Research Article
Capacity Analysis in the Cognitive Heterogeneous Cellular Networks with Stochastic Methods
@INPROCEEDINGS{10.1007/978-3-319-66628-0_25, author={Yinglei Teng and Mengting Liu and Mei Song}, title={Capacity Analysis in the Cognitive Heterogeneous Cellular Networks with Stochastic Methods}, proceedings={Communications and Networking. 11th EAI international Conference, ChinaCom 2016 Chongqing, China, September 24-26, 2016, Proceedings, Part II}, proceedings_a={CHINACOM}, year={2017}, month={10}, keywords={Cognitive heterogeneous cellular networks (CHCNs) Markov chain Stochastic geometry Homogeneous Poisson point process (HPPP)}, doi={10.1007/978-3-319-66628-0_25} }- Yinglei Teng
Mengting Liu
Mei Song
Year: 2017
Capacity Analysis in the Cognitive Heterogeneous Cellular Networks with Stochastic Methods
CHINACOM
Springer
DOI: 10.1007/978-3-319-66628-0_25
Abstract
Small cells are widely being deployed to enhance the performance of cellular networks, which results in a random distribution of base stations as well as a complex interference problem. Therefore, it becomes considerably challenging to derive a closed-form expression for the capacity of small cell enhanced heterogeneous cellular network especially when the cognitive radio (CR) technology is utilized to mitigate the possible interference. In this paper, we first use the discrete time Markov chain (DTMC) to achieve the spectrum mobility of macro base station (MBS) users, i.e. primary users (PUs) in the cognitive heterogeneous cellular networks (CHCNs). Meanwhile, by modeling MBSs and small base stations (SBSs) as two independent homogeneous Poisson point processes (HPPPs), we propose an integral way based on stochastic geometry (SG) to get the calculation of the interference. Simulation results show that our capacity analysis method of CHCNs serves well in approximating the network capacity by conquering the complex interference and the uncertainty of spectrum mobility, which turns out to be an efficient and promising approach.
