4.7 Article

Generalized User Grouping in NOMA Based on Overlapping Coalition Formation Game

Journal

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
Volume 39, Issue 4, Pages 969-981

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSAC.2020.3018832

Keywords

NOMA; Uplink; Games; Performance gain; Optimization; 5G mobile communication; Power control; NOMA; overlapping; generalized user grouping; coalition formation; power control

Funding

  1. National Key Research and Development Project [2019YFB2102300, 2019YFB2102301]
  2. National Natural Science Foundation of China [61936014, 61901302]
  3. Scientific Research Project of Shanghai Science and Technology Committee [19511103302]
  4. Fundamental Research Funds for the Central Universities
  5. National Science Foundation [CPS1932413, ECCS-1935915]
  6. Natural Science Foundation of Shanghai [20ZR1462400]

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The research proposes a novel user grouping approach for NOMA systems which allows users to participate in multiple groups while adhering to individual maximum power constraint. By optimizing power control and user grouping to maximize system sum rate, significant performance gains are achieved compared to traditional NOMA user grouping schemes.
Non-orthogonal multiple access (NOMA) is regarded as a promising technology to provide high spectral efficiency and support massive connectivity in 5G systems. In most existing NOMA user grouping approaches, users are grouped into disjoint groups, which may lead to a waste of power resources within each NOMA group. Motivated by this, in this paper we propose a novel generalized user grouping (GuG) concept for NOMA from an overlapping perspective, which allows each user to participate in multiple groups but subject to individual maximum power constraint. In order to achieve effective GuG and maximize the system sum rate, we formulate a joint power control and GuG optimization problem. Then, we address this problem by exploiting the overlapping coalition formation (OCF) game framework, and we further propose an OCF-based algorithm in which each user can be self-organized into a desirable overlapping coalition structure. Simulation results verify the efficiency of GuG in NOMA systems and indicate that compared with traditional NOMA user grouping schemes, our proposed OCF-based GuG NOMA scheme achieves significant performance gains in terms of system sum rate.

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