User scheduling for non-orthogonal multiple access-enabled 5G aeronautical mobile airport communications system

Physical Communication(2024)

Cited 0|Views1
No score
Abstract
The recent concept of aeronautical mobile airport communications system with the 5th generation mobile communication technology (5G AeroMACS) for enhancing real-time and efficient flight information transmission has attracted wide attention from the civil aviation industry. In addition, non-orthogonal multiple access (NOMA) is also a promising solution to further improve the sum rate. However, the fundamental limit of the conventional 5G AeroMACS is that, the base station (BS) equipped with dozens of antennas can not support more users than its number of antennas using the same time-frequency resources. To break this limit, for the first time, we investigate user scheduling policies for the integration of NOMA in 5G AeroMACS, i.e., 5G AeroMACS-NOMA, employing a half-duplex (HD) BS for serving multiple HD downlink users simultaneously. The two proposed user scheduling policies are obtained from the sub-optimal solution of mixed combinatorial non-convex optimization problems for the maximization of the achievable sum rate of the entire system. To mitigate the inter-beam interference (IBI), a user clustering algorithm based on the principle of maximizing the channel spatial correlation is designed, and an iterative power allocation algorithm is utilized for maximizing the achievable sum rate of the entire system. Furthermore, to mitigate the serious error propagation caused by the nature in NOMA, a scenario with user division is considered, and an user scheduling policy based on successive convex approximation is designed to strike a balance between computational complexity and optimality. Simulation results show that the proposed 5G AeroMACS-NOMA schemes can achieve a higher achievable sum rate compared with conventional 5G AeroMACS.
More
Translated text
Key words
5G AeroMACS,Non-orthogonal multiple access,Resource allocation,Multiple-input-multiple-output
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined