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.     

大规模MIMO相关信道下的联合天线分组和天线选择

在大规模多输入多输出系统中,针对密集部署的大型天线阵列之间的强相关性会抑制天线选择增益效果的问题。在系统下行链路场景下建立空间相关信道模型,提出了基于天线分组的天线选择算法。根据瞬时信道相关矩阵将天线阵列划分为若干组,保证各组内天线之间相关性较强。在完成天线分组的基础上,基于信道矩阵列范数准则在各组发射天线与接收天线之间构成的子信道矩阵中选择天线,进而构造有效发射天线与接收天线之间的信道矩阵。仿真分析了所提天线选择算法对系统遍历和速率的影响,结果表明,在基站天线数为32、接收天线数为2、选择天线数为2、天线相关因子为0.9的假设下,当信噪比为10 dB时,与基于相邻天线分组的天线选择算法相比,所提算法使系统和速率约提高了27.5%,且所提算法若要与最优天线选择算法达到相同的和速率,仅需将其信噪比提升1～2 dB即可。     

大规模MIMO系统多用户PSK调制方案的优化

针对超可靠低时延通信短包传输特征,在大规模多输入多输出( Multiple-Input Multiple-Output,MIMO)上行链路系统中,利用较低导频开销来设计相移键控( Phase Shift Keying,PSK)调制方案,并对该方案进行优化兼顾无线链路传输的可靠性.首先,在接收端构建基于最小欧式距离的非相...     

面向5G的大规模MIMO天线的波束规划及天线选型探讨

大规模MIMO天线技术作为5G技术的关键,在解决超高容量和多用户连接的问题上极具优势。天线的实际增益效果与多波束的管理和天线的选型紧密相关。基于此,本文先行阐述了大规模MIMO天线的波束形成技术,提出了不同场景下的多套波束规划方案,并进一步地对不同覆盖场景给出天线选型建议,为5G的网络设计与建设提供切实可行的参考依据。     

一种改进的大规模MIMO发射天线选择算法

为了降低天线选择算法在大规模多输入多输出（Multiple-Input Multiple-Output,MIMO）系统下的误码率和复杂度,以用户端接收的总功率为优化目标,提出一种最大化所有用户接收总功率的天线选择算法。该算法将优化目标函数转化为凸函数,并利用凸优化方法求得其有效解。仿真结果表明,所提天线选择算法与传统的最大和容量算法相比,具有较好的系统误码率性能,且运算复杂度低,但系统容量有所降低。     

Novel transmit antenna selection strategy for massive MIMO downlink channel

In this paper, we deal with the problem of acquiring the channel state information (CSI) at the transmitter in large-scale multiple input multiple output (MIMO) systems, so-called massive MIMO systems. Clearly, obtaining CSI plays a central role to provide high system performance. Even though, in frequency-division duplexed systems, acquiring this information requires a prohibitive amount of feedback, since it increases with the number of transmit antenna. In this work, we design an efficient transmit antenna selection strategy aware of the amount of required CSI for a point-to-multipoint transmission in massive MIMO systems. The proposed strategy provides high sum-rate with limited CSI feedback and limited computational complexity. Innovatively, the antenna selection in our strategy is performed in a decentralized fashion successively at the receiving users. Two schemes are proposed in this work to perform the antenna selection at each user. Next, taking into consideration that the large-scale MIMO transmitter suffers from imperfect knowledge of CSI, we design a new performance criterion. Computer simulations validate that, when the CSI is perfectly known, the proposed strategy is able to achieve high performance in terms of system sum-rate while a significant reduction in both CSI feedback overhead and computational complexity is observed. Moreover, assuming imperfect CSI, the new proposed criterion achieves higher performance when the estimation accuracy is low and at high SNR regime.     

一种5G手机的紧凑型16单元多频MIMO天线

提出一种应用于5G智能手机中结构紧凑的16单元多频段多输入多输出(MIMO)天线阵列。该多天线系统由8个紧凑天线阵列对组成,为了预留2G/3G/4G天线的布局空间,这8个天线阵列印刷在智能手机的两侧边上。每个天线阵列对由2个紧凑的间隙耦合环路天线组成,分别布置在系统板的上、下两侧;其中上侧天线工作在LTE band 46(5 150~5 925 MHz),下侧天线覆盖LTE band 42/43(3 400~3 800 MHz)。测试结果表明该天线阵列具有良好的阻抗匹配和隔离性能。同时还对MIMO一些包络相关系数进行了研究分析。最后研究了人手和头对整个天线性能的影响,仿真结果表明,在日常各种使用情况下,该天线阵列也具有良好的辐射特性。     

大规模MIMO系统中收发联合阈值天线选择算法

在大规模多输入多输出(massive MIMO)系统中使用天线选择算法可提高能效和系统吞吐量,然而适用于传统MIMO系统的天线选择算法具有高复杂度,很难用于massive MIMO系统。为优化天线选择算法,以算法复杂度和系统容量为优化目标,提出了收发联合阈值天线选择算法。该算法在发射端使用最大范数双向天线选择算法进行天线选择,在接收端使用分组maxvol算法并通过仿真实验结果的预设阈值进行天线选择。仿真实验表明,收发联合阈值天线选择算法在降低复杂度的同时可以提高系统容量,与递增天线选择算法相比,系统容量最多可提高52.2 bit/s/Hz。提出的天线选择算法可以满足不同天线相关度和信噪比的传输环境。     

Energy-efficiency based downlink multi-user hybrid beamforming for millimeter wave massive MIMO system

The fifth generation mobile communication(5G) systems can provide Gbit/s data rates from massive multiple-input multiple-output(MIMO) combined with the emerging use of millimeter wavelengths in small heterogeneous cells. This paper develops an energy-efficiency based multi-user hybrid beamforming for downlink millimeter wave(mm Wave) massive MIMO systems. To make better use of directivity gains of the analog beamforming and flexible baseband processing of the digital beamforming, this paper proposes the analog beamforming to select the optimal beam which can maximize the power of the objective user and minimize the interference to all other users. In addition, the digital beamforming maximizes the energy efficiency of the objective user with zero-gradient-based approach. Simulation results show the proposed algorithm provide better bit error rate(BER) performance compared with the traditional hybrid beamforming and obviously improved the sum rate with the increase in the number of users. It is proved that multi-user MIMO(MU-MIMO) can be a perfect candidate for mm Wave massive MIMO communication system. Furthermore, the analog beamforming can mitigate the inter-user interference more effectively with the selection of the optimal beam and the digital beamforming can greatly improve the system performance through flexible baseband processing.     

基于联合用户分组及天线选择的大规模MIMO波束成形

大规模MIMO系统中,当小区用户数与基站天线数较大时,各用户的信道条件不尽相同,提出一种适用于大规模MIMO下行链路的基于联合用户分组及天线选择的迫零波束成形算法。将用户分成两组,选择信道条件较优的一组用户来接收信号,并为每一个发送数据流选择最优的基站天线组合进行通信,以较小的性能损失,换取大规模MIMO 射频电路的成本与功耗的大幅度降低。仿真结果证明,该算法能够较好地实现系统性能与硬件复杂度的折中。     

5G通信与massive MIMO天线技术研究

5G通信相对4G优势是全方位的,特别是毫米波、小基站、massive MIMO、全双工、波束成形等5大技术,应用领域宽广如物联网、车联网、VR等,是面向2020年以后的通信需求的新一代通信系统。而大规模天线是未来天线的发展趋势,5G是无线关键技术之一,是5G通信的高速公路,但利弊共存,且其测试也具有挑战性。文章对5G通信与massive MIMO天线技术进行了研究。     

Experimental evaluation of smart antenna system performance forwireless communications

In wireless communications, smart antenna systems (or antenna arrays) can be used to suppress multipath fading with antenna diversity and to increase the system capacity by supporting multiple co-channel users in reception and transmission. This paper presents experimental results of diversity gain, interference cancellation, and mitigation of multipath fading obtained by using a smart antenna system in typical wireless scenarios. Also given are experimental results for the signal-to-interference ratio (SIR) of two moving users, comparing different beamforming algorithms in typical wireless scenarios. All of the experiments were performed using the 900-MHz smart antenna testbed at The University of Texas at Austin     

A projected fast ISTA algorithm for joint beam forming and antenna selection in massive MIMO

Wireless Networks - The joint beam-forming and antenna selection problem encountered in modern multi-user massive multiple input multiple output (MIMO) communication systems is solved using the...     

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.     

智能天线系统中上行多用户相干信号的分离与DOA估计方法研究

本文研究了平主道中的窨特征估计问题。提出了一种工于循环累量的多用户空间牲针该算法用于智能天线中的ＳＤＭＡ实现。该算法构造了循环累量域四,通过对空间特征循环矩阵的特征分解可以得到用户信号的空间特征估计。并以此为基础,设计了用于上行多波束成形的窨滤波器组实现了上行多用户信号的分离,利用空间滤波器的空间频率响应确定共信道多用户信号的ＤＯＡ《     

一种适用于下行多用户MIMO信道的预处理方法

在研究了多用户MIMO下行信道矩阵的基础上,本文提出了一种基于信道矩阵奇异值分解的多用户预处理方法。该方法将预编码矩阵分解为一些特殊矩阵的加权和。利用这种分解方法,本文研究了信道反转(CI)方法和规则化反转(RCI)方法,结果显示这两种方法均是本文提出的方法的特殊解。在发射功率约束条件下,本文给出了基于最大平均信道容量准则的迭代的参数优化方法。计算机仿真结果显示,本文提出的方法具备了较好的性能:相对于CI和RCI算法,有效提升了系统的平均信道容量和中断容量并且能够更好的处理远近效应问题。     

PN code acquisition using smart antenna for spread-spectrum wireless communications. I

The smart antenna (a blind adaptive antenna array) has brought much attention to its ability to improve the future code-division multiple-access (CDMA) wireless communications systems. However, Adachi et al. (1998), employed only one out of M elements that are in a smart antenna array during the pseudonoise (PN) code acquisition process due to the difficulty in obtaining the weight coefficients of the smart antenna and PN code acquisition jointly and adaptively. Yet, as the PN code is acquired, all M elements are used by Adachi et al. to improve the signal-to-noise ratio (SNR) at a reverse link. We propose an efficient PN code acquisition scheme where all elements are employed during PN code acquisition. Also, we show that by using all elements, the PN code acquisition time can be shortened by at least 40% for a given signal-to-noise ratio and M=5, compared to the single element case. Furthermore, the power of a random access user signal in the reverse link can be lowered at least 3 dB. The additional computational load and complexity to use the proposed PN code acquisition are insignificant.     

Sustainable simultaneous communications in ad-hoc networks using smart antenna systems

This article proposes an analytical model for evaluating the number of simultaneous communications that can be sustained by an ad-hoc network in which the nodes are equipped with fully adaptive smart antennas. The presented mathematical framework adopts realistic models for the antenna radiation pattern and the channel behavior, and is able to take into account the network topology and the characteristics of the medium access control (MAC) protocol in the spatial domain. The model is employed to investigate the impact of the spatial channel model and of the angular spread on network performance. Additionally, this article examines the influence of the transmission policy of the control and data packets of the MAC layer on the number of simultaneous communications.     

Miniaturized four port MIMO antenna for automotive communications

Analog Integrated Circuits and Signal Processing - This paper presents the design, fabrication and testing of a novel circular slot antenna with an arc-shaped feed line for industrial scientific...     

Low complexity detection algorithm based on optimized Neumann series for massive MIMO system

An optimized Neumann series ( NS ) approximation isdescribed based on Frobenius matrix decomposition, this method aims to reduce the high complexity, which caused by the large matrix inversion of detection algorithm in the massive multiple input multiple output (MIMO) system. The large matrix in the inversion is decomposed into the sum of the hollow matrix and a Frobenius matrix, and the Frobenius matrix has the diagonal elements and the first column of the large matrix. In order to ensure the detection performance approach to minimum mean square error (MMSE) algorithm, the first three terms of the series approximation are needed, which results in high complexity as O(K³), where K is the number of users. This paper further optimize the third term of the series approximation to reduce the computational complexity from O(K³) to O(K²). The computational complexity analysis and simulation results show that the performance of proposed algorithm can approach to MMSE algorithm with low complexity O(K²).