【作者】 陈睿；

【导师】 李建东；

【作者基本信息】 西安电子科技大学 ， 通信与信息系统， 2011， 博士

【摘要】 近年来,随着实时多媒体通信、高速Internet接入等数据业务的发展,提高通信系统的速率、频带利用率和服务质量已成为亟待解决的问题。在无线通信系统中,OFDM技术由于能够抵抗多径带来的符号间干扰而成为宽带无线通信系统的关键技术之一,而MIMO技术能够在不增加发射功率和带宽的条件下,利用空域资源显著地提高信道容量,频谱利用率和通信可靠性。MIMO和OFDM结合的方案被广泛认为是未来无线通信系统的核心方案之一。本文分别对OFDM系统和MIMO系统的预编码技术做了较为深入的研究,具体内容如下：1.针对OFDM系统所有子信道的增益相差较大导致容量与误码率无法同时优化,提出三种基于几何均值分解(GMD)的联合预编码器检测器方案(JPD方案),这三种方案利用非线性的预编码器或检测器将OFDM系统的所有子信道转变为具有相等信道增益的等效子信道,因此达到了更低的平均误码率性能。我们通过仿真和曲线拟合得到了ZFDP-JPD方案中等效信道的信道增益概率密度函数(PDF)得到近似误码率结果,与蒙特卡洛仿真得到的误码率结果吻合,仿真结果表明与等比特分配(EBA)的使用迫零检测器的OFDM方案相比,JPD方案能够在高信噪比下达到更低的误码率。与使用迫零检测器的OFDM (EBA)方案相比,在误码率为10-3时,JPD方案对QPSK调制和16QAM调制可以分别带来约8dB和6dB的增益。2.针对时分双工(TDD)的点对点MIMO空间相关信道,提出格规约辅助的有限前馈线性预编码器。系统的下行信道状态信息通过上行的小均方误差估计器获得。发射端通过一个低速率的下行控制信道将整数或者二进制的格规约变换矩阵发送给接收端。我们推导出所提算法的分集阶数等于发射天线数,说明所提算法在相关信道下获得了完全发射分集。仿真结果表明所提算法获得了完全发射分集。空间相关系数的增加使误码率曲线右移,带来了与编码增益相反的效应。3.提出不完美信道信息下点对点MIMO系统联合预编码检测方案。我们将收发两端的信道误差分为两种情况分别讨论。第一种情况为收发两端具有相同的不完美信道状态信息。我们将完美信道信息假设下被证明在误码率和容量上均达到最优的均匀信道分解方案推广到更加实际的场景中,在最小均方误差准则下推导了新的鲁棒均匀信道分解方案。与传统均匀信道分解方案和A. D. Dabbagh等提出的鲁棒线性预编码方案相比,所提算法具有更低的误码率,且在高信噪比下降低了误码平层,并证明了提出的鲁棒均匀信道分解方案是没有容量损失的。通过计算得出所提方案与传统均匀信道分解方案和A. D. Dabbagh等提出的鲁棒线性预编码方案具有相同级数的计算复杂度。第二种情况为收发两端具有不同的不完美信道状态信息。例如有限反馈的MIMO系统,如果发送端和接收端直接使用两个不同的信道状态信息,系统性能会极度恶化。针对这种情况,我们提出了一种简单的匹配方案。随后在SVD, GMD和UCD联合预编码检测算法上分析了匹配方案能够减小性能损失的原因。随后,利用香农率失真理论,我们得出了信道量化误差方差的近似表达式,提高了匹配方案的实用性。仿真结果表明在不同的信道估计误差和矢量量化误差下,匹配方案都要远远好于不匹配的方案,对信道量化误差方差的近似是正确的。4.提出了基于三种不同准则的低复杂度多用户多流矢量扰动预编码算法(MUMS-VP):迫零扩展信道逆矢量扰动(ZF ECI-VP)算法,最小总均方误差矢量扰动(MTMSE-VP)算法Ⅰ和Ⅱ,最大信漏噪比矢量扰动(MSLNR-VP)算法。推导了MTMSE-VP和MSLNR-VP的可达速率。分析和仿真结果表明ZFECI-VP与BD-VP等价,MTMSE-VPⅡ具有最大的可达速率。无论是固定调制还是在自适应调制,MTMSE-VP和MSLNR-VP的误码率都低于块对角化矢量扰动算法的误码率,MSLNR-VP具有最低的误码率。另外,所提算法都有比块对角化矢量扰动算法低得多的计算复杂度。更多还原

【Abstract】 In recent years, with the rapid increase of data services, e.g., real-time multimedia communications and high-speed Internet access, enhancing the transmission rate, bandwidth efficiency and quality of service (Qos) of communication systems has become a problem demanding prompt solution. Orthogonal frequency division multiplexing (OFDM) is one key technology of broadband wireless communication, because it can resist inter-symbol interference (ISI) caused by multi-path fading. While Multiple-input multiple-output (MIMO) can make use of space resource to increase the channel capacity, spectral efficiency and communication reliability significantly without increasing the transmit power and bandwidth. The combination of MIMO and OFDM is widely regarded as the core scheme of future wireless communication systems. This dissertation deals with the precoding techniques of OFDM systems and MIMO systems respecitively. The main achievements and results of this dissertation are listed as follows:1. In OFDM systems, the very different output SNR values of the subchannels will lead to poor bit error performance when equal bit allocation (EBA) is adopted. So, we proposed three novel joint precoder and detector (JPD) schemes that can transform all subchannels of an OFDM system into subchannels with identical channel gain. Two schemes are designed based on ZF criterion and the other scheme based on minimum mean square error (MMSE) criterion. Numerical analysis helps us to obtain the theoretical approximate BER values of the JPD schemes. Simulation results verify the numerical analysis and confirm that the performance of our proposed JPD schemes greatly outperform linear equalizer with EBA at high SNR values. JPD schemes outperforms ZF equalizer with EBA about 8 dB for QPSK modulation and about 6dB for 16QAM modulation at BER=10-3.2. A lattice-reduction aided linear MMSE (LMMSE) precoding with limited feedforward for spatial correlated MIMO channels is proposed to achieve lower BER by use of complex Lenstra-Lenstra-Lovasz (CLLL) algorithm. Then, we prove that the proposed algorithm obtains the full transmit diversity in correlated MIMO channels through diversity order derivation. The simulation results show that in TDD MIMO systems assuming correlated block flat fading channel, with QPSK modulation and MMSE uplink channel estimator at the transmitter, the uncoded BER of LR-aided LMMSE precoder is lower than that of traditional LMMSE precoder when Eb/NO is greater than 10dB, while with (2,1,3) convolutional channel coding and Viterbi decoding the coded BER of LR-aided LMMSE precoder is lower than that of traditional LMMSE precoder when Eb/NO is greater than 12dB at all correlation coefficients. Furthermore, the LR-aided LMMSE precoding also obtains the full transmit diversity M (the number of transmit antenna).3. In point to point MIMO systems, uniform channel decomposition (UCD) has been proven to be optimal in bit error rate (BER) performance and strictly capacity lossless when perfect channel state information (CSI) are assumed to be available at both the transmitter and the receiver side. However, in practice, CSI can be obtained at the transmitter if there is reciprocity between the forward and reverse channels in time division duplex (TDD) systems or can be conveyed from the receiver to the transmitter via a feedback channel. In any case, channel error is inevitable. In the first section, we consider the case of imperfect CSI at the receiver (CSIR) and imperfect CSI at the transmitter (CSIT) are the same. A novel robust UCD scheme and corresponding optimal robust power allocation are proposed, which are capable of improving the BER performance compared to the conventional UCD scheme and the robust linear precoding scheme. Simulation results show that the MIMO channel capacity of the proposed robust UCD scheme is higher than that of the conventional UCD scheme. By deriving and analyzing the MIMO channel capacity lower bound of the robust UCD scheme, we prove that our proposed robust UCD scheme is capacity lossless in a channel estimation error existing MIMO system. In the second section, we consider the case of imperfect CSIR and imperfect CSIT are different. A simple practical scheme for mismatch between CSIR and CSIT in limited feedback MIMO joint transceiver design is proposed. The proposed scheme designs the nulling vector or matrix at the receiver side with the quantized estimated CSI, which seems losing some information about channel, but eliminates the mismatch between CSIR and CSIT that may cause greater deterioration than the lost channel information. Moreover, we applied our scheme to three popular joint transceiver designs based on ZF and MMSE criterion respectively (SVD, GMD and UCD) and analyzed why the matching architecture of CSI will achieve better performance. Subsequently, using Shannon rate-distortion theory and generalized Lloyd vector quantization algorithm (GLA), we obtain the approximate variance of channel quantization error which can be substituted into the expression of nulling matrix of robust UCD scheme. The approximation enhances the practicability of our proposed robust UCD scheme in the more pratical scenario that imperfect CSIR and imperfect CSIT are different. The first set of simulation results show that the proposed matching architecture outperforms the conventional architecture at different channel estimation errors and vector quantization errors. The second set of simulation results in BER and ergodic capacity show the validation of the approximation of the variance of channel quantization error.4. Three criteria based multi-user multi-stream VP (MUMS-VP) algorithms are proposed:zero forcing expanded channel inversion (ZF ECI)-VP algorithm, minimum total mean square error criterion (MTMSE) based two MUMS-VP algorithms and maximum signal to leakage and noise ratio (MSLNR) criterion based MUMS-VP algorithm. The general expression of achievable rates of MUMS-VP algorithms is derived. Analysis and simulation results show that the proposed ZF MUMS-VP is equivalent to BD-VP, while MTMSE MUMS-VPⅡhas the maximum achievable sum rates among these algorithms. All proposed algorithms have much lower complexity than BD-VP. Furthermore, MTMSE MUMS-VPⅠ,Ⅱand MSLNR MUMS-VP greatly outperform BD-VP in BER performance for both fixed modulation scenario and adaptive modulation scenario.更多还原