Optimal Antenna Selection Research Articles

Multiple Transmit Antenna Selection in MIMO-OSTBC System in Nakagami-m Fading Channel

Abstract Transmit Antenna Selection (TAS) is essential part of future wireless systems to reduce the complexity of multiple antenna techniques and to satisfy the need of higher data rates. In this paper, we present TAS technique based on Maximal Ratio Combining (MRC) scheme with multiple antenna selection. The sub optimal antenna selection is carried out for selecting more than one subset of antenna which minimizes the upper bound of pair wise error probability. The performance analysis of the system is carried out under Nakagami-m flat fading channel. The Bit Error Rate (BER) analysis is performed for multiple antenna selection in MIMO-OSTBC system for arbitrary values of ‘m’ in Nakagami-m fading channel.

Beacon Antenna Controller based on Synchronous Satellite

In order to improve the communication efficiency between beacon antennas of flight recorder and the synchronous satellite, a beacon antenna controller based on synchronous satellite has been designed. The optimal communication antenna selection is realized by calculating the angle between the aircraft and the synchronous satellite using Global Positioning System (GPS) position information and flight attitude. The simulation and experimental results show that reliable automatic switch of the antenna can be realized by the antenna controller which can accurately calculate the angle between the aircraft and the satellite after receiving the position and posture information.

Low-Complexity Transmit Antenna Selection and Beamforming for Large-Scale MIMO Communications

Transmit antenna selection plays an important role in large-scale multiple-input multiple-output (MIMO) communications, but optimal large-scale MIMO antenna selection is a technical challenge. Exhaustive search is often employed in antenna selection, but it cannot be efficiently implemented in large-scale MIMO communication systems due to its prohibitive high computation complexity. This paper proposes a low-complexity interactive multiple-parameter optimization method for joint transmit antenna selection and beamforming in large-scale MIMO communication systems. The objective is to jointly maximize the channel outrage capacity and signal-to-noise (SNR) performance and minimize the mean square error in transmit antenna selection and minimum variance distortionless response (MVDR) beamforming without exhaustive search. The effectiveness of all the proposed methods is verified by extensive simulation results. It is shown that the required antenna selection processing time of the proposed method does not increase along with the increase of selected antennas, but the computation complexity of conventional exhaustive search method will significantly increase when large-scale antennas are employed in the system. This is particularly useful in antenna selection for large-scale MIMO communication systems.

A Low Complexity Algorithm for Receiver Antenna Selection in MIMO Systems

For a multiple-input multiple-output (MIMO) system with more antennas at the receiver than the transmitter, selecting the same number of receiver antennas as the number of transmitter antennas can take most of the advantages of MIMO capacity performance and at the same time reduce the system hardware cost and computational complexity. In this paper, a novel effective low complexity near-optimal antenna selection algorithms based on maximization channel capacity is proposed for the MIMO array configuration. Different from many existing fast antenna selection algorithms which obtain the sub-optimal channel sub matrix by adding or removing one row per step exploit re-computing formula, our algorithm acquires the near-optimal channel matrix by a faster updating formula. In such faster updating formula, the formula is updating rather than re-c omputing, so that the matrix inverse operation is avoided. Due to using an effective iteration processing, our antenna selection algorithm reduces computational complexity and leads to a substantial improvement in the capacity optimally for moderating to high signal to noise ratio (SNRs), and obtains almost the same capacity and bit error ratio (BER) performance as that of the exhaustive-search-based optimal antenna selection algorithm. Compared to the conventional sub-optimal antenna selection algorithms, our algorithm has lower computational complexity and achieves almost the same capacity and BER performance as the optimal selection algorithm. Finally, theoretical analysis and simulation results illustrate that the new algorithm outperforms the existing sub-optimal antenna selection methods.

Comments on "Antenna Selection in Spatial Modulation Systems"

The first contribution of this letter is to correct an error in the formulation of the Low-Complexity Euclidean Distance optimized Antenna Selection scheme for Spatial Modulation (SM), (SM-EDAS-LC). Secondly, due to a simulation error the Monte Carlo simulation results presented in the above letter for SM-EDAS-LC are erroneous, thus we present the correct results for the scheme, which demonstrates that the error performance in fact outperforms that of Capacity Optimized Antenna Selection for SM. The third contribution is to propose two modifications to SM-EDAS-LC that significantly reduce the computational complexity.

Antenna Selection in Spatial Modulation Systems

Novel transmit antenna selection techniques are conceived for Spatial Modulation (SM) systems and their symbol error rate (SER) performance is investigated. Specifically, low-complexity Euclidean Distance optimized Antenna Selection (EDAS) and Capacity Optimized Antenna Selection (COAS) are studied. It is observed that the COAS scheme gives a better SER performance than the EDAS scheme. We show that the proposed antenna selection based SM systems are capable of attaining a significant gain in signal-to-noise ratio (SNR) compared to conventional SM systems, and also outperform the conventional MIMO systems employing antenna selection at both low and medium SNRs.

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.

Performance of MIMO cross‐layer MAC protocol based on antenna selection in ad hoc networks

AbstractIn this paper, we investigate the performance of a cross‐layer (physical and MAC) design for multiple‐input multiple‐output (MIMO) system that aims at maximizing the throughput of ad hoc networks by selecting the optimum antenna combination. Employing this cross‐layer design is shown to improve the overall network performance relative to the case where no antenna selection (AS) is used. To solve the node blocking problem associated with the IEEE 802.11 medium‐access control (MAC) protocol, the proposed protocol leverage the available degrees of freedom offered by the MIMO system to allow neighboring nodes to simultaneously communicate using the zero‐forcing (ZF) Bell‐labs layered space‐time (BLAST) architecture. Using the cross‐layer design, neighboring nodes share their optimum antenna selection (AS) information through control messages. Given this shared information, nodes set their decisions on the number of selected antennas based on the available spatial channels that guarantees collision‐free transmissions. At the destination node, the ZF receiver is employed to extract the desired user data while treating the data from neighboring users as interference. The performance of the proposed cross‐layer design is examined through simulations, where we show that the network throughput is significantly improved compared to conventional MAC protocols. Copyright © 2010 John Wiley & Sons, Ltd.

Transmit Antenna Selection OFDM Systems With Transceiver I/Q Imbalance

One of the serious imperfections affecting orthogonal frequency-division multiplexing (OFDM) systems is transceiver in-phase/quadrature-phase (I/Q) imbalance. In this paper, the effect of I/Q imbalances on the transmit antenna selection (TAS) OFDM system is studied. The optimum antenna selection in presence of transmit and receive I/Q imbalances are proposed. We derive closed-form expressions for ergodic capacity of the system with transmit and receive I/Q imbalances. Moreover, some tight and simple lower and upper bounds for the ergodic capacity of the TAS OFDM system are derived. The simplicity of the proposed formula gives insight into the performance and optimization of the system. Finally, the analytical results are confirmed by simulations.

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.

A New Joint Antenna Selection Algorithm Based on Capacity

Antenna Selection in MIMO systems can increase the system capacity, reduce the MIMO system complexity and cost of radio links effectively. In this paper, a new joint antenna selection algorithm was presented which can adaptively change the number of the selected transmitting and receiving antenna number according to the channel station. It can obtain the similar system capacity with the optimal joint antenna selection algorithm in any correlation coefficient, but the calculated amount is far less than the optimal joint algorithm.

Amplify-and-Forward Relaying with Optimal and Suboptimal Transmit Antenna Selection

Antenna selection schemes offer a good complexity versus performance tradeoff for amplify-and-forward (AF) relay network implementation. In this paper, we consider a dual-hop channel state information assisted AF relay network with a direct source-destination link and investigate the performance of two antenna selection schemes (one optimal and another suboptimal). We derive analytical expressions for the systems' rate outage probabilities and the average bit error rate (BER) that match perfectly with simulation based results in the medium to high signal-to-noise ratio (SNR) regimes. We also investigate the channel capacity of the two schemes by deriving tight upper bounds. In order to gain further insights, simple high SNR approximations for the outage probability and the average BER have also been developed. Our theoretical analysis shows that the performance gap between the optimal and suboptimal schemes largely diminishes in the high SNR regime by increasing the number of antennas at the source. Since the suboptimal scheme has a near optimal performance as well as low signaling overhead compared to the optimal scheme, it seems to be a promising solution for implementing future cellular networks expecting to support relay based communications.

On the Diversity Enhancement and Power Balancing of Per-Subcarrier Transmit Antenna Selection in OFDM Systems

In this paper, we consider multicarrier systems with multiple transmit antennas under a power-balancing constraint. Applying transmit antenna selection and discrete rate-adaptive modulation using <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> -ary quadrature-amplitude modulation (QAM) according to the channel variation per subcarrier, we develop an optimal transmit antenna selection scheme in terms of the maximum spectral efficiency, where all the possible groupings for sending the same information-bearing signals in a group of subcarriers are searched, and the groups of subcarriers for providing the frequency diversity gain are formed. In addition, we propose a suboptimal method for reducing the computational complexity of the optimal method. The suboptimal scheme considers only the subcarriers under outage, and these subcarriers are sequentially combined until the required signal-to-noise ratio (SNR) is met. Numerical results show that the proposed suboptimal method with diversity combining outperforms the optimal antenna selection without diversity combining, as introduced in the work of Sandell and Coon, particularly for low-SNR regions, and offers the spectral efficiency close to the optimal method with diversity combining while maintaining lower complexity.

Low Complexity Transmit Antenna Selection with Power Balancing in OFDM Systems

In this paper, we consider multi-carrier systems with multiple transmit antennas under the power balancing constraint, which is defined as the constraint that the power on each antenna should be limited under a certain level due to the linearity of the power amplifier of the RF chain. Applying transmit antenna selection and fixed-power variable-rate transmission per subcarrier as a function of channel variations, we propose an implementation-friendly antenna selection method which offers a reduced complexity in comparison with the optimal antenna selection scheme. More specifically, in order to solve the subcarrier imbalance across the antennas, we operate a two-step reallocation procedure to minimize the loss of spectral efficiency. We also provide an analytic lower bound on the spectral efficiency for the proposed scheme. From selected numerical results, we show that our suboptimal scheme offers almost the same spectral efficiency as the optimal one.

Global and Fast Receiver Antenna Selection for MIMO Systems

For a multiple-input multiple-output (MIMO) system with more antennas at the receiver than the transmitter, selecting the same number of receiver antennas as the number of transmit antennas captures most of the advantages of MIMO capacity performance and reduces the system hardware and computational cost at the same time. In this paper, a fast and global-search receive antenna selection algorithm is proposed for this MIMO array configuration. Different from many existing fast but `local' antenna selection algorithms which obtain the sub-optimal channel submatrix by adding or removing one row per step, our algorithm acquires the near-optimal channel matrix by {directly} and {rapidly} the maximum-volume submatrix of the original channel matrix. Due to its globally searching property, our antenna selection algorithm leads to a substantial improvement in the capacity optimality for moderate to high SNRs, and obtains almost the same capacity performance as that of the exhaustive-search-based optimal antenna selection algorithm. Furthermore, the computational load and memory requirement for our antenna selection method are still comparable to those of the existing sub-optimal antenna selection methods. Numerical results are provided to verify the validity of the proposed methods.

Global and Fast Receiver Antenna Selection for MIMO Systems

For a multiple-input multiple-output (MIMO) system with more antennas at the receiver than the transmitter, selecting the same number of receiver antennas as the number of transmit antennas captures most of the advantages of MIMO capacity performance and reduces the system hardware and computational cost at the same time. In this paper, a fast and global-search receive antenna selection algorithm is proposed for this MIMO array configuration. Different from many existing fast but `local' antenna selection algorithms which obtain the sub-optimal channel submatrix by adding or removing one row per step, our algorithm acquires the near-optimal channel matrix by {directly} and {rapidly} searching the maximum-volume submatrix of the original channel matrix. Due to its "globally searching" property, our antenna selection algorithm leads to a substantial improvement in the capacity optimality for moderate to high SNRs, and obtains almost the same capacity performance as that of the exhaustive-search-based optimal antenna selection algorithm. Furthermore, the computational load and memory requirement for our antenna selection method are still comparable to those of the existing sub-optimal antenna selection methods. Numerical results are provided to verify the validity of the proposed methods.

Transmit Antenna Selection in the Alamouti-Coded MIMO Relay Systems

In the Alamouti-coded multiple-input multiple-output relay systems, we consider selecting two transmit antennas from all available antennas, at the source and relay respectively, to maximize received signal-to-noise ratio (SNR) at the destination. Since the optimal antenna selection rule is intractable, we propose three suboptimal antenna selection rules (rule one, two and three). While these rules all select two best antennas at the relay to maximize the SNR of relay-destination link. They have different selection criteria at the source. Rule one maximizes the SNR of source-relay link but ignores source---destination link. Oppositely, rule two maximizes the SNR of source---destination link but ignores source-relay link. Rule three considers both links together. We derive the closed-form outage probability expressions of rule one and two, and find an upper bound for the outage probability of rule three. The analysis results show that rule one and two cannot achieve full diversity order, and rule three can. Simulation results verify the analysis results.

Receive antenna selection for closely-spaced antennas with mutual coupling

We investigate the achievable rate of receive antenna selection MIMO systems in the presence of mutual coupling and spatial correlation. For that, we assume the antenna array to consist of dipole antennas placed side-by-side in a linear pattern and in a very limited physical space. In a first step, we will assume perfect channel state information at the receiver side only and a negligible training overhead compared with the payload. We will demonstrate that in contrast to what might be expected based on results for cases without mutual coupling, MIMO receive antenna selection can achieve higher data rates than the system using all antennas provided that the total number of receive antennas is larger than a critical value that we will further discuss. We then propose an optimal antenna selection processing that ensures rate maximization regardless of the number of antennas used. In a later step, we will address the impact of training overhead on the system achievable rate when the training overhead is considerable. We will show that such a rate is reduced dramatically due to the large amount of training overhead arising from the presence of mutual coupling. To overcome this problem, we will thus propose a novel channel estimation method, which reduces the training overhead greatly and improves the system achievable rate performance.

A Low-Complexity Antenna Selection Scheme in MIMO Systems

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.