Optimal User Pairing and Power Allocation in 5G Satellite Random Access Networks

In this paper, we study a joint user pairing and power allocation problem in the 5th generation (5G) satellite random access (RA) networks, where some user equipments (UEs) are assisted by relay satellite UEs to establish satellite access. We aim to maximize the total sum rate of the RA system by jointly optimizing user pairing and power allocation. The above joint optimization problem is a non-convex mixed-integer problem, which is challenging to solve. To solve this problem, we decompose it into two subproblems. Firstly, a problem for optimal user pairing is formulated to find the optimal user pairing relationship. To solve this subproblem efficiently, a Q-learning based distributed user pairing algorithm (QL-DUPA) is proposed, which converts the user pairing problem to a Q-learning process. The Q-learning process can achieve a near-optimal solution and is practically feasible. Then, a problem for optimal power allocation is formulated to find the optimal power allocation coefficients in each user pair. The subproblem is convex and the optimal solution is obtained using convex optimization. Next, a satellite RA scheme with collision resolution is proposed based on the joint optimization of user pairing and power allocation, and we analyze its total sum rate. Simulation results show that the proposed satellite RA scheme with collision resolution greatly outperforms the existing schemes in terms of total sum rate.