本文为英国剑桥大学（作者：InakiBerenguer）的博士论文，共205页。
移动计算和其它无线多媒体服务的快速增长激发了许多有关高速无线通信系统的研发活动。该领域的主要挑战包括研发有效的编码和调制技术，以提高无线系统的质量和频谱效率。最近出现的用于无线通信的多输入多输出（MIMO）技术，为迎接上述挑战提供了强有力的技术支撑。特别地，MIMO系统构成了对广泛范围的不同通信信道进行建模的统一方式，可以用紧凑的向量矩阵符号来表示。本文提出了用于MIMO系统的两个典型案例的新的信号处理技术：（a）系统采用多副发射和接收天线，（b）多个用户同时发送，时间和频率资源存在重叠。由于MIMO系统模型表示的通用性，本论文将证实类似的信号处理技术都适用于上述两种场景。
第二章对多天线MIMO通信系统的空时编码和信号处理技术最新发展进行了综述。我们首先回顾了关于采用多副发射和接收天线的无线系统容量的信息理论结果。然后，我们描述两类有代表性的空时系统，即BLAST系统和采用空时分组编码的系统。还讨论了MIMO技术在频率选择信道中的扩展。最后，还简要地讨论了用于多副发射和接收天线的无线系统的可替代编码和信号处理技术。
多天线设备中最昂贵的元器件通常是RF链路(放大器、滤波器、数模转换器等)。在保持MIMO系统的高潜在数据速率的同时，降低成本和复杂性的一种有效方法是在接收机(或发射机)处采用尽量少的RF链路，并尝试将每个链路最优地分配给数量较多的接收（发射）天线。采用这种方式，仅使用最佳天线组合，从而减少所需的RF链路数量。在第3章中提出了选择最佳天线的不同方法。特别地，我们考虑了在噪声环境下天线子集选择的新框架以及快速天线选择算法。
使用多副天线的无线通信可以增加衰落信道中通信系统的多路复用增益(即吞吐量)和分集增益(即鲁棒性)。已有的研究表明，对于任意给定数量的天线，在这两种增益之间存在基本的折衷关系。空时结构的开创性工作主要集中在分集增益或复用增益最大化上。然而，最近的工作已经提出了同时实现良好分集和多路复用性能的空时架构。在本论文的第四章中，我们提出了一种LAST编码，它能够在时延受限的MIMO信道中达到最佳的分集复用折衷。在第4章中，利用随机优化技术设计了能够进一步优化误码率的LAST码。最小误码率LAST码的设计还被扩展到多个发射终端通过共享天线进行协作的情形。
在论文的最后部分，我们考虑多用户MIMO系统，而不再是多天线系统。特别地，我们讨论了时域双工码分多址（TD-CDMA）系统的下行链路。首先，我们获得并比较CDMA系统下行链路的容量及多用户检测(即接收机处理)或预编码(即发射机处理)的结果。结果表明，这两种方案具有相似的容量区域，从而推动了高效发射机预编码技术的发展，以在不降低系统性能的情况下降低移动终端的接收机复杂度。然后，我们比较了多径衰落信道下TDD-CDMA系统下行链路的两类线性干扰抑制技术，即线性多用户检测方法和线性预编码方法。随后，我们设计了非线性多用户预编码方法，以消除多用户干扰、码间干扰和符号间干扰，还设计了用于多用户功率加载和排序取消的高效算法。综上所述，本文提出了一系列适用于MIMO通信系统的信号处理算法工具。
Rapid growth in mobile computing and otherwireless multimedia services is inspiring many research and developmentactivities concerning high-speed wireless communication systems. The mainchallenges in this area include the development of efficient coding andmodulation techniques to improve the quality and spectral efficiency ofwireless systems. Multiple-input multiple-output (MIMO) techniques for wirelesscommunication have recently emerged and offer a powerful paradigm for meetingthese challenges. In particular, MIMO systems constitute a unified way ofmodeling a wide range of different communication channels, which can be handledwith a compact vector-matrix notation. This thesis proposes new signalprocessing techniques for two representative cases of MIMO systems: (a) systemsemploying multiple transmit and receive antennas, and (b) systems with multipleusers transmitting simultaneously and overlapping in both time and frequency.Owing to the common MIMO system model notation, similar signal processingtechniques are applicable to both scenarios as will be demonstrated in thethesis. Chapter 2 gives an overview of the recent development in space-timecoding and signal processing techniques for MIMO communication systems havingmultiple antennas. We first review the information theoretic results on thecapacities of wireless systems employing multiple transmit and receiveantennas. We then describe two representative categories of space-time systems,namely, the BLAST systems and systems employing space-time block coding. Theextension of MIMO techniques to frequency-selective channels is also addressed.Finally, alternative coding and signal processing techniques for wirelesssystems employing multiple transmit and receive antennas are also brieflytouched upon. The most costly element of a multiple antenna device is usuallythe RF chains (amplifiers, filters, digital-to-analog converters, etc.). Apromising approach for reducing the cost and complexity while retaining areasonably large fraction of the high potential data rate of a MIMO system isto employ a reduced number of RF chains at the receiver (or transmitter) andattempt to optimally allocate each chain to one of a larger number of receive(transmit) antennas. In this way, only the best set of antennas is used, whilethe remaining antennas are not employed, thus reducing the number of RF chainsrequired. Different approaches to selecting the best antennas are proposed inChapter 3. In particular, we consider a new framework for antenna subsetselection in noisy environments and also fast antenna selection algorithms.Wireless communication using multiple antennas can increase the multiplexinggain (i.e., throughput) and diversity gain (i.e., robustness) of acommunication system in fading channels. It has been shown that for any givennumber of antennas there is a fundamental tradeoff between these two gains.Pioneering works on space-time architectures had focused on maximizing eitherthe diversity gain or the multiplexing gain. However, recent works haveproposed space-time architectures that simultaneously achieve good diversityand multiplexing performance. In Chapter 4 of this thesis a family of latticespace-time (LAST) codes is presented that can achieve the optimumdiversity-multiplexing tradeoff in delay limited MIMO channels. In Chapter 4,using stochastic optimization techniques we design LAST codes that can furtheroptimize the error rate. The design of minimum error rate LAST codes is laterextended to scenarios in which multiple transmitting terminals cooperate bysharing their antennas. In the final part of the thesis we consider MIMOsystems with multiple users instead of multiple antennas. In particular, weaddress the downlink of time domain duplex code division multiple access(TDD-CDMA) systems. First we obtain and compare the capacity results of adownlink CDMA system with either multiuser detection (i.e., receiverprocessing) or precoding (i.e., transmitter processing). It is demonstratedthat the two schemes exhibit similar capacity regions, which motivates thedevelopment of efficient transmitter precoding techniques to reduce thereceiver complexity at the mobile units without degrading the systemperformance. We then compare two classes of linear interference suppressiontechniques for downlink TDD-CDMA systems over multipath fading channels,namely, linear multiuser detection methods and linear precoding methods. Welater develop non-linear multiuser precoding methods, to remove multiuserinterference, interchip interference and inter-symbol interference. Efficientalgorithms for multiuser power loading and cancellation ordering are alsodeveloped. In summary, a range of signal processing tools appropriate for usein MIMO communication systems have been developed in the work presented in thisthesis.
1 引言
2 MIMO回顾
3 天线选择
4 Lattice空时编码
5 MIMO预编码
6 结论与未来研究工作展望
附录A 式(3.30)中det()的无偏估计
附录B 球面中所有lattice点列举
附录C MMSE无约束线性编码求解
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