Massive multiple-input multiple-output (MIMO) is promising for low earth orbit (LEO) satellite communications due to the potential in enhancing the spectral efficiency. However, the conventional fully digital precoding architectures might lead to high implementation complexity and energy consumption. In this paper, hybrid analog/digital precoding solutions are developed for the downlink operation in LEO massive MIMO satellite communications, by exploiting the slow-varying statistical channel state information (CSI) at the transmitter. First, we formulate the hybrid precoder design as an energy efficiency (EE) maximization problem by considering both the continuous and discrete phase shift networks for implementing the analog precoder. The cases of both the fully and the partially connected architectures are considered. Since the EE optimization problem is nonconvex, it is in general difficult to solve. To make the EE maximization problem tractable, we apply a closed-form tight upper bound to approximate the ergodic rate. Then, we develop an efficient algorithm to obtain the fully digital precoders. Based on which, we further develop two different efficient algorithmic solutions to compute the hybrid precoders for the fully and the partially connected architectures, respectively. Simulation results show that the proposed approaches achieve significant EE performance gains over the existing baselines, especially when the discrete phase shift network is employed for analog precoding.
翻译:由于有可能提高光谱效率,因此低地球轨道(LEO)卫星通信(MIMO)的大规模多输出多输出(MIMO)前景良好,因为有可能提高光谱效率,低地球轨道(LEO)卫星通信(LEO)的热度多输出(MIMO)前景良好。然而,常规的完全数字预编码结构可能会导致高执行复杂性和能源消耗。在本论文中,为低地球轨道大型MIMO卫星通信的下行连接操作开发了混合的模拟/数字预编码解决方案。通过在发射机中利用缓慢变化的统计频道国家信息,我们开发了一种高效的混合预编码设计作为能源效率最大化(EEE)的问题。基于这一方法,我们进一步开发了两种不同的高效的离散相相位转换网络配置方法,完全和部分连接的结构。由于EEE优化的问题是非连接的,因此一般难以解决。为了使EEE最大化之前的运行问题变得易于理解,我们采用了一种封闭式的紧凑紧紧的算法,以获得完全的数字预编码。基于这个方法,我们进一步开发了两种不同的高效的算法转变方法,以便在分别连接的模型上,在模拟模型中分别进行模拟模型的模型的模型的模型的模型上,特别是模拟式的模型的模型的模型的模型的模型的模型的模型的模型的模型的模型的模型的模型的升级。