一种MIMO系统中的新型资源分配算法

本文提出了一种MIMO(Multi-Input and Multi-Output)系统中的新型自适应调制和功率分配算法,在奇异值分解的基础上通过注水算法进行功率分配,此后根据所分配的功率与信道状态信息来确定自适应调制的门限及相应的调制阶数,并在自适应调制后通过功率修正因子来弥补常见算法中功率不能得到有效利用的问题,仿真结果表明该算法可以得到较高的频谱效率.     

MIMO系统中16-QAM信号的软值输出半正定松弛检测

使用最优化理论与方法研究了MIMO系统中16-QAM信号的软值输出半正定松弛检测问题,推导了16-QAM信号的软值输出半正定松弛检测器软值计算所需附加的约束条件,并提出了一种降维近似处理方法,通过降维近似处理大大降低了软输出检测器的复杂度。仿真结果表明:通过附加约束条件和降维近似处理,软值输出半正定松弛检测器获得了较好的检测性能,降维近似处理降低了软输出SDR检测器的运算复杂度,但会产生0.2～0.4dB的性能损失。     

一种低复杂度软入软出迭代检测方案

在MIMO系统中,以软输入软输出方式为基础的迭代检测方式,性能要明显优于基于硬判决的迭代方案。因此基于软信息传递的迭代检测理论具有广泛的应用。但是,其复杂度较高,特别是应用于MIMO系统时,复杂度的限制尤为明显。球形译码是一种近似最大似然检测的低复杂度方案,在这里,引入一种低复杂度的软入软出（SISO）球形译码迭代方案,并给出球形译码中搜索树的删减简化方案。     

CRC-aided turbo equalization for MIMO frequency selective fading channels

This paper presents a CRC （Cyclic Redundancy Check）-aided turbo equalization approach to reduce the computational complexity. In this approach, CRC code bits are padded to the end of each transmit block, and a cyclic redundancy check is performed after decoding each block at the receiver en.d. If the check sum is zero, which means the receive block is correct, the corresponding LLRs （Log Likelihood Ratios） of this block are set high reliable values, and all the computations corresponding to this block can be cancelled for the subsequent outer iterations. With a lower computational complexity the proposed approach can achieve the same as or even better performance than the conventional non-CRC method.     

FIR channel-shortening equalizers for MIMO ISI channels

Finite-length delay-optimized multi-input multi-output (MIMO) equalizers that optimally shorten the impulse response memory of frequency-selective MIMO channels are derived. The MIMO equalizers are designed to minimize the average energy of the error sequence between the equalized MIMO channel impulse response and an MIMO target impulse response (TIR) with shorter memory. Two criteria for optimizing the MIMO TIR are analyzed and compared. The presented analytical framework encompasses a multitude of previously-studied finite-length equalization techniques     

A recursive link adaptation algorithm for MIMO systems

An algorithm to adjust the coding/modulation (CM) scheme in a multiple-input multiple-output (MIMO) wireless communication system is proposed and analysed. The CM scheme selected for each transmitter is determined by a recursive procedure at the receiver, taking into account estimated signal-to-noise ratio and the properties of available CM schemes. The algorithm performance was tested with different detection algorithms: pseudo-inverse (PINV), V-BLAST and maximum likelihood (ML).     

基于序贯蒙特卡罗算法的多天线快时变信道的盲跟踪

针对通信系统时变信道采用蒙特卡罗算法进行盲信道跟踪,并将该盲跟踪算法用于多天线信道及空时分组编码的情况,在相同的系统条件下与卡尔曼滤波跟踪算法进行了性能比较,并讨论了系统存在载波频偏情况下的跟踪性能。仿真结果表明,序贯蒙特卡罗算法可以对时变信道进行很好的跟踪。     

基于MIMO系统的MDCMA盲均衡算法

基于对线性多输入多输出(MIMO)系统的自适应盲源分离和盲均衡的研究,为了能够有效恢复输入信号,提出了一种在MIMO系统中引入抖动处理技术的修正抖动符号误差恒模算法.仿真结果表明,该算法可以在仅已知输入信号统计量的情况下跟踪信道变化,并且有效克服多个均衡器的输出可能锁定到相同的源信号问题,抑制ISI和MUI,恢复所有发射天线的发送信息.     

An iterative particle filter signal detector for MIMO fast fading channels

For flat fast fading Multiple-Input Multiple-Output （MIMO） channels, this paper presents a sampling based channel estimation and an iterative Particle Filter （PF） signal detection scheme. The channel estimation is comprised of two parts： the adaptive iterative update on the channel distribution mean and a regular update on the ＂adaptability＂ via pilot. In the detection procedure, the PF is employed to produce the optimal decision given the known received signal and the sequence of the channel samples, where an asymptotic optimal importance density is constructed, and in terms of the asymptotic update order, the Parallel Importance Update （PIU） and the Serial Importance Update （SIU） scheme are performed respectively. The simulation results show that for the given fading channel, if an appropriate pilot mode is selected, the proposed scheme is more robust than the conventional Kalman filter based superimposed detection scheme.     

适用于大规模MIMO系统的低复杂度RZF-SOR预编码算法

在大规模多输入多输出(MIMO)系统中,为了降低传统预编码算法的复杂度,在原有正则化迫零(RZF)预编码算法的基础上,提出用超松驰迭代(SOR)法代替矩阵求逆的高复杂度运算,得到一种改进算法RZF-SOR,并应用随机矩阵原理得出其最优相关参数的近似表达式和取值的必要条件.实验仿真表明,提出的RZF-SOR预编码算法与RZF预编码相比有效地降低了一个数量级的复杂度,在很小的迭代次数下达到接近于RZF预编码的误码率性能,并且优于基于Neumann级数预编码算法的误码率性能.     

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...     

Improved smoothed LO reconstruction algorithm for ISI sparse channel estimation

In this paper, the problem of inter symbol interference （ISI） sparse channel estimation in wireless communication with the application of compressed sensing is investigated. However, smoothed L0 norm algorithm （SL0） has ＇notched effect＇ due to the negative iterative gradient direction. Moreover, the property of continuous function in SL0 is not steep enough, which results in inaccurate estimations and low convergence. Afterwards, we propose the Lagrange multipliers as well as Newton method to optimize SL0 algorithm in order to obtain a more rapid and efficient signal reconstruction algorithm, improved smoothed L0 （ISL0）. ISI channel estimation will have a direct effect on the performance of ISI equalizer at the receiver. So, we design a pre-filter model which with no considerable loss of optimality and do analyses of the equalization methods of the sparse multi-path channel. Real-time simulation results clearly show that the ISL0 algorithm can estimate the ISI sparse channel much better in both signal noise ratio （SNR） and compression levels. In the same channel conditions, ISL0 algorithm has been greatly improved when compared with the SL0 algorithm and other compressed-sensing algorithms.     

MIMO系统中的迭代分组MAP检测算法

该文提出了在分组MAP检测器内部进行干扰信息更新和检测信息迭代反馈的检测算法。在MIMO系统基本的分组MAP检测算法基础上,利用先检测分组产生的后验信息替代先验信息提高干扰信号的估计精确度,进一步可以使用迭代反馈的方法在检测器内部进行反馈检测分组的后验信息,从而提高了检测信号的分集度。仿真结果表明在未编码系统中改进的分组检测方法能够显著地提高系统误码率性能,在编码系统中能够加快整个系统的收敛。     

A novel artificial bee colony detection algorithm for massive MIMO system

As a hot‐spot of 5G, the research on detection algorithms for massive multiple input multiple output (MIMO) system is significant but difficult. The traditional MIMO detection algorithms or their improvements are not appropriate for large scaled antennas. In this paper, we propose artificial bee colony (ABC) detection algorithm for massive MIMO system. As one advanced technology of swarm intelligence, ABC algorithm is most efficient for large scaled constrained numerical combinatorial optimization problem. Therefore, we employ it to search the optimum solution vector in the modulation alphabet with linear detection result as initial. Simulation and data analysis prove the correctness and efficiency. Versus the scale of massive MIMO systems from 64 × 64 to 1024 × 1024 with uncoded four‐quadrature‐amplitude‐modulation signals, the proposed ABC detection algorithm obtains bit error rate of 10 ^− 5 at low average received signal‐to‐noise‐ratio of 12 dB with rapid convergence rate, which approximates the optimum bit error rate performance of the maximum likelihood and achieves the theoretical optimum spectral efficiency with low required average received signal‐to‐noise‐ratio of 10 dB in similar increasing regularity, over finite time of low polynomial computational complexity of per symbol, where N_T denotes the transmitting antennas' number. The proposed ABC detection algorithm is efficient for massive MIMO system. Copyright © 2016 John Wiley & Sons, Ltd.     

MIMO雷达系统中的Cyclic-Esprit算法

一些人工信号通常具有特殊的时间特性——循环平稳特性,此时,在MIMO雷达中运用传统的DOA估计算法得到的估计结果精度很差,甚至失效。针对这一情况,文中提出了一种适用于在MIMO雷达中运用的Cyclic-Esprit算法,从理论方面推导证明了算法在MIMO雷达中运用的合理性和有效性。仿真实验表明对于具有循环平稳特性的人工信号的DOA估计,算法取得了非常好的效果。     

Optimal transmit antenna selection using hybrid algorithm for massive MIMO technology

Massive multiple input multiple output (M-MIMO) methods make reference to a useful method for using multipath propagation to communicate and receive multiple data signals at once over a single radio channel. To simultaneously transfer numerous data streams, it makes use of various antennas. The quantity of power used grows as the quantity of antennas rises. As a result, choosing the best transmit antennas, which is a major difficulty in M-MIMO systems, becomes important. In this research, “Hybrid Sea Lion-Whale Algorithm (HS-WA)” is introduced by choosing a best transmit antenna while taking into account several objectives. This method optimizes overall capacity and efficiency. The chosen method combines the “Whale Optimization Algorithm (WOA) and Sea Lion Optimization Algorithm (SLnO)” that determines which antenna should be chosen while also optimizing the antenna quantity. Finally, energy efficiency (EE) and capacity analysis results demonstrate that the provided approach is superior to all other models.     

基于协作MIMO机制的预编码算法

针对在协作机制下多输入多输出系统中用户干扰对系统容量的影响,提出了一种基于多点协作多输入多输出系统的预编码设计算法,所提算法基于系统和速率最大化构建了预编码矩阵目标函数,并给出了借助凸优化理论的预编码矩阵求解方法和实施步骤,最后通过系统的平均速率对所提算法与现有算法的性能进行了仿真对比,并验证了目标函数的收敛性能．仿真结果证明了所提算法的可行性。     

一种多用户MIMO系统干扰对齐优化算法

干扰对齐技术可以获得干扰信道自由度的最佳值,从而有效改善系统的性能。在实际系统中干扰对齐技术通常采用迭代的方法进行预编码矩阵与干扰抑制矩阵的设计,而迭代方法都需要对发送预编码矩阵进行初始化处理。然而,目前大多数已有的研究所采用的初始化处理方法都忽略了干扰的影响。因此,在此基础上提出了一种基于新的初始化方法的优化算法,该方法在初始化预编码矩阵中既考虑了干扰信号也考虑了有用信号。首先,选取均方误差和最小化作为优化目标,然后利用正交三角（QR）分解将信道空间分为有用信号空间与干扰信号空间来进行预编码矩阵的初始化设计,经过反复迭代得到发送预编码矩阵与干扰抑制矩阵的最优解。理论分析和仿真结果表明,所提算法在收敛性、均方误差、和速率等方面都优于其他算法。     

Low-complexity adaptive decision-feedback equalization of MIMO channels

A new adaptive MIMO channel equalizer is proposed based on adaptive generalized decision-feedback equalization and ordered-successive interference cancellation. The proposed equalizer comprises equal-length subequalizers, enabling any adaptive filtering algorithm to be employed for coefficient updates. A recently proposed computationally efficient recursive least squares algorithm based on dichotomous coordinate descents is utilized to solve the normal equations associated with the adaptation of the new equalizer. Convergence of the proposed algorithm is examined analytically and simulations show that the proposed equalizer is superior to the previously proposed adaptive MIMO channel equalizers by providing both enhanced bit error rate performance and reduced computational complexity. Furthermore, the proposed algorithm exhibits stable numerical behavior and can deliver a trade-off between performance and complexity.     

基于遗传算法的毫米波大规模MIMO系统混合预编码

目前混合预编码方案中,大多采取高精度的移相器作为模拟预编码的设计基础,使得系统成本增加。针对这一问题,探讨了有限精度射频前端的混合预编码设计。为了实现更高的频谱利用率,考虑到天线权值的最优组合为一NP（Non-deterministic Polynomial）问题,受机器学习启发,采用遗传算法对阵列中阵元的相位取值进行建模设计模拟预编码。通过信道矩阵与模拟预编码矩阵的乘积引入等效信道矩阵,考虑用户间干扰,以最大信干噪比准则进行数字预编码设计。仿真结果表明,该方案得到的混合预编码矩阵其系统性能可逼近全数字预编码矩阵的性能。