毫米波无线通信系统混合波束成形综述

毫米波频段拥有大量未充分使用的频谱资源,能有效缓解低频段频谱拥塞,并且由于毫米波波长较短,能极大地减小大规模天线系统的物理尺寸,使得毫米波通信成为5 G无线通信系统潜在的关键技术之一。考虑到毫米波传播路径损耗严重,毫米波系统需采用波束成形技术改善传输质量。在毫米波大规模多输入多输出(Multiple-input multiple-out, MIMO)系统中,由于数字波束成形高功耗、高成本问题,混合数模波束成形成为重要的替代方案。本文首先阐述了毫米波混合波束成形的研究现状,而后给出了系统模型,最后介绍了信道估计、码本设计和低复杂度设计等混合波束成形的关键技术。     

An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications

To meet the future demand for huge traffic volume of wireless data service, the research on the fifth generation (5G) mobile communication systems has been undertaken in recent years. It is expected that the spectral and energy efficiencies in 5G mobile communication systems should be ten-fold higher than the ones in the fourth generation (4G) mobile communication systems. Therefore, it is important to further exploit the potential of spatial multiplexing of multiple antennas. In the last twenty years, multiple-input multiple-output (MIMO) antenna techniques have been considered as the key techniques to increase the capacity of wireless communication systems. When a large-scale antenna array (which is also called massive MIMO) is equipped in a base-station, or a large number of distributed antennas (which is also called large-scale distributed MIMO) are deployed, the spectral and energy efficiencies can be further improved by using spatial domain multiple access. This paper provides an overview of massive MIMO and large-scale distributed MIMO systems, including spectral efficiency analysis, channel state information (CSI) acquisition, wireless transmission technology, and resource allocation.     

面向5 G无线通信系统的关键技术综述

对未来无线通信系统的几种潜在的关键通信技术,如异构网络、大规模多输入多输出(MIMO)通信、绿色通信和毫米波通信,给出了较详尽的论述与讨论。首先简要介绍了未来无线通信网络结构的异构化变化所引起的复杂干扰信号的出现及能源消耗增加问题。介绍了大规模MIMO通信技术的优点,大规模MIMO通信的研究现状与研究难点。详尽叙述了分别以频谱效率、能源效率和资源效率最大化为目标的绿色无线通信传输优化问题的解决方案。最后,给出了进一步解决频谱稀缺问题的毫米波无线通信系统的混合波束成形的方案。     

Space-time coding and signal processing for MIMO communications

Rapid growth in mobile computing and other wireless multimedia services is inspiring many research and development activities on high-speed wireless communication systems.Main challenges in this area include the development of efficient coding and modulation signal processing techniques for improving the quality and spectral efficiency of wireless systems.The recently emerged space-time coding and signal processing techniques for wireless communication systems employing multiple transmit and receive antennas offer a powerful paradigm for meeting these challenges.This paper provides an overview on the recent development in space-time coding and signal processing techniques for multiple-input multiple-output (MIMO) communication systems.We first review the information theoretic results on the capacities of wireless systems employing multiple transmit and receive antennas.We then describe two representative categoriesof space-time systems,namely,the BLAST system and the space-time block coding system,both of which have been proposed for next-generation high-speed wireless system.Signal processing techniques for channel estimation and decoding in space-time systems are also discussed. Finally,some other coding and signal processing techniques for wireless systems employing multiple transmit and receive antennas that are currently under intensive research are also briefly touched upon.     

大规模MIMO系统研究进展

随着无线通信技术的快速发展和智能手机的迅速普及,人们对数据传输速率提出了更高的需求。为进一步提高数据传输速率,通过增加基站天线数目构建大规模MIMO系统,是一种高效而相对便捷的方式。大规模MIMO系统能深度发掘空间维的自由度,使得基站能够利用同一时频资源服务于多个用户。本文探讨了大规模MIMO系统的导频污染问题及解决方案、适用于大规模MIMO系统的信道模型以及低复杂度的传输技术与实现方法三项关键技术。与现有MIMO系统相比,大规模MIMO系统能显著提高频谱效率、能量效率和系统的鲁棒性能。作为第五代移动通信（5G）最具潜力的研究内容之一,大规模MIMO无线通信技术已引起国内外的广泛关注,但相关研究工作尚处在起步阶段,还有大量的技术难点需要进一步突破。     

基于随机波束成形MIMO系统的信道反馈算法

MIMO系统是未来移动通信发展的趋势.随机波束成形利用包含信道质量的反馈信息,可以开发多用户分集增益,进一步提高MIMO系统的容量.然而繁重的反馈信息会占据大量的无线资源,降低系统的实际效率.主要研究降低随机波束成形MIMO系统反馈开销的方法,提出了两种部分信道反馈算法:门限反馈和最优反馈.理论推导表明了系统平均容量与反馈率之间的权衡关系,仿真结果证明了只要恰当地选取反馈参数,这两种反馈算法可以在几乎不牺牲系统容量的前提下,极大节省反馈开销.其中,门限反馈在系统容量方面表现要好于最优反馈,而最优反馈在实现简便性方面要强于门限反馈,因此实际设计时要折中考虑.     

多速率CDMA系统下行波束成形的联合多变量优化

下行波束成形能用来限制由于高速率数据用户引起的干扰，也能改善系统性能。另一方面，功率控制、数据速度分配也是改善无线多媒体通信频谱利用率的两种基本技术。在文章里，阐述了DS—CDMA系统中给定系统吞吐量和软的目标SIR门限值条件下，下行波束成形权值和数据速率的优化问题。基于上面的内容，给出了一种改进的IVPW算法，可以将其应用于未来的无线通信系统，为所有用户提供稳定的最大吞吐量。     

MIMO通信系统的移动台单站定位算法

无线MIMO通信系统中在发射和接收端使用天线阵列,充分利用冗余多径信号结合阵列信号处理技术可提取出更多参量,比如AOA、AOD、DOA。该文基于MIMO通信系统多径信号参量的估计,推出一种单基站定位的新方法。该方法将多径参数误差的出现概率降到最低并通过同时解一系列数学定位方程给出移动台位置定位的最佳估计。测量均方误差并与克拉美罗界下界比较,证明了该方法的性能。     

Energy- and spectral-efficiency of zero-forcing beamforming in massive MIMO systems with imperfect reciprocity calibration: bound and optimization

In a time-division duplex (TDD) system with massive multiple input multiple output (MIMO), channel reciprocity calibration (RC) is generally required in order to cope with the reciprocity mismatch between the uplink and downlink channel state information. Currently, evaluating the achievable spectral efficiency (SE) and energy efficiency (EE) of TDD massive MIMO systems with imperfect RC (IRC) mainly relies on exhausting Monte Carlo simulations and it is infeasible to precisely and concisely quantify the achievable SE and EE with IRC. In this study, a novel method is presented for tightly bounding the achievable SE of massive MIMO systems with zero-forcing beamforming under IRC. On the basis of the analytical results, we demonstrate key insights for practical system design with IRC in three aspects: the scaling rule for interference power, saturation region of the SE, and the bound on the SE loss. Finally, the trade-off between spectral and energy efficiencies in the presence of IRC is determined with algorithms developed to optimize SE (EE) under a constrained EE (SE) value. The loss of optimal total SE and EE due to IRC is also quantified, which shows that the loss of optimal EE is more sensitive to IRC in a typical range of transmit power values.     

无线网络协作MAC 机制

协作通信利用空闲节点的天线,构成虚拟的MIMO(multiple-input multiple-output)系统,从而对抗无线信道衰落,获取分集增益.协作通信是下一代无线移动网络的关键技术,也是近几年的一个研究热点.目前,已有的研究成果大多集中在如何根据信道状态选取合适的协作节点,以增加信道容量、减低能量消耗及减小中断概率等方面.但由于协作通信改变了以往的传统通信模式,因此需要设计新的MAC(medium access control)机制(协作MAC机制),以适应协作通信的特点.针对协作MAC机制进行综述,重点讨论了协作通信中MAC机制面临的问题,并对现有的协作MAC机制进行分析和比较,最后给出协作MAC的进一步的研究方向.     

Cooperative beamforming design for physical-layer security of multi-hop MIMO communications在多跳MIMO通信系统下的基于物理层安全的协作波束赋形设计

The security issue is critically important for wireless communications, especially for multi-hop communications. In this paper, we propose a cooperative secrecy beamforming scheme for a multi-hop MIMO communication network, in which there is a single-antenna source, multiple multi-antenna relays and a singleantenna destination. Moreover, two types of eavesdroppers exist in the network, one of which has known channel state information (CSI), while the other not. To achieve security communications, in our work null-space beamforming and artificial noise beamforming are jointly optimized to improve the secrecy rate of the multi-hop network. In nature, the joint optimization is nonconvex and challenging. Exploiting its structure, the considered optimization problem is decoupled into a series of subproblems that can be efficiently solved based on convex optimization theory. Finally, some numerical experiment results are provided to assess the performance of the proposed secrecy beamforming design.     

Genetic algorithms with applications in wireless communications

Genetic algorithms (GAs) are known to locate the global optimal solution provided sufficient population and/or generation is used. Practically, a near-optimal satisfactory result can be found by Gas with a limited number of generations. In wireless communications, the exhaustive searching approach is widely applied to many techniques, such as maximum likelihood decoding (MLD) and distance spectrum (DS) techniques. The complexity of the exhaustive searching approach in the MLD or the DS technique is exponential in the number of transmit antennas and the size of the signal constellation for the multiple-input multiple-output (MIMO) communication systems. If a large number of antennas and a large size of signal constellations, e.g. PSK and QAM, are employed in the MIMO systems, the exhaustive searching approach becomes impractical and time consuming. In this paper, the GAs are applied to the MLD and DS techniques to provide a near-optimal performance with a reduced computational complexity for the MIMO systems. Two different GA-based efficient searching approaches are proposed for the MLD and DS techniques, respectively. The first proposed approach is based on a GA with sharing function method, which is employed to locate the multiple solutions of the distance spectrum for the Space-time Trellis Coded Orthogonal Frequency Division Multiplexing (STTC-OFDM) systems. The second approach is the GA-based MLD that attempts to find the closest point to the transmitted signal. The proposed approach can return a satisfactory result with a good initial signal vector provided to the GA. Through simulation results, it is shown that the proposed GA-based efficient searching approaches can achieve near-optimal performance, but with a lower searching complexity comparing with the original MLD and DS techniques for the MIMO systems.     

全双工MIMO中继系统中一种高性能波束成形算法

全双工中继系统相比于半双工中继系统可以极大地提高频谱利用率,但是中继收发端之间的信号泄漏严重影响全双工系统的性能。为了抑制基于译码转发的全双工多输入多输出中继系统的自干扰,提高信息传输速率,提出了一种波束成形算法。该算法在中继站采用基于最小均方误差的接收与发射波束成形,并联合两个波束成形矩阵建立迭代结构以得到最优解。仿真表明,同传统的零空间投影与最大化信干比算法相比,提出的算法能够有效提高系统性能。在中高信噪比时,该算法较最大化信干比算法获得0.8 bit/(s·Hz)左右的速率增益;当误码率达到10-3以及更低时,该算法相比于最大化信干比算法能获得1.5 dB左右的信噪比增益。     

MIMO双向中继的最优波束形成滤波器的设计

在多用户MIMO (multiple-input multiple-output)放大转发中继通信网络中,针对双向中继的传输特点,采用最小和归一化均方误差(SNMSE)准则设计了一种新的中继最优波束形成滤波器,并将OFDM (orthogonalfrequency division multiplexing)技术与所提的SDMA (space division multiple access)策略相结合,通过充分利用频率分集和空间分集来提高系统性能.仿真结果表明,所提出的双向中继策略在系统和速率和误比特率性能上显著优于其它中继策略.     

无线MIMO系统的上行资源分配算法研究

在存在同信道干扰的无线MIMO系统中,为具有多种QoS需求的调度业务分配资源是一个具有挑战性的问题.提出一种实用的、基于SDMA的贪婪资源分配(SGRA)算法.在高效的干扰管理基础上,SGRA算法可以执行两阶段启发式计算和搜索.在第1阶段,包括上行调度和子信道分配的贪婪资源分配首先在时域频域二维进行;在第2阶段,资源分配被扩展到时域频域空域三维进行.SGRA的算法复杂度低,适用于实际无线通信系统.仿真结果表明,与同类算法相比,SGRA算法可以提高系统吞吐量,更好地保证实时业务的时延和最小数据速率需求,同时兼顾系统公平性.     

无线传感器网络协作通信技术综述

无线传感器网络的发展中存在生存周期和资源共享两大瓶颈,其重要原因之一在于缺乏射频信号级协作,通信能耗难以降低,通信资源难以虚拟化.协作通信技术通过节点间射频信号级的协作处理,使仅具单根天线的节点彼此共享天线,从而得到类似于“多入多出”系统的空间分集增益,显著地提升了通信的能量效率,它将是未来传感器网络的重要技术.综述了传感器网络中的协作通信技术,内容包括：在局部构造协作通信节点组以形成虚拟通信链路,利用协作通信组以直传或中继方式实现端到端的数据传输,协作通信与传感器网络的系统优化和资源虚拟化手段等.总结了传感器网络协作通信研究中的主要趋势、技术进展与关键问题.     

双无线供能IRS辅助的无线通信系统的吞吐量优化研究

在未来物联网等新型无线网络场景中,需要进行信息和能量同步传输,而且通信环境复杂多变,通信设备维护成本较高。一方面,智能反射面(IRS)能通过对无线信道的智能调控提高无线通信与无线传能的性能,另一方面,通过无线能量传输对IRS进行供能,解决部署IRS时存在的供能不便的问题,降低设备维护成本。研究双无线供能IRS辅助的无线通信系统的吞吐量优化,在该系统中,多天线基站先向IRS无线传输能量,然后在IRS的辅助下向多个单天线用户发送信息。针对基站与IRS之间的信道不受阻和受阻两种情况,分别提出两时隙和三时隙的传输模式,并研究优化它们的吞吐量。具体而言,研究联合优化基站的发射波束成形、IRS的反射波束成形以及各时隙长度,在基站最大发射功率、各用户最小接收速率、各时隙持续时间和IRS反射系数的模一约束下,最大化系统的总吞吐量。由于优化变量高度耦合,难以直接求最优解,提出了基于交替优化、连续凸逼近和半正定松弛的优化算法,以求得优化问题的高质量次优解。仿真结果显示,所提联合优化算法取得了明显高于基准算法的吞吐量性能,并且揭示了两时隙和三时隙传输模式的适用场景。     

多模无线传感器网络的容量

密集无线传感网络中,可通过配置多个Sink收集节点来观察所监测区域内的多个随机过程,并在相应的Sink节点处重建所观察到的过程。当网络中传感器节点的功率固定时,分析了采用基于波束成形的通信方式时网络的可达容量域,推导出每个过程可获得的传输容量为专(log(N)),并进一步分析了该网络可以同时观察到的随机过程的数目为O(N茁)。     

面向MIMO多跳无线网络的多用户视频传输优化方法

MIMO(multi-input multi-output)作为一种有效提高无线信道可靠性和带宽的新兴技术,已在无线网络中得到广泛应用.但是,如何利用MIMO在多跳无线网络中为多用户提供高质量视频服务,尚未得到广泛关注.多跳无线链路之间的共信道干扰是需要解决的关键问题.提出一种面向多跳无线网络的多用户视频传输方法,利用链路选择、MIMO的空间复用和空间分集等特点,减少链路间的共信道干扰,最大化多用户的平均视频传输质量.通过对链路选择和天线分组进行建模,将上述传输策略抽象成一个最优化问题,该问题是一个NP-hard问题.为了降低求解复杂度,引入遗传算法来求解链路选择问题.该算法采用基因遗传“优胜劣汰”的特性,在保证性能的同时,大幅度降低了求解复杂度.另外,由于遗传算法中每条“染色体”的“优劣”与天线分组策略有关,因此结合可伸缩视频的失真模型,将天线分组问题转化为一个标准的0/1背包问题,并在搜索时采用深度优先和分支限界技术,进一步降低算法复杂度.实验结果表明,所提出的链路选择算法和天线分组算法均能显著提高用户接收视频的质量.     

Internet of surveillance: a cloud supported large-scale wireless surveillance system

Large-scale video surveillance systems are among the necessities for securing our life these days. The high bandwidth demand and the large storage requirements are the main challenges in such systems. To face these challenges, the system can be deployed as a multi-tier framework that utilizes different technologies. In such a framework, technologies proposed under the umbrella of the Internet of Things (IoT) can play a significant rule in facing the challenges. In video surveillance, the cameras can be considered as “the things” that are streaming videos to a central processing and storage server (the cloud) through the Internet. Wireless technologies can be used to connect wireless cameras to the surveillance system more conveniently than wired cameras. Unfortunately, wireless communication in general tend to have limited bandwidth that needs careful management to achieve scalability. In this paper, we design and evaluate a reliable IoT-based wireless video surveillance system that provides an optimal bandwidth distribution and allocation to minimize the overall surveillance video distortion. We evaluate our system using NS-3 simulation. The results show that the proposed framework fully utilizes the available cloud bandwidth budget and achieves high scalability.