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.     

Reduced-Complexity Time-Domain Equalization for Turbo-MIMO Systems

A reduced-complexity time-domain equalization scheme for wideband turbo-multiple-input multiple-output (turbo-MIMO) systems is presented. This scheme, called iterative trellis search equalization, is based on a modified version of the M-Bahl-Cocke-Jelinek-Raviv (M-BCJR) algorithm, applied to a suitably chosen trellis representation of the wideband MIMO channel process. Exploiting the properties of quadrature amplitude modulation (QAM) signal constellations with block-partitionable labels, this modified M-BCJR algorithm has complexity per bit that is independent of the constellation size, and polynomial in the number of transmit antennas and channel memory. Results from computer simulations show that the new scheme successfully mitigates intersymbol interference even if only a very small fraction of trellis state transitions is considered. It is also demonstrated that asynchronous transmission of the spatially multiplexed symbol streams can result in considerable performance improvement compared to synchronous MIMO systems.     

Soft input soft output Kalman equalizer for MIMO frequency selective fading channels

We consider the Kalman filter for equalization of a multiple-input multiple-output (MIMO), frequency selective, quasi-static fading channel. More specifically, we consider a coded system, where the incoming bit stream is convolutionally encoded, interleaved and then spatially multiplexed across the transmit antennas. Each substream is modulated into M-ary symbols before being transmitted over a frequency selective channel. At the receiver, we propose to use the Kalman filter as a low complexity MIMO equalizer, as opposed to the trellis based maximum a-posteriori (MAP) equalizer whose computational complexity grows exponentially with the channel memory, the number of transmit antennas and the spectral efficiency (bits/s/Hz) of the system. We modify the structure of the Kalman filter and enable it to process the a-priori (soft) information provided by the channel decoder, thereby allowing us to perform iterative (turbo) equalization on the received sequence. The iterative equalizer structure is designed for general M-ary constellations. We also propose a low complexity version of the above algorithm whose performance is comparable to its full complexity counterpart, but which achieves a significant complexity reduction. We demonstrate via simulations that for higher order constellations, when sufficient number of receive antennas are available (e.g. for a 2 transmitter, 3 receiver system, QPSK), the performance of the proposed algorithms after 4 iterations is within 1.5 dB of the non-iterative MAP algorithm with close to an order of magnitude complexity reduction. By objectively quantifying the complexity of all the considered algorithms we show that the complexity reduction for the proposed schemes becomes increasingly significant for practical systems with moderate to large constellation sizes and a large number of transmit antennas     

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.     

Spatial multiplexing with transmit antenna and constellation selection for correlated MIMO fading channels

We consider spatial multiplexing systems in correlated multiple-input multiple-output (MIMO) fading channels with equal power allocated to each transmit antenna. Under this constraint, the number and subset of transmit antennas together with the transmit symbol constellations are determined assuming knowledge of the channel correlation matrices. We first consider a fixed data rate system and vary the number of transmit antennas and constellation such that the minimum margin in the signal-to-noise ratio (SNR) is maximized for linear and Vertical Bell Laboratories Layered Space-Time (V-BLAST) receivers. We also derive transmit antenna and constellation selection criteria for a successive interference cancellation receiver (SCR) with a fixed detection order and a variable number of bits transmitted on each substream. Compared with a system using all available antennas, performance results show significant gains using a subset of transmit antennas, even for independent fading channels. Finally, we select a subset of transmit antennas to maximize data rate given a minimum SNR margin. A lower bound on the maximum outage data rate is derived. The maximum outage data rate of the SCR receiver is seen to be close to the outage channel capacity.     

Sum Capacity of Multiuser MIMO Broadcast Channels with Block Diagonalization

The sum capacity of a Gaussian broadcast MIMO channel can be achieved with dirty paper coding (DPC). However, algorithms that approach the DPC sum capacity do not appear viable in the forseeable future, which motivates lower complexity interference suppression techniques. Block diagonalization (BD) is a linear preceding technique for downlink multiuser MIMO systems. With perfect channel knowledge at the transmitter, BD can eliminate other users' interference at each receiver. In this paper, we study the sum capacity of BD with and without receive antenna selection. We analytically compare BD without receive antenna selection to DPC for a set of given channels. It is shown that (1) if the user channels are orthogonal to each other, then BD achieves the same sum capacity as DPC; (2) if the user channels lie in the same subspace, then the gain of DPC over BD can be upper bounded by the minimum of the number of transmit and receive antennas. These observations also hold for BD with receive antenna selection. Further, we study the ergodic sum capacity of BD with and without receive antenna selection in a Rayleigh fading channel. Simulations show that BD can achieve a significant part of the total throughput of DPC. An upper bound on the ergodic sum capacity gain of DPC over BD is proposed for easy estimation of the gap between the sum capacity of DPC and BD without receive antenna selection.     

Effective capacity of receive antenna selection MIMO–OSTBC systems in co-channel interference

In this paper, delay constrained performance of a multiple-input multiple-output (MIMO) communication system in a dense environment with co-channel interference is investigated. We apply orthogonal space-time block coding (OSTBC) at the transmitter, and for alleviating the high complexity and cost of the MIMO system, receive antenna selection (RAS) scheme is employed in the downlink. Here, for simple and cheap mobile handsets, one antenna is chosen at the receiver in each utilization of the channel. Under these assumptions, a maximum constant arrival rate with the delay quality-of-service guarantee in a wireless channel is extracted. We obtain a closed-form solution for the effective capacity of the MIMO–OSTBC channel with the RAS scheme in a quasi-static Rayleigh fading conditions and co-channel interference. After all, the numerical simulations are provided and verified the theoretical results.     

Improved spectral efficiency of SM-OFDM using a set of rotated constellations

Spatial Modulation (SM) is a technique that targets to achieve a compromise between the two conflicting objectives in multiple-input multiple-output (MIMO) networks, namely the simultaneous enhancements of data reliability and data rate, by adjusting the index of the operational transmit antenna in the transmitted information bits. Orthogonal frequency division multiplexing (OFDM) has become a widely accepted technique to combat inter-symbol interference (ISI) present in frequency selective channels, such as the ones conveying very high data rates. In this paper, a new SM-OFDM-based scheme is proposed, which adds another element of information in the transmitted SM-data block consisting of a chosen constellation among the available rotated set. To attain this, an additional index is used to select the specific constellation. At the receiver, a set of detectors is proposed to jointly estimate the transmitted symbol, as well as the used constellation and the active transmit antenna indices. The comparison of the performance of this new scheme against the conventional SM-OFDM shows an increased spectral efficiency at the price of a slight degradation in bit error rate. The proposed scheme permits a trade-off between the quality of the communication and the achieved spectral efficiency.     

Robust linear MIMO receivers: a minimum error-rate approach

This paper looks at the linear reception of spatially multiplexed signals across MIMO channels. We address the problem of robustness in the presence of detrimental effects such as correlation and Ricean components. We consider the error-rate performance of MIMO linear filters as these can be used in purely linear receivers or as part of each stage in successive interference canceling (SIC) receivers. We know from multiuser detection theory that minimum error-rate (MER) linear receivers significantly outperform minimum mean-square error (MMSE) receivers when correlation is high; however, no direct method exist to design the MER receiver simply. We derive a scheme allowing a closed-form approximate solution to this problem. The solution is a good approximation to the true MER receiver upon fulfillment of a certain, easily checkable, channel-related condition. The algorithms are derived first for the two-input many-output case. A generalized scheme is provided for the case of arbitrary number of inputs and outputs. The performance gain compared with that MMSE is significant and evaluated for various correlated and Ricean channels and transmit power allocation strategies.     

线性离散码系统中基于近似容量分析的发送天线选择算法

为了降低应用线性离散码(LDC)的多输入多输出系统中发送天线选择算法的复杂度,该文利用LDC的线性变换矩阵的酉矩阵参数化性质,推导出了一种考虑LDC矩阵平均影响的近似容量表达式。近似容量表达式不涉及时间扩展的高阶等效信道矩阵的运算,从而基于近似容量的发送天线选择算法可以有效地降低运算复杂度。该文从近似容量出发,给出了最大化近似容量的发送天线选择算法和基于矩阵消元的天线选择算法。近似容量表达式为基于垂直空时分层码(V-BLAST)提出的低复杂度天线选择算法在LDC系统中的直接应用提供了理论支持。仿真结果表明,所提方案具有与最优天线选择算法相近的性能,但具有更低的计算复杂度。基于矩阵消元的天线选择算法与在V-BLAST系统中提出的基于范数和相关性的天线选择算法相比,可以获得更好的分集增益,因而具有更好的误码率性能。     

Simulation results for an interference-limited multiple-inputmultiple-output cellular system

We describe a simulation study of a cellular system using multiple-input multiple-output (MIMO) antenna techniques along with adaptive modulation and aggressive frequency reuse. We show for the case of 3 transmit and 3 receive antennas, how much MIMO systems outperform systems with receive-diversity-only when noise dominates. When co-channel interference from surrounding cells dominates, the differences shrink, as do the absolute numbers. We quantify these reductions for the specific cases studied, and discuss further areas of research     

MIMO Systems with Transmit Antenna Selection and Power Allocation over Correlated Channels

In this paper, we present a comprehensive performance analysis of multiple-input multiple-output (MIMO) systems with transmit antenna selection (TAS) and stochastic power allocation (SPA) for the spatially correlated fading channels. Two best transmit antennas that maximize the instantaneous received signal-to-noise (SNR) are selected to transmit the Alamouti scheme and maximal-ratio combining (MRC) is applied at the receiver. With correlation matrices available to the transmitter, SPA is applied on these selected antennas. Two different methods are given to derive the explicit upper bounds on the bit-error rate (BER) performance. Finally we present numerical results to verify our analysis. It is shown that the TAS/SPA scheme can achieve high performance in spatially correlated channels.     

Energy efficiency of massive MIMO wireless communication systems with antenna selection

Massive multiple-input multiple-output (MIMO) requires a large number (tens or hundreds) of base station antennas serving for much smaller number of terminals, with large gains in energy efficiency and spectral efficiency compared with traditional MIMO technology. Large scale antennas mean large scale radio frequency (RF) chains. Considering the plenty of power consumption and high cost of RF chains, antenna selection is necessary for Massive MIMO wireless communication systems in both transmitting end and receiving end. An energy efficient antenna selection algorithm based on convex optimization was proposed for Massive MIMO wireless communication systems. On the condition that the channel capacity of the cell is larger than a certain threshold, the number of transmit antenna, the subset of transmit antenna and servable mobile terminals (MTs) were jointly optimized to maximize energy efficiency. The joint optimization problem was proved in detail. The proposed algorithm is verified by analysis and numerical simulations. Good performance gain of energy efficiency is obtained comparing with no antenna selection.     

Low-complexity diversity combining algorithms and circuitarchitectures for co-channel interference cancellation andfrequency-selective fading mitigation

In a high capacity personal communication system (PCS), for a given bandwidth, co-channel interference (CCI) limits the system capacity. Low-complexity diversity combining algorithms and circuit architectures for co-channel interference cancellation and frequency-selective fading mitigation, which do not require training sequences, are introduced. Results obtained from computer simulation of hardware show that two-antenna diversity combining gives wireless communication systems a signal to interference ratio improvement of at least 3 dB over conventional two-antenna selection diversity. The technique is also effective in mitigating frequency-selective fading without using conventional equalization-an average irreducible word error rate (WER) of 2.4% is obtained in computer simulation of hardware for radio channels with normalized delay spread of 0.3. In contrast, for the same WER, selection diversity and single antenna without diversity can sustain normalized delay spread up to about 0.16 and 0.06 respectively     

Dynamics of spatial correlation and implications on MIMO systems

The use of multiple antennas has found various applications in the area of wireless communications. One such application has recently become very popular and is referred to as the multiple-input multiple-output (MIMO) antenna system. The main idea behind MIMO is to establish independent parallel channels between multiple transmit and receive antennas. Each channel uses the same frequency, and the transmissions occur simultaneously. In such a configuration, the amount of data transmitted increases linearly with the number of parallel channels, which is what makes MIMO so popular in the wireless world. The enormous capacity offered by MIMO systems is not realizable when the parallel channels are highly correlated. The goal of this article is to highlight the correlation concept and its impact on MIMO systems. Although correlation can be defined in many dimensions, here we focus on spatial correlation, and specifically consider antenna correlations in mobile units. We provide an overview of spatial correlation and present its underlying parameters in detail. Special attention is given to mutual coupling since it has signal decorrelation and antenna gain reduction effects. We then present how correlation in a MIMO system affects the amount of data that can be transmitted (MIMO capacity) and briefly review how power should be distributed with the knowledge of correlation. Analyses indicate that in real propagation environments, the high capacity gain of MIMO systems can be realized with improved antenna selection algorithms and power allocation strategies.     

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     

Robust Transmit Antenna Selection with Phase Feedback Over Correlated Fading Channels

A new transmit antenna selection (TAS) scheme with phase feedback for multiple-input multiple-output systems is proposed in this paper. This scheme allows two or more transmit antennas to simultaneously use one radio frequency chain. By grouping the transmit antennas according to their similarities in instantaneous channel coefficients into two subsets and treating each subset as a single antenna, both hardware complexity reduction and antenna array gain can be achieved. Compared with the transmit antenna selection combined with space-time block code (TAS/STBC) scheme, the proposed TAS scheme provides excellent robustness, in terms of symbol error rate performance, against spatially correlated fading channels. Moreover, the proposed TAS scheme need not use STBC encoder and decoder which used in the TAS/STBC schemes. Therefore, the proposed TAS scheme is simpler than the TAS/STBC schemes in practical hardware implementation.     

一种移动终端多天线方向图重构快速选择算法与基于滑动时间窗的加速实现

 多输入多输出(MIMO)系统中,天线选择技术可以在降低复杂度的同时,有效地提高系统的性能.但对于天线安装空间受限的小型终端,天线的数目将受到很大限制,本文结合方向图可重构技术,考虑基于线性接收机的空间复用系统,通过在已选择的发射天线上采用等功率分配等增益传输以减少反馈信息量.在此条件下,推导出空间相关衰落信道下自适应发射天线选择的统计容量公式下限,然后,在此基础上提出基于方向图重构的发射天线快速选择方法以最大化该容量值.此外,在实现中提出了一种基于滑动时间窗的梯度更新估计模型,缩短了算法所需时间.     

Joint estimation of the channel and I/Q imbalance for two-way relay networks

In modern day communication systems, the massive MIMO architecture plays a pivotal role in enhancing the spatial multiplexing gain, but vice versa the system energy efficiency is compromised. Consequently, resource allocation in-terms of antenna selection becomes inevitable to increase energy efficiency without having any obvious effect or compromising the system spectral efficiency. Optimal antenna selection can be performed using exhaustive search. However, for a massive MIMO architecture, exhaustive search is not a feasible option due to the exponential growth in computational complexity with an increase in the number of antennas. We have proposed a computationally efficient and optimum algorithm based on the probability distribution learning for transmit antenna selection. An estimation of the distribution algorithm is a learning algorithm which learns from the probability distribution of best possible solutions. The proposed solution is computationally efficient and can obtain an optimum solution for the real time antenna selection problem. Since precoding and beamforming are also considered essential techniques to combat path loss incurred due to high frequency communications, so after antenna selection, successive interference cancellation algorithm is adopted for precoding with selected antennas. Simulation results verify that the proposed joint antenna selection and precoding solution is computationally efficient and near optimal in terms of spectral efficiency with respect to exhaustive search scheme. Furthermore, the energy efficiency of the system is also optimized by the proposed algorithm, resulting in performance enhancement of massive MIMO systems.

     

MIMO空间复用系统的最小BER比特分配

该文基于最小误比特率(BER)准则,提出了多输入多输出(MIMO)空间复用系统的贪婪比特分配算法和基于二分法的比特分配算法。在总比特速率和每个发射天线分配相等功率的约束条件下,通过比特分配优化每个发射天线的调制方式,改善了系统的BER性能。仿真结果表明,与传统的MIMO系统相比,比特分配的MIMO系统可获得显著的信噪比(SNR)增益;与功率分配相比,比特分配在性能损失很小的情况下减少了每个发射天线的功率放大器的动态范围。