User Selection Method Adopting Cross-Entropy Method for a Downlink Multiuser MIMO System

This letter presents a novel method of user selection in a downlink multi-user multiple input multiple output (MU-MIMO) system employing the precoding procedures of zero forcing or block diagonalization (BD). The proposed technique utilizes the cross-entropy method (CEM) in order to maintain a performance level comparable to that of the full search (FS) method with reasonable complexity. With the CEM, the proposed system can select multiple users at once instead of selecting a single user at each step. From various computer simulations, it has been verified that the proposed method exhibits nearly 98 % of the sum-rate compared to the FS method, which implies that the proposed method far outperforms conventional methods such as semi-orthogonal user selection (SUS) or the capacity-based suboptimal user selection (CBSUS) algorithm. Compared to CBSUS, the proposed technique enhances the sum-rate by approximately 1.1 bps/Hz with about half the complexity when each user is equipped with two receiving antennas. In the case where each user is equipped with a single antenna, the proposed method outperforms the method of SUS by about 0.3 bps/Hz, at the expense of a complexity increase of $O(2M)$ times.     

Antenna and User Subset Selection in Downlink Multiuser Orthogonal Space-Division Multiplexing

Block diagonalization (BD) and successive optimization (SO) are two suboptimal but more practical (compared to dirty paper coding (DPC)) orthogonal linear precoding techniques for the downlink of multiuser MIMO systems. Since the numbers of users supported by BD or SO for a given number of transmit antennas are limited, BD or SO should be combined with scheduling so that a subset of users is selected at a given time slot while meeting the dimensionality requirements of these techniques. On the other hand, receive antenna selection (RAS) is a promising hardware complexity reduction technique. In this paper, we consider user scheduling in conjunction with receive antenna selection. Since exhaustive search is computationally prohibitive, we propose simplified and suboptimal user scheduling algorithms for both BD and SO. For BD, we propose capacity and Frobenius-norm based suboptimal algorithms with the objective of sum rate maximization. Starting from an empty set, each step of proposed algorithms adds the best user from the set of users not selected yet until the desired number of users have been selected. Proposed receive antenna selection works in conjunction with user scheduling to further enhance the sum rate of BD. For SO, a Frobenius-norm based low complexity algorithm is proposed, which maximizes the ratio of the squared Frobenius norm of the equivalent channel (projected to the joint null space of the previously selected users) to the sum of the squared Frobenius norms of the previously selected users’ preprocessed channels. Simulation results demonstrate that the proposed algorithms achieve sum rates close to exhaustive search algorithms with much reduced complexity. We also show that in addition to reduced hardware complexity at the receiver, antenna selection enhances multiuser diversity gain that is achieved with user scheduling.     

Grassmannian precoding MU-MIMO scheme

In this article, a Grassmannian precoding multiuser multiple-input multiple-output （MU-MIMO） scheme for downlink transmission is proposed. The proposed MU-MIMO scheme will perform scheduling and precoding simultaneously at the base station, to obtain both the multiuser diversity gain and the precoding gain, to maximize the system capacity. The precoding method is related to Grassmannian precoding, which extends the point-to-point single-user Grassmannian precoding to point-to-multipoint multiuser Grassmannian precoding. It provides further significant system capacity enhancement than the single user MIMO （SU-MIMO） system and also outperforms the block dia~onalization （BD） algorithm under the same simulation environment.     

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.     

多用户MIMO系统广播信道的连续块对角化预编码算法

针对块对角化(BD)算法无法满足各个用户的需要、串行优化(SO)算法排序复杂、容量较低的问题,提出了一种连续块对角化(SBD)算法.该算法按照各用户的信道条件、服务质量(QoS)需求给用户定义不同的优先级,并按优先级次序进行块对角化,后续用户在对高优先级用户及同优先级用户不干扰的条件下采用块对角化法抵消共信道干扰(CC...     

Low Complexity Iterative-QR (IQR) Precoder Design Based on Structure Blocks for Massive MIMO System

Massive multiple-input multiple-output (MIMO) technology is a promising technique having a high spectral efficiency for future wireless systems. Counterintuitively, the practical issues of transmitted signals are being attenuated by fading, propagation limitations, and implement non-linear precoding are solved by enlarging system dimensions. However, the computational complexity of precoding grows with the system dimensions. The existence block diagonalization (BD) precoding, which completely pre-cancels the multiuser interference is very complicated to implement with the use of a large number of BS antennas, since it considers full multiplexing order. Motivated by the high performance of the BD and generalized for the case when the users have multiple antennas, we propose a structure blocks based on iterative QR decompositions (IQRDs) to compute the precoding scheme. The proposed BLIQR-based precoder designed partitioned the channel matrix into capable square-wise blocks matrix and the IQRDs are applied to the blocks channel matrix. The channel matrix is partitioned such that it can fulfill the multiplexing order for the use in Massive MIMO. The computational complexity of the proposed design is effectively reduced and the sum-rate performance is improved, especially in large number of BS antennas. The performance of the proposed scheme achieves a good trade-off between throughput and computational complexity.     

User selection strategies for multiuser MIMO systems with block diagonalization

Block diagonalization （BD） is an efficient precoding technique that eliminates inter-user interference in downlink multiple-input multiple-output （MIMO） systems. User selection strategies applied to multiuser MIMO systems with BD are investigated in this article. To enhance the capacity of multiuser MIMO systems, an equivalent capacity maximum （ECM） user selection strategy is proposed with low computational complexity. Considering both the factors of channel correlations and channel conditions, the proposed strategy can select a group of users to serve for maximizing the total throughput. Simulation results indicate that, for various channel conditions, proposed ECM strategy gains a better performance compared with traditional user selection strategies, and achieves a near optimal throughput as the exhaustive search.     

MU-MIMO系统下行链路中的自适应用户调度算法

在多用户MIMO系统下行链路中,经典的半正交用户调度算法(SUS)难以控制备选用户的门限参数值,且该算法没有考虑QOS对时延的要求。为此,提出一种自适应用户调度算法(AUS),在其调度过程中根据备选用户数及基站端天线数动态改变门限参数值,同时将用户最大时延限制作为用户选择准则的权重。仿真结果表明,与其他算法比,该算法提高了系统吞吐率,在加权用户选择准则时最大可减少24%的平均时延。     

利用最大信号泄露噪声比设计多用户VBLAST系统下行链路

该文针对多用户MIMO系统提出利用最大信号泄漏信噪比准则设计多用户VBLAST下行链路的方法。相对于以多用户系统中广泛关注的块对角化方法设计多用户VBLAST下行链路,所提方法性能有较大的提高。另外,相对于块对角化方法对天线数目的约束,该文所提方法在不满足块对角化的条件下仍能拥有不错的性能。仿真表明该方法拥有优异的性能。     

Spectral efficiency evaluation of full‐duplex mode of communications based on SLNR approach

Full‐duplex (FD) mode of communication with efficient transmission scheme is a promising approach for 5G wireless systems by improving the spectral efficiency. This can be attained by making use of various precoding approaches. We propose a new co‐channel interference (CCI)‐aware improvement to signal‐to‐leakage‐and‐noise ratio (SLNR) technique and a suppression filter at the receiver to whiten the interference for the downlink channel. As well, for the uplink (UL) communication, we propose a self‐interference (SI)‐aware enhancement to SLNR scheme and designing a precoder using self‐interference plus noise covariance matrix. The total spectral efficiency is obtained from the sum‐rates of both downlink and uplink communication systems. Simulation results verify that the spectral efficiency (SE) of FD using the proposed scheme performs well relative to the half‐duplex system for all Rician factor and for small powers at the base station (BS) and UL communication channel users. Moreover, as the number of users grows, which entails that as the number of receiving antennas greater than the number of antennas at the BS the SLNR scheme still works, nonetheless, zero‐forcing (ZF) and block‐diagonalization (BD) precoding schemes failed. This is due to the fact that designing a precoder based on SLNR scheme supports multiple numbers of antennas at the base station and users compared with ZF and BD by compromising the interference and noise. However, for the cases of ZF and BD approaches failed due to both schemes require the number of transmit antennas at the BS to be larger than the sum of the receiving antennas at all users.     

基于块对角化的格基规约GMD矢量预编码

研究了对多用户多输入多输出下行链路进行块对角化后,使用格基规约算法的几何均值分解矢量预编码的实现方法。根据块对角化思想将多用户多天线信道分解为等价并行子信道,基于等价子信道给出了单个用户的几何均值分解矢量预编码的传输方案,通过使用格基规约算法分别结合连续干扰消除和垂直分层空时编码两种方法,求解矢量预编码中的扰动矢量。仿真表明,提出的方法误码率性能优于块对角化矢量预编码算法2 dB以上,而且能在不降低系统性能的前提下降低计算复杂度。     

Efficient user selection for multi-cell multi-user MIMO systems with limited backhaul

Multi-cell multi-user multiple-input multiple-output (MC-MU-MIMO) is a promising technique to eliminate inter-user interference and inter-cell cochannel interference in wireless telecommunication syste...     

一种改进的多用户下行MIM0系统用户选择算法

为了克服多用户下行MIMO系统采用迫零波束成形算法时基站天线的数目要大于等于所有同时工作的用户接收天线的数目之和的缺点,丈中提出了一种改进的多用户下行MIMO系统用户选择算法。该算法具有较低的算法复杂度,性能优于常规的基于贪婪算法的用户选择方法。     

分布式MIMO系统发送天线选择与预编码联合设计

为了抑制多用户分布式多入多出(MIMO)系统中的同道干扰(CCI),使系统同时服务于更多用户,提出一种发送天线选择与预编码的联合设计方法。该方法立足于分布式MIMO系统基站端天线较多的特点,将下行发送天线选择与信漏噪比(SLNR)预编码相结合,通过为用户选择不同天线,从根本上减少CCI;在为每个用户选择天线时,先以信道子矩阵的迹为依据进行端口选择,再采用逐减的方法选择使SLNR损失值最小的天线,以保证每个用户对其他用户的干扰尽量小,从而达到进一步抑制CCI的目的。复杂度分析和仿真结果表明,该方法在具有较低复杂度同时,其容量性能仍可逼近最优算法;较之单纯的SLNR预编码,在相同的容量性能约束下,其能够有效增加系统同时服务的用户数。     

Performance of Alamouti Scheme with Transmit Antenna Selection for M-ray Signals

In this letter, we present a comprehensive performance analysis of orthogonal space-time block codes (STBCs) with transmit antenna selection under uncorrelated Rayleigh fading channels. Two best transmit antennas that maximize the instantaneous received signal-to-noise (SNR) are selected. Using the well-known moment generating function-based analysis approach, we derive the exact average symbol error rate (SER) for M-ary signals. Furthermore, we provide tight upper bounds on the SER for any number of transmit antennas and receive antennas. The tightness is verified by simulation results. It is shown that the diversity order, with antenna selection, is maintained as that of the full complexity systems     

Low Complexity Antenna Selection Scheme for Multicarrier MIMO Broadcast Communication

A low complexity antenna selection scheme for multicarrier MIMO (Multiple Input Multiple Output) broadcast systems is proposed in this paper. Under special condition of single user in the system or when the number of subcarrier is only one, the system reduces to conventional MIMO-OFDM (Orthogonal Frequency Division Multiplexing) system or MIMO-BC (Broadcast Channel) system respectively. By analysing sub-optimal antenna selection schemes developed earlier for single user MIMO-OFDM systems and single carrier MIMO-BC systems, one can see many similarities which can be extended to multicarrier MIMO broadcast systems. The proposed method exploits these similarities to obtain a low complexity system design with acceptable performance. The performance of the proposed scheme is studied via extensive simulation, and the computational complexity involved is compared to the conventional scheme. A selection gain of approximately 0.5 b/s/Hz is shown to be achievable using only two out of three antennas, and the proposed scheme is able to achieve up to 90% of the gain. This is achieved at a complexity that is significantly lower than the conventional methods, hence the practical implementation of the proposed scheme can be justified.     

Maximum product of effective channel gains: an innovative user selection algorithm for downlink multi‐user multiple input and multiple output

Recently, zero‐forcing beamforming has been widely used for multiple‐input and multiple‐output broadcast channels, because it could provide suboptimal capacity with low complexity. To increase the sum data rate, a good user selection algorithm is attractive. In this paper, a new user selection algorithm named maximum product of effective channel gains is presented. The proposed algorithm is described mathematically, and the lower bound of the sum capacity is demonstrated to be proportional to the product of effective channel gains. Our simulation results show that maximum product of effective channel gains can achieve higher sum rate compared with the classical algorithm, semi‐orthogonal user selection, with the same complexity order, especially when the signal‐to‐noise ratio is high; in addition, the complexity of the proposed algorithm is superior to minimum of the Frobenius norm of the pseudo‐inverse algorithm. Meanwhile, the number of users that can be served simultaneously is equal to the number of transmission antennas, which is the maximum performance that can be achieved.Copyright © 2012 John Wiley & Sons, Ltd.     

Multiuser beamforming based on max SINR for downlink spatial multiplexing MIMO

In this article, a method based on max signal interference noise ratio (SINR) criterion is proposed, to mitigate the interuser interference for downlink multiuser spatial multiplexing multi-input multi-output (MIMO) systems.Unlike the zero forcing (ZF) scheme in which the SNR is decreased when the interference is eliminated completely, max SINR method makes a compromise between noise and interuser interference.When the number of substreams is larger than the difference between the number of base station antennas and the sum of interference mobile station antennas, the ZF is infeasible.An existing coordinated TX-RX block diagonalization (COOR BD) method uses preprocessing at the receiver to cancel the interuser interference.However, it cannot obtain more receive diversity gain because of the preprocessing.Analysis and simulation show that the max SINR scheme has better performance than the ZF method.Moreover, when the ZF is infeasible, the max SINR scheme can obtain more receive diversity gain than COOR BD in the two-user case.     

简明的联合收发端天线选择算法

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 selec-tion algorithm. Using a novel partition of the channel matrix, we drive a concise formula. This formula enables us to augment the chan-nel 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 4nL, where nL is the number of selected antennas. A de-coupled version of the proposed algorithm is also proposed to further improve the efficien-cy of the JTRAS algorithm, with some capacity degradation as a tradeoff. The computational complexity and the perform-ance of the proposed approaches are evalu-ated 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 1/4nL 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.     

多用户分布式MIMO-OFDM系统中天线与子载波分配算法研究

本文针对多用户分布式MIMO-OFDM系统中的资源联合分配问题,提出了一种基于端口选择的天线与子载波分配算法。该算法依据计算复杂度容限设定用户通信静态端口数,以此为每个用户选取信道状况最好的通信端口进行通信,进而通过天线端口与下属用户的相互配合,并行地完成天线与子载波的分配。仿真结果表明,该算法在系统天线数大于用户数的情况下容量性能优于MASA算法,且其端口并行处理机制可以有效提高资源分配效率。