Energy-efficient hybrid beamforming for millimeter-wave-based massive multiple-input multiple-output system

The advanced wireless communication system requires abridged energy consumption, enhanced data rate, and good signal coverage. The massive MIMO technology for 5G systems has been developed to accommodate several users simultaneously with superior throughput. The claim for high data rate wireless communication services is expanding quickly as time goes. Thus, the key difficulty is that as the number of users grows, the number of phase shifters grows as well, causing the system to consume more power; as a result, the system's energy efficiency decreases. Hybrid beamforming has recently emerged as an attractive technique for millimeter-wave (mmWave) communication systems. The analog beamformer in the RF domain and digital beamformer in the baseband are coupled through a minimal number of RF chains in hybrid beamforming architecture. Hybrid beamforming utilizes fewer RF (radio frequency) chains than the total number of antennas to have a lower energy consumption design. The hybrid beamforming for a mmWave-based massive MIMO system through different phase shifter selection mechanisms is proposed to achieve the highest energy efficiency for mmWave communications systems. The fully connected with phase shifter selection, sub-connected with phase shifter selection (SPSS), and fully connected and sub-connected with phase shifter selection with halved and doubled switches are considered for this research. The simulation results show the SPSS with halved switch outperforms on energy efficiency.     

基于MIMO系统的天线选择

多天线MIMO（Multiple Input Multiple Output）系统利用多个收、发天线有效地改善无线通信系统性能，提高系统容量，增强系统可靠性。然而，由于使用多天线同时收发，这要求发射机和接收机使用与天线一样多的射频链路，增加了系统成本和复杂度。使用天线选择技术可以降低系统成本和复杂度，同时保留MIMO系统的优越性能。文中首先介绍了MIMO系统的实现方式，然后讨论天线选择的方法及性能，最后提出天线选择技术还存在的问题，并得出相关的结论。     

太赫兹超大规模3D MIMO系统中的波束斜视补偿技术

太赫兹通信技术凭借超大带宽的优势成为未来6G的关键技术之一。超大规模天线技术可以提供巨大的空间分集,提升频谱效率,同样在6G无线通信系统中起到关键作用。在基于移相器的大规模MIMO（multiple-input multiple-output）混合预编码中,由于太赫兹频段的超大带宽,不同频率的子载波信道具有不同的等效空间方向,发射端波束形成时,将带来严重的波束斜视问题。与此同时,随着天线规模的不断增长,超大规模天线技术的应用更进一步扩大了波束斜视造成的影响。针对超大规模天线阵列带来的波束斜视现象放大问题,本文利用3D MIMO平面天线阵列来改善这一状况。为进一步改善太赫兹频段超大带宽引起的波束斜视,在3D大规模MIMO系统的基础上,本文提出了基于两层移相器结构的混合预编码方案,利用第二层移相器,对不同频率的子载波进行补偿。实验结果表明,本方法可以有效地弥补波束斜视带来的阵列增益损失,实现接近最优的系统性能。      

Receiver Algorithms for Multi-stream Data Transmission in WLAN 802.11n Networks

Multiple Input Multiple Output (MIMO) systems employ multiple antennas to provide high spectral efficiency and wireless link reliability thanks to multipath diversity and space multiplexing. This technology is now being implemented into wireless standards such as 802.11n, as well as the 4th generation cellular networks. In this paper we present results of an extensive simulation research in which we compare three receiver models for MIMO WLAN 802.11n system. We investigate maximum-likelihood, zero-forcing and Vertical Bell Laboratories Layered Space Time receivers. Performance of these receivers for a range of 802.11n environments, i.e. for several channel models and different number of transmitter and receiver antennas is evaluated. The results of the comparison highlight the benefits of MIMO technology and show to what extent it is possible to improve the MIMO 802.11n system performance increasing the receiver complexity.     

Beam Tracking Particle Filter for Hybrid Beamforming and Precoding Systems

Because millimeter wave (mmWave) systems can span notably wide spectral bands, mmWave systems are expected to dominate fifth-generation (5G) communication systems. Due to the short wave-length of mmWave radiation, multiple-input multiple-output (MIMO) systems can use massive antennas and precoding technology to overcome signal attenuation in mmWave channels. However, the cost and power consumption of radio frequency (RF) chains would increase substantially with the number of antennas. Hence, hybrid beamforming was proposed to reduce the number of RF chains in massive MIMO systems. Hybrid beamforming involves RF beamforming matrix construction and baseband precoding matrix derivation. This study focused on the design and implementation of an algorithm for the RF beamforming matrix construction for mobile environments. Accordingly, this study presents a mixture particle filter that exploits the temporal continuity of beam clusters in a mobile mmWave channel to reduce the computational complexity of RF beamforming matrix construction. Moreover, this beam-tracking particle filter is based on parallel processing architecture to support the tracking of multiple beam clusters in the mmWave channel. Finally, the beam-tracking particle filter was implemented on a field-programmable gate array platform and was verified in a hybrid beamforming system for mmWave MIMO systems. The particle filter processor achieved a maximal throughput of 9.198k matrices/s with a clock rate of 192 MHz, which could support a speed of up to 88.5 km/h for mobile users.

     

RF beamforming for MIMO cognitive user

Using Multiple Input Multiple Output (MIMO) architecture in cognitive radio (CR) secondary users improves the system performance in terms of interference cancellation and data rate enhancement but at the expense of adding complexity and cost. A solution to reduce this complexity is employing radio frequency (RF) beamforming networks at the transmitter/receiver front-ends. In this paper, we consider a MIMO secondary user equipped with such RF beamforming network. Moreover, we find the transmit/receive optimum RF beamforming network for a MIMO spatial multiplexing system. We evaluate the performance of the optimally designed RF beamforming technique over a Rician channel via computer simulations. The simulation results are assessed for different RF beamforming structures and the number of primary transmitters which cause interference on the secondary receiver.     

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.     

MIMO系统中天线选择的关键技术及其应用

多天线MIMO系统利用多个收、发天线有效地改善无线通信系统性能,提高系统容量,增强系统可靠性.然而使用多个射频的MIMO系统增加了天线的体积、功率和硬件,从而增加了成本.天线选择是一种低成本、低复杂度的有效方法,可以利用多天线系统的多数优点.使用天线选择技术可以降低系统成本和复杂度,同时保留MIMO系统的优越性能.文中考虑了天线选择系统的一些实际应用问题,RF预处理,训练序列等的实际应用.最后,给出了一些天线选择的结论.     

Multiple-antenna techniques for wireless communications - a comprehensive literature survey

The use of multiple antennas for wireless communication systems has gained overwhelming interest during the last decade - both in academia and industry. Multiple antennas can be utilized in order to accomplish a multiplexing gain, a diversity gain, or an antenna gain, thus enhancing the bit rate, the error performance, or the signal-to-noise-plus-interference ratio of wireless systems, respectively. With an enormous amount of yearly publications, the field of multiple-antenna systems, often called multiple-input multiple-output (MIMO) systems, has evolved rapidly. To date, there are numerous papers on the performance limits of MIMO systems, and an abundance of transmitter and receiver concepts has been proposed. The objective of this literature survey is to provide non-specialists working in the general area of digital communications with a comprehensive overview of this exciting research field. To this end, the last ten years of research efforts are recapitulated, with focus on spatial multiplexing and spatial diversity techniques. In particular, topics such as transmitter and receiver structures, channel coding, MIMO techniques for frequency-selective fading channels, diversity reception and space-time coding techniques, differential and non-coherent schemes, beamforming techniques and closedloop MIMO techniques, cooperative diversity schemes, as well as practical aspects influencing the performance of multiple-antenna systems are addressed. Although the list of references is certainly not intended to be exhaustive, the publications cited will serve as a good starting point for further reading.     

THz antennas design,developments, challenges,and applications: A review

Terahertz (0.1–10 THz) wireless communication will be the future technology to reach a top-notch data rate. THz is one of the most promising candidates for 6G systems because it provides enormous bandwidth, up to 100 GHz, and a massive data rate of up to 1 Tbps. THz antennas, antenna arrays, and MIMO antenna arrays in 6G are hot research topics for implementing 6G wireless communication systems. The 6G aims to continue to enhance the features of the 5G as it is capable of achieving the maximum high-speed data rate, excellent reliable communication, massive connectivity, and very low latency connectivity. The 6G requirements need high-gain antenna arrays and MIMO antenna arrays to combat the effect of atmospheric losses in high frequencies. An in-depth discussion of the planar THz antennas that have been extensively used in THz applications like imaging, sensing, and Internet-of-Things (IoT) has been conducted. The study of the THz antennas, antenna arrays, and MIMO antennas on different conducting materials such as copper and graphene, which are designed on different dielectric substrates such as polyimide, quartz, liquid crystalline polymer, and polytetrafluoroethylene, has been carried out in detail. Metamaterial, photoconductive, plasmonic antennas, and THz beamforming are significant parts of THz communications. This paper also provides antennas and antenna arrays based on them.     

Optimal antenna selection based on capacity maximization for MIMO systems in correlated channels

Recent work has shown that multiple-input multiple-output (MIMO) systems with multiple antennas at both the transmitter and receiver are able to achieve great capacity improvement. In such systems, it is desirable to select a subset of the available antennas so as to reduce the number of radio frequency (RF) chains. This paper addresses the problem of antenna selection in correlated channels. We consider a narrowband communication system with M transmit and N receive antennas. We present the criterion for selecting the optimal L/sub t/ out of M transmit and L/sub r/ out of N receive antennas in terms of capacity maximization, assuming that only the long-term channel statistics, instead of the instantaneous channel-state information, are known. Simulations will be used to validate our theoretical analysis and demonstrate that the number of required RF chains can be significantly decreased using our proposed selection strategy, while achieving even better performance than the conventional MIMO system without antenna selection.     

Asymptotic RZF cooperative beamforming algorithm based on energy efficiency

A low complexity asymptotic regularized zero forcing cooperative beamforming algorithm based on energy efficiency in heterogeneous massive MIMO system was proposed,aiming at the problem that the current multi-flow regularization zero forcing beamforming algorithm sets the power constraint of each antenna in the regularization term as a fixed value and ignores the influences of factors such as the number of antennas,the number of users and QoS.The algorithm selects the optimal antenna power constraint set through the optimization method,and the optimal beamforming was asymptotically ob-tained to balance the interference among users to achieve the optimal energy efficiency,considering the impact of the number of antennas and users with the constraints of the antenna power and QoS.In view of the importance of backhaul in massive MIMO system,a backhaul power consumption model and the impact of backhaul power consumption on system performance was analyzed.Analysis and simulation results show that the proposed algorithm has great improvement of the performance,especially when the number of antennas is large.The algorithm is close to optimal performance,especially suitable for massive MIMO system of next generation communication.     

多进多出系统中圆形天线阵列的空间相关性研究

多进多出通信系统是近来出现的新的技术，用于无线通信下的多径环境中。相对于普通技术，他能增加频谱利用率。MIMO系统是利用多径干扰，在不增加频带的条件下成倍增加信道容量的技术。在独立的瑞利分布状态下，MIMO系统可随天线数目增加而线性增加容量。在真实环境下，无线信道会出现明显退化。天线之间的空间相关性对系统容量有影响。空间相关性是多进多出无线系统必须处理的实际损害。     

An adaptive spatio-temporal coding scheme for indoor wireless communication

Systems that employ multiple antennas in both the transmitter and the receiver of a wireless system have been shown to promise extraordinary spectral efficiency. With full channel knowledge at the transmitter and receiver, Raleigh and Cioffi (1998) proposed a spatio-temporal coding scheme, discrete matrix multitone (DMMT), to achieve asymptotically optimum multiple-input-multiple-output (MIMO) channel capacity. The DMMT can be regarded as an extension of the discrete multitone for a digital subscriber lines (DSL) system to the MIMO wireless application. However, the DMMT is basically impracticable in nonstationary wireless environments due to its high-computational complexity. Exploring second-order statistics, we develop an efficient adaptive blind coding scheme for a high-capacity time-division duplexing (TDD) system with slow time-varying frequency-selective MIMO channels. With this method, neither a training sequence nor feedback of channel information is required in the proposed blind approach. Besides, the computational complexity of the proposed scheme is significantly lower than that of the coding scheme described by Raleigh and Cioffi. Simulation results show that the proposed architecture works efficiently in indoor wireless local area network applications.     

Performance analysis of time-hopping m-ary UWB wireless system using V-BLAST algorithm

Ultra WideBand (UWB) transmissions are attractive for low power, baseband asynchronous multiple access and peer-to-peer wireless communications. Multiple Input Multiple Output (MIMO) technology is useful in combating against multipath and at the same time improves system performance by using multielement antennas at both transmitter and receiver. This letter proposes a time hopping M-ary UWB systems using V-BLAST algorithm, and power control is considered for better performance. Simulations are provided to compare performance with different antennas.     

Energy and spectral efficiency improvement using improved shark smell-coyote optimization for massive MIMO system

Massive multiple-input multiple-output (MIMO) can considerably enhance the “spectral efficiency and energy efficiency” since it is a major technique for future wireless networks. Thus, the performance needs a huge count of base station antennas to serve a smaller number of terminals in conventional MIMO methodology. Large-scale radio frequency (RF) chains represent the large-scale antennas. There is a need of implementing an effective massive MIMO system for maximizing the efficient performance of the system with high “spectral efficiency and energy efficiency” owing to the high cost of RF chains, and the higher power consumption. In this paper, a massive MIMO communication system is implemented to satisfy the requirements regarding “energy efficiency and spectral efficiency.” Here, the number of base station antennas, the transmit power, and beam forming vectors are optimized to maximize “energy efficiency and spectral efficiency” when the channel capacity is known to be higher than some threshold values. The novelty of this work is a new hybrid optimization adaptive shark smell-coyote optimization (ASS-CO) algorithm is developed for improving energy efficiency. The optimization is done with the help of the hybrid optimization ASS-CO Algorithm. The proposed ASS-CO algorithm-based massive MIMO communication system is evaluated by experimental analysis. From the result analysis, the maximum resource efficiency is observed by SS-WOA, which is 6.6%, 50%, 6.6%, 6.6%, and 6.6% maximized than rider optimization algorithm (ROA), spotted hyena optimization (SHO), lion algorithm (LA), Shark Smell Optimization (SSO), and Coyote Optimization Algorithm (COA) by taking the count of base stations as 4. The superior performance enhancement regarding “spectral efficiency and energy efficiency” is accomplished over the traditional systems.     

基于天线选择的低秩信道MIMO系统容量研究

最近的研究表明,在衰落信道多天线MIMO系统的容量随发射天线数线性增加.而对于低散射环境,即使信号经历独立的衰落,信道秩的降低也会严重影响系统容量的增加.对于这种低秩环境,选择天线发射或接收可以有效地降低系统的成本.本文研究了天线选择对低秩信道MIMO系统容量的影响.仿真结果表明,对不同的信道条件,适当选择天线发射不仅可以增加信道容量,而且可以降低系统的复杂度和射频成本.适当选择天线接收,在不严重降低系统容量的前提下,也达到了降低系统成本的目的.     

多用途双频双极化双通道MIMO 室内基站天线

多输入多输出(Multiple Input Multiple Output,MIMO)天线是MIMO技术的关键,现代无线通信领域的迅速发展对MIMO天线提出了许多新的要求.该文利用微带天线的低剖面特性,采用双线馈电的方式实现了两款双端口的MIMO天线,其中一款基于正方形辐射贴片,两个端口都工作于2.4GHz并且具有相同的辐射特性;改变贴片的尺寸可以得到另一款双频MIMO天线,分别工作于2.4GHz和3.5GHz,可以同时覆盖LTE(Long Term Evolution)、WiMAX(Worldwide Interoperability for Microwave Access)频段与WiFi(Wireless Fidelity)的部分频段,该天线的最大增益可达8dB,并且两个端口对应两个互相垂直的极化,满足室内基站的需要.     

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.

     

基于5G技术的无线通信系统设计

5G技术是一种全新的无线通信技术，其通过高频带、低时延、大容量优势以及强大的连接能力等优势，实现了快速的数据传输和更好的用户体验。其关键技术包括MIMO（多输入多输出）技术、Beamforming技术、超密集波束技术等。这些技术的应用可以大大提高无线通信系统的吞吐量和传输效率。文中主要分析了基于5G技术的无线通信系统的架构、发射端和接收端的设计，以期为用户提供更加高效、可靠的无线通信服务。