【作者】 闫正航；

【导师】 杨宇航；

【作者基本信息】 上海交通大学 ， 通信与信息系统， 2010， 博士

【摘要】 多入多出(MIMO)通信技术比单入单出(SISO)通信技术最吸引人的优势是能够同时获得复用增益和分集增益。MIMO通信系统能在不增加带宽的情况下成倍地提高通信系统的容量和频谱利用率,成为3G和B3G无线通信系统中不可或缺的关键技术。空时编码(STC)是MIMO通信系统中被广泛采用的编码调制技术。正交空时块编码(OSTBC)因其简单的编解码算法和良好的分集性能得到深入研究和广泛应用。因为当发射天线数目超过2的时候,OSTBC的编码速率总小于1。所以,空时码家族中陆续出现了在分集增益和编码效率之间平衡的编码方案,如通用分层空时码(GLSTC)、准正交空时块编码(QOSTBC)等。MIMO信道中阵元接收电波的波达方向具有非全向性以及非均匀性,空间上反射体和散射体的分布具有不均匀性,造成处于不同位置阵元的接收信号具有不同程度的空间相关特性。和衰落与噪声一样,信道之间的空间相关会导致MIMO信道容量和通信性能下降。在本文中主要讨论了几类STC在衰落MIMO信道中性能优化的算法。OSTBC系统能够在接收端实现单符号的极大似然(ML)解码,并且可以对发射符号的实数部分和虚数部分分别进行实数域的极大似然解码,从而降低计算复杂度。然而,极大似然解码算法的计算量会随着调制阶次的增加而呈指数级别增加。随着无线通信技术的不断发展,MIMO系统中使用的发射天线数目越来越多,调制阶次也越来越大,极大似然解码算法的计算量会成为制约OSTBC使用的一个重要的因素。本文提出了一种简化的OSTBC解码算法。首先把通信系统的接收方程写成等效信道的表达形式,引用迫零(ZF)解码的原理得到发射符号的估计矢量,再分别对得到的估计矢量的实数部分和虚数部分进行球形解码。等效信道矩阵列间的正交性使迫零解码能够达到极大似然解码的性能。球形解码算法中球半径和可能坐标集合的确定会增加部分额外的计算量,但随着发射符号调制阶次的增加,球形解码算法的总计算量不会随着调制阶的增加呈指数增加。与两种极大似然解码算法相比,球形解码算法节省的计算量越来越多。信道估计是许多无线通信技术的基础,使用训练序列和插值是基本的信道估计技术。通信过程中发送过多的训练序列降低了信道利用率,训练序列过少会引起信道估计误差增大降低性能。由于使用了空时码结构的系统能够获得分集增益而具有较低的错误概率,可以把解码后的数据还原成发射时的状态作为训练序列。本文提出了一种重编码插值信道估计方案。接收端每隔一段时间将接收到的信号重新进行空时编码并作为训练序列来估计最新的信道信息,其他时间段的信道参数通过插值算法获得。重编码插值信道估计算法能够更好地适应时变的无线信道,与使用训练序列插值算法相比,在同等通信环境,误码率10-6时有1.5 dB的性能增益。并且重编码插值算法能够在保证性能的前提下仅仅使用非常少的训练序列,可以作为一项准盲信道估计技术。GLSTC是贝尔实验室空时结构(BLAST)和STC结合的一种技术。发射端把发射天线分组分别在每个组内进行空时编码,在接收端使用组干扰抑制和组干扰消除算法进行解码。先前解码组发生解码错误的情况下会对后续的组产生干扰,影响后面解码的性能。由于误码的分布非常复杂,很难直接得到误码传播的概率分布密度,现有文献中对误码传播的影响或者忽略,或者简单认为误码传播肯定会造成之后的解码出错。本文使用理论分析结合数值仿真的方法定量分析了GLSTC系统中误码传播对总体性能和功率分配结果的影响,并在考虑误码传播的影响为GLSTC系统构造了一个更加准确的误符号率函数模型,在这个模型的基础上使用拉格朗日乘子法得出最优功率分配的结果。仿真结果表明考虑了误码传播的功率分配策略在和现有的几类功率分配算法相比能够取得一定的性能改进,在低信噪比时候有大约1.0 dB的性能增益,并且无论在低信噪比还是高信噪比的时候所提功率分配算法的性能都是最佳。此外,根据接收端组干扰抑制和组干扰消除算法的原理,结合无线个人区域网(WPAN)的特点设计了一类多址接入技术,仿真结果显示使用组干扰抑制和组干扰消除算法能够满足高速率通信的WPAN中的多址接入。QOSTBC是在STBC基础上牺牲全分集增益实现更高速率传输的编码技术。本文提出一个QOSTBC和前向纠错(FEC)码级联结构的性能优化算法。在接收端,先利用QOSTBC联合检测方案解出发射的符号,在纠错之后重构发射符号并分组,实行并行干扰消除(PIC)的处理方法。经过干扰消除之后的系统等效于两个OSTBC。这时对系统使用一个双正交空时块解码运算重新检测出发射的符号。在整个解码的过程中,级联结构干扰消除算法可以获得和OSTBC一样的全分集增益,能够获得QOSTBC的编码效率,还可以获得FEC的编码增益。仿真结果也表明,除了在信噪比非常低的情况下,级联方案的性能远远优于了单个OSTBC或QOSTBC结构的性能。应用了并行干扰消除之后的解码算法能够进一步提高级联发射方案的性能。对星座旋转QOSTBC级联FEC码方案而言,干扰消除算法和完全没有干扰时双正交空时块编码结构的性能损失小于0.5 dB。并且本文提出的干扰消除算法对最低的接收端天线数目没有要求。时变性和空间相关是MIMO无线信道的两个特点,衰落和相关都影响通信系统的性能。MIMO通信系统中自适应调制编码(AMC)技术能够根据时变信道特征选择发射方案提高通信性能。本文提出了一种实时、判决简单且不需要大量信息反馈的AMC方案。根据MIMO通信系统内不同发射方案性能在不同的信噪比区间受空间相关的影响不同,选择受影响较小的发射方案,达到在多变的信道环境中改善误码性能。之前的一些自适应通信系统都需要复杂的切换判决算法计算所有可能发射方案的信道容量或者误码性能,并且需要大量的信息反馈,本文把发射方案的判决算法简化为根据信噪比和误码率的线性判决。使用天线子集选择和QOSTBC两种发射方案切换来适应时变空间相关衰落信道。仿真结果表明,在低信噪比场合,天线子集选择和QOSTBC切换发射方案能够显著改善误码性能。而这是在非常简单的线性判决和几乎不占用带宽的情况下实现的。在慢时变空间相关衰落信道中,所提自适应切换算法能够简化AMC系统的判决并提高MIMO通信系统误码性能的鲁棒性。更多还原

【Abstract】 Comparing with conventional single-input single-output (SISO) communication systems, Multi-input Multi-output (MIMO) communication systems have two attractive advantages. These are multiplexing gain (or spectral efficiency gain) and diversity gain. MIMO technology can remarkably improve channel capacity and spectral efficiency in the premise of the same bandwidth. MIMO has been adopted as a key technology of standard for 3G and B3G wireless communications. Space-time coding (STC) has been popular since its inception. Specially, orthogonal space-time block code (OSTBC) becomes one prominent STC for its full diversity performance and simple maximum likelihood (ML) decoding algorithms. When the number of transmit antennas is larger than 2, the code rate of OSTBC is less than 1. Therefore, some new codes are designed to balance diversiy gain and code rate in STC family, such as general layered space-time code (GLSTC) and quais-orthogonal space-time block code (QOSTBC). In real wireless environments, reflectors and scatters are not uniformly deployed and directions-of-arrival (DOA) at antennas are not omnidirectional and not uniform. These cause spatial correlations among MIMO antennas. Like fading and noise, spatial correlations deteriorate channel capacity and error performance in MIMO communication systems. In this dissertation, several performance optimization algorithms have been discussed for STC over MIMO fading channels.When ML decoding is used for OSTBC, its computational complexity exponentially increases with the modulation order increases. Even ML decoding is respectively used for real part and imaginary part of one symbol, the computational complexity increases a lot with the increase of modulation order. If modulation order is high, computational complexity is an important obstacle which affects the application of STBC. A simplified orthogonal STBC decoding algorithm is put forward in this dissertation. At first, the communication equation is represented by equivalent channels matrix. An estimated vector of transmited symbols can be obtained by using zero-forcing (ZF) decoding. Sphere decoding is deployed to real part and imaginary part of the estimated vector, respectively. The orthogonality character among columns of the equivallent channel matrix provides sphere decoding has the same performance with ML decoding. With increase of modulation order, sphere decoding algorithm can reduce more computation than ML decoding algorithm.Training sequence and interpolation are fundamental channel estimation techniques in wireless communication systems. In MIMO communication systems, using plenty of training sequence for channel estimation and channel tracking will decrease bandwidth efficiency. If reducing training sequence, the error of channels estimation increases. In this dissertation, a recoding and interpolation scheme is proposed for channel estimation and channel tracking in OSTBC systems. At receiver, except for training sequence at the begin of one frame, one slot’s data are recoded as training sequence for channels estimation in several slots. In other slots, the channels parameters are calculated by interpolation. Compared with the method using training sequence and interpolation, the recoding and interpolation scheme can achieve 1.5 dB gains at 10-6 bit error rate in the same environment. The recoding and interpolation can be used as a quasi-blind channels estimation algorithm.GLSTC is a combined technology of Bell Labs layered space-time (BLAST) and STBC which can provide both antenna diversity gain and spectral efficiency gain. At transimtter, antennas are devided into several groups and STC is implemented in each group. At receiver, interference suppression and interference cancellation are used for decoding. The errors in one group will deteriorate succedent decoding. Because the distributation of errors is very complex, error propagation has been ignored or overestimated in the existing literature. The effect of unsuccessful decoding and error propagation has been derived by using theoretic analysis combining with simulation in this dissertation. A new power allocation strategy considering error propagation is proposed by using Lagrangian multiplier method. The new optimal power allocation has the best error performance among all existing power allocation strategies from low singal-to-noise ratio (SNR) to high SNR scenarios. Furthermore, a multiple access algorithm using interference suppression and interference cancellation is designed for wireless personal area network (WPAN). The multiple access algorithm adapts to WPAN with few communication nodes and very high communication rate.QOSTBC is an attractive transmission and coding technology because it can achieve high transmission rate compared to OSTBC by scarifying partial diversity. In this dissertation, we present a parallel interference cancellation (PIC) algorithm for QOSTBC concatenated error correction code structure. At the receiver, transmitted symbols are detected by pairwise decoding algorithm at first. After error correction, the data are regrouped. PIC and dual OSTBC decoding are deployed. The proposed system can achieve full diversity same as OSTBC, full code rate same as QOSTBC and error correction code gain simultaneously. The concatenated structure has better performance than both QOSTBC and OSTBC schemes except at very low SNR scenarios. The proposed PIC algorithm can improve the error performance further.Time-varying and spatial correlations are two characters of MIMO channels. Fading and spatial correlations affect performance of communication systems. Adaptive modulation and code (AMC) can improve system performance by using corresponding transmission schemes. One realtime AMC scheme is proposed for time-varying spatial correlated fading MIMO systems. The decision algorithm is simple linear decision according SNR and error rate. Only a few indicator informations are required to feed back to transmitter. Antenna subset selection and QOSTBC are two candidate transmission schemes because they are suffered with SNR and spatial correlations in different degree. Simulation results show that the proposed AMC scheme can achieve considerable gain in low SNR and week spatial correlations at the expense of simple decision calculation and tiny feedbacks. The proposed AMC algorithm improves robustness of MIMO communication systems over slowly time-varying spatial correlated channels.更多还原