Hybrid Analog/Digital Precoding for Downlink Massive MIMO LEO Satellite Communications

Abstract

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.

Optimizing Massive MIMO Design for Non Uniform Traffic in Broadband Telecommunication Satellites Networks

“…In particular, M-MIMO CSI estimation complexity reduction adopting statistical CSI is investigated in [13]. The use of an hybrid analog/digital precoding exploiting the statistical CSI at the transmitter is investigated in [14]. Similarly to [12], the idea to use a codebook of 1 Typically the precoding is implemented at the gateway to reduce the onboard complexity burden.…”