Non-Orthogonal Multiple Access Based Integrated Terrestrial-Satellite Networks

TLDR

The study investigates downlink transmission in a NOMA‑based integrated terrestrial‑satellite network, proposing a channel‑quality‑based satellite user selection and a max‑min terrestrial user pairing to maximize minimum channel correlation. The authors employ multi‑antenna beamforming and power allocation, analyze terrestrial and satellite capacities separately, and then use a joint iterative algorithm with an interference‑temperature constraint to maximize total system capacity. Numerical simulations show that the proposed user‑pairing scheme and joint optimization outperform existing algorithms in overall system capacity.

Abstract

In this paper, we investigate the downlink transmission of a non-orthogonal multiple access (NOMA)-based integrated terrestrial-satellite network, in which the NOMA-based terrestrial networks and the satellite cooperatively provide coverage for ground users while reusing the entire bandwidth. For both terrestrial networks and the satellite network, multi-antennas are equipped and beamforming techniques are utilized to serve multiple users simultaneously. A channel quality-based scheme is proposed to select users for the satellite, and we then formulate the terrestrial user pairing as a max-min problem to maximize the minimum channel correlation between users in one NOMA group. Since the terrestrial networks and the satellite network will cause interference to each other, we first investigate the capacity performance of the terrestrial networks and the satellite networks separately, which can be decomposed into the designing of beamforming vectors and the power allocation schemes. Then, a joint iteration algorithm is proposed to maximize the total system capacity, where we introduce the interference temperature limit for the satellite since the satellite can cause interference to all base station users. Finally, numerical results are provided to evaluate the user paring scheme as well as the total system performance, in comparison with some other proposed algorithms and existing algorithms.