Hybrid OMA/NOMA Mode Selection and Resource Allocation in Space-Air-Ground Integrated Networks | IEEE Journals & Magazine | IEEE Xplore

Hybrid OMA/NOMA Mode Selection and Resource Allocation in Space-Air-Ground Integrated Networks


Abstract:

Ground networks are facing severe challenges posed by the conflict between the increasing number of terminals and limited coverage and network resources. The space-air-gr...Show More

Abstract:

Ground networks are facing severe challenges posed by the conflict between the increasing number of terminals and limited coverage and network resources. The space-air-ground integrated network (SAGIN) is a promising solution due to its global coverage and multi-dimensional heterogeneous resources. In this paper, we investigate a scenario, where the terminals are served by networks in SAGIN with hybrid orthogonal multiple access (OMA)/non-OMA (NOMA) transmission. According to the network characteristics in SAGIN, such as communication link, movement, and communication resources, we build up an utility function. We further formulate the problem of joint hybrid OMA/NOMA mode selection and resource allocation to maximize the system utility. Due to the non-convexity of the formulated problem, we decompose the original problem into two subproblems, which can be solved by the successive convex approximation, Lagrange dual method, and deep Q-network (DQN) learning, respectively. Moreover, to guarantee the constraints, an efficient reward function is further designed in DQN. Finally, simulation results show that compared with the benchmark schemes, the proposed algorithm can achieve better performance in terms of the achievable sum rate, the average achievable rate, and outage probability. Compared with the existing algorithms, the proposed algorithm can always facilitate terminals to flexibly select the suitable transmission mode according to the characteristics of the connected network, achieving better system performance.
Published in: IEEE Transactions on Vehicular Technology ( Volume: 74, Issue: 1, January 2025)
Page(s): 699 - 713
Date of Publication: 30 August 2024

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