Research Article
An Effective Interference Management Framework to Achieve Energy-Efficient Communications for Heterogeneous Network through Cognitive Sensing
@INPROCEEDINGS{10.1109/ChinaCom.2012.6417541, author={Shibo Hou and Xing Zhang and Huanyang Zheng and Long Zhao and Wei Fang}, title={An Effective Interference Management Framework to Achieve Energy-Efficient Communications for Heterogeneous Network through Cognitive Sensing}, proceedings={7th International Conference on Communications and Networking in China}, publisher={IEEE}, proceedings_a={CHINACOM}, year={2012}, month={10}, keywords={heterogeneous network; ofdma networks; icic; cognitive sensing; energy consumption model;reward power; parallel vepso}, doi={10.1109/ChinaCom.2012.6417541} }- Shibo Hou
Xing Zhang
Huanyang Zheng
Long Zhao
Wei Fang
Year: 2012
An Effective Interference Management Framework to Achieve Energy-Efficient Communications for Heterogeneous Network through Cognitive Sensing
CHINACOM
IEEE
DOI: 10.1109/ChinaCom.2012.6417541
Abstract
In this paper, we develop an effective inter-cell interference coordination (ICIC) scheme for co-channel interference in downlink orthogonal frequency division multiple access (OFDMA) networks through cognitive sensing performed by subnet nodes in heterogeneous network (Het-Net). The more co-channel interference is detected and avoided, the more power is saved for both macro BS and subnet nodes. The strategy framework of the cognitive critical ratio and the number of subnet nodes is set up for interference management aiming at maximizing net saving power for the whole system. The framework is modeled as multiple objective non-linear programming (MONLP), employing parallel vector evaluated particle swarm optimization algorithm (VEPSO) to obtain the global optimum solution. Utilizing dynamic traffic loads, we could figure out the optimal deployment of low-power BSs. Finally, the practical implementation in Het-Net for long term evolution advanced (LTE-A) is designed. The numerical evaluation and system simulation results demonstrate the applicability and effectiveness of the proposed interference management framework.