Receive Antenna Selection Research Articles

Training for Antenna Selection in Time-Varying Channels: Optimal Selection, Energy Allocation, and Energy Efficiency Evaluation

Single receive antenna selection (AS) is a popular method for obtaining diversity benefits without the additional costs of multiple radio receiver chains. Since only one antenna receives at any time, the transmitter sends a pilot multiple times to enable the receiver to estimate the channel gains of its N antennas to the transmitter and select an antenna. In time-varying channels, the channel estimates of different antennas are outdated to different extents. We analyze the symbol error probability (SEP) in time-varying channels of the N-pilot and (N + 1)-pilot AS training schemes. In the former, the transmitter sends one pilot for each receive antenna. In the latter, the transmitter sends one additional pilot that helps sample the channel fading process of the selected antenna twice. We present several new results about the SEP, optimal energy allocation across pilots and data, and optimal selection rule in time-varying channels for the two schemes. We show that due to the unique nature of AS, the (N +1)-pilot scheme, despite its longer training duration, is much more energy-efficient than the conventional N-pilot scheme. An extension to a practical scenario where all data symbols of a packet are received by the same antenna is also investigated.

协同多点传输中迫零预编码和天线选择技术

Communication system capacity is greatly improved by multiple input multiple output (MIMO) wireless transmission technology. In a commercial cellular system, the entire network is essentially an interferencelimited system. While the problem of other-cell interference (OCI) is inherent in cellular systems, its affect on MIMO transmission is more significant, because each neighboring base station (BS) antenna element can act as a unique interfering source. Because of the fast improvement in processing capability at BSs and the increase in the backhaul capacity, coordinated multi-cell MIMO communications with cooperative processing among BSs have attracted a significant amount of interest in recent years. Most of the current work is focused on the study of system capacity, but the equivalent SNR of each user (i.e., fairness) has an important influence on system performance, such as the frame error rate. Considering the single antenna configuration for the user, the system capacity and fairness based on a zero-forcing precoding design are studied in the case of the total power and per antenna power constraints. The fairness is analyzed for the two types of power constraints, and a closed solution is given. Considering the multiple antenna configuration for the user, the receive antenna selection algorithm, which maximizes the channel norm, is used to reduce the computational complexity. Thus the case for the user with a multiple antenna configuration is transformed into the case for the user with a single antenna configuration, The fairness algorithm for the user with a single antenna is still applicable. The simulation results show that multi-cell collaboration with zero-forced precoding can significantly improve system performance. In the same zero-forced precoding, different power allocation strategies have a significant affect on system capacity and fairness. Compared with the user with a single antenna, the antenna selection algorithm can enhance system capacity and fairness. The tradeoff between user fairness throughput and maximum system throughput is considered, and simulation results are also given.

A concise joint transmit/receive antenna selection algorithm

For reducing the computational complexity of the problem of joint transmit and receive antenna selection in Multiple-Input-Multiple-Output (MIMO) systems, we present a concise joint transmit/receive antenna selection algorithm. Using a novel partition of the channel matrix, we drive a concise formula. This formula enables us to augment the channel matrix in such a way that the computational complexity of the greedy Joint Transmit/Receive Antenna Selection (JTRAS) algorithm is reduced by a factor of 4nL, where nL is the number of selected antennas. A decoupled version of the proposed algorithm is also proposed to further improve the efficiency of the JTRAS algorithm, with some capacity degradation as a tradeoff. The computational complexity and the performance of the proposed approaches are evaluated mathematically and verified by computer simulations. The results have shown that the proposed joint antenna selection algorithm maintains the capacity performance of the JTRAS algorithm while its computational complexity is only 1/4nL of that of the JTRAS algorithm. The decoupled version of the proposed algorithm further reduces the computational complexity of the joint antenna selection and has better performance than other decoupling-based algorithms when the selected antenna subset is small as compared to the total number of antennas.

A Fast Adaptive Receive Antenna Selection Method in MIMO System

Antenna selection has been regarded as an effective method to acquire the diversity benefits of multiple antennas while potentially reduce hardware costs. This paper focuses on receive antenna selection. According to the proportion between the numbers of total receive antennas and selected antennas and the influence of each antenna on system capacity, we propose a fast adaptive antenna selection algorithm for wireless multiple-input multiple-output (MIMO) systems. Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory requirement and achieves considerable system capacity gain compared with the optimal selection technique in the same time.

Energy Efficiency Maximization through Cooperative Transmit and Receive Antenna Selection for Multicell MU-MIMO System

The capacity of Multiple Input Multiple Output (MIMO) system is highly related to the number of active antennas. But as the active antenna number increases, the MIMO system will consume more energy. To maximize the energy efficiency of MIMO system, we propose an antenna selection scheme which can maximize the energy efficiency of BS cluster. In the scheme, ergodic energy efficiency is derived according to large scale channel state information (CSI). Based on this ergodic energy efficiency, we introduce a cost function varied with the number of antennas, in which the effect to the energy efficiency of both the serving BS and the neighbor BS is considered. With this function, we can transform the whole system optimization problem to a sectional optimization problem and obtain a suboptimal antenna set using a heuristic algorithm. Simulation results verify that the proposed approach performs better than the comparison schemes in terms of network energy efficiency and achieves 98% network energy efficiency of the centralized antenna selection scheme. Besides, since the proposed scheme does not need the complete CSI of the neighbor BS, it can effectively reduce the signaling overhead.

Joint Antenna Selection and MIMO Symbol De-tection Using Multiobjective Optimization

This study uses the joint receive antenna selection and symbol detection (JRAS/SD) technique to simultaneous- ly improve the bit error rate and channel capacity while reducing the cost of the radio-frequency chains in multiple- input multiple-output (MIMO) systems. Optimal antenna selection methods in the literatureare based on the criteria of maximal capacity or minimal bit error rate. Either of these criteria requires an exhaustive search over all subma- trices in the full channel response matrix, resulting in high complexity. This study proposes a new multiobjective JRAS/SD using the cross-entropy optimizationto reduce the bit error rate while approaching the maximal channel ca- pacity in MIMO systems. Simulation results show that the proposed approach achievesimproved performance in both channel achievable rate and bit error rate performance compared with previous works. 

Fast Receive Antenna Selection for Spatial Multiplexing MIMO over Correlated Rayleigh Fading Channels

It is well known that the capacity of spatial multiplexing multiple-input multiple-output (SM-MIMO) system employing optimal antenna selection can significantly outperform a system without selection for same number of costly radio frequency chains. However, it requires an exhaustive search for the optimal selection (OS) that grows exponentially with the available number of transmit (u) and receive (m) antennas. In this paper, a novel low complexity receive antenna selection (RAS) technique is proposed for SM-MIMO to maximize the channel capacity over correlated Rayleigh fading environment. It is based on the Euclidean norms of channel matrix rows and the corresponding phase differences due to their direct impact on the capacity. Extensive analysis and simulations have shown near optimal performance for any signal-to-noise-ratio and correlation values with low complexity of $${\mathcal{O} \left({u^{2}m}\right)}$$ vector calculations. This technique provides fast RAS to capture most of the capacity gain promised by multiple antenna systems over different channel conditions. Furthermore, it enables efficient spectrum utilization for next generation wireless communications.

Receive Antenna Selection for Time-Varying Channels Using Discrete Prolate Spheroidal Sequences

Receive antenna selection (AS) has been shown to maintain the diversity benefits of multiple antennas while potentially reducing hardware costs. However, the promised diversity gains of receive AS depend on the assumptions of perfect channel knowledge at the receiver and slowly time-varying fading. By explicitly accounting for practical constraints imposed by the next-generation wireless standards such as training, packetization and antenna switching time, we propose a single receive AS method for time-varying fading channels. The method exploits the low training overhead and accuracy possible from the use of discrete prolate spheroidal (DPS) sequences based reduced rank subspace projection techniques. It only requires knowledge of the Doppler bandwidth, and does not require detailed correlation knowledge. Closed-form expressions for the channel prediction and estimation error as well as symbol error probability (SEP) of M-ary phase-shift keying (MPSK) for symbol-by-symbol receive AS are also derived. It is shown that the proposed AS scheme, after accounting for the practical limitations mentioned above, outperforms the ideal conventional single-input single-output (SISO) system with perfect CSI and no AS at the receiver and AS with conventional estimation based on complex exponential basis functions.

Receive antenna selection in diversely polarized MIMO transmissions with convex optimization

In this paper, we present a low complexity approach to receive antenna selection for capacity maximization, based on the theory of convex optimization. By relaxing the antenna selection variables from discrete to continuous, we arrive at a convex optimization problem. We show via extensive Monte-Carlo simulations that the proposed algorithm provides performance very close to that of the optimal selection based on an exhaustive search. We consecutively optimize not only the selection of the best antennas but also the angular orientation of individual antenna elements in the array for a so-called true polarization diversity system. Dual- and triple-polarized antenna structures are a very good solution for realizing compact devices and also robust against many imperfections as compared to spatially separated antenna structures. Effectively we extend our work from two dimensional antenna structures to three dimensions. We model such polarized antenna systems and then apply convex optimization theory for selecting the best possible antennas in terms of capacity maximization. Channel parameters like transmit and receive correlations, and cross-polarization discrimination (XPD) are taken into consideration while modeling polarized systems. We compare our results with the Spatially Separated (SP) MIMO with and without selection by performing extensive Monte Carlo simulations. We found that by using a convex optimization algorithm, the performance of multiple polarized systems can be significantly enhanced. For certain channel conditions we observe that triple polarized systems increase the performance significantly compared to dual-polarized and spatially separated systems. We observed that applying selection at the receiver only boosts the performance in Non-Line of Sight (NLOS) channels compared to Line of Sight (LOS) channels.

Performance Analysis of Maximal-Ratio Transmission/Receive Antenna Selection in Nakagami- $m$ Fading Channels With Channel Estimation Errors and Feedback Delay

This paper focuses on multi-antenna systems that employ both maximal-ratio transmission and receive antenna selection (MRT&RAS) in independent and identically distributed Nakagami-m flat-fading channels with channel estimation errors (CEE) [or feedback quantization errors (FQE)] and feedback delay (FD). Useful statistics of the postprocessing signal-to-noise ratio (SNR) such as the probability density function, cumulative distribution function, moment-generating function, and th-order moments are presented. To examine the capacity and the error performances of the MRT&RAS scheme, ergodic capacity, outage probability, and bit error rates/symbol error rates (BERs/SERs) for binary and M-ary modulations are analyzed. Exact analytical expressions for all the performance metrics are separately derived for practical situations that consist of CEE (or FQE) and FD, as well as ideal estimation and feedback conditions. By considering approximations for the statistics of the postprocessing SNR, it is shown that, at high SNRs, the investigated system achieves full-diversity orders in the ideal case, whereas it keeps maintaining receive diversity at practical impairments. The performance superiority of the MRT&RAS scheme to other diversity schemes is also shown by numerical comparisons. In addition, analytical performance results related to the outage probability and BERs/SERs are validated by Monte Carlo simulations.

Diversity order analysis of orthogonal space–time block coding over keyhole fading channels with antenna selection

SUMMARYAlthough there are many research results for the keyhole fading channels in the current literature, fewer results have investigated the antenna selection scheme and quantified the diversity order. In this letter, we first derive some simple statistics of the output signal‐to‐noise ratio for the orthogonal space–time block coding over keyhole fading channels. On the basis of these results, we derive an approximate BER expression for the keyhole MIMO channels with receive antenna selection scheme. Results show that the diversity order with receive antenna selection is min{nR,nT}for nR ≠ nT, which means that the full diversity order with antenna selection is maintained. Finally, numerical results demonstrate the accuracy of our analytical expressions and the tightness of approximate formulas. Copyright © 2012 John Wiley & Sons, Ltd.

Performance of joint transmit and receive antenna selection in dual hop amplify‐and‐forward relay network over Nakagami‐m fading channels

ABSTRACTIn this paper, performance of joint transmit and receive antenna selection in each hop of dual hop amplify‐and‐forward relay network is analyzed over flat and asymmetric Nakagami‐m fading channels. In the network, source, relay, and destination are equipped with multiple antennas. By considering relay location, we derive exact closed‐form cumulative distribution function, moment generating function, moments of end‐to‐end signal‐to‐noise ratio and closed form symbol error probability expressions for fixed and channel state information‐based relay gains. We also derive the asymptotical outage probability and symbol error probability expressions to obtain diversity order and array gain of the network. Analytical results are validated by the Monte Carlo simulations. Copyright © 2012 John Wiley & Sons, Ltd.

Optimal Antenna Selection Designs for Coupled MIMO Systems

We consider the impact of antenna mutual coupling on receive antenna selection systems. Prior work on selection with mutual coupling has not considered the effects of the inactive (i.e., unselected) antenna terminations and spatial noise correlation. In this work, we show that the presence of inactive antennas can profoundly alter system performance when the antennas are strongly coupled. We also propose a new antenna selection technique that seeks to exploit coupling to improve performance. Simulations suggest that the new technique can significantly outperform traditional selection when coupling is present.

Particle Swarm Optimization for Antenna Selection in MIMO System

This paper investigates the receive antenna selection problem to maximize capacity in wireless MIMO communication system, which can be formulated as an integer programming optimization problem and ...

On the Diagonal Distribution of a Complex Wishart Matrix and its Application to the Analysis of MIMO Systems

The statistical properties of Wishart matrices have been extensively used to analyze the performance of multiple-input multiple-output (MIMO) systems. In particular, the signal-to-noise ratio (SNR) output statistics of several MIMO systems depends on the diagonal distribution of a complex Wishart matrix. In this paper, we derive the joint density of the diagonal elements of a complex Wishart matrix, which follows a multivariate chi-square distribution. The density expression is in the form of an infinite series representation which converges rapidly and is easy to compute. This expression is used to obtain the distribution of the maximum of the diagonal elements, which allows analyzing the performance of two different MIMO systems under practical conditions. First, our statistical results are applied to the outage probability characterization of MIMO systems with receive antenna selection in spatially correlated Rayleigh fading. Then, the same results are used to analyze the outage probability of transmit beamforming systems under limited-rate feedback.

Joint user and antenna selection for multiuser MIMO downlink with block diagonalization

User selection is necessary for multiuser multiple-input multiple-output (MIMO) downlink systems with block diagonalization (BD) due to the limited free spatial transmit dimensions. The pure user selection algorithms can be improved by performing receive antenna selection (RAS) to increase sum rate. In this paper, a joint user and antenna selection algorithm, which performs user selection for sum rate maximization in the first stage and then performs antenna selection in the second stage, is proposed. The antenna selection process alternately drops one antenna with the poorest channel quality based on maximum determinant ranking (MDR) from the users selected during the first stage and activates one antenna with the maximum norm of projected channel from the remaining users. Simulation results show that the proposed algorithm significantly outperforms the algorithm only performing user selection as well as the algorithm combining user selection with MDR receive antenna selection in terms of sum rate.

MIMO Cognitive Radios with Antenna Selection

In this paper, we propose two solutions to the problem of joint transmit-receive antenna selection in a multiple-input multiple-output (MIMO) cognitive radio (CR) system. Our objective is to maximize CR data rates and satisfy interference constraints at the primary user (PU) receiver(s). In the first we approximate the original non-convex optimization problem using an iterative approach solving a series of smaller convex problems. Second we present a novel, norm-based transmit receive antenna selection technique that simultaneously improves throughput while maintaining the PU interference constraints. We show that this approach yields near optimal results with massive complexity reductions. We make a performance comparison between the proposed approaches and the optimal exhaustive search approach. We provide an analysis of the exhaustive search and relate selection gains to system parameters such as the shadow fading standard deviation, the path loss exponent and the number of PUs per square kilometer. Our results establish that antenna selection is a promising option for future MIMO CR devices in sparse PU environments.

Performance analysis of joint single transmit and receive antenna selection in non-identical Nakagami- m fading channels

In this study, joint single transmit and receive antenna selection systems are examined for independent but non-identically distributed flat Nakagami-m fading channels. Exact bit/symbol error rate expressions are derived for binary and M-ary signals by using the conventional probability density function-based analysis method and the moment generating function based analysis method for arbitrary and integer values of the fading parameters, respectively. Upper bounds are obtained in order to show that the investigated systems achieve full diversity order at high SNRs. Also, outage probability analysis has been carried out for examining system capacity. Theoretical results are validated by Monte Carlo simulations.

Per-layer transmit and receive filters design for Tomlinson-Harashima precoding in multiuser MIMO systems

In this paper, the per-layer design for Tomlinson-Harashima precoding (THP) in the downlink of multiuser multiple-input multiple-output (MIMO) systems is investigated. In these systems, the number of the receivers is equal to that of the transmit antennas. Based on the criterion of maximum system sum-capacity, we study two per-layer joint transmit and receive filters design schemes with receive antenna beamforming (RAB) and receive antenna selection (RAS), respectively. Moreover, the differences of the equivalent channel gains and capacities between these two schemes are analyzed theoretically. Simulation results show that by these per-layer schemes, the system sum-rate is improved significantly with respect to the per-user processing scheme.

Novel Representations for the Equicorrelated Multivariate Non-Central Chi-Square Distribution and Applications to MIMO Systems in Correlated Rician Fading

Novel representations for the multivariate probability density function and cumulative distribution function of the non-central chi-square distribution are derived. The solutions are expressed in terms of well known functions which are available in common mathematical software. When the number of degrees of freedom, m, is even, the new representation has the advantage that only a single-integral computation is needed to compute a N-dimensional distribution. The new representations are used to numerically evaluate the outage probability of multiple input multiple output systems with receiver antenna selection, operating in correlated Rician fading. The well known equal correlation model, which is considered to be a useful model for a closely placed set of antennas, is used for the analysis.