User Behavior Aware Cell Association in Heterogeneous Cellular Networks

Sun, Y. , Feng, G., Qin, S., Sun, S. and Zhang, L. (2017) User Behavior Aware Cell Association in Heterogeneous Cellular Networks. In: 2017 IEEE Wireless Communications and Networking Conference Workshops (WCNCW '17), San Francisco, CA, USA, 19-22 Mar 2017, ISBN 9781509041831 (doi: 10.1109/WCNC.2017.7925955)

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Abstract

In heterogeneous cellular networks (HetNets), cell association of User Equipment (UE) affects UE transmit rate and network throughput. Conventional cell association rules are usually based on UE received Signal-to-Interference-and-Noise-Ratio (SINR) without taking into account user behaviors, which can indeed be exploited for improving network performance. In this paper, we investigate UE cell association in HetNets based on individual user behavior characteristics with aim to maximize long- term expected system throughput. We model the problem as a stochastic optimization model Restless Multi-Armed Bandit (RMAB). As it is a PSPACE-hard problem, we develop a primal-dual heuristic index algorithm and the solution specifies the rule that determines which arms in the RMAB model to be selected at each decision time. According to the solution of RMAB, we propose a new cell association strategy called Index Enabled Association (IDEA). We also conduct simulation experiments to compare IDEA with conventional max-SINR cell association strategy and an existing game-based RAT selection scheme. Numerical results demonstrate the advantages of IDEA in typical scenarios.

Item Type:Conference Proceedings
Additional Information:This work is supported in part by the National Science Foundation of China (No. 61401076 and No. 61631005) and Research Funds of Sci. & Tech. on Info. Trans. & Disse. Commu. Net. Lab (No. KX152600017/ITD-U15008).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Sun, Dr Yao and Feng, Professor Gang
Authors: Sun, Y., Feng, G., Qin, S., Sun, S., and Zhang, L.
College/School:College of Science and Engineering > School of Engineering
ISSN:1558-2612
ISBN:9781509041831
Copyright Holders:Copyright © 2017 IEEE
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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