MIMO信道预编码技术研究
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摘要
在多输入多输出(MIMO)系统中,为了提高频谱利用率和功率利用率,人们在发射端对信道状态信息(CSI)加以利用,提出了MIMO预编码的概念。然而,在实际中,绝大多数情况下发射端CSI是通过接收端反馈来获得,这使得发射端只能得到非理想CSI。鉴于此,本文重点对发射端具有非理想CSI的MIMO信道预编码问题进行了研究,取得的主要创新性成果如下。
针对MIMO系统,首先,基于均值反馈信道模型,在传统的注水方案基础上,提出一种MIMO系统的联合功率分配与自适应调制方案。此方案将注水算法与自适应调制相结合,对注水定理功率分配的结果进行二次分配。这种非连续的功率分配方案,在功率分配的同时自适应确定了调制方式。然后,在有限比特反馈模型下,讨论了基于格拉斯曼空间装箱(Grassmannian spacepackings)的MIMO系统波束成形和功率分配,证明了波束成形矩阵的码本设计问题可以转化为最优格拉斯曼装箱问题,并且基于MMSE准则给出了波束成形和功率分配方案。最后,由于格拉斯曼装箱方法只适用于高斯信道,针对其它类型的信道,本文又给出了一种利用改进的Lloyd矢量量化算法进行码本设计的方法;并且证明了,在大信噪比条件下,矢量量化方法与格拉斯曼装箱方法是等效的。
针对MIMO-OFDM系统,首先,研究了空间分集MIMO-OFDM系统的预编码,给出了波束成形、功率分配和自适应调制相结合的预编码方案。此方案利用格拉斯曼空间装箱原理预先构建波束成形矢量的码本,在接收端确定最优波束成形矢量并利用有限个比特反馈其索引到发射端。在发射端利用“贪婪算法”进行功率分配和自适应调制。与现有预编码方案相比能够大大减少反馈数据量。然后,研究了空间复用MIMO-OFDM系统的预编码,提出了一种基于插值的矢量量化预编码方案。该方案根据载波相关性将载波分簇,每个载波簇的预编码矩阵由接收端根据容量最大化准则在码本中选择,并利用有限个比特反馈到发射端。发射端通过插值的方法获得所有载波的预编码矩阵。在此方案中,码本的构建通过“矢量量化”方法实现。最后,将空间分集MIMO-OFDM系统基于格拉斯曼装箱的预编码推广到多用户MIMO-OFDMA系统,给出了多用户情况下的一种自适应预编码方案。
针对MIMO-STBC系统,在信道均值反馈模型下,以最小化平均误码率为准则,给出了发射端最优波束成形器的设计方法,并讨论了波束上的功率分配方案。在有限反馈模型下,讨论了MIMO-STBC系统的预编码。证明了预编码矩阵码本的设计问题等价为格拉斯曼空间装箱问题,给出了基于最小化符号错误概率上限的预编码矩阵选择策略。仿真证明,以同样的反馈比特数,有限反馈的预编码方案比天线子集选择方案有明显的性能提升。最后,讨论了基于自动重传请求(ARQ)协议的STBC系统多速率调制问题,给出了固定速率调制和多速率调制的系统吞吐量;并且证明了多速率调制吞吐量的极限为香农容量。
In multiple input multiple output(MIMO)systems,the precoding schemes at the transmitter,which uses the channel state information(CSI),are proposed to improve the spectrum efficiency and the power efficiency.However,in practice,the CSI at the transmitter is obtained from the receiver,which results in imperfect CSI at the transmitter.This dissertation deals with the precoding problems in MIMO systems with imperfect CSI at the transmitter and the main contributions achieved are as follows.
In MIMO systems,firstly,using the channel mean feedback model,we improve the traditional water filling algorithm and present a joint power allocation and adaptive modulation scheme.In this scheme,the power determined by the water filling algorithm is reallocated with the combination of adaptive modulaiotn.The discontinuous power allocation scheme determines the allocated power and modulation constellation on each subchannel simultaneously.Then,using the limied feedback model,we discuss the beamforming and power allocation for MIMO systems based on Grassmannian space packings.The codebook design of beamforming matrices is proved to be a problem of Grassmannian space packings and the beamforming and power allocation scheme is presented based on the MMSE criterion.Finally,since the Grassmannian space packings can only be applied on Gaussian channels,as for other channels, we present a codebook design method by using ameliorated Lloyd vector quantization algorithm.Additionally,the vector quantization algorithm is proved equivalent to Grassmannian space packings at high SNR.
In MIMO-OFDM systems,firstly,the precoding for space diversity MIMO-OFDM systems is studied.A precoding scheme including beamforming,power allocation and adaptive modulaiton is presented.By using the beamforming codebook constructed according to Grassmannian space packing,the optimal beamforming vector is determined at the receiver and its index is conveyed to the transmitter.Then the power and bits are allocated to each subcarrier using 'greedy algorithm' at the transmitter. The feedback data are greatly decreased compared with the previous schemes while maintaining a comparatively large capacity.Then,we study the precoding for space multiplexing MIMO-OFDM systems.Here,we propose an interpolation-based vector quantization precoding scheme.In this scheme,the subcarriers are divided into clusters whose precoding matrices are selected in a codebook aiming at capacity maximization at the receiver.And the index of precoding matrix for each cluster is conveyed back to the transmitter,which obtains all the subcarriers' precoding matrices through interpolation.In this scheme,the codebook is designed through vector quantization medthod.At last,the precoding schemes for space diversity MIMO-OFDM systems is extended to multiuser space diversity MIMO-OFDM systems and a multiuser adaptive precoding scheme is provided.
In space-time block coding systems,using the channel mean feedback model, the design of optimal beanforming filters under the minimum average bit error rate (BER)criterion is presented,and the power allocation method on each beam is discussed. When the feedback bandwidth is limited,the precoding scheme for STBCMIMO systems is proposed.The codebook design is proved to be a Grassmannian space packings problem and the precoding matrices selection strategy for the purpose of minimizing the upper bound of the symbol error rate(SER)is presented.Simulation results show the limited feedback precoding scheme outperforms the antenna selection scheme with the same number of feedback bits.Finally,the multiple rate modulaiton scheme based on ARQ protocol is studied.The throughputs of constant rate modulaiton and multiple rate modulaiton are deduced.Further,we prove the upper bound of the throughput of multiple rate modulaiton is Shannon capacity.
针对MIMO系统,首先,基于均值反馈信道模型,在传统的注水方案基础上,提出一种MIMO系统的联合功率分配与自适应调制方案。此方案将注水算法与自适应调制相结合,对注水定理功率分配的结果进行二次分配。这种非连续的功率分配方案,在功率分配的同时自适应确定了调制方式。然后,在有限比特反馈模型下,讨论了基于格拉斯曼空间装箱(Grassmannian spacepackings)的MIMO系统波束成形和功率分配,证明了波束成形矩阵的码本设计问题可以转化为最优格拉斯曼装箱问题,并且基于MMSE准则给出了波束成形和功率分配方案。最后,由于格拉斯曼装箱方法只适用于高斯信道,针对其它类型的信道,本文又给出了一种利用改进的Lloyd矢量量化算法进行码本设计的方法;并且证明了,在大信噪比条件下,矢量量化方法与格拉斯曼装箱方法是等效的。
针对MIMO-OFDM系统,首先,研究了空间分集MIMO-OFDM系统的预编码,给出了波束成形、功率分配和自适应调制相结合的预编码方案。此方案利用格拉斯曼空间装箱原理预先构建波束成形矢量的码本,在接收端确定最优波束成形矢量并利用有限个比特反馈其索引到发射端。在发射端利用“贪婪算法”进行功率分配和自适应调制。与现有预编码方案相比能够大大减少反馈数据量。然后,研究了空间复用MIMO-OFDM系统的预编码,提出了一种基于插值的矢量量化预编码方案。该方案根据载波相关性将载波分簇,每个载波簇的预编码矩阵由接收端根据容量最大化准则在码本中选择,并利用有限个比特反馈到发射端。发射端通过插值的方法获得所有载波的预编码矩阵。在此方案中,码本的构建通过“矢量量化”方法实现。最后,将空间分集MIMO-OFDM系统基于格拉斯曼装箱的预编码推广到多用户MIMO-OFDMA系统,给出了多用户情况下的一种自适应预编码方案。
针对MIMO-STBC系统,在信道均值反馈模型下,以最小化平均误码率为准则,给出了发射端最优波束成形器的设计方法,并讨论了波束上的功率分配方案。在有限反馈模型下,讨论了MIMO-STBC系统的预编码。证明了预编码矩阵码本的设计问题等价为格拉斯曼空间装箱问题,给出了基于最小化符号错误概率上限的预编码矩阵选择策略。仿真证明,以同样的反馈比特数,有限反馈的预编码方案比天线子集选择方案有明显的性能提升。最后,讨论了基于自动重传请求(ARQ)协议的STBC系统多速率调制问题,给出了固定速率调制和多速率调制的系统吞吐量;并且证明了多速率调制吞吐量的极限为香农容量。
In multiple input multiple output(MIMO)systems,the precoding schemes at the transmitter,which uses the channel state information(CSI),are proposed to improve the spectrum efficiency and the power efficiency.However,in practice,the CSI at the transmitter is obtained from the receiver,which results in imperfect CSI at the transmitter.This dissertation deals with the precoding problems in MIMO systems with imperfect CSI at the transmitter and the main contributions achieved are as follows.
In MIMO systems,firstly,using the channel mean feedback model,we improve the traditional water filling algorithm and present a joint power allocation and adaptive modulation scheme.In this scheme,the power determined by the water filling algorithm is reallocated with the combination of adaptive modulaiotn.The discontinuous power allocation scheme determines the allocated power and modulation constellation on each subchannel simultaneously.Then,using the limied feedback model,we discuss the beamforming and power allocation for MIMO systems based on Grassmannian space packings.The codebook design of beamforming matrices is proved to be a problem of Grassmannian space packings and the beamforming and power allocation scheme is presented based on the MMSE criterion.Finally,since the Grassmannian space packings can only be applied on Gaussian channels,as for other channels, we present a codebook design method by using ameliorated Lloyd vector quantization algorithm.Additionally,the vector quantization algorithm is proved equivalent to Grassmannian space packings at high SNR.
In MIMO-OFDM systems,firstly,the precoding for space diversity MIMO-OFDM systems is studied.A precoding scheme including beamforming,power allocation and adaptive modulaiton is presented.By using the beamforming codebook constructed according to Grassmannian space packing,the optimal beamforming vector is determined at the receiver and its index is conveyed to the transmitter.Then the power and bits are allocated to each subcarrier using 'greedy algorithm' at the transmitter. The feedback data are greatly decreased compared with the previous schemes while maintaining a comparatively large capacity.Then,we study the precoding for space multiplexing MIMO-OFDM systems.Here,we propose an interpolation-based vector quantization precoding scheme.In this scheme,the subcarriers are divided into clusters whose precoding matrices are selected in a codebook aiming at capacity maximization at the receiver.And the index of precoding matrix for each cluster is conveyed back to the transmitter,which obtains all the subcarriers' precoding matrices through interpolation.In this scheme,the codebook is designed through vector quantization medthod.At last,the precoding schemes for space diversity MIMO-OFDM systems is extended to multiuser space diversity MIMO-OFDM systems and a multiuser adaptive precoding scheme is provided.
In space-time block coding systems,using the channel mean feedback model, the design of optimal beanforming filters under the minimum average bit error rate (BER)criterion is presented,and the power allocation method on each beam is discussed. When the feedback bandwidth is limited,the precoding scheme for STBCMIMO systems is proposed.The codebook design is proved to be a Grassmannian space packings problem and the precoding matrices selection strategy for the purpose of minimizing the upper bound of the symbol error rate(SER)is presented.Simulation results show the limited feedback precoding scheme outperforms the antenna selection scheme with the same number of feedback bits.Finally,the multiple rate modulaiton scheme based on ARQ protocol is studied.The throughputs of constant rate modulaiton and multiple rate modulaiton are deduced.Further,we prove the upper bound of the throughput of multiple rate modulaiton is Shannon capacity.
引文
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