Effective Spectrum Sensing By Weighted Data Fusion In Full Duplex Cognitive Radio Networks

DOI

10.2991/jimec-17.2017.110How to use a DOI?

Keywords

Full duplex, Cognitive radio, LAT protocol, Data fusion, Convex optimization

Abstract

As the full duplex (FD) technique becoming more sophisticated, a novel cognitive radio network (CRN) protocol called "listen-and-talk"(LAT) was proposed. Based on self-interference cancellation (SIC) technique, LAT protocol can promote the utilization of spectrum resources with the cost of the performance of spectrum sensing. Several researchers made efforts to overcome this shortcoming. In this paper, a more effective cooperative spectrum sensing strategy based on weighted data fusion was proposed. Convex optimization is used to solve the math model. Simulation results show that the method of weighted data fusion (WDF) highly improves the performance of spectrum sensing in FDCRN, also outperforms the previous studies.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qiming Yu
AU  - Hu Jin
AU  - Yifan Liu
AU  - Wenqing Zheng
PY  - 2017/10
DA  - 2017/10
TI  - Effective Spectrum Sensing By Weighted Data Fusion In Full Duplex Cognitive Radio Networks
BT  - Proceedings of the 2017 2nd Joint International Information Technology, Mechanical and Electronic Engineering Conference (JIMEC 2017)
PB  - Atlantis Press
SP  - 508
EP  - 511
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimec-17.2017.110
DO  - 10.2991/jimec-17.2017.110
ID  - Yu2017/10
ER  -