This paper investigates the uplink (UL) transmit design for massive multiple-input multiple-output (MIMO) low-earth-orbit (LEO) satellite communication (SATCOM), where the long-term statistical channel state information is utilized at the user terminals (UTs). We consider that the uniform planar arrays are deployed at both the satellite and UTs, and derive the UL massive MIMO LEO satellite channel model. With the aim to achieve the ergodic sum rate capacity, we show that the rank of each UT's optimal transmit covariance matrix does not exceed that of its channel correlation matrix at the UT sides. This reveals the maximum number of independent data streams that can be transmitted from each UT to the satellite. We further show that the design of the transmit covariance matrices can be reduced into that of lower-dimensional matrices, for which a stochastic programming based algorithm is developed by exploiting the optimal lower-dimensional matrices' structure. To reduce the computational complexity, we invoke the asymptotic programming and develop a computationally efficient algorithm to compute the transmit covariance matrices. Simulations show that the proposed UL transmit strategies are superior to the conventional schemes, and the low-complexity asymptotic programming based UL transmit design can attain near-optimal performance in massive MIMO LEO SATCOM.
翻译:本文调查了用户终端(UTs)使用长期统计渠道状态信息的用户终端(LEO)卫星通信(SATCOM)的大规模多投入多输出量(MIMO)低地轨道(LEO)卫星通信(SATCOM)传输设计。我们认为,在卫星和UTs中都部署了统一的分布式阵列,并得出了UL大规模大型MIMO LEO卫星信道模型。为了实现超低空间总和率能力,我们显示,每个UT的最佳传输变量矩阵的级别不超过UT两边的频道相关矩阵的级别。这显示了从每个UTS向卫星传输的独立数据流的最大数量。我们进一步表明,传输变量矩阵的设计可以缩减为低空间矩阵的设计,为此,通过利用最佳的低空间矩阵结构开发了基于透析的编程算算算算算法。为了降低计算复杂性,我们引用了每个UTF的最佳配置和开发了一种计算高效的算法,以将传输到接近轨道的频率矩阵系统。我们进一步展示了基于U-L的高级设计式设计系统。