An adaptive partial parallel multistage detection for MIMO systems

The full parallel multistage detection for multiple-input multiple-output systems has less processing delay and better performance than the vertical Bell Laboratories layered space-time detection scheme. However, due to the disadvantage of full parallel interference cancellation, its performance degrades when the received power of the substreams at one receiving antenna is unbalanced and/or when the system is heavily loaded. Therefore, we introduce adaptive partial weighting coefficients into the parallel multistage detection. The weighting coefficients are evaluated using the average decision correct probabilities in the previous stage. The simulation results show that the uncoded error probability of the proposed method is lower than that of the recently proposed full parallel multistage detection scheme with perfect or imperfect channel estimation.     

接近最优检测性能的低复杂度线性并行MIMO检测算法

在高阶正交幅度调制下,现有用于MIMO系统的并行检测算法复杂度极高,且随着天线数增多复杂度快速增加;而低复杂度的非并行检测算法与最优检测算法相比,其误比特率性能仍存在一定差距。针对上述问题,提出了一种接近最优检测性能的低复杂度并行MIMO检测算法,该算法基于信道分组检测的思想,对通过受噪声干扰严重的子信道信号采用遍历所有空间映射点的方式进行检测,对其余信号则采用新的基于lattice reduction的线性并行检测算法进行检测。仿真结果表明该算法在获得近似最优检测性能以及提高分集增益的同时,仍可保持较低的复杂度,且在高阶QAM调制方式下,复杂度降低尤为明显。     

大规模MIMO系统中的一种自适应SIC检测算法

与传统系统相比,大规模多入多出（MIMO）系统能更加有效地提高频谱效率。利用传统的最小均方误差（MMSE）信号检测算法求解大规模MIMO系统,虽然检测结果接近最优,但是矩阵的求逆运算导致计算的复杂度非常高。提出了一种自适应排序干扰消除（SIC）检测算法,在逐次超松弛（SOR）迭代运算的基础上,通过干扰消除降低待检测矩阵的维度。通过仿真分析,得出所提算法的复杂度低于Jacobi、SOR检测算法,且在迭代次数较少的情况下,算法的误码率（BER）性能明显优于SOR检测算法。     

Performance and optimization of multistage partial parallel interference cancellation for wideband CDMA systems in multipath fading channels

In this paper, a closed-form bit error rate (BER) of hard-decision multistage partial parallel interference cancellation (PPIC) having perfect and imperfect channel estimation for complex spreading code-division multiple access (CDMA) over multipath Rayleigh channels was derived. The effects of receiving BER, power ratio of pilot to data channels, multiple-access interference (MAI) and multipath interference, additive white Gaussian noise, and other factors affecting channel estimation error are analyzed. The expression determining the optimal interference cancellation weight at path level for PPIC is first derived. Then, the oscillatory behavior of user-level-optimized PIC and the convergence of perfect channel estimation PIC and path-level-optimized PIC are validated. Results indicate that all factors determining the optimal weight certainly affect the BER performance of PPIC and that the lower BER limit of multistage PPIC depends on the adjustable factors, which include power ratio, observation length, and signal-to-noise ratio, and an unchangeable factor, i.e., number of users. In addition, the variance of MAI for complex spreading sequence is obtained, and the analytical expression can also be employed to predict the performance of multicode CDMA.     

Distributed adaptive algorithms for large dimensional MIMO systems

An algorithm for multi-input multi-output (MIMO) adaptive filtering is introduced that distributes the adaptive computation over a set of linearly connected computational modules. Each module has an input and an output and transmits data to and receives data from its nearest neighbor. A gradient-based algorithm for adapting the parameters in each module to minimize the global mean-squared error is derived using principles of back propagation. The performance surface is explored to understand the characteristics of the adaptive algorithm. The minimum mean-squared error is a many to one function of the parameters; therefore, upper bounds on each parameter are used to prevent excessive parameter drift and ensure stability with fixed step sizes. Guidelines for choosing the LMS algorithm step sizes and initial conditions are developed. Several examples illustrate the performance of the algorithm     

Blind adaptive receiver for uplink multiuser massive MIMO systems

Herein, we consider uplink multiuser massive multiple‐input multiple‐output systems when multiple users transmit information symbols to a base station (BS) by applying simple space‐time block coding (STBC). At the BS receiver, two detection filters for each user are used to detect the STBC information symbols. One of these filters is for odd‐indexed symbols and the other for even‐indexed symbols. Using constrained output variance metric minimization, we first derive a special relation between the closed‐form optimal solutions for the two detection filters. Then, using the derived special relation, we propose a new blind adaptive algorithm for implementing the minimum output variance‐based optimal filters. In the proposed adaptive algorithm, filter weight vectors are updated only in the region satisfying the special relation. Through a theoretical analysis of the convergence speed and a computer simulation, we demonstrate that the proposed scheme exhibits faster convergence speed and lower steady‐state bit error rate than the conventional scheme.     

Multifunctional reconfigurable MEMS integrated antennas for adaptive MIMO systems

Multi-input multi-output systems with associated technologies such as smart antennas and adaptive coding and modulation techniques enhance channel capacity, diversity, and robustness of wireless communications as has been proven by many recent research results both in theory and experiments. This article focuses on the antenna aspect of MIMO systems. In particular, we emphasize the important role of the reconfigurable antenna and its links with space-time coding techniques that can be employed for further exploitation of the theoretical performance of MIMO wireless systems. The advantages of the reconfigurable antenna compared to the traditional smart antenna are discussed. Establishment of reconfigurable antennas requires novel radio frequency microelectromechanical systems technology, which has recently been developed in the authors' group. We briefly introduce this technology with emphasis on its distinct advantages over existing silicon-based MEMS technologies for reconfigurable antennas. A reconfigurable antenna design that can change its operating frequency and radiation/polarization characteristics is described. Finally, we present the experimental and theoretical results from impedance and radiation performance characterization for different antenna configurations.     

自适应MIMO系统中的支持选择功能的四单元天线

天线选择是自适应MIMO系统中实现可重构多天线的一种有效方法.提出了一种支持选择功能的四单元天线.通过在馈电网络中增加PIN二极管,该天线具备选择任意一组天线单元的功能,同时未被选择的天线单元终端加载匹配的集总负载以维持方向图的稳定.测量结果表明:在任意一种天线单元组合下,该天线都可以覆盖UMTS频段并保持较低的互耦;同时天线单元的方向图具有稳定性.     

DC compensated adaptive modulation in MIMO systems

A DC offset compensated variable rate variable power (VRVP) adaptive modulation (AM) MIMO system with perfect channel state information is introduced. By this approach, BER degradation of AM MIMO due to DC offset is removed considerably. This technique provides a good trade-off between BER and average spectral efficiency (ASE) and increases the robustness of the system relative to DC offset.     

CDMA无线通信正交分级式自适应波束接收机

提出了一种用于CDMA无线通信系统的正交分级式空域自适应波束接收机的结构与算法。与其他相关算法相比,采用该算法后,系统误码性能有明显的改进,尤其是在由多径传播信道引起的相关性信号环境下,效果更为明显。系统采用了新颖的正交分级优化方式,只需进行简单的运算,即可决定其正交级的有关系统参数。正交级数的多少可根据信号环境来决定。系统权值系数的优化分别在各正交级中独立进行,避免了传统优化方法的复杂运算过程。     

大规模MIMO系统中块高斯-赛德尔检测算法

最小均方误差(Minimum Mean Square Error,MMSE)检测算法,虽然能在大规模多输入多输出系统中获得接近最优的线性检测性能,但是涉及高维矩阵求逆运算,难以在实际应用中快速有效地实现.提出了块高斯-赛德尔(Block Gauss-Seidel,BGS)低复杂度信号检测算法,将MMSE检测器的滤波矩阵...     

Iterative tree search detection for MIMO wireless systems

This paper presents a reduced-complexity soft-input soft-output detection scheme, called iterative tree search detection, for multiple-input multiple-output wireless communication systems employing turbo processing at the receiver. In this scheme, a reduced search space is selected with the aid of the M-algorithm, and QAM signal constellations with block partitionable labels are used in order to make the detection complexity per bit almost independent of the modulation order, as well as asymptotically linear in the number of transmit antennas. Results from computer simulations are presented which demonstrate the capability of the scheme to approach optimal performance at considerably reduced complexity.     

Optimum consultation for parallel distributed detection systems

Wireless Networks - An optimum consultation scheme for parallel distributed detection system is proposed. Two-way communication links are assumed between a set of local sensors and the fusion...     

基于频谱效率的低复杂度自适应MIMO系统

在一定的误比特率(BER)下,使用自适应MQAM调制可以最大化MIMO系统的频谱效率。通过不同的算法可以得到自适应调制MIMO系统的离散速率频谱效率(DRSE)。为了进一步提高频谱效率,提出了一种基于DRSE,在不同的算法之间进行切换的低复杂度自适应机制。研究了在两种2×2信道下即:独立同分布(i.i.d)的平坦瑞利衰落信道和空间相关的瑞利衰落信道,自适应MIMO系统在正交空时块编码(OSTBC)和空间复用(SM)之间切换的自适应机制。仿真结果表明,通过选择一种最优的调制模式及发射模式的组合方式,此切换算法可以使系统的频谱效率得到有效提高,同时只增加有限的反馈信息,降低了系统复杂度。     

An adaptive modulation algorithm for performance improvement of MIMO ML systems

In this letter, we propose a simplified adaptive modulation algorithm for a multiple input multiple output (MIMO) system with a maximum likelihood (ML) receiver to minimize BER under a fixed data rate. The proposed algorithm has the advantages of good system performance and low computational complexity, when compared to previous algorithms.     

Optimal diversity-multiplexing tradeoff with group detection for MIMO systems

It is well known that multiple-input multiple-output (MIMO) systems provide two types of gains: diversity gains and spatial multiplexing gains. Recently, a tradeoff function of these two gains has been derived for a point-to-point MIMO system when optimal detection is used. In this paper, we extend the previous work to a more general MIMO system, where the transmitted data is coded in groups. Group detection is applied at the receiver to retrieve the data. It consists of a zero-forcing decorrelation that separates the groups, followed by a joint detection for each of the groups. Two receiver structures are considered in this paper; namely, group zero forcing (GZF) and group successive interference cancellation (GSIC). We assess the diversity-multiplexing tradeoff function of each of these receivers over a richly scattered Rayleigh fading channel. Three rate-allocation algorithms will be considered here; namely, equal rate, group-size proportional rate, and optimal-rate allocation. An explicit expression of the system tradeoff will be derived for both receivers with these three rate allocations. The obtained results will first be optimized over all possible group partitions for a given number of groups. Next, the number of groups will be varied to further optimize the system-tradeoff performance. An overall optimum tradeoff for a general MIMO system with group detection will then be obtained. Numerical results will indicate that optimum performance can be approached with very-low-complexity schemes for a wide range of data rates. It will be also demonstrated that group detection bridges the gap between the traditional decorrelator and the optimal receiver tradeoff performances.     

Probabilistic data association for symbol detection in MIMO systems

The application of the probabilistic data association (PDA) algorithm to the symbol detection in narrowband spatial multiplexed multiple input multiple output systems with known channel state information is investigated. The performance of a new proposed complex formulation of PDA algorithm, which matches the full parameters of the complex Gaussian distribution (which are the mean vector, covariance matrix and the pseudo-covariance matrix), is compared with the real vector formulation of a generalised PDA algorithm and a PDA implementation, which employs complex Gaussian approximations with matched mean and covariance only     

分布式MIMO系统中最优检测的简化算法

在V-BLAST结构的分布式MIMO系统中,针对发射天线地域上的分布性所引起的发射符号异步到达接收天线的问题,提出了一种接近最优检测性能简化算法。该算法首先遍历部分码元符号,且每次遍历时都使用分布式排序干扰抵消算法检测剩余符号,然后对得到的符号候选集进行搜索,恢复发送信号。莱斯衰落信道下的计算机仿真表明,该算法对接收端天线数目没有要求,且在获取接近最优检测性能的同时,有效地降低了计算复杂度。     

Near maximum likelihood detection schemes for wireless MIMO systems

In this letter, we propose two near maximum-likelihood detection (MLD) schemes for multiple input-multiple output antenna systems over flat fading channels. The schemes are based on utilizing an initial estimate of the received symbol and improving it by selectively updating various bits within the symbol. Simulation results show that the performance of the proposed schemes can approach that of MLD but with a significant reduction in complexity.     

Clustered linear precoding for downlink network MIMO systems with partial CSI

We propose two novel clustered linear precoding schemes applicable to network multi‐input multi‐output systems using only partial channel state information to enhance the sum‐rate of the system. Using a channel model that decomposes a multi‐input multi‐output channel matrix into transmit and receive steering vectors and assuming that only transmit steering vectors are available at the base transmit stations, we, first, propose a regularized channel inversion precoding scheme to enhance the sum‐rate assuming only single‐antenna users are available in the system. Next, because of the limitation of regularized channel inversion to handle users with multiple receive antennas, a novel block diagonalization method is proposed. We construct the precoding matrices that jointly eliminate inter‐cell interference and maximize the sum‐rate for a given input covariance matrix. Assuming total power constraint and per‐base‐station power constraints, optimal power allocation schemes are further developed to optimize the sum‐rate. We analytically show that the sum‐rate increases linearly with the number of users when only single‐antenna users are present in the system. Numerical results show that at low signal‐to‐noise ratios, the block diagonalization precoding outperforms the regularized channel inversion in terms of the bit error rate; while at high signal‐to‐noise ratios, the regularized channel inversion provides a better performance. Copyright © 2016 John Wiley & Sons, Ltd.