Abstract
Non-orthogonal multiple access (NOMA) has become the key technology in the future 5G wireless networks. It can achieve multi-user multiplexing in the transmit power domain by allocating different power, which can effectively improve the system capacity and spectral efficiency. Aiming at the problem of high computational complexity and improving system capacity in non-orthogonal multiple access (NOMA) based on orthogonal frequency division multiple access (OFDMA) for 5G wireless cellular networks, this paper proposes an improved low complexity radio resource allocation algorithm for user grouping and power allocation optimization. The optimization model is established with the goal of maximizing system capacity. Through the step-by-step optimization idea, the complex non-convex optimization problem is decomposed into two sub-problems to be solved separately. Firstly, all users are grouped based on the greedy method, and then the power allocation is performed on the sub-carriers of the fixed group. Simulation results show that the proposed algorithm has better system capacity than the existing state-of-the-art algorithms and reduced complexity performance.
Highlights
The rapid development of the mobile Internet and the Internet of Things and the popularization of the application of intelligent terminals have placed higher demands on future wireless networks
In order to reduce the complexity of resource allocation in the non-orthogonal multiple access (NOMA) system, this paper decomposes it into two sub-problems of user grouping and power allocation on sub-carriers and uses the step-by-step solution to obtain the sub-optimal solution of the optimization problem
This section mainly simulated the downlink NOMA system and used MATLAB software to verify the performance of the proposed algorithm
Summary
The rapid development of the mobile Internet and the Internet of Things and the popularization of the application of intelligent terminals have placed higher demands on future wireless networks. In view of the problems in the above research, this paper proposes an improved user grouping and power allocation scheme, aiming to further reduce the complexity of the algorithm and optimize the system capacity. To obtain the desired signal, the receiver where hk , n represents the channel gain of the base station to the k-th user on the n-th subcarrier and can use the successive interference cancellation (SIC) technique [27,28,29] for signal detection. In order to reduce the complexity of resource allocation in the NOMA system, this paper decomposes it into two sub-problems of user grouping and power allocation on sub-carriers and uses the step-by-step solution to obtain the sub-optimal solution of the optimization problem
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