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QoE-oriented resource allocation for dense cloud NOMA smallcell networks

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Abstract

In this paper, we investigate the resource allocation for dense cloud non-orthogonal multiple access smallcell networks (NOMA SCN), aimed at maximizing the users’ quality of service (QoE). First, we construct a directed hypergraph to model the complex inter-interference relationship for cloud NOMA SCN. Then, we formulate the QoE-oriented channel allocation and user pairing problem in NOMA SCN as a local cooperation game. The game is proved to be an exact potential game. Moreover, the optimal pure strategy Nash equilibrium (PNE) in the proposed game can maximize the network QoE level. To achieve the optimal PNE in the proposed game, we redesign a directed-hypergraph-based multi-agent learning algorithm, which allows multiple non-coupled agents in directed hypergraph to simultaneously update their actions. Finally, simulation results are presented to validate the proposed learning scheme.

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Authors and Affiliations

  1. Luoyang Institute of Science and Technology, Luoyang, 471000, China

    Hongxiang Shao

  2. Army Engineering University, Nanjing, 210000, China

    Youming Sun & Jihao Cai

  3. National University of Defense Technology, Changsha, 410000, China

    Zhiyong Du & Zhentao Duan

Authors
  1. Hongxiang Shao
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  2. Youming Sun
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  3. Zhiyong Du
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  4. Jihao Cai
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  5. Zhentao Duan
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Correspondence to Youming Sun.

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This work was supported in part by the National Science Foundation of China under Grant No.61901518, No. 61401508, No.61631020 and No.61501510, in part by science and technology breakthrough project of Henan science and technology department (222102210094 ), and in part by key projects of colleges and universities in Henan province (19B510007).

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Shao, H., Sun, Y., Du, Z. et al. QoE-oriented resource allocation for dense cloud NOMA smallcell networks. Wireless Netw 28, 1757–1769 (2022). https://doi.org/10.1007/s11276-022-02929-7

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