Transmit Antenna Selection Schemes for Spatial Modulation Systems: Search Complexity Reduction and Large-Scale MIMO Applications

Recently massive MIMO systems have attracted a lot of attention. A serious limitation in implementing massive MIMO is the number of RF chains required, which is due to its high implementation cost and power consumption. Antenna selection is a wise remedy, that not only reduces the number of required RF chains, but also improves the system’s performance. In this work, two low complexity capacity-maximizing transmit antenna selection (TAS) schemes, one for low SNR region and one for medium to high SNR region, are proposed. It is shown that the proposed antenna selection schemes enhance the MIMO link’s capacity at low SNRs, and select only one antenna in more than $$90\%$$ of channel realizations, which in terms of numbers of required RF chains is very promising. The performance of the proposed schemes are compared to an existing high performance greedy TAS technique in terms of average capacity and complexity. Finally, a close analytical approximation for average capacity of the proposed capacity-based subset selection scheme is presented.

In this paper, the bit error rate (BER) performance of multiuser multiple-input multiple-output (MIMO) systems over Rayleigh fading channels is studied, and corresponding asymptotic performance is analyzed. Based on the asymptotic analysis at high signal to noise ratio (SNR), using the probability density functions (PDF) of the instantaneous channel power gain, the diversity gain and coding gain of the system with transmit antenna selection (TAS) scheme and space-time block coding (STBC) scheme are derived, respectively. As a result, the same full diversity gain is achieved for two transmission schemes, but their coding gains are different. With the obtained diversity gain and coding gain, the asymptotic BER expressions for two transmission schemes are respectively derived, which are in good agreement with the corresponding simulation results. The results show that the multiuser MIMO system with TAS scheme has better BER performance than that with STBC scheme due to higher coding gain.

Euclidean distance optimized antenna selection (EDAS) can significantly improve the bit-error-rate (BER) performance of spatial modulation (SM) systems. However, the exhaustive search over all possible antenna subsets leads to inherently high-search complexity. In this letter, a cross-entropy-based antenna selection (CEAS) scheme is proposed, by formulating the antenna selection problem in SM as a combinatorial optimization one. Simulation results show that the proposed CEAS scheme achieves considerable reduction in search complexity, while approaching the optimal performance of exhaustive search.

In this paper, transmit antenna selection (TAS) is applied to space shift keying (SSK) modulation to obtain diversity gain. The receiver selects a transmit antenna subset in each transmission block according to the channel state information (CSI) and sends the subset index to the transmitter through feedback. Several antenna selection schemes are evaluated for SSK from perspectives of performance, feedback overhead and complexity. A greedy transmit antenna selection scheme is proposed to reduce the computation complexity, which shows almost the same performance as exhaustive search. In the special case that the number of active antennas equals two, an antenna selection scheme with one transmit antenna fixed (Fix-1 scheme) is proposed to reduce the amount of feedback, whose exact bit error ratio (BER) performance is derived. Through asymptotic BER analysis we show that Fix-1 scheme has the same diversity order as exhaustive search.

In this paper, the effective capacity of a multiple-input multiple-output (MIMO) system in two different cases with receive antenna selection (RAS) and transmit antenna selection (TAS) schemes is investigated. A closed-form solution for the maximum constant arrival rate of this network with statistical delay quality of service (QoS) constraint is extracted in the quasi-static fading channel. This study is conducted in two different cases. When channel state information (CSI) is not available at the MIMO transmitter, implementation of TAS is difficult. Therefore, RAS scheme is employed and one antenna with the maximum instantaneous signal to noise ratio is chosen at the receiver. On the other hand, when CSI is available at the transmitter, TAS scheme is executed. In this case, one antenna is selected at the transmitter. Moreover, an optimal power-control policy is applied to the selected antenna and the effective capacity of the MIMO system is derived. Finally, this optimal power adaptation and the effective capacity are investigated in two asymptotic cases with the loose and strict QoS requirements. In particular, we show that in the TAS scheme with the loose QoS restriction, the effective capacity converges to the ergodic capacity. Then, an exact closed-form solution is obtained for the ergodic capacity of the channel here.

In this paper, we introduce a joint antenna selection and user sorting scheme in multi-user multiple-input multiple-output (MU-MIMO) systems, in which Tomlinson-Harashima precoding (THP) is adopted. In MU-MIMO with THP, antenna selection and user sorting are important means to improve the system performance. By considering the interrelationship between antenna selection and user sorting in THP, based on the scheme, we propose an efficient algorithm to solve the antenna selection and user sorting jointly, which achieves near performance of the optimal one obtained by exhaustive search. Analytical results demonstrate the proposed scheme has low complexity. Simulation results show the availability of our proposed scheme.

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.

In this paper, we present a comprehensive performance analysis of multiple-input multiple-output (MIMO) systems with transmit antenna selection (TAS) and stochastic power allocation (SPA) for the spatially correlated fading channels. Two best transmit antennas that maximize the instantaneous received signal-to-noise (SNR) are selected to transmit the Alamouti scheme and maximal-ratio combining (MRC) is applied at the receiver. With correlation matrices available to the transmitter, SPA is applied on these selected antennas. Two different methods are given to derive the explicit upper bounds on the bit-error rate (BER) performance. Finally we present numerical results to verify our analysis. It is shown that the TAS/SPA scheme can achieve high performance in spatially correlated channels.

This paper applies transmit antenna selection algorithms to spatial-temporal combining-based spatial multiplexing (SM) ultra-wideband (UWB) systems. The employed criterion is based on the largest minimum output signal-to-noise ratio of the multiplexed streams. It is shown via simulations that the bit error rate (BER) performance of the SM UWB systems based on the two-dimensional Rake receiver is significantly improved by antenna diversity through transmit antenna selection on a log-normal multipath fading channel. When the transmit antenna diversity through antenna selection is exploited in the SM UWB systems, the BER performance of the spatial-temporal combining-based zero-forcing (ZF) receiver is also compared with that of the ZF detector followed by the Rake receiver.

In recent years, due to the increasing demand of the data transmission rate, a lot of research based on Multiple- Input Multiple-Output (MIMO) system is established. MIMO systems can increase the system capacity and improve transmission reliability. However, the multiple RF chains associated with multiple antennas are costly in terms of size, power and hardware. Antenna selection techniques have been applied in MIMO system design to reduce the system complexity and cost. In this paper, we consider two schemes of antenna selection in correlated Rayleigh channels i.e. the maximal ratio transmission and Orthogonal Space-Time Block Code technique. The simulation results illustrate that; the new antenna selection scheme can obtain performance close to the optimum selection with low computational complexity.

In wireless communications, antenna selection (AS) is a widely used method for reducing comparable cost of multiple RF chains in MIMO systems. As is well known, most of literatures on combining AS with MIMO techniques concern linear modulations such as phase shift keying (PSK) and quadrature amplitude modulation (QAM). The combination of CPM and MIMO has been considered an optimal choice that can improve its capacity without loss of power and spectrum efficiency. The aim of this paper is to investigate joint transmit and receive antenna selection (JTRAS) in CPM MIMO systems. Specifically, modified incremental and decremental JTRAS algorithms are proposed to adapt to arbitrary number of selected transmit or receive antennas. The computational complexity of several JTRAS algorithms is analyzed from the perspective of channel capacity. As a comparison, the performances of bit error rate (BER) and spectral efficiency are evaluated via simulations. Moreover, computational complexity of the JTRAS algorithms is simulated in the end. It is inferred from discussions that both incremental JTRAS and decremental JTRAS perform close to optimal JTRAS in BER and spectral efficiency. In the sense of practical scenarios, adaptive JTRAS can be employed to well tradeoff performance and computational complexity.

We analyze the asymptotic performance of rate adaptation for Transmit Antenna Selection (TAS) and Maximum Eigenmode Beamforming (MEB) schemes in Multiple-Input Multiple-Output (MIMO) systems under imperfect channel state information (CSI) and feedback delay. The rate is adapted according to a target outage probability. We derive lower and upper bounds to this rate. We also asymptotically characterize the multi-step prediction error when MMSE prediction is used to combat feedback delay. Using the bounds and the prediction error asymptotics, we show that the rate gap from the ideal CSI scenario asymptotically grows logarithmically with SNR. The slope is at most the target outage probability. We find that when the target outage probability is decreased faster than an identified growth rate and prediction error goes to zero, then the rate gap remains bounded.

The paper considers two different antenna selection schemes for space-time coded systems over flat fading channels. First we explore antenna selection at the transmitter side based on the received signal to noise ratios. We then study the joint selection of receive and transmit antennas. Both schemes assume a slowly fading channel (i.e., quasi-static fading) and require some limited feedback from the receiver to the transmitter. By computing upper bounds on the pairwise error probabilities and conducting extensive simulations, we show that the space-time coded systems achieve full diversity even with antenna selection provided that the code is full rank. These results are extensions of earlier work on antenna selection for MIMO systems (Bahceci et al., 2003) which only considers receive antenna selection.

In multiple-input multiple-output (MIMO) systems, transmit antenna selection is a very promising technique for reducing implementation cost and computational complexity. In this paper, we propose two novel fast near-optimal antenna selection algorithms based on channel capacity maximization, whose core idea is to use an effective iterative process to reduce computational complexity and retain near-optimal performance. Compared with the conventional algorithm, the proposed algorithms have lower computational complexity and achieve almost the same capacity and bit-error rate (BER) performance as the optimal one. In particular, the BER performance gain of the proposed algorithms is much larger than the conventional algorithms in correlated fading channels. Finally, computer simulations are presented to validate and demonstrate performance of our algorithms.

In this letter, we propose two different joint transmit and receive antenna subset selection schemes for multiple-input multiple-output (MIMO) systems on the basis of capacity maximization criterion. We assume that perfect channel state information (CSI) is known at the receiver but unknown to the transmitter. As the selection signaling is perfectly fed back to the transmitter, we propose a flexible two-step selection algorithm (TSSA) in practical MIMO channel scenarios. Computer simulations show that TSSA can maximize the capacity at low computation cost in most scenarios. It performs well in terms of capacity, computational complexity and flexibility. Furthermore, we propose a simplified algorithm based on the correlation matrix when the channel correlation information (CCI) is known to the transmitter. Simulation results show that the proposed correlation matrix based selection algorithm is only slightly inferior to an optimal selection algorithm.