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Volume 8 Issue 3
Mar.  2021

IEEE/CAA Journal of Automatica Sinica

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Zhixin Liu, Changjian Liang, Yazhou Yuan, Kit Yan Chan and Xinping Guan, "Resource Allocation Based on User Pairing and Subcarrier Matching for Downlink Non-Orthogonal Multiple Access Networks," IEEE/CAA J. Autom. Sinica, vol. 8, no. 3, pp. 679-689, Mar. 2021. doi: 10.1109/JAS.2021.1003886
Citation: Zhixin Liu, Changjian Liang, Yazhou Yuan, Kit Yan Chan and Xinping Guan, "Resource Allocation Based on User Pairing and Subcarrier Matching for Downlink Non-Orthogonal Multiple Access Networks," IEEE/CAA J. Autom. Sinica, vol. 8, no. 3, pp. 679-689, Mar. 2021. doi: 10.1109/JAS.2021.1003886

Resource Allocation Based on User Pairing and Subcarrier Matching for Downlink Non-Orthogonal Multiple Access Networks

doi: 10.1109/JAS.2021.1003886
Funds:  This work was partly supported by the Natural Science Foundation of Hebei Province (F2019203095), the National Natural Science Foundation of China (61873223, 61803328), the National Key R&D Program of China (2018YFB1702100)
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  • The traditional orthogonal multiple access (OMA) is unable to satisfy the needs of large number of smart devices. To increase the transmission rate in the limited spectrum resource, implementation of both non-orthogonal multiple access (NOMA) and successive interference cancelation (SIC) is essential. In this paper, an optimal resource allocation algorithm in NOMA is proposed to maximize the total system rate in a multi-sector multi-subcarrier relay-assisted communication network. Since the original problem is a non-convex problem with mixed integer programming which is non-deterministic polynomial-time (NP)-hard, a three-step solution is proposed to solve the primal problem. Firstly, we determine the optimal power allocation of the outer users by using the approach of monotonic discrimination, and then the optimal user pairing is determined. Secondly, the successive convex approximation (SCA) method is introduced to transform the non-convex problem involving central users into convex one, and the Lagrangian dual method is used to determine the optimal solution. Finally, the standard Hungarian algorithm is utilized to determine the optimal subcarrier matching. The simulation results show that resource allocation algorithm is able to meet the user performance requirements with NOMA, and the total system rate is improved compared to the existing algorithms.

     

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    Highlights

    • A joint resource allocation framework is proposed for two-layer multi-sector NOMA network.
    • The allocation scheme consists of user pairing, power control and subcarrier matching.
    • The user pairing strategy is proposed to reduce decoding complexity caused by SIC.
    • An practical approach is proposed to solve the non-convex resource allocation problem.
    • The developed scheme is able to improve the achieved transmitting rate greatly.

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