在多用户MIMO系统下行链路中,块对角化(Block diagonalization,BD)预编码算法的和速率性能要优于匹配滤波算法(Matched filter,MF)和迫零算法(Zero-forcing,ZF)。然而,传统的BD算法利用矩阵分解来构造除当前用户的其他所有用户信道的零空间,需要O(N2)浮点运算次数(Float point operations,FLOPs)。当基站的天线数N趋向于大规模时,BD算法计算复杂度巨大。本文提出一种基于投影子方法构造其他用户合成信道的零空间的BD算法,该算法仅需O(N)FLOPs。仿真表明:同传统的BD算法相比,本文所提出的低复杂度BD算法显著地降低了实现复杂度,而和速率性能损失微小,仍然优于MF和ZF,并且当N趋向于大规模时,它的和速率性能趋向于传统的BD算法和SVD算法。
To improve the reliable performance of information transmission in cooperative relay networks, the scheme of the max-rate spatial channel pairing （SCP） based on maximum ratio combining （MRC） is proposed. The scheme includes three steps： channel phase cancellation, MRC, and SCP. Eventually, the solution of the scheme is modeled as convex optimization. The objective function of the optimization problem is to maximize the transmission rate and the optimization variable is the strategy of pairing between the uplink spatial sub-channels of each user and the corresponding downlink spatial ones. The theorem of the arrangement inequalities is adopted to obtain the approximate closed-form solution of the optimal pairing for this convex optimization. Simulation results demonstrate that compared to the existing distributed space-time block coding and coherent combined schemes without SCP, the proposed max-rate SCP plus MRC algorithm achieves appreciable improvements in symbol error rate in medium and high signal-to-noise ratio regimes. The achievable performance gain is due to the use of maxrate SCP.
考虑到天线选择(AS)具有实现简单和性能好等优点,通过仿真评估在不同中继策略场景下天线选择的性能。评估方法如下:中继站第1时隙采用最大比合并算法(MRC),第2时隙选择中继处理后具有最大信道增益的单天线进行信号传输。仿真结果表明:与现有的分布式空时码(DSTBC)和最大比合并、最大比合并和匹配滤波(MF)算法相比,最大比合并加天线选择混合方案在转发重传(AF)和译码重传(DF)策略下都能够提供更优的合速率与误码性能;并且在中继站采用译码转发策略时,该方案表现出优于采用放大转发策略的情形。例如,当误码率(SER)等于10-3时,译码转发策略具有1 d B的信噪比(SNR)增益。
为进一步提高多输入多输出(MIMO)双向中继系统性能,该文在梯度下降法的基础上,引入用户端功率分配和发射预编码与接收波束成形,结合中继站波束成形矩阵和分配功率相,构成一个完整的联合交替迭代结构(AIS);通过固定变量循环计算,逐个得到各个变量的最优值。仿真表明,与梯度下降法、迫零和最小均方误差加注水功率分配法相比,该文交替迭代结构方法的速率有所提高,误码性能提高较明显。当误码率等于10-2时,与3种算法中最优的梯度下降法相比,该文方法可获得2.5 d B的信噪比增益。
