Power Allocation and Antenna Selection for Heterogeneous Cellular Networks

In this paper,we investigate the system performance of a heterogeneous cellular network consisting of a macro cell and a small cell,where each cell has one user and one base station with multiple antennas.The macro base station(MBS)and the small base station(SBS)transmit their confidential messages to the macro user(MU)and the small user(SU)over their shared spectrum respectively.To enhance the system sum rate(SSR)of MBS-MU and SBS-SU transmission,we propose joint antenna selection combined with optimal power allocation(JAS-OPA)scheme and independent antenna selection combined with optimal power allocation(IAS-OPA)scheme.The JAS-OPA scheme requires to know the channel state information(CSI)of transmission channels and interference channels,while the IAS-OPA scheme only needs to know the CSI of transmission channels.In addition,we carry out the analysis for conventional round-robin antenna selection combined with optimal power allocation(RR-OPA)as a benchmark scheme.We formulate the SSR maximization problem through the power allocation between MBS and SBS and propose iterative OPA algorithms for JAS-OPA,IAS-OPA and RR-OPA schemes,respectively.The results show that the OPA schemes outperform the equal power allocation in terms of SSR.Moreover,we provide the closed-form expression of the system outage probability(SOP)for IAS scheme and RR scheme,it shows the SOP performance can be significantly improved by our proposed IAS scheme compared with RR scheme.

Analysis of handoff in distributed mobile communications system based on remote antenna unit selection

A remote antenna unit （RAU） selection model is presented, and two kinds of handoffs, intra-cell handoff （HO） and inter-cell HO, are defined in distributed mobile communications systems （DAS）. After that, an inter-cell HO model is proposed, in which the average power of the active set （AS） is used to predict the position of the mobile station （MS）. The total power of the AS and the handoff set （HOS） are utilized to determine whether an inter-cell HO is necessary. Furthermore, the relationship between HO parameters and performance metrics is studied in detail based on RAU selection. Simulation results show that both the intra-cell HO and the inter-cell HO can achieve oerfect performance by aoprooriate settings of HO parameters.

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 4n L , where n L 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 perormance of the JTRAS algorithm while its computational complexity is only 1/4n L 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.

Antenna selection in MIMO radar with collocated antennas

An antenna adjustment strategy is developed for the target tracking problem in the collocated multiple-input multipleoutput(MIMO)radar.The basic technique of this strategy is to optimally allocate antennas by the prior information in the tracking recursive period,with the objective of enhancing the worst-case estimate precision of multiple targets.On account of the posterior Cramer-Rao lower bound(PCRLB)offering a quantitative measure for target tracking accuracy,the PCRLB of joint direction-of-arrival(DOA)and Doppler is derived and utilized as the optimization criterion.It is shown that the dynamic antenna selection problem is NP-hard,and an efficient technique which combines convex relaxation with local search is put forward as the solution.Simulation results demonstrate the outperformance of the proposed strategy to the fixed antenna configuration and heuristic search algorithm.Moreover,it is able to offer close-to performance of the exhaustive search method.

Novel antenna selection algorithm based on Tanimoto similarity

A new antenna selection algorithm for multiple input multiple output （MIMO） wireless systems is proposed. The modified Tanimoto coefficient is used to compare the similarity of the rows/columns of the channel matrix. Based on the calculated similarity, the proposed algorithm chooses the antenna subset, which has the maximum product of dissimilarity and Frobenius norm. The proposed algorithm requires low computational complexity as to the optimal selection but with comparative outage capacity and average signal to noise ratio （SNR） performance. It can improve both the outage capacity and the average SNR as compared to random selection. The simulation results are shown to validate our algorithm.

Ergodic Rate Analysis on Applying Antenna Selection in D2D Communication Underlaying Cellular Networks

By reusing the spectrum of a cellular network, device-to-device(D2D) communications is known to greatly improve the spectral efficiency bypassing the base station(BS) of the cellular network. Antenna selection is the most cost efficient scheme for interference management, which is crucial to D2D systems. This paper investigates the achievable rate performance of the D2D communication underlaying the cellular network where a multiple-antenna base station with antenna selection scheme is deployed. We derive an exact closed-form expression of the ergodic achievable rate. Also, using Jensen's inequality, two pairs of upper and lower bounds of the rate are derived and we validate the tightness of the two sets of bounds. Based on the bounds obtained, we analyze the ergodic achievable rate in noise-limited scenario, interference-limited high SNR scenario and larger-scale antenna systems. Our analysis shows that the presence of D2D users could be counter-productive if the SNR at cellular UE is high. Further analysis shows that the relationship between the ergodic rate and the number of antennas it positive, but keeps decreasing as the antenna number increasing. These show the inefficiency of antenna selection in D2D interference management.

Joint Antenna Selection and Robust Beamforming Design in Multi-cell Distributed Antenna System

Most of studies on Distributed Antenna System(DAS) focus on maximizing the sum capacity and perfect channel state information at transmitter(CSIT).However,CSI is inevitable imperfect in practical wireless networks.Based on the sources of error,there are two models.One assumes error lies in a bounded region,the other assumes random error.Accordingly,we propose two joint antenna selection(AS) and robustbeamforming schemes aiming to minimize the total transmit power at antenna nodes subject to quality of service(QoS) guarantee for all the mobile users(MUs) in multicell DAS.This problem is mathematically intractable.For the bounded error model,we cast it into a semidefinite program(SDP) using semidefinite relaxation(SDR) and S-procedure.For the second,we first design outage constrained robust beamforming and then formulate it as an SDP based on the Bernstein-type inequality,which we generalize it to the multi-cell DAS.Simulation results verify the effectiveness of the proposed methods.

Joint User Scheduling and Antenna Selection in Distributed Massive MIMO Systems with Limited Backhaul Capacity

Massive MIMO systems offer a high spatial resolution that can drastically increase the spectral and/or energy efficiency by employing a large number of antennas at the base station(BS).In a distributed massive MIMO system,the capacity of fiber backhaul that links base station and remote radio heads is usually limited,which becomes a bottleneck for realizing the potential performance gain of both downlink and uplink.To solve this problem,we propose a joint antenna selection and user scheduling which is able to achieve a large portion of the potential gain provided by the massive MIMO array with only limited backhaul capacity.Three sub-optimal iterative algorithms with the objective of sumrate maximization are proposed for the joint optimization of antenna selection and user scheduling,either based on greedy fashion or Frobenius-norm criteria.Convergence and complexity analysis are presented for the algorithms.The provided Monte Carlo simulations show that,one of our algorithms achieves a good tradeoff between complexity and performance and thus is especially fit for massive MIMO systems.

Invited Paper: Antenna Selection in Energy Efficient MIMO Systems: A Survey

With the explosive growth and need for high-speed wireless communications, more and more energy is consumed to support the required quality of service. Therefore, energy efficient or green communication has become a very hot topic under the ground of limited energy resource and environmentally friendly transmission schemes. MIMO technique is capable of reducing the transmission power thanks to its diversity and multiplexing gain. Moreover, antenna selection(AS) is an alternative to extract many of the benefits in MIMO systems with a reduced cost of complexity and power. Although many works including several survey papers have investigated AS in MIMO systems, the goal of these works is only the capacity maximization or error rate minimization, which fails to guarantee the optimality of the energy efficiency in MIMO systems. In this paper, we overview the state of the art in the AS schemes in energy efficient MIMO systems, the goal of which is to optimize the energy efficiency of the whole system. Specifically, we introduce energy efficient AS in point-to-point MIMO, cooperative MIMO, multiuser MIMO and largescale MIMO systems, respectively. Several challenging and practical issues in this area are also addressed.

COMBINED TRANSMIT ANTENNA SELECTION AND DETECTION OVER SPATIAL CORRELATED MIMO SYSTEMS

In this paper a method that combines transmit antenna selection and reduced-constellation detection in spatially correlated Multi-Input Multi-Output （MIMO） fading channels is presented. To mitigate the performance degradation caused by the use of antenna selection that is based on correlation among columns, an iterative receiver scheme that uses only a subset of the constellation points close to the expected symbol vahle estimated in the previous iteration is proposed. The size of the subset can adapt to the maximum correlation of the sub-matrix after the simple antenna selection. Furthermore, the error rate performance of the scheme under linear Miniinutn Mean Square Error （MMSE） or Ordered Successive Interference Cancellation （OSIC） for the first run detection and different interleaver lengths is investigated while the transnlit antenna selection is considered. The simulation results show a significant advantage both for implementation complexity and for error rate performance under a fixed data rate.

RECEIVE ANTENNA SUBSET SELECTION BASED ON ORTHOGONAL COMPONENTS

A new receive antenna subset selection algorithm with low complexity for wireless Multipie-Input Multiple-Output （MIMO） systems is proposed, which is based on the orthogonal components of the channel matrix. Larger capacity is achieved compared with the existing antenna selection methods. Simulation results of quasi-static fiat fading channel demonstrate the significant performance of the proposed selection algorithm.

TRANSMIT ANTENNA SELECTION IN V-BLAST SYSTEM

In order to reduce the cost of Radio Frequency (RF) chains in the spatial multiplexing systems with Vertical-Bell Labs Layered Space-Time (V-BLAST) nonlinear receiver, a novel transmit antenna selection cri-terion is proposed with the motivation of minimizing the Vector Symbol Error Rate (VSER). In the proposed scheme, both the number of substreams and the mapping of substreams to antennas are dynamically adjusted based on the knowledge of channel. Simulation results illustrate that the proposed two-step selection criterion outperforms the existing eigenmode based selection criterion by 0.3dB at a VSER of 10?3.

Antenna Selection in Energy Harvesting Relaying Networks Using Q-Learning Algorithm

In this paper,a novel opportunistic scheduling(OS)scheme with antenna selection(AS)for the energy harvesting(EH)cooperative communication system where the relay can harvest energy from the source transmission is proposed.In this considered scheme,we take into both traditional mathematical analysis and reinforcement learning(RL)scenarios with the power splitting(PS)factor constraint.For the case of traditional mathematical analysis of a fixed-PS factor,we derive an exact closed-form expressions for the ergodic capacity and outage probability in general signal-to-noise ratio(SNR)regime.Then,we combine the optimal PS factor with performance metrics to achieve the optimal transmission performance.Subsequently,based on the optimized PS factor,a RL technique called as Q-learning(QL)algorithm is proposed to derive the optimal antenna selection strategy.To highlight the performance advantage of the proposed QL with training the received SNR at the destination,we also examine the scenario of QL scheme with training channel between the relay and the destination.The results illustrate that,the optimized scheme is always superior to the fixed-PS factor scheme.In addition,a better system parameter setting with QL significantly outperforms the traditional mathematical analysis scheme.

Hybrid transmit antenna selection and maximal-ratio transmission systems

Maximal-ratio transmission systems with transmit antenna selection is investigated. According to the order statistics of channel fiat fading coefficients, the closed-form expressions axe derived for average SNR with any amount of RF chains and average BER with two RF chains, respectively. The algorithm for calculating the minimum of total transmit antennas is presented in terms of reduced RF chains. The method of quantizing transmit precoders is employed in this study to decrease feedback information. Simulation results demonstrate the superiority of the proposed systems under full and quantized transmit precoders. The SNR of the proposed systems has been less degraded by the quantization of transmit precoder than that of pure maximal-ratio transmission systems.

Closed-loop transmit diversity systems with hybrid antenna selection

The paper investigates closed-loop transmit diversity （CLTD） systems with antenna selection technique. The expected received signal-noise-ratio （RxSNR） of the proposed systems is analyzed and compared with CLTD systems. An algorithm is proposed for determining the number of increased transmit antennas in terms of a reduced RF chains without performance degradation. Since a feedback channel is bandwidth-limited, we present a method of quantizing transmit-weight vectors. Simulation results demonstrate advantage of the proposed systems with full and quantized feedback information. Quantized feedback has less effect on the proposed systems than CLTD systems.

An antenna selection algorithm for spatial multiplexing systems in BLAST receiver

In this paper, the antenna selection problem for spatial multiplexing systems in a BLAST receiver is investigated. In order to search the optimal antenna subset, a selection criterion is proposed, which is able to obtain the largest minimum post-detection SNR. The number of required antennas is deduced, which is determined by the system performance requirement for the existing RF chains. Simulation result shows that the optimal subset in a BLAST receiver has higher minimum sub-channel SNR than that in a ZF receiver. Computation of system performance can be fitted to a simple function, and it is simpler for the proposed algorithm to compute the required antenna number.

An Introduction to Transmit Antenna Selection in MIMO Wiretap Channels

This paper is a survey of transmit antenna selection-a low-complexity, energy-efficient method for improving physical layer security in multiple-input multiple-output wiretap channels. With this method, a single antenna out of multiple antennas is selected at the transmitter. We review a general analytical framework for analyzing exact and asymptotic secrecy of transmit antenna selection with receive maximal ratio combining, selection combining, or generalized selection combining. The analytical results prove that secrecy is significantly improved when the number of transmit antennas increases.

Zero-forcing beamforming with receiver antenna selection in downlink multi-antenna multi-user system

A study on the zero-forcing beamforming （ZFBF） scheme with antenna selection at user terminals in downlink multi-antenna multi-user systems is presented. Simulation results show that the proposed ZFBF scheme with receiver antenna selection （ZFBF-AS） achieves considerable throughput improvement over the ZFBF scheme with single receiver antenna. The results also show that, with multi-user diversity, the ZFBF-AS scheme approaches the throughput performance of the ZFBF scheme using all receiver antennas （ZFBF-WO-AS） when the base station adopts semi-orthogonal user selection （SUS） algorithm, and achieves larger throughput when the base station adopts the Round-robin scheduling algorithm. Compared with ZFBF-WO-AS, the proposed ZFBF-AS scheme can reduce the cost of user equipments and the channel state information requirement at the transmitter （CSIT） as well as the multiuser scheduling complexity at the transmitter.

A LOWER COMPLEXITY ANTENNA SELECTION FOR DF RELAY MIMO SYSTEMS

Based on the existing incremental selection algorithm for Decode-and-Forward (DF) Multiple Input Multiple Output (MIMO) systems, a faster one which combines the incremental selection with the decremental exclussion is proposed. Firstly, the algorithm selects one antenna which makes the increment of the capacity greatest in every step. Then, excludes the antennas whose contribution to the capacity is less than μ% of that of the best antenna. Simulations show that the proposed algorithm achieves comparable performance to the existing one and has obviously decreased complexity under the appropriate threshold μ% .

Antenna selection based on large-scale fading for distributed MIMO systems

An antenna selection algorithm based on large-scale fading between the transmitter and receiver is proposed for the uplink receive antenna selection in distributed multiple-input multiple-output(D-MIMO) systems. By utilizing the radio access units(RAU) selection based on large-scale fading,the proposed algorithm decreases enormously the computational complexity. Based on the characteristics of distributed systems,an improved particle swarm optimization(PSO) has been proposed for the antenna selection after the RAU selection. In order to apply the improved PSO algorithm better in antenna selection,a general form of channel capacity was transformed into a binary expression by analyzing the formula of channel capacity. The proposed algorithm can make full use of the advantages of D-MIMO systems,and achieve near-optimal performance in terms of channel capacity with low computational complexity.