相关衰落MIMO信道下的联合天线子集选择

针对相关衰落MIMO信道下的联合天线子集选择,提出了2种选择算法。首先,在已知精确信道知识的情况下,选择算法选择以使接收数据流的SNR最大化和瞬时误差概率即误符号率最小化的天线子集,从而得到平均SNR增益改善的解析表达式;其次,当信道迅速变化时,在已知信道统计知识的情况下,选择算法选择以使全部可能信道实现的平均误差概率最小化的天线子集,从而得到编码增益,在极端相关信道条件下,也可以得到分集增益;基于2种选择算法的性能分析和仿真结果验证了本文提出算法的有效性。     

Joint antenna selection and link adaptation for MIMO systems

Multi-input multi-output (MIMO) systems, with multiple antennas at both the transmitter and the receiver, are anticipated to be widely employed in future wireless networks due to their predicted tremendous system capacity. To protect the transmitted data against random channel impairment, it is desirable to consider link adaptation, such as rate adaptation and power control, to improve the system performance and guarantee certain quality of service. Based on the observation that link adaptation and antenna selection problems are often coupled, we propose a joint antenna subset selection and link adaptation study for MIMO systems. After the formulation of the multidimensional joint optimization problem, the main contribution of this paper lies in the design of efficient algorithms approaching the optimal solution for both uncorrelated and correlated MIMO channels. Specifically, we propose one simplified antenna selection and link adaptation rule based on the expected optimal number of active antennas for uncorrelated MIMO with Rayleigh fading and one for correlated MIMO channels only based on the slowly varying channel correlation information. Our proposed algorithms are verified through numerical results, demonstrating significant gains over traditional MIMO signaling, while feasible for practical implementation.     

MIMO antenna selection with lattice-reduction-aided linear receivers

A method to improve the performance of multiple-input-multiple-output systems is to employ a large number of antennas and select the optimal subset depending on the specific channel realization. A simple antenna-selection criterion is to choose the antenna subset that maximizes the mutual information. However, when the receiver has finite complexity decoders, this criterion does not necessarily minimize the error rate (ER). Therefore, different selection criteria should be tailored to the specific receiver implementation. In this paper, we develop new antenna-selection criteria to minimize the ER in spatial multiplexing systems with lattice-reduction-aided receivers. We also adapt other known selection criteria, such as maximum mutual information, to this specific receiver. Moreover, we consider adaptive antenna-selection algorithms when the channel is not perfectly known at the receiver but can only be estimated. We present simulation examples to show the ER of the different selection criteria and the convergence of the adaptive algorithms. We also discuss the difference in complexity and performance among them.     

Limited feedback unitary precoding for spatial multiplexing systems

Multiple-input multiple-output (MIMO) wireless systems use antenna arrays at both the transmitter and receiver to provide communication links with substantial diversity and capacity. Spatial multiplexing is a common space-time modulation technique for MIMO communication systems where independent information streams are sent over different transmit antennas. Unfortunately, spatial multiplexing is sensitive to ill-conditioning of the channel matrix. Precoding can improve the resilience of spatial multiplexing at the expense of full channel knowledge at the transmitter-which is often not realistic. This correspondence proposes a quantized precoding system where the optimal precoder is chosen from a finite codebook known to both receiver and transmitter. The index of the optimal precoder is conveyed from the receiver to the transmitter over a low-delay feedback link. Criteria are presented for selecting the optimal precoding matrix based on the error rate and mutual information for different receiver designs. Codebook design criteria are proposed for each selection criterion by minimizing a bound on the average distortion assuming a Rayleigh-fading matrix channel. The design criteria are shown to be equivalent to packing subspaces in the Grassmann manifold using the projection two-norm and Fubini-Study distances. Simulation results show that the proposed system outperforms antenna subset selection and performs close to optimal unitary precoding with a minimal amount of feedback.     

Interference Mitigation in MIMO Systems by Subset Antenna Transmission

This paper investigates subset antenna transmission (SAT) for multiple-input multiple-output (MIMO) systems in the presence of strong dominant co-channel interferer. The capacity gain from SAT is investigated in the context of optimal antenna subset selection and power allocation. The SAT does not require channel state information of the co-channel interference, and achieves capacity gains by distributing the transmit power equally over a selected subset of the transmit antennas. The capacity gain of the SAT method is analyzed in terms of transmit power and eigenvalues of channel matrix, and its performance in V-BLAST MIMO systems with various signal constellations is evaluated by computer simulation.     

Adaptive transmit antenna selection with pragmatic space-time trellis codes

We consider the problem of selecting a subset of transmit antennas in MIMO systems to minimize error probability when only partial channel information is available at the transmitter. An upper bound for error probability of space-time coded transmit antenna selection scheme conditioned on the channel state information is presented. Based on the performance analysis, a criterion of selecting a subset of available transmit antennas to minimize the upper bound on the PEP is proposed. In contrast to other transmit antenna selection schemes for uncoded transmission or with a fixed number of antennas within the selection subset in the literature, the proposed scheme can adaptively select both a variable number of transmit antennas and their corresponding space-time codes for transmission. Furthermore, we present pragmatic space-time trellis coding schemes for slow Rayleigh fading channels. The principal advantage of the schemes is that a single encoder and decoder can be used for systems with a variable number of transmit antennas. The performance of the pragmatic space-time codes with adaptive antenna selection and the effect of the imperfect channel estimation on performance are evaluated by simulations. It is shown that the adaptive selection offers considerable antenna selection gain relative to the antenna selection system with a fixed number of antennas within the selection subset     

Performance evaluation of spatially multiplexed MIMO systems with subset antenna transmission in interference limited environments

Transmit antenna selection in spatially multiplexed multiple-input multiple-output (MIMO) systems is a low complexity low-rate feedback technique, which involves transmission of a reduced number of streams from the maximum possible to improve the error rate performance of linear receivers. It has been shown to be effective in enhancing the performance of single-user interference-free point-to-point MIMO systems. However, performance of transmit antenna selection techniques in interference-limited environments and over frequency selective channels is less well understood. In this paper, we investigate the performance of transmit antenna selection in spatially multiplexed MIMO systems in the presence of co-channel interference. We propose a transmission technique for the downlink of a cellular MIMO system that employs transmit antenna selection to minimize the effect of co-channel interference from surrounding cells. Several transmit antenna selection algorithms are proposed and their performance is evaluated in both frequency flat and frequency selective channels. Various antenna selection algorithms proposed in the literature for single user MIMO links are extended to a cellular scenario, where each user experiences co-channel interference from the other cells (intercell interference) in the system. For frequency selective channels, we consider orthogonal frequency division multiplexing (OFDM) with MIMO. We propose a selection algorithm that maximizes the average output SINR over all subcarriers. A method to quantify selection gain in frequency selective channel is discussed. The effect of delay spread on the selection gain is studied by simulating practical fading environments with different delay spreads. The effect of the variable signal constellation sizes and the number of transmitted streams on the bit error rate (BER) performance of the proposed system is also investigated in conjunction with the transmit antenna selection. Simulation results show that for low to moderate interference power, significant improvement in the system performance is achievable with the use of transmit antenna selection algorithms. Even though the gain due to selection in frequency selective channels is reduced compared to that in flat fading channels due to the inherent frequency diversity, the performance improvement is significant when the system is interference limited. The performance improvement due to reduced number of transmit streams at larger signal constellation sizes is found to be more significant in spatially correlated scenarios, and the gain due to selection is found to be reduced with the increased delay spread. It is found that employing transmit antenna selection algorithms in conjunction with adaptation of the number of transmitted streams and the signal constellation sizes can significantly improve the performance of MIMO systems with co-channel interference.     

一种新型低复杂度双层分组天线选择算法

针对平坦相关瑞利衰落信道环境下的端到端大规模MIMO系统复杂度过高的问题,提出一种基于离散布谷鸟搜索的低复杂度双层分组天线选择算法。该算法首先基于天线信道相关性对大规模天线阵列进行分组处理,进而利用新型双层算法对分组的天线集合进行优化天线选择。其中,新型双层算法的第一层是每小组天线基于离散布谷鸟搜索的内部选择,第二层是对第一层选择的所有天线利用离散布谷鸟搜索进行最终的选择。提出的新型天线选择算法可有效降低大规模MIMO系统复杂度。仿真结果验证了在平坦相关瑞利衰落信道环境下,提出的天线选择算法能够以较低选择复杂度获得接近最优选择方法的容量性能和较优的BER性能。     

Achievable sum‐rate maximization using relay/antenna selection for MIMO two‐way AF relaying with channel uncertainties

This paper focuses on the layered relay‐and‐antenna selection (LRAS) for achievable sum‐rate (ASR) maximization while considering the impacts of residual self‐interference due to channel estimation errors in multiple‐input multiple‐output two‐way amplify‐and‐forward relaying systems. Two LRAS algorithms, namely, the Gram–Schmidt and the adaptive discrete stochastic approximation selection techniques, are investigated based on the ASR maximization under an equal power allocation. To alleviate the complexity burden of the LRAS strategies, the optimal relay and the subset of transmit‐and‐receive antenna pairs are determined by a two‐stage selection mechanism. By taking two LRAS strategies and correlated channel uncertainties into account, the development of a two‐way multiple‐input multiple‐output multi‐amplify‐and‐forward‐relay system is able to provide improved robustness against the channel state information mismatch and the residual self‐interference. Copyright © 2016 John Wiley & Sons, Ltd.     

接近最优的编码MIMO系统的发送天线子集选择算法

多天线无线系统可提供更大的信道容量和更好的抗衰落能力,发送端利用反馈的部分信道状态信息进行发送天线子集选择能够进一步提高信道容量。该文提出了一种MIMO系统的快速的、动态的天线子集选择算法,其提供的信道容量高于已有的静态算法,且接近于最优天线选择算法,而无需计算所有可能的天线子集组合的信道容量,因而具有更低的复杂度。将本文算法与比特交织编码调制(BICM)技术相结合,对各天线速率进行适配,提出了空时自适应比特交织编码调制(ST-ABICM)方案。仿真结果证实了该方案性能的优越性。     

Channel estimation for multi-panel millimeter waveMIMO based on joint compressed sensing

Channel state information (CSI) is essential for downlink transmission in millimeter wave( mmWave) multipleinput multiple output (MIMO) systems. Multi-panel antenna array is exploited in mmWave MIMO system due to itssuperior performance. Two channel estimation algorithms are proposed in this paper, named as generalized jointorthogonal matching pursuit (G-JOMP) and optimized joint orthogonal matching pursuit (O-JOMP) for multi-panelmmWave MIMO system based on the compressed sensing (CS) theory. G-JOMP exploits common sparsity structureamong channel response between antenna panels of base station ( BS) and users to reduce the computationalcomplexity in channel estimation. O-JOMP algorithm is then developed to further improve the accuracy of channelestimation by optimal panel selection based on the power of the received signal. Simulation results show that theperformance of the proposed algorithms is better than that of the conventional orthogonal matching pursuit (OMP)based algorithm in multi-panel mmWave MIMO system.     

Adaptive opportunistic fair scheduling over multiuser spatial channels

We consider the problem of opportunistic fair scheduling (OFS) of multiple users in downlink time-division multiple-access (TDMA) systems employing multiple transmit antennas and beamforming. OFS is an important technique in wireless networks to achieve fair bandwidth usage among users, which is performed on a per-frame basis at the media access control layer. Multiple-transmit-antenna beamforming provides TDMA systems with the capability of supporting multiple concurrent transmissions, i.e., multiple spatial channels at the physical layer. Given a particular subset of users and their channel conditions, the optimal beamforming scheme can be calculated. The multiuser opportunistic scheduling problem then refers to the selection of the optimal subset of users for transmission at each time instant to maximize the total throughput of the system subject to a certain fairness constraint on each individual user's throughput. We propose discrete stochastic approximation algorithms to adaptively select a better subset of users. We also consider scenarios of time-varying channels for which the scheduling algorithm can track the time-varying optimal user subset. We present simulation results to demonstrate the performance of the proposed scheduling algorithms in terms of both throughput and fairness, their fast convergence, and the excellent tracking capability in time-varying environments.     

Throughput-Optimal Multi-Mode Precoding MIMO System with Per-Substream AMC

In this paper, we study a multi-mode quantized precoding multiple-input multiple-output (MIMO) system with per-substream adaptive modulation and coding under a maximal throughput target. An analytical throughput expression is firstly presented by recurring to Gaussian mixed approximation for block error rate of Turbo codes. An optimal mode-MCS (modulation and coding scheme) selection algorithm is then developed to achieve maximal throughput performance based on throughput criterion. Further, a complexity-reducing selection algorithm with negligible performance loss is proposed by making full use of the information provided by singular value decomposition of the instantaneous channel matrix at the receiver side. Simulation results show that both selection algorithms can achieve good throughput performance in the above mentioned MIMO system.     

基于分布式天线选择的TD—SCDMA动态小区覆盖技术

分布式M IMO天线结构可以降低发射功率,减少小区干扰,而天线选择技术在保持了M IMO系统优点的同时降低成本。TD-SCDMA有独特的时隙结构,可将不同时隙用于不同的天线组来覆盖不同的小区。基于此,提出了一种分布式天线选择的动态小区覆盖技术,采用两级天线选择,第一级可根据用户的具体位置选择天线组并确定覆盖范围,有效减少小区干扰,同时采用了预分配天线组方法,避免了通用天线选择算法的复杂性;第二级在选定的天线组内确定具体的天线,仿真结果说明该方法具有与一般天线选择相同的性能但更简单。     

A new class of soft MIMO demodulation algorithms

We propose a new class of soft-input soft-output demodulation schemes for multiple-input multiple-output (MIMO) channels, based on the sequential Monte Carlo (SMC) framework under both stochastic and deterministic settings. The stochastic SMC sampler generates MIMO symbol samples based on importance sampling and resampling techniques, whereas the deterministic SMC approach recursively performs exploration and selection steps in a greedy manner. By exploiting the artificial sequential structure of the existing simple Bell-Labs layered space-time (BLAST) detection method based on ing and cancellation, the proposed algorithms achieve an error probability performance that is orders of magnitude better than the traditional BLAST detection schemes while maintaining a low computational complexity. In fact, the new methods offer performance comparable with that of the sphere decoding algorithm without attendant increase in complexity. More importantly, being soft-input soft-output in nature, both the stochastic and deterministic SMC detectors can be employed as the first-stage demodulator in a turbo receiver in coded MIMO systems. Such a turbo receiver successively improves the receiver performance by iteratively exchanging the so-called extrinsic information between the soft outer channel decoder and the inner soft MIMO demodulator under both known channel state and unknown channel state scenarios. Computer simulation results are provided to demonstrate the performance of the proposed algorithms.     

Broadband MIMO-OFDM wireless communications

Orthogonal frequency division multiplexing (OFDM) is a popular method for high data rate wireless transmission. OFDM may be combined with antenna arrays at the transmitter and receiver to increase the diversity gain and/or to enhance the system capacity on time-varying and frequency-selective channels, resulting in a multiple-input multiple-output (MIMO) configuration. The paper explores various physical layer research challenges in MIMO-OFDM system design, including physical channel measurements and modeling, analog beam forming techniques using adaptive antenna arrays, space-time techniques for MIMO-OFDM, error control coding techniques, OFDM preamble and packet design, and signal processing algorithms used to perform time and frequency synchronization, channel estimation, and channel tracking in MIMO-OFDM systems. Finally, the paper considers a software radio implementation of MIMO-OFDM.     

MIMO系统中改进的二进制粒子群天线选择算法

在多输入多输出系统中,发射端和接收端的多天线配置提高了信道容量和传输可靠性,而天线选择技术能在保持系统优点的同时有效地降低运算复杂度以及硬件成本。为了能在时变的信道条件下快速地选择出一组最优的天线子集,提出了一种基于二进制粒子群算法的改进的天线选择算法。推导出了二进制粒子群联合收发端天线选择的信道容量公式,并将其作为粒子群算法的适应度函数,使天线选择问题转换成二进制编码串的组合优化问题。通过改进模糊函数提高粒子群算法的收敛性,让二进制粒子群尽可能地收敛于全局最优位置。仿真结果表明,改进的算法能在降低运算复杂度的同时提高收敛性,且系统信道容量趋近于最优算法。     

基于天线子集选择算法的DSTBC优化

为进一步提高空时码性能,在信道模型为瑞丽和莱斯慢衰落信道的情况下,文中提出了一种优化差分空时分组码的＂天线子集选择算法＂——假设发射信号为特定的Alamouti正交空时分组码,通过最大化信道参数矩阵F范数的方法,优化了MIMO系统的天线集。仿真结果表明：此方法可降低码元的比特错误率,并且可获得相当客观的分集增益和能量增益。此外,还讨论了该优化方法的适用范围。     

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 value 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 Minimum Mean Square Error (MMSE) or Ordered Successive Interference Cancellation (OSIC) for the first run detection and different interleaver lengths is investigated while the transmit antenna selection is considered. The simulation results show a sig- nificant advantage both for implementation complexity and for error rate performance under a fixed data rate.     

GMD V-BLAST系统天线选择

基于最大容量和最小差错率准则,研究了在GMD V-BLAST系统中的天线选择问题。选用以信道矩阵非零奇异值的几何均值最大化为目标函数,可以避免容量与差错率性能之间的矛盾。在所有可用天线中进行选择的全搜索算法虽有最佳性能,但复杂度太高。基于贪婪算法,对发射天线采用快速的逐增选择策略,对接收天线采用快速的逐减选择策略,可以显著降低计算的复杂性。计算机仿真结果表明,所采用的快速天线选择算法可以较低的复杂度获得接近全搜索法的容量和分集增益。