Performance Of Antenna Selection Research Articles

Analysis the efficiency of multi-input-multi-output (MIMO) transmit receive systems

Transmit antennas are chosen in multi-input-multi-output (MIMO) systems. Effective in improving system capacity while lowering RF connection costs and simplifying the system. Complete method with greatest accuracy for joint transmits and receive antenna selection (JTRAS), capable of scanning all subsets of both transmitting and receiving antennas for the optimal solution. However, when as the number of antennas but also computational complexity increase grows too great, limiting its application. Antennas are coded fractionally channel capacity maximizing coding is used as a basic criterion in this paper, and an intelligent algorithm Particle swarm algorithm, generic algorithm are used to pick antennas. The simulation results show that both algorithms are capable of performing antenna selection.

Receive Antenna Selection Under Discrete Inputs: Approximation and Applications

To analyze the achievable performance of antenna selection (AS) in practical multi-antenna systems, this paper studies the receive antenna selection (RAS) in single-input multiple-output (AS-SIMO) systems under discrete inputs. We first propose an approximate expression to evaluate the instantaneous mutual information (MI) of $M$ -ary quadrature amplitude modulation ( $M$ -QAM) signaling over additive white Gaussian noise (AWGN) channels. Then, by exploiting this approximate formula, we develop a closed-form formula for the ergodic MI in AS-SIMO systems with $M$ -QAM signaling. Additionally, we also analyze the asymptotic MI for a large number of receive antennas $N_{\mathrm{r}}$ . This asymptotic analysis suggests that the scaling rate of the MI with $N_{\mathrm{r}}$ becomes zero rate in contrast to the double logarithmic rate under Gaussian inputs. Besides, our result is also extended to discuss the mutual information of multiple-input multiple-output (MIMO) systems having discrete inputs with receive antenna selection, and an upper bound for the MI is derived. Finally, the derived result is applied to analyze several performance measures of the discrete inputs driven AS-SIMO systems. Specifically, it is first used to discuss the relationship between the ergodic MI and the number of active antennas. Our investigation shows that this relationship follows Pareto principle, i.e., 80% of the MI of full-antenna selection can be achieved via 20% of the total antennas. Then, our proposed approximation is employed to analytically study the effective MI which takes channel estimation (CE) into consideration, indicating that CE is a main limit of large-scale systems. Moreover, the energy efficiency (EE) is explored on the basis of our results, and we find there exists an optimal number of active antennas to maximize the energy efficiency. In addition to theoretical derivations, all the analytical results are validated by numerical simulations.

Performance analysis for high-speed railway distributed antenna systems with imperfect channel state information

This paper studies the performance of antenna selection for high-speed railway (HSR) distributed antenna systems with imperfect channel state information (CSI). In HSR systems, distributed antennas mounted on top of the train carriage are connected to a mobile relay, which serves as an intermediate node between the base station (BS) and the users inside the train. An important feature of high mobility networks is the fast time-variation of the fading channel caused by the large Doppler spread. It is difficult to accurately estimate, track, and predict the fast time-varying fading coefficients; thus, channel estimation error is usually inevitable and it may seriously degrade system performance. In order to offer a good tradeoff between system performance, cost, and overhead, antenna selection is performed by considering the impacts of both channel estimation errors and noise, such that the antenna with the best link to the BS will be selected to serve users inside the train. The channel estimation error is quantified through the estimation mean squared error (MSE), which is expressed as a closed-form function of the maximum Doppler spread and signal-to-noise ratio (SNR). Several performance metrics, such as outage probability, symbol error rate, spectral efficiency lower bound, and switching rate, are developed as a function of the channel estimation MSE and the geometric layout of the antennas. The analytical and simulation results quantify the significant impacts of imperfect CSI on antenna selection for HSR systems in practical applications.

Physical and MAC Cross-Layer Analysis of Energy-Efficient Cooperative MIMO Networks

We study the cross-layer energy efficiency of cooperative MIMO networks. At the physical layer, the transmit power determines the outage probability and the number of contending nodes per unit area. At the medium access control (MAC) layer, accessing the channel takes additional time and energy, which impacts the throughput and the energy efficiency. Then, we propose a new cooperative MAC protocol based on IEEE 802.11 in order to coordinate cooperation and to improve the energy efficiency. Moreover, we focus on slow fading scenarios and we analyze the performance of antenna selection (AS), singular value decomposition (SVD) diversity beamforming, and spatial multiplexing (SM) transmission schemes. Results show that SVD and SM have smaller delay and, consequently, larger throughput; however, AS is more energy efficient.

Performance of antenna selection schemes in dual hop full-duplex decode-and-forward relaying over Nakagami-m fading channels

In this paper, we investigate the outage performance of several antenna selection (AS) schemes in dual hop full-duplex (FD) multiple-input multiple-output (MIMO) relay networks in which the relay adopts decode-and-forward (DF) protocol over Nakagami-m fading channels. In the network, the source (S), destination (D) and relay (R) are assumed to be equipped with multiple antennas. We assume that the line-of-sight component between S and D cannot be established due to the poor fading environment conditions. For signal transmission-reception during the training period, only a single antenna at each node is selected according to selection techniques, and then with the help of an error-free feedback channel the selected antenna index is sent to the related node. Outage probability (OP) expressions related to AS schemes are obtained in closed forms and asymptotic OPs are also derived in order to get more meaningful insights into OP and diversity behaviour. The theoretical results are verified by Monte Carlo simulations. We show that performance of the FD relay can be significantly improved by using selection techniques compared to half-duplex (HD), especially at low signal-to-noise ratio (SNR) region. In addition, results show that the performance floor level meaning zero diversity at high SNR region, which is also confirmed by asymptotic analysis and is an inherent disadvantage of FD relay, can be decreased. Moreover, it is shown that the FD relay with AS schemes outperforms HD as the target rate increases for a certain value of SNR and residual self-interference power.

Joint Relay and Antenna Selection in MIMO PLNC Inter-vehicular Communication Systems over Cascaded Fading Channels

We investigate the joint relay and antenna selection performance in a multiple input multiple output (MIMO) Vehicle-to-Vehicle (V2V) communication system employing physical layer network coding (PLNC) with amplify-and-forward (AF) scheme at the relay antenna. Analytic results are derived under the cascaded Nakagami-m fading channel model assumption, which covers cascaded Rayleigh and conventional cellular channel models as well. We evaluate the performance of the system in terms of joint outage probability of sources and derive closed-form expressions for lower and upper bounds while an exact expression is found as a single integral form. Besides, the asymptotic diversity order is analyzed and quantified as a function of number of relays and antennas installed on the source and relay vehicles, and channel parameters. Finally, we verify the analytic derivations by computer simulations. Our results show that the outage probability performance decreases with the increasing cascading degrees of the channels but joint relay and antenna selection enhances the performance of the system superbly with the increasing number of relays and antennas. Also it is shown throughout all the simulation results, the lower bound for the joint outage probability seems to consistently be well tight for large SNR. Therefore it can be used for practical design of inter-vehicular communication systems which contain multiple relays and antennas.

Unified Analysis and Optimization Study of Antenna Selection in Two-Way Relay Networks

In this letter, we investigate the performance of antenna selection in amplify-and-forward (AF) MIMO two-way relay networks (TWRNs) where a simple unified system outage probability (OP) expression is obtained for Nakagami- m , Rician, and Weibull fading channels. To quantify the error performance of the TWRN, a closed-form expression of the overall symbol-error-rate (OSER) is derived for Nakagami- m fading. In addition, to gain further insights on the diversity order, asymptotic expressions of the system OP and OSER are obtained at high signal-to-noise ratio (SNR) regime. Moreover, the joint optimization problems of power allocation and relay location are considered to minimize the asymptotic system OP. Finally, the analytical findings are validated by the simulations.

Antenna Selection With Erroneous Covariance Matrices Under Secrecy Constraints

The authors maximize achievable secrecy rate while performing antenna selection (AS) when the authors do not have perfect availability of instantaneous channel covariance matrices of the legitimate (maths ƒ L) and eavesdropper/wiretapper (maths ƒ E) nodes. Instead, the authors have at the authors disposal corrupted estimates of the channel covariance matrices. The error component of the estimated matrices is assumed to be weighted by a norm-bounded error vector. For a class of norms, irrespective of the distribution of the error vector, the authors devise a so-called convex inner approximation (CIA) semidefinite program (SDP)-based solution that yields a transmit precoder with the desired sparsity as dictated by the number of antennas to be selected. The authors numerical results reveal that the CIA procedure works close to exhaustive results and possesses amenable polynomial complexity properties. The authors conclude numerical investigations by demonstrating the effectiveness of AS under the circumstances considered in this paper.

Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally?

Massive MIMO can greatly increase both spectral and transmit-energy efficiency. This is achieved by allowing the number of antennas and RF chains to grow very large. However, the challenges include high system complexity and hardware energy consumption. Here we investigate the possibilities to reduce the required number of RF chains, by performing antenna selection. While this approach is not a very effective strategy for theoretical independent Rayleigh fading channels, a substantial reduction in the number of RF chains can be achieved for real massive MIMO channels, without significant performance loss. We evaluate antenna selection performance on measured channels at 2.6 GHz, using a linear and a cylindrical array, both having 128 elements. Sum-rate maximization is used as the criterion for antenna selection. A selection scheme based on convex optimization is nearly optimal and used as a benchmark. The achieved sum-rate is compared with that of a very simple scheme that selects the antennas with the highest received power. The power-based scheme gives performance close to the convex optimization scheme, for the measured channels. This observation indicates a potential for significant reductions of massive MIMO implementation complexity, by reducing the number of RF chains and performing antenna selection using simple algorithms.

Performance Analysis of a Power Limited Spectrum Sharing System With TAS/MRC

Capacity of the cognitive radio network degrades due to the interference constraint from the primary network. The secondary network capacity can be enhanced in a cost effective way by means of spatial diversity, that can be achieved by adding multiple antennas on the secondary network terminals and performing antenna selection. In this paper, the performance of a multiple-input multiple-output (MIMO) secondary link with transmit antenna selection (TAS) at the transmitter and maximum ratio combining (MRC) at the receiver is analyzed. A peak transmit power constraint at the secondary transmitter is considered in addition to the interference power constraint and two scenarios are considered; 1) the MIMO cognitive system with TAS/MRC (MCS-TM) does not experience interference from the primary network (denote by MCS-TM-NI), and 2) MCS-TM does experience interference from the primary network (denote by MCS-TM-WI). The performance of both MCS-TM-NI and MCS-TM-WI is analyzed and, for a Rayleigh faded channel, closed-form expression for the outage probability is derived. In addition, closed-form expressions of the moment generating function, the symbol error rate and the ergodic capacity are obtained for the MCS-TM-NI. Asymptotic performance analysis of the MCS-TM-NI reveals that TAS/MRC in a MIMO cognitive system achieves a generalized diversity gain equal to the product of the number of transmit and receive antennas. Numerical results are also presented to corroborate the derived analytical results.

Interference mitigation in an LTE femtocell base station using uplink antenna selection

Abstract Antenna selection represents an attractive technique that allows to improve performance of wireless systems due to its simplicity and ease of implementation. Antenna selection is able to provide diversity through the use of multiple antennas while keeping low cost and energy consumption by selecting only a subset of the available elements at any given time, hence requiring a smaller number of RF transmitter and receiver chains. This makes it especially suitable for femtocell or small-cell base stations, typically employed by cellular operators to provide indoor radio coverage in customer premises. This article presents an analysis and validation of antenna selection using a LTE-FDD femtocell prototype. The effects on antenna selection performance of different antenna training schedules and channel variation rates are investigated under realistic propagation conditions. It is observed that antenna selection is able to provide substantial gains in terms of channel quality and reliability in interference-limited scenarios, attesting its suitability for large-scale femtocell deployments.

Performance of Antenna Selection in MIMO System Using Channel Reciprocity with Measured Data

The channel capacity of MIMO system increases as a function of antenna pairs between transmitter and receiver but it suffers from multiple expensive RF chains. To reduce cost of RF chains, antenna selection (AS) method can offer a good tradeoff between expense and performance. For a transmitting AS system, channel state information (CSI) feedback is required to choose the best subset of available antennas. However, the delay and error in feedback channel are the most dominant factors to degrade performances. In this paper, the concept of AS method using reciprocal CSI instead of feedback channel is proposed. The capacity performance of proposed system is investigated by own developing Testbed. The obtained results indicate that the reciprocity technique offers a capacity close to a system with perfect CSI and gains a higher capacity than a system without AS method. This benefit is from 0.9 to 2.2 bps/Hz at SNR 10 dB.

Antenna selection for space-time coded systems with imperfect channel estimation

This paper studies the performance of antenna selection (AS) for space-time (ST) coded systems with noisy channel estimates. For coherent AS systems over Rayleigh flat fading channels, we derive the pairwise error probability (PEP) in the presence of imperfect channel estimation, where the channel is estimated using training insertion and minimum mean square error (MMSE) estimation. Multiplexed training is employed, where the antennas are multiplexed to the small number of RF chains available in the AS system. AS is performed only at the receiver, using the maximum estimated channel power selection rule. Both the maximum likelihood (ML) decoder taking into account the channel estimation error, and the minimum distance decoder are considered, and full diversity gain is shown to be preserved for both cases. Based on the derived training-based PEP, the effective SNR and the coding gain loss due to training are quantified for square unitary and orthogonal codes. The optimal power allocation between the training and data symbols is obtained by minimizing the PEP. For AS systems employing orthogonal designs, we further derive the exact PEP expression in closed-form. We also show that when square unitary training is employed, AS using the norm of MMSE channel estimates is equivalent to AS using the norm (power) of the received signal. Exploiting this fact, we propose an alternate training scheme which avoids multiplexing, has higher spectral efficiency, and better performance compared to the multiplexed training scheme. Simulations are shown to validate our analysis

Performance of convolutionally-coded MIMO systems with antenna selection

In this work, we study the performance of a serial concatenated scheme comprising a convolutional code (CC) and an orthogonal space-time block code (STBC) separated by an inter-leaver. Specifically, we derive performance bounds for this concatenated scheme, clearly quantify the impact of using a CC in conjunction with a STBC, and compare that to using a STBC code only. Furthermore, we examine the impact of performing antenna selection at the receiver on the diversity order and coding gain of the system. In performing antenna selection, we adopt a selection criterion that is based on maximizing the instantaneous signal-to-noise ratio (SNR) at the receiver. That is, we select a subset of the available receive antennas that maximizes the received SNR. Two channel models are considered in this study: Fast fading and quasi-static fading. For both cases, our analyses show that substantial coding gains can be achieved, which is confirmed through Monte-Carlo simulations. We demonstrate that the spatial diversity is maintained for all cases, whereas the coding gain deteriorates by no more than 10 log 10 (M/L) dB, all relative to the full complexity multiple-input multiple-output (MIMO) system.