• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Matching game based resource allocation algorithm for energy-harvesting small cells network with NOMA

Vol. 12, No. 11, November 29, 2018
10.3837/tiis.2018.11.002, Download Paper (Free):

Abstract

In order to increase the capacity and improve the spectrum efficiency of wireless communication systems, this paper proposes a rate-based two-sided many-to-one matching game algorithm for energy-harvesting small cells with non-orthogonal multiple access (NOMA) in heterogeneous cellular networks (HCN). First, we use a heuristic clustering based channel allocation algorithm to assign channels to small cells and manage the interference. Then, aiming at addressing the user access problem, this issue is modeled as a many-to-one matching game with the rate as its utility. Finally, considering externality in the matching game, we propose an algorithm that involves swap-matchings to find the optimal matching and to prove its stability. Simulation results show that this algorithm outperforms the comparing algorithm in efficiency and rate, in addition to improving the spectrum efficiency.


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Cite this article

[IEEE Style]
X. Wang and Q. Zhu, "Matching game based resource allocation algorithm for energy-harvesting small cells network with NOMA," KSII Transactions on Internet and Information Systems, vol. 12, no. 11, pp. 5203-5217, 2018. DOI: 10.3837/tiis.2018.11.002.

[ACM Style]
Xueting Wang and Qi Zhu. 2018. Matching game based resource allocation algorithm for energy-harvesting small cells network with NOMA. KSII Transactions on Internet and Information Systems, 12, 11, (2018), 5203-5217. DOI: 10.3837/tiis.2018.11.002.

[BibTeX Style]
@article{tiis:21914, title="Matching game based resource allocation algorithm for energy-harvesting small cells network with NOMA", author="Xueting Wang and Qi Zhu and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2018.11.002}, volume={12}, number={11}, year="2018", month={November}, pages={5203-5217}}