Adaptive MIMO antenna selection via discrete stochastic optimization

Recently it has been shown that it is possible to improve the performance of multiple-input multiple-output (MIMO) systems by employing a larger number of antennas than actually used and selecting the optimal subset based on the channel state information. Existing antenna selection algorithms assume perfect channel knowledge and optimize criteria such as Shannon capacity or various bounds on error rate. This paper examines MIMO antenna selection algorithms where the set of possible solutions is large and only a noisy estimate of the channel is available. In the same spirit as traditional adaptive filtering algorithms, we propose simulation based discrete stochastic optimization algorithms to adaptively select a better antenna subset using criteria such as maximum mutual information, bounds on error rate, etc. These discrete stochastic approximation algorithms are ideally suited to minimize the error rate since computing a closed form expression for the error rate is intractable. We also consider scenarios of time-varying channels for which the antenna selection algorithms can track the time-varying optimal antenna configuration. We present several numerical examples to show the fast convergence of these algorithms under various performance criteria, and also demonstrate their tracking capabilities.     

A Low-Complexity Receive-Antenna-Selection Algorithm for MIMO–OFDM Wireless Systems

In this paper, a novel low-complexity antenna-selection algorithm based on a constrained adaptive Markov chain Monte Carlo (CAMCMC) optimization method is proposed to approach the maximum capacity or minimum bit error rate (BER) of receive-antenna-selection multiple-input multiple-output (MIMO)–orthogonal frequency division multiplexing (OFDM) systems. We analyze the performance of the proposed system as the control parameters are varied and show that both the channel capacity and the system BER achieved by the proposed CAMCMC selection algorithm are close to the optimal results obtained by the exhaustive search (ES) method. We further demonstrate that this performance can be achieved with less than 1% of the computational complexity of the ES rule and is independent of the antenna-selection criteria, outage rate requirements, antenna array configuration, and channel frequency selectivity. Similar to the existing antenna-selection algorithms, both channel capacity and system BER improvements achieved by the proposed CAMCMC method are reduced as the channel frequency selectivity increases. Therefore, we conclude that, whether it is designed to maximize the channel capacity or minimize the system BER, the CAMCMC-optimization-method-based antenna-selection technique is appropriate for a MIMO–OFDM system with low frequency selectivity.      

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     

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.     

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。     

Fading Channel Prediction for Mobile Radio Adaptive Transmission Systems

Adaptive transmission methods can potentially aid the achievement of high data rates required for mobile radio multimedia services. To realize this potential, the transmitter needs accurate channel state information (CSI) for the upcoming transmission frame. In most mobile radio systems, the CSI is estimated at the receiver and fed back to the transmitter. However, unless the mobile speed is very low, the estimated CSI cannot be used directly to select the parameters of adaptive transmission systems, since it quickly becomes outdated due to the rapid channel variation caused by multipath fading. To enable adaptive transmission for mobile radio systems, prediction of future fading channel samples is required. Several fundamental issues arise in the design and testing of fading prediction algorithms for adaptive transmission systems. These include complexity, robustness, choice of an appropriate channel model for algorithm validation, channel estimation and noise reduction required for reliable prediction, and design and analysis of adaptive transmission methods aided by fading prediction algorithms. We use these criteria in the review of recent advances in the area of fading channel prediction. We also demonstrate that reliable fading prediction makes adaptive transmission feasible in diverse wireless communication systems.     

Direct Blind Adaptive MOE Receiver for PAM Modulated Time-Hopping UWB System Over Frequency-Selective Fading Channel

Ultra wideband impulse radio systems have attracted great attention for their promised applications in high-speed short-range indoor wireless communication systems. Among the various modulation and multiple access schemes, this paper deals with time-hopping (TH) antipodal pulse amplitude modulation operating in the presence of a multipath fading downlink channel. We first employ a constrained optimization technique to design a batch mode blind (without exploiting training sequences and undesired users’ time-hopping (TH) codes) mobile station receiver. To reduce the computational complexity, we propose a blind adaptive receiver that is based on the criterion of maximizing the receiver’s minimum possible output energy. The algorithm jointly and iteratively optimizes the weight vector and channel impulse response to improve system performance. Simulation results show that the proposed adaptive receiver converges to the optimum batch mode receiver. Moreover, the algorithms are shown to be robust to multi-user interference and near-far problems.     

Antenna selection for unitary space-time modulation

This correspondence studies receive antenna selection (AS) for multiple-antenna systems that employ unitary space-time (ST) signals, where the channel state information (CSI) is known neither at the transmitter nor at the receiver. Without CSI at the receiver, we perform AS only at the receiver and the selection is based on a maximum-norm criterion, i.e., a subset of receive antennas that have the largest received signal power is chosen. Using a Chernoff bound approach, we present theoretical performance analysis based on the pairwise error probability (PEP) and quantify the asymptotic performance at high signal-to-noise ratio (SNR) by giving the diversity and coding gain expressions. We prove that with no CSI at the receiver, the diversity gain with AS is preserved for unitary ST codes with full spatial diversity, the same as the case with known CSI. As a concrete example, for differential unitary ST modulation with M=2 transmit antennas and N=2 receive antennas, we have devised new excellent-performing parametric codes based on the derived PEP bound. The new codes, which are specifically designed for differential AS systems, outperform known differential codes when AS is employed. Corroborating simulations validate our analysis and code design.     

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。     

Space-time trellis codes over rapid rayleigh fading channels with channel estimation?part ii: performance analysis and code design for non-identical channels

We consider the maximum likelihood (ML) receiver design, performance analysis and code design for space-time trellis codes (STTC) over non-identical, rapid fading channels with imperfect channel state information (CSI). The exact pairwise error probability (PEP) and PEP bounds for the ML receiver are obtained. A new code design criterion exploiting the statistical information of the channel estimates is proposed, which can minimize the performance loss caused by channel estimation error. New codes are obtained via an iterative search algorithm with reduced complexity. Under actual channel estimation conditions, our codes perform better than the existing codes in the literature which are designed on the assumption of identical channels, and perfect CSI at the receiver. More performance gain can be achieved by our codes when the degree of imbalance among the links is higher.     

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.     

Transmit antenna selection in linear receivers: geometrical approach

Transmit antenna subset selection in spatial multiplexing systems is considered. In particular, selection algorithms aiming to minimise the error rate when linear detectors are used at the receiver are proposed. Previous work on antenna selection has considered capacity and post-processing SNR selection criteria. However, a geometrical interpretation of the decoding process which also permits development of a suboptimal algorithm that yields a considerable complexity reduction with only a small loss in performance, is considered.     

Code and receiver design for the noncoherent fast-fading channel

This paper deals with the design of coding/modulation and demodulation/decoding schemes for single- or multiple-antenna systems with focus on fast-fading channels, where channel state information (CSI) is not available at the transmitter and the receiver. We explore two possible solutions for this channel with increasing degree of sophistication. The first one utilizes pilots at the transmitter and a simple and explicit noniterative channel estimation algorithm at the receiver. We show that this pilot-assisted system is exactly equivalent, in terms of performance analysis and design, to an appropriately "degraded" system having perfect CSI at the receiver. The second scheme utilizes pilots and a family of well-justified and simple suboptimal iterative detection/estimation algorithms. It is shown that when turbo-like codes are considered in conjunction with this pilot-assisted transmission scheme and the proposed receiver algorithm, the unitary constellations investigated in the literature are inferior to simple pilot-assisted constellations in both complexity and performance. Specific instances of the proposed systems (that use optimized irregular low-density parity-check outer codes) are designed. The design examples provided show that the proposed systems can achieve a good tradeoff between complexity and performance and can be used to bridge the gap between the high complexity/high-performance optimal scheme and low-complexity/mediocre performance noniterative estimation/coherent detection scheme.     

Space-time coding over correlated fading channels with antenna selection

In a previous paper by Bahceci et al., antenna selection ' for multiple-antenna transmission systems under the assumption that the subchannels between antenna pairs fade independently was studied. In this paper, the performance of such systems when the subchannels experience correlated fading is considered. It is assumed that the channel-state information (CSI) is available only at the receiver, the antenna selection is performed only at the receiver, and the selection is based on the instantaneous received signal power. The effects of channel correlations on the diversity and coding gain when the receiver system is a subset of the antennas are quantified. Theoretical results indicate that the correlations in the channel do not degrade the diversity order, provided that the channel is full rank. However, it does result in some performance loss in the coding gain.     

Differential MMSE: A Framework for Robust Adaptive Interference Suppression for DS-CDMA Over Fading Channels

The linear minimum mean-squared error (MMSE) criterion is known to provide adaptive algorithms for interference suppression in direct-sequence (DS) code-division multiple-access (CDMA) systems. However, standard MMSE adaptation is not robust to fast fading, being unable to compensate for rapid channel variations. In this paper, we provide a framework for deriving robust adaptive algorithms in this setting based on a new differential MMSE (DMMSE) criterion, which is a constrained optimization problem in which the quantity to be tracked is the ratio of the data appearing in two successive observation intervals. When applied to a DS-CDMA system with short spreading waveforms (i.e., with period equal to the symbol interval) operating over a flat-fading channel, the DMMSE criterion avoids tracking the fades, exploiting the negligible variation of the fading gain over two consecutive symbols. For frequency-selective fading, the DMMSE criterion is extended to provide a new eigenrake receiver which provides interference suppression and diversity combining without requiring explicit information regarding the desired user's propagation channel.     

Channel estimation techniques for linear precoded systems: Supervised, unsupervised, and hybrid approaches

Linear precoding is an attractive technique to combat interference in multiple-input multiple-output systems because it reduces cost and power consumption at the receiver. Frequency division duplex systems with linear precoding acquire the channel state information at the receiver side by using supervised algorithms. Such methods make use of pilot symbols periodically provided by the transmitter. Next, this channel state information is sent to the transmitter side through a low-cost feedback channel. Thus, the available channel information allows the transmitter to adapt signals to the channel conditions. Given that pilot symbols do not convey user data, they penalize throughput, spectral efficiency, and transmission energy consumption of the system. In this work, we propose to mitigate the aforementioned limitations by combining both supervised and unsupervised algorithms to acquire the channel state information needed by the transmitter. The key idea consists in introducing a simple criterion to determine whether the channel has suffered a significant variation which requires the transmission of pilot symbols. Otherwise, when small fluctuations happen, an unsupervised method is used to track these channel variations instead. This criterion will be evaluated by considering two types of strategies for the design of the linear precoders: Zero-Forcing and Wiener criteria.     

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.     

Optimal antenna selection based on capacity maximization for MIMO systems in correlated channels

Recent work has shown that multiple-input multiple-output (MIMO) systems with multiple antennas at both the transmitter and receiver are able to achieve great capacity improvement. In such systems, it is desirable to select a subset of the available antennas so as to reduce the number of radio frequency (RF) chains. This paper addresses the problem of antenna selection in correlated channels. We consider a narrowband communication system with M transmit and N receive antennas. We present the criterion for selecting the optimal L/sub t/ out of M transmit and L/sub r/ out of N receive antennas in terms of capacity maximization, assuming that only the long-term channel statistics, instead of the instantaneous channel-state information, are known. Simulations will be used to validate our theoretical analysis and demonstrate that the number of required RF chains can be significantly decreased using our proposed selection strategy, while achieving even better performance than the conventional MIMO system without antenna selection.     

Channel estimation with ISFLA based pilot pattern optimization for MIMO OFDM system

In multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems, the channel state information should be known by the receiver for obtaining transmitted data. Channel estimation algorithms are used to examine the multipath effects of frequency selective Rayleigh fading channels. In this paper, Compressed Sensing (CS) based channel estimation technique is considered for reconstructing the signal with improved spectral efficiency. It requires transmitting the known pilot data to the receiver for estimating channel information. The optimum pilot patterns are selected through reducing the mutual coherence of measurement matrix. In order to maximize the accuracy of sparse channel estimation and to reduce the computational complexity, an optimization algorithm Improved Shuffled Frog Leaping (ISFL) is proposed. When compared with the traditional estimation methods like least squares (LS), and minimal mean square error (MMSE), 4.7% of spectral efficiency is increased with ISFLA based channel estimation. Implementation results show that, by using the proposed algorithm, the bit error rate (BER) and Mean Square Error (MER) performance of the system is increased with 1.5 dB and 2 dB respectively.     

Limited feedback unitary precoding for orthogonal space-time block codes

Orthogonal space-time block codes (OSTBCs) are a class of easily decoded space-time codes that achieve full diversity order in Rayleigh fading channels. OSTBCs exist only for certain numbers of transmit antennas and do not provide array gain like diversity techniques that exploit transmit channel information. When channel state information is available at the transmitter, though, precoding the space-time codeword can be used to support different numbers of transmit antennas and to improve array gain. Unfortunately, transmitters in many wireless systems have no knowledge about current channel conditions. This motivates limited feedback precoding methods such as channel quantization or antenna subset selection. This paper investigates a limited feedback approach that uses a codebook of precoding matrices known a priori to both the transmitter and receiver. The receiver chooses a matrix from the codebook based on current channel conditions and conveys the optimal codebook matrix to the transmitter over an error-free, zero-delay feedback channel. A criterion for choosing the optimal precoding matrix in the codebook is proposed that relates directly to minimizing the probability of symbol error of the precoded system. Low average distortion codebooks are derived based on the optimal codeword selection criterion. The resulting design is found to relate to the famous applied mathematics problem of subspace packing in the Grassmann manifold. Codebooks designed by this method are proven to provide full diversity order in Rayleigh fading channels. Monte Carlo simulations show that limited feedback precoding performs better than antenna subset selection.