基于不完全信道信息的MIMO双向中继系统线性预编码算法#br#

针对配置两个通信节点的多输入多输出双向中继系统,提出一种基于不完全信道状态信息的预编码设计方案,该方案综合考虑信道估计误差与信道反馈延迟的情况。在中继发射功率受限的条件下,以最小均方误差为准则设计以预编码矩阵为变量的优化问题,提出矩阵分解和联合迭代两种线性预编码算法。矩阵分解法通过矩阵分解推导得到中继矩阵的闭式解;联合迭代法利用迭代算法交替迭代来联合优化预编码矩阵和接收端处理矩阵,直到算法收敛数。仿真结果表明,随着信噪比由0到25 dB逐渐增大,与现有方案相比,矩阵分解法能有效地降低系统的误比特率,联合迭代法能获得最佳的系统性能提升。     

双向中继网络中基于正交预编码的盲干扰抵消

双向中继网络(two way relay network, TWRN)在提高频谱效率的同时会引入额外的自干扰,针对放大转发模式下的自干扰抵消问题,从消除非理想信道估计带来的剩余自干扰着手,提出一种基于正交预编码的盲干扰抵消方案。新方案通过对端节点信号进行“右乘”正交预编码,将期望目标信号与自干扰信号映射到不依赖于信道状态信息的正交子空间,实现未知信道状态下自干扰抵消和期望信号分离,从而消除非理想信道估计带来的剩余自干扰对TWRN性能的影响,提高了系统的鲁棒性。在此基础上,通过推导平均误比特率(bit error rate, BER)的闭合表达式和渐进表达式,分析不同方案下信道估计误差对平均BER的影响,并通过仿真对比验证了理论推导的正确性。     

Improved scheme with cooperative diversity based on distributed space-time block coding

An improved scheme with cooperative diversity based on distributed space-time block coding (WCD-DSTBC) is proposed, which effectively achieves diversity gains and improves the performance of the system by sharing some single-antenna users' antennas to form a virtual antenna array and combining with distributed space-time block coding (DSTBC) mode. Then the relation between the system BER and the interuser BER for WCD-DSTBC scheme is theoretically derived and the closed-form expression of BER for WCD-DSTBC system is obtained. The simulation results show that the proposed WCD-DSTBC scheme achieves distinct gains over the non-cooperative multi-carrier CDMA (MC-CDMA) system. When system BER is le-3 and interuser BER is le-3, about 2.5 dB gain can be gotten. When interuser channel state information (CSI) outgoes the users' individual CSI, about 3 dB gain is also achieved.     

MISO无线携能通信系统保密波束形成方法

为有效应对多输入单输出(multiple input single output, MISO)无线携能通信(simultaneous wireless information and power transfer，SWIPT)系统中的信息安全问题，提出人工噪声(artifical noise, AN)辅助的波束形成方案, 并进一步将这一问题表述为用户需求限制的功率控制问题。然而, 该问题具有典型的非凸复杂性, 其最优解无法在多项式时间内得到有效解决。为此，基于必要简化, 提出了双层优化算法来快速求取其次优解; 同时, 又进一步把该双层算法推广到非理想信道条件下, 构建了鲁棒波束形成方法。仿真实验表明，与经典迫零算法相比，双层算法具有更好的性能，且更具鲁棒性；而且，随着信道估计误差的增加，双层优化算法的优势更加明显。     

能量有效的NOMA多用户-多信道匹配算法

针对非理想信道状态信息(channel state information, CSI)下面向海量用户的无线资源高效分配难题,通过引入非正交多址(non-orthogonal multiple access, NOMA)技术提出了一种能量有效的多用户-多信道匹配方案。首先,考虑用户中断概率约束,建立以最大化系统能量效率为目标的非理想CSI蜂窝下行NOMA系统信道和功率联合分配优化问题;然后,将建立的含概率约束的优化问题转化为非概率约束优化问题,并从中解耦出用户-信道匹配优化问题;最后,将面向能量效率的NOMA用户-信道匹配优化问题映射为婚姻匹配问题,进而提出一种高效低复杂度的双边匹配算法实现了多用户-多信道的动态匹配。仿真结果表明,提出的匹配算法性能优于传统匹配算法,能够提供更高的系统能效、实现更低的用户中断概率且收敛速度更快。     

能量有效的NOMA多用户-多信道匹配算法

针对非理想信道状态信息(channel state information, CSI)下面向海量用户的无线资源高效分配难题,通过引入非正交多址(non-orthogonal multiple access, NOMA)技术提出了一种能量有效的多用户-多信道匹配方案。首先,考虑用户中断概率约束,建立以最大化系统能量效率为目标的非理想CSI蜂窝下行NOMA系统信道和功率联合分配优化问题;然后,将建立的含概率约束的优化问题转化为非概率约束优化问题,并从中解耦出用户-信道匹配优化问题;最后,将面向能量效率的NOMA用户-信道匹配优化问题映射为婚姻匹配问题,进而提出一种高效低复杂度的双边匹配算法实现了多用户-多信道的动态匹配。仿真结果表明,提出的匹配算法性能优于传统匹配算法,能够提供更高的系统能效、实现更低的用户中断概率且收敛速度更快。     

稀疏码分多址收发端改进方案的设计

为降低传统稀疏码分多址接入(sparse code multiple access,SCMA)系统的译码复杂度,同时保证系统误比特率(bit error ratio,BER)性能,考虑信道质量因素提出SCMA系统收发端改进方案.在接收端,提出基于信道质量动态选择节点改进消息传递算法(message passing al...     

基于反馈信道状态信息的水声自适应OFDMA

在时变水声信道中, 为了提高自适应正交频分多址(orthogonal frequency division multiple access, OFDMA)在时延反馈信道状态信息(channel state information, CSI)条件下的资源分配性能, 提出多节点反馈CSI的时隙复用接入方法, 降低反馈时延; 提出载波时-频相关系数和载波时-频均值两种反馈CSI表征参数, 通过实验数据分析了两种反馈CSI参数及其对水声自适应OFDMA性能的影响; 提出多节点公平的自适应载波、比特、功率联合分配算法, 在最大功率和节点吞吐量约束条件下最小化系统误比特率。仿真和湖上实验数据的结果显示, 所构建的水声自适应OFDMA系统在多种反馈CSI条件下误比特率均低于交织载波分配, 表明其在实际的水声信道应用中具有良好性能。     

MIMO模型下的多元混合调制DCSK方案

为了提升多输入多输出差分混沌移位键控(multiple input multiple output difference chaotic shift keying, MIMO-DCSK)系统的误码性能, 提出一种多元混合调制MIMO-DCSK方案(M-ary hybrid modulation MIMO-DCSK, MHM-MIMO-DCSK)。首先，将一帧的多元信息拆分, 分别通过混沌扩频码和索引码进行调制, 以实现高效的传输。其次，接收端利用混沌序列的类正交特性消除多天线干扰和多路干扰。最后将多天线的相关运算结果等增益合并, 最终在不需要信道状态信息的前提下获取多径多输入多输出系统的全分集增益。仿真结果表明，所提MHM-MIMO-DCSK比现有的多元MIMO-DCSK拥有更好的误码性能, 尤其是在高阶调制情况下性能提升更明显。     

基于LDPC码与星座旋转准正交STBC的级联编译码方法

在4×4多输入多输出(multiple input multiple output, MIMO)系统中,为了同时达到全分集增益和全速率数据传输,进而达到降低系统误码率及提高系统可靠性的要求,提出将低密度奇偶校验(low density parity check, LDPC)码与基于星座旋转的准正交空时分组码级联的编码方案,并找出了在全数据传输速率的前提下能够获得满分集增益的最优旋转角度。仿真结果表明,该级联编码方案误码率低于传统的LDPC编码与空时分组码级联的编码方案,在误码率为10^-5的情况下,比LDPC码与正交空时分组码级联的编码方案有8 dB左右的增益。     

非理想反馈MIMO信道发射功率的信息论分析

研究了发射端只有非理想信道状态信息反馈的单用户多输入多输出(MIMO)无线通信系统的最优发送策略。当发射端具有信道协方差矩阵信息时,使得平均信道容量达到最大的发射方向和信道状态协方差反馈矩阵的特征矢量相一致,而相应的发射天线上的最优功率分配则难以解析获得。通过研究舒尔-凹函数的性质,对平均信道容量函数进行理论分析,并推导了输入协方差矩阵特征值分布达到信道容量的最优条件,以此探究发射天线上的最优功率分配方案。数值结果验证了上述结论的正确性。     

毫米波大规模MIMO-NOMA系统中基于动态子连接混合结构的预编码设计

针对毫米波大规模多输入多输出-非正交多址接入(massive multiple input multiple output non-orthogonal multiple access, mMIMO-NOMA)系统硬件成本和功耗过大问题, 基于动态子连接混合结构(dynamically sub-connected hybrid architecture, DSC-HA), 提出一种高效预编码方案。首先，在用户分组的基础上, 基于等效信道增益最大化原则, 利用Kuhn-Munkras算法匹配各NOMA簇用户的信道状态信息, 以实现动态天线分组, 进而完成模拟预编码设计。接着, 利用NOMA簇内强用户的等效信道来实现数字预编码设计, 以减小簇间干扰。最后, 通过优化簇内用户间功率分配来减小簇内用户间干扰。仿真结果表明, 基于DSC-HA的预编码方案不但系统和速率优于基于子连接混合结构的预编码方案, 而且能效明显优于基于全连接混合结构和基于全数字结构的预编码方案。     

New method for detection fusion of MAC based on DCM and NP rule

The problem of distributed detection fusion using multiple sensors for remote underwater target detection is studied. Considering that multiple access channel (MAC) schemes are able to offer high efficiency in bandwidth usage and consume less energy than the parallel access channel (PAC), the MAC scheme is introduced into the underwater target detection field. The model of underwater distributed detection fusion based on MAC schemes is established. A new method for detection fusion of MAC based on deflection coefficient maximization (DCM) and Neyman-Pearson (NP) rule is proposed. Under the power constraint of local sensors, this paper uses the DCM theory to derive the optimal weight coefficients and offsets. The closed-form expressions of detection probability and false alarm probability for fusion systems are obtained. The optimal detection performance of fusion systems is analyzed and deeply researched. Both the theory analysis and simulation experiments indicate that the proposed method could improve the detection performance and decrease the error probability effectively under power constraints of local sensors and low signal to noise ratio.     

非理想信道状态信息下的OFDM比特分配算法

提出一种在非理想信道状态信息条件下,以平均误比特率为目标的正交频分复用(OFDM)比特分配算法.该算法对子信道当前频率响应值进行估计,估计值经延时后反馈至发送端,并以此作为自适应比特分配的依据.仿真结果表明,当信道估计器的均方误差小于-15dB时,信道估计误差对自适应OFDM系统的性能影响不大.采用多个信道估计值来确定比特分配可以减小信道信息延时对系统性能的影响,有效提高系统性能.     

基于动态功率阈值降低PAPR的部分传输序列算法

为了改善正交频分复用(orthogonal frequency division multiplexing, OFDM)系统的峰均功率比(peak-to-average power ratio, PAPR)性能,提出了一种基于动态功率阈值的低复杂度部分传输序列(partial transmit sequences, PTS)方法。在新的PTS方法中,引入了基于功率的判别函数,并给出了一种基于功率合理选择阈值的方法。在选取最小的PAPR值进行传输时,只对P-n大于等于阈值的样本信号进行峰值功率的计算。与传统的PTS算法相比,本文提出的算法在保证PAPR性能和误码率的情况下,能够更有效地降低计算复杂度。     

非完美CSI情况下大规模MIMO系统的下行链路能效优化

为了满足密集的用户需求, 正在发展的蜂窝网络增加了移动系统下的能量消耗, 但更广的网络覆盖范围和功耗更低的无线通信系统也给无线通信系统带来了更多的挑战。针对这些持续增长的需求, 本文设计了一种能实现能量效率最大化的多小区大规模多输入多输出(multiple input multiple output, MIMO)系统下行链路的实现方法, 提出了在非完美信道状态信息(channel state information, CSI)情况下包含基站天线数、导频复用因子以及用户数量等参数的信干噪比最佳闭式表达, 通过最大比合并(maximal ratio combining, MRC)接收技术推导出大规模MIMO系统的下行链路频谱效率, 再根据功耗模型得到系统的整体能量效率, 利用交替迭代的优化算法进行优化求解, 得出最大能效时的相关参数数值。由仿真结果可知, 本文所提的多小区大规模MIMO系统的下行链路的实现方法与现有多小区方法相比, 能量效率有12.2%的提升, 并且对于环境的变化有更好的鲁棒性, 对于多小区大规模MIMO系统具有一定参考意义。     

Lattice-reduction-aided MMSE precoding for correlated MIMO channels and performance analysis

The lattice-reduction (LR) has been developed to improve the performance of the zero-forcing (ZF) precoder in multiple input multiple output (MIMO) systems. Under the assumptions of uncorrelated flat fading channel model and perfect channel state information at the transmitter (CSIT), an LR-aided ZF precoder is able to collect the full transmit diversity. With the complex LenstraLenstra-Lova′sz (LLL) algorithm and limited feedforward structure, an LR-aided linear minimum-mean-square-error (LMMSE) precoder for spatial correlated MIMO channels and imperfect CSIT is proposed to achieve lower bit error rate (BER). Assuming a time division duplexing (TDD) MIMO system, correlated block flat fading channel and LMMSE uplink channel estimator, it is proved that the proposed LR-aided LMMSE precoder can also obtain the full transmit diversity through an analytical approach. Furthermore, the simulation results show that with the quadrature phase shift keying (QPSK) modulation at the transmitter, the uncoded and coded BERs of the LR-aided LMMSE precoder are lower than that of the traditional LMMSE precoder respectively when E b / N0 is greater than 10 dB and 12 dB at all correlation coefficients.     

Compressive sensing based multiuser detector for massive MBM MIMO uplink

Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.     

Improved H-infinity channel estimator based on EM for MIMO-OFDM systems

H-infinity estimator is generally implemented in timevariant state-space models,but it leads to high complexity when the model is used for multiple input multiple output with orthogonal frequency division multiplexing (MIMO-OFDM) systems.Thus,an H-infinity estimator over time-invariant system models is proposed,which modifies the Krein space accordingly.In order to avoid the large matrix inversion and multiplication required in each OFDM symbol from different transmit antennas,expectation maximization (EM) is developed to reduce the high computational load.Joint estimation over multiple OFDM symbols is used to resist the high pilot overhead generated by the increasing number of transmit antennas.Finally,the performance of the proposed estimator is enhanced via an angle-domain process.Through performance analysis and simulation experiments,it is indicated that the proposed algorithm has a better mean square error (MSE) and bit error rate (BER) performance than the optimal least square (LS) estimator.Joint estimation over multiple OFDM symbols can not only reduce the pilot overhead but also promote the channel performance.What is more,an obvious improvement can be obtained by using the angle-domain filter.     

Resource allocation with minimum transmit power in multicast OFDM systems

To minimize the total transmit power for multicast service in an orthogonal frequency division multiplexing (OFDM) downlink system, resource allocation algorithms that adaptively allocate subcarriers and bits are proposed. The proposed algorithms select users with good channel conditions for each subcarrier to reduce the transmit power, while guaranteeing each user’s instantaneous minimum rate requirement. The resource allocation problem is first formulated as an integer programming (IP) problem, and then, a full search algorithm that achieves an optimal solution is presented. To reduce the computation load, a suboptimal algorithm is proposed. This suboptimal algorithm decouples the joint resource allocation problem by separating subcarrier and bit allocation. Greedy-like algorithms are employed in both procedures. Simulation results illustrate that the proposed algorithms can significantly reduce the transmit power compared with the conventional multicast approach and the performance of the suboptimal algorithm is close to the optimum.