상세정보
학술지
Learning-based Resource Partitioning in Heterogeneous Networks with Multiple Network Operators
- 저자
- 정병창, 조동호
- 발행일
- 202103
- 출처
- IEEE Communications Letters, v.25 no.3, pp.869-873
- ISSN
- 1089-7798
- 출판사
- IEEE
- 협약과제
- 20HR3500, 다매체 다중경로 적응적 네트워크 기술 개발, 박혜숙
- 초록
- In heterogeneous network, it is important to mitigate cross-tier interference. Resource partitioning is the one of solution to reduce interference. However, most of studies on partitioning assumed that there was only one network operator to cooperate with. In this letter, we study the network selection problem of small access points in heterogeneous networks, which are provided by multiple network operators. We model the multiple network operators scenario as a congestion game. To solve the equilibrium point of suggested game, we analyze some features of proposed model such as potential game property, smoothed best response dynamics and logit equilibrium. Then, we propose a reinforcement learning algorithm that can reach logit equilibrium in distributed way. Moreover, we also suggest the adjustment of learning parameters to enhance adaptability. By means of simulations, it is shown that proposed algorithm has near-optimal performance in view of throughput, fairness and adaptability.
- KSP 제안 키워드
- Access point, Best response dynamics, Congestion Game, Cross-tier interference, Game property, Learning parameters, Learning-based, Multiple network, Network operator, Network selection, Proposed model