversity gain and it has a huge complexity. To tackle this problem, we propose a decoupled TRAS selection method which selects receive antenna subset (RAS) and transmit antenna subset (TAS) in a two-step serial manner. By computing a lower bound on the pairwise error probability and conducting extensive simulations, it is shown that the zero-forcing (ZF)-based PSM system with $N_{T} $ transmit antennas, $N_{S} $ selected transmit antennas, $N_{R} $ receive antennas, and $N_{D} $ selected receive antennas achieves diversity order of $(N_{T} -N_{D} +1)(N_{R} -N_{D} +1)$ even with TAS selection. Furthermore, decreasing the number of active transmit antennas by TAS selection after RAS selection is analytically shown to always degrade the bit error rate performance. The analysis results are validated by simulations. These analytical and simulation results can be regarded as natural extensions of earlier works on receive antenna selection and transmit antenna selection for the PSM systems. In addition, we study and compare two efficient algorithms for TRAS selection. First, incremental and decremental algorithms are employed for separable RAS and TAS successive selection, respectively, which have an excellent performance. It is analytically shown that the computational complexity of the first proposed decoupled suboptimal TRAS selection scheme is enormously reduced compared to the joint optimal and decoupled optimal algorithms. Second, an incremental TAS selection approach replaces the decremental strategy in the first TRAS selection algorithm to further reduce the complexity.

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.

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.

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.

Transmit Antenna Subset Selection in MIMO OFDM System using Adaptive Mutuation Genetic Algorithm

Multiple input multiple output techniques are considered attractive for future wireless communication systems, due to the continuing demand for high data rates, spectral efficiency, suppress interference ability and robustness of transmission. MIMO-OFDM is very helpful to transmit high data rate in wireless transmission and provides good maximum system capacity by getting the advantages of both MIMO and OFDM. The main problem in this system is that increase in number of transmit and receive antennas lead to hardware complexity. To tackle this issue, an effective optimal transmit antenna subset selection method is proposed in paper with the aid of Adaptive Mutation Genetic Algorithm (AGA). Here, the selection of transmit antenna subsets are done by the adaptive mutation of Genetic Algorithm in MIMO-OFDM system. For all the mutation points, the fitness function are evaluated and from that value, best fitness based mutation points are chosen. After the selection of best mutation points, the mutation process is carried out, accordingly. The implementation of proposed work is done in the working platform MATLAB and the performance are evaluated with various selection of transmit antenna subsets. Moreover, the comparison results between the existing GA with mutation and the proposed GA with adaptive mutation are discussed. Hence, using the proposed work, the selection of transmit antenna with the maximum capacity is made and which leads to the reduced hardware complexity and undisturbed data rate in the MIMO-OFDM system

Comparison of Adaptive Mutation Genetic Algorithm and Genetic Algorithm for Transmit Antenna Subset Selection in MIMO- OFDM

Multiple input multiple output techniques are considered attractive for future wireless communication systems, due to the continuing demand for high data rates, spectral efficiency, suppress interference ability and robustness of transmission. MIMO-OFDM is very helpful to transmit high data rate in wireless transmission and provides good maximum system capacity by getting the advantages of both MIMO and OFDM. The main problem in this system is that increase in number of transmit and receive antennas lead to hardware complexity. To tackle this issue, an effective optimal transmit antenna subset selection method is proposed in paper with the aid of Adaptive Mutation Genetic Algorithm (AGA). Here, the selection of transmit antenna subsets are done by the adaptive mutation of Genetic Algorithm in MIMO-OFDM system. For all the mutation points, the fitness function are evaluated and from that value, best fitness based mutation points are chosen. After the selection of best mutation points, the mutation process is carried out, accordingly. Moreover, the comparison results between the GA with mutation and our GA with adaptive mutation are discussed. Hence, using the proposed work, the selection of transmit antenna with the maximum capacity is made and which leads to the reduced hardware complexity and undisturbed data rate in the MIMO-OFDM system General Terms Signal to noise ratio, Ergodic Capacity, Fitness Function

Transmit antenna subset selection for high-rate MIMO-OFDM systems in the presence of nonlinear power amplifiers

The deployment of antenna subset selection on a per-subcarrier basis in MIMO-OFDM systems could improve the system performance and/or increase data rates. This paper investigates this technique for the MIMO-OFDM systems suffering nonlinear distortions due to high-power amplifiers. At first, some problems pertaining to the implementation of the conventional per-subcarrier antenna selection approach, including power imbalance across transmit antennas and noncausality of antenna selection criteria, are identified. Next, an optimal selection scheme is devised by means of linear optimization to overcome those drawbacks. This scheme optimally allocates data subcarriers under a constraint that all antennas have the same number of data symbols. The formulated optimization problem to realize the constrained scheme could be applied to the systems with an arbitrary number of multiplexed data streams and with different antenna selection criteria. Finally, a reduced complexity strategy that requires smaller feedback information and lower computational effort for solving the optimization problem is developed. The efficacy of the constrained antenna selection approach over the conventional selection approach is analyzed directly in nonlinear fading channels. Simulation results demonstrate that a significant improvement in terms of error performance could be achieved in the proposed system with a constrained selection compared to its counterpart.

On capacity gain of antenna subset selection for multiple antenna multicasting

AbstractIn this letter, we consider the transmit antenna subset selection scheme in multicast channels where the antenna subset is selected to maximise the minimum signal‐to‐noise power ratio among the associated users. Using an asymptotic analysis, the average capacity is derived for the large number of users asymptote under the assumption that the antennas are divided into non‐overlapping subsets, and each of them is independent, identical, spatially uncorrelated, and Rayleigh distributed. The numerical results demonstrate that the asymptotic average capacity is close to the exact capacity when signal‐to‐noise power ratio is not large or the number of users is large. Using this result, we compare the asymptotic average capacity of the selection scheme with that of the open‐loop multiple antenna multicasting scheme, in which only one antenna subset is employed, and its number of antennas is the same as that of the antenna subset of the selection scheme. Specifically, it is shown that the asymptotic capacity gain over the open‐loop scheme is significant when the number of antennas in each antenna subset is small. Copyright © 2013 John Wiley &amp; Sons, Ltd.

Transmit Antenna Subset Selection for Downlink MIMO Systems in Multicell Environments

This letter proposes a statistical cooperative scheme for transmit antenna subset selection in multiple-input multiple-output (MIMO) multicell systems. The proposed scheme is practical in that it only utilizes the statistical information for the adjacent links. However, it provides almost 90 percent of the average mutual information of the full cooperative scheme which requires a large amount of the instantaneous information and joint cooperation between base stations. Furthermore, the proposed scheme shows substantial performance enhancements over the competitive scheme in which the effects of intercell interference generated by the antenna selection are not considered.

Hybridization of ANN and GA with Adaptive Mutation: A Proficient Technique for Optimal Transmit Antenna Subset Selection for MIMO-OFDM Systems

Hybridization of ANN and GA with Adaptive Mutation: A Proficient Technique for Optimal Transmit Antenna Subset Selection for MIMO-OFDM Systems

Statistical Multimode Transmit Antenna Selection for Limited Feedback MIMO Systems

In a wireless multiple-input multiple-output (MIMO) system, transmit antenna selection is an effective means of achieving good performance with low complexity. We consider spatial multiplexing with linear receivers, and equal power and equal rate allocation over different selected transmit antennas in order to reduce feedback overhead. Under these constraints, we address the problem of statistical multimode transmit antenna subset selection to improve the capacity of spatially correlated MIMO fading channels. In particular, we first derive an analytical closed-form expression for the expectation of the lower bound on the capacity using the smallest eigenvalue distribution of a Wishart matrix. Then, we propose a transmit antenna subset selection criterion of maximizing this average lower-bound capacity.

Outage Probability Based Optimal Transmission of Space Time Block Codes over Correlated Distributed Antennas

Aiming to optimally transmit space-time block codes (STBCs) over distributed antennas (DAs), this paper examines downlink transmit antenna subset selection with power allocation for STBCs in non-ergodic Rayleigh fading channels with receive antenna correlations. Closed-form outage probability is first derived, which is a function of data rate, rate of STBCs, transmit power, large-scale fading (shadowing and path loss), power allocation weights to each DA and receive antenna correlation. However, achieving the optimal power allocation solution is computationally demanding and the use of sub-optimal techniques is necessitated. Assuming feedback of eigenvalues of transmit and receive antenna correlation matrix at the transmitter and accurate channel state information (CSI) at the receiver, an antenna subset selection with sub-optimal power allocation scheme is proposed, whose performance approaches optimal. The effectiveness of this sub-optimal method has been demonstrated by numerical results.

Transmit antenna selection in linear receivers: geometrical approach

Transmit antenna subset selection in spatial multiplexing systems is considered. In particular, selection algorithms aiming to minimise the error rate when linear detectors are used at the receiver are proposed. Previous work on antenna selection has considered capacity and post-processing SNR selection criteria. However, a geometrical interpretation of the decoding process which also permits development of a suboptimal algorithm that yields a considerable complexity reduction with only a small loss in performance, is considered.