Research Article
Fairness-Based Distributed Resource Allocation in Cognitive Small Cell Networks
@INPROCEEDINGS{10.1007/978-3-030-06161-6_35, author={Xiaoge Huang and Dongyu Zhang and She Tang and Qianbin Chen}, title={Fairness-Based Distributed Resource Allocation in Cognitive Small Cell Networks}, proceedings={Communications and Networking. 13th EAI International Conference, ChinaCom 2018, Chengdu, China, October 23-25, 2018, Proceedings}, proceedings_a={CHINACOM}, year={2019}, month={1}, keywords={Cognitive small cell Resource allocation Channel reuse radius Fairness}, doi={10.1007/978-3-030-06161-6_35} }- Xiaoge Huang
Dongyu Zhang
She Tang
Qianbin Chen
Year: 2019
Fairness-Based Distributed Resource Allocation in Cognitive Small Cell Networks
CHINACOM
Springer
DOI: 10.1007/978-3-030-06161-6_35
Abstract
In this paper, we aim to maximize the total throughput of the cognitive small cell networks by jointly considering interference management, fairness-based resource allocation, average outage probability and channel reuse radius. In order to make the optimization problem tractable, we decompose the original problem into three sub-problems. Firstly, we derive the average outage probability function of the system with respect to the channel reuse radius. With a given outage probability threshold, the associated range of the channel reuse radius is obtained. In addition, a fairness-based distributed resource allocation (FDRA) algorithm is proposed to guarantee the fairness among cognitive small cell base stations (CSBSs). Finally, based on the channel reuse range we could find the maximum throughput of the small cell network tire. Simulation results demonstrate that the proposed FDRA algorithm could achieve a considerable performance improvement relative to the schemes in literature, while providing a better fairness among CSBSs.
