In this letter, we propose an efficient relay antenna selection algorithm for the amplify and forward (AF) two-way multiple-input multiple-output (MIMO) relay systems with analogue network coding (ANC). The proposed algorithm greedily selects the additional receive-transmit antenna pair that provides the maximum sum-rate. An iterative computation method is also designed to evaluate the sum-rate efficiently.

In this letter, we propose an antenna selection single frequency network precoding (AS-SFNP) scheme for downlink cooperative multiple-input multiple-output (MIMO) systems, which efficiently improves system capacity with low feedback overhead and low complexity.

This letter presents a criterion for selecting a transmit antenna subset when ZF detectors followed by Rake combiners are employed for spatial multiplexing (SM) ultra-wideband (UWB) multiple input multiple output (MIMO) systems. The presented criterion is based on the largest minimum post-processing signal to interference plus noise ratio of the multiplexed streams, which is obtained on the basis of QR decomposition. Simulation results show that the proposed antenna selection algorithm considerably improves the BER performance of the SM UWB MIMO systems when the number of multipath diversity branches is not so large and thus offers diversity advantages on a log-normal multipath fading channel.

This letter introduces a closed form expression for the channel capacity increase achieved by adding a new pair of transmit and receive antennas. By analyzing this expression, an iterative transmit/receive antenna selection algorithm of low computational complexity is proposed. The new algorithm has higher computational complexity than some existing algorithms, but as the results show, the performance improvement of the proposed algorithm approaching more to the optimal algorithm.

This letter presents structurally simpler symbol error rate (SER) expressions for Transmit Antenna Selection/Maximal-Ratio Combining (TAS/MRC) scheme in independent Nakagami-m fading channels in a comparison with those in the literature. First, the SER is derived as a single infinite series of simple functions for arbitrary m. For integer m, the SER can be attained as a closed-form expression with a double finite series. Moreover, simple asymptotic SER expressions suggest that the TAS/MRC scheme can achieve a full diversity order at high SNR. Numerical and simulation results verify the conciseness of the derived expressions.

In the conventional multi-input multi-output (MIMO) communication systems, most of the antenna selection methods considered are suitable only for spatially separated uni-polarized system under Rayleigh fading channel in non-line of sight (NLOS) condition. There have a few antenna selection schemes for the cross-polarized system in LOS condition and Ricean fading channel, and no antenna selection scheme for the MIMO channel with both LOS and NLOS. In the practical MIMO channel case, influence of LOS and NLOS conditions in the channel can vary from time to time according to the channel parameters and user movement in the system. Based on these influences and channel condition, uni-polarized system may outperform a cross-polarized. Thus, we should consider this kind of practical MIMO channel environment when developing the antenna selection scheme. Moreover, no research work has been done on reducing the complexity of antenna selection for this kind of practical MIMO channel environment. In this paper, reduced complexity in antenna selection is proposed to give the higher throughput in the practical MIMO channel environment. In the proposed scheme, suitable polarized antennas are selected based on the calculation of singular value decomposition (SVD) of channel matrix and then adaptive bit loading is applied. Simulation results show that throughput of the system can be improved under the constraint of target BER and total transmit power of the MIMO system.

In this letter, we propose a novel antenna selection algorithm for amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay systems with Zero-Forcing (ZF) processing applied both at the source node and at the destination node. We obtain the optimum antenna selection criterion by deriving an iterative closed-form expression for capacity maximization.

In this paper, we investigate the antenna and node selection issues for amplify-and-forward (AF) and decode-and-forward (DF) multi-antenna relay networks in correlated channels. Based on the channel statistics, optimal selection criteria for antenna and relay node are derived jointly, aiming to maximize the ergodic capacity. Instantaneous channel knowledge-based selection schemes, motivated by traditional antenna selection algorithms, are investigated as well. It is shown that the proposed node selection schemes derived from antenna selection on relay nodes are feasible and effective in relay systems. Statistical selection shows considerable capacity gain compared to full complexity scheme and random selection strategy in AF mode, while instantaneous selection performs better in DF relaying. Furthermore, the proposed schemes are shown to be robust to channel estimation errors due to their correlation-oriented nature.

This paper considers the use of an antenna selection mechanism to reduce the cost of multiple analog transmit/receive chains in multiple-input multiple-output (MIMO) systems. With the optimal antenna selection scheme, radio-frequency chains can optimally connect with the best subset of transmitter and/or receiver antennas. However, the optimal antenna selection algorithm requires an exhaustive search of all possible combinations to find the optimum subset at the transmitter and/or receiver, thus resulting in high complexity. In order to reduce the computational load while still maximizing channel capacity, we introduce the simulated annealing (SA) method, an effective algorithm that solves various combinatorial optimization problems, to search the optimal subset. The simulation results show that the performance of the proposed SA method provides almost the same channel capacity as that of the optimal exhaustive search algorithm while maintaining low complexity.

Antenna selection is a practical way to decrease system complexity and the hardware cost of radio frequency (RF) chains in multiple input multiple output (MIMO) system. In this study, we give a simple characterization of the optimal diversity and multiplexing tradeoff (DMT) curve of the MIMO system with antenna subset selection at both the transmitter and the receiver for Rayleigh fading channel.

In MIMO systems, the deployment of a multiple antenna technique can enhance the system performance. However, since the cost of RF transmitters is much higher than that of antennas, there is growing interest in techniques that use a larger number of antennas than the number of RF transmitters. These methods rely on selecting the optimal transmitter antennas and connecting them to the respective. In this case, feedback information (FBI) is required to select the optimal transmitter antenna elements. Since FBI is control overhead, the rate of the feedback is limited. This motivates the study of limited feedback techniques where only partial or quantized information from the receiver is conveyed back to the transmitter. However, in MIMO/OFDM systems, it is difficult to develop an effective FBI quantization method for choosing the space-time, space-frequency, or space-time-frequency processing due to the numerous subchannels. Moreover, MIMO/OFDM systems require antenna separation of 5 10 wavelengths to keep the correlation coefficient below 0.7 to achieve a diversity gain. In this case, the base station requires a large space to set up multiple antennas. To reduce these problems, in this paper, we propose the link correlation based transmit sector antenna selection for Alamouti coded OFDM without FBI.

We address the issue of MIMO channel estimation with the aid of a priori temporal correlation statistics of the channel as well as the spatial correlation. The temporal correlations are incorporated to the estimation scheme by assuming the Gauss-Markov channel model. Under the MMSE criteria, the Kalman filter performs an iterative optimal estimation. To take advantage of the enhanced estimation capability, we focus on the problem of channel estimation from a partial channel measurement in the MIMO antenna selection system. We discuss the optimal training sequence design, and also the optimal antenna subset selection for channel measurement based on the statistics. In a highly correlated channel, the estimation works even when the measurements from some antenna elements are omitted at each fading block.

This letter analyzes the outage probability of limited feedback beamforming systems with receive antenna selection. Tight analytical closed-form expressions of outage performance are derived for both cases, with and without spatial fading correlation, which allow for evaluation of the performance as a function of the codebook size, the level of fading correlation, and the number of transmit and receive antennas. Simulation results are also provided to verify the analysis.

We propose an antenna grouping method that improves the error rate performance of space-time codes in a wide range of mobility environments. The idea is to group symbols to antennas based on limited feedback from the mobile station to utilize all antennas. Our approach requires only two bits of feedback information to achieve better link performance and full rate for a certain four transmit antenna system. Numerical results confirm the bit/frame error gains over the Alamouti-based space-time block code and antenna subset selection strategies.

Combining relaying and multi-input multi-output (MIMO) transmission is a generic way to overcome the channel-fading impairments. Best antenna selection is a simple but efficient MIMO method that achieves the full diversity and also serves as a lower bound reference of MIMO performance. For a dual-hop MIMO system with an ideal amplify-and-forward (AF) relaying gain and best antenna selection, we provide a probability density function (PDF) of received signal-to-noise ratio (SNR) and an analytic BER equation when using M-ary PSK in Rayleigh fading channels. The analytic result is shown to exactly match with simulated one. Furthermore, the effect of link unbalance between the first hop and the second hop, due to differences in the number of antennas deployed in both hops as well as in the average power of channel coefficients, on the BER performance is numerically investigated and the results show that the links with better balance give better performance.

In this letter, we develop a two-step receive antenna selection method to maximize channel capacity. Different from previous work, we first derive a lower bound on capacity based on Hadamard inequality and arithmetic-geometric mean inequality, which is then used to iteratively drop the worst-performing antennas according to their measure. The recursive nature of this method helps to largely reduce the computational complexity.

Multi-user MIMO (Multiple Input Multiple Output) systems, in which multiple Mobile Stations (MSs) equipped with multiple antennas simultaneously communicate with a Base Station (BS) equipped with multiple antennas, at the same frequency, are attracting attention because of their potential for improved transmission performance in wireless communications. In the uplink of Space Division Multiplexing based multi-user MIMO (multi-user MIMO/SDM) systems that do not require full Channel State Information (CSI) at the transmitters, selecting active MS antennas, which corresponds to scheduling transmit antennas, is an effective technique. The Full search Selection Algorithm based on exhaustive search (FSA) has been studied as an optimal active MS antenna selection algorithm for multi-user MIMO systems. Unfortunately, FSA suffers from extreme computational complexity given large numbers of MSs. To solve this problem, this paper introduces the Gram-Schmidt orthogonalization based Selection Algorithm (GSSA) to uplink multi-user MIMO/SDM systems. GSSA is a suboptimal active MS antenna selection algorithm that offers lower computational complexity than the optimal algorithm. This paper evaluates the transmission performance improvement of GSSA in uplink multi-user MIMO/SDM systems under realistic propagation conditions such as spatially correlated BS antennas and clarifies the effectiveness of GSSA.

This paper proposes an antenna selection method for terminal antennas employing orthogonal polarizations and patterns, which is suitable for outdoor MultiUser Multi-Input Multi-Output (MU-MIMO) systems. In addition, this paper introduces and verifies two other antenna selection methods for comparison. For the sake of simplicity, three orthogonal dipoles are considered, and this antenna configuration using the proposed selection method is compared to an antenna configuration with three vertical or horizontal dipoles. In the proposed antenna selection method, we always choose the vertical dipole, and choose one of two horizontal dipoles, which are orthogonal to each other, based on the Signal-to-Noise Ratio (SNR). We measured the MU-MIMO transmission properties and found that the proposed selection method employing the antenna with orthogonal polarizations and patterns can offer fairly high channel capacity in a multiuser scenario.

In this letter, a simple but effective antenna selection algorithm for orthogonal space-time block codes with a linear complex precoder (OSTBC-LCP) is proposed and compared with two conventional algorithms in temporally and spatially correlated fading channels. The proposed algorithm, which minimizes pairwise error probability (MinPEP) with an error codebook (EC) constructed from the error vector quantization, is shown to provide nearly the same performance of MinPEP based on all possible error vectors, while keeping the complexity close to that of antenna selection algorithm based on maximum power criterion (Maxpower).

Vector precoding is a nonlinear broadcast precoding scheme in the downlink of multi-user MIMO systems which outperforms linear precoding and THP (Tomlinson-Harashima Precoding). This letter discusses the problem of joint receive antenna selection in the multi-user MIMO downlink with vector precoding. Based on random matrix analysis, we derive a simple heuristic selection criterion using singular value decomposition (SVD) and carry out an exhaustive search to determine for each user which receive antenna should be used. Simulation results reveal that receive antenna selection using our proposed criterion obtains the same diversity order as the optimal selection criterion.