Resource Allocation to Maximize the Average Sum Rate of the Uplink SCMA Networks

• Published in: 2021 IEEE/CIC International Conference on Communications in China (ICCC) pp. 984 - 989
• Main Authors: Cheraghy, Maryam, Chen, Wen
• Format: Conference Proceeding
• Language: English
• Published: IEEE 28.07.2021
• Subjects: average sum rate; Codes; Interference; randomly distributed users; resource allocation; Resource management; Signal to noise ratio; Simulation; Sparse code multiple access; Sparse matrices; Uplink
• DOI: 10.1109/ICCC52777.2021.9580379

Considering the performance of the sparse code multiple access (SCMA) networks at the entirely different signal to noise ratios (SNRs) of users is crucial. In this paper, a near-optimal resource allocation algorithm to maximize the average sum rate is investigated, where the users are randomly distributed in a circular cell. To obtain the factor graph matrix of uplink SCMA systems, the existing works are usually based on three steps to maximize the sum rate, i.e., choosing a random initial assignment matrix, allocating the subcarriers to the users based on channel gains, and maximizing the individual rate considering the interference of all users. Unlike the existing works, we consider a more general scenario and propose a new algorithm based on the individual rate with interference updating. After the factor graph matrix is derived, the optimal power coefficients are obtained based on the Lagrange method. The simulation results in terms of average sum rate show that our proposed method can outperform and guarantee stronger optimality compared to the existing algorithms.