Channel Sensing Order for Distributed Cognitive Radio Networks Using No-Regret Learning

DOI

10.2991/icwcsn-16.2017.138How to use a DOI?

Keywords

sensing order; spatially distributed networks; noncooperative game ;no-regret learning

Abstract

This work investigates the problem of channel sensing order in spatially distributed networks with multi-user. We model this problem into a non-cooperative game and define a generalized interference metric. In order to minimize the aggregate interference and maximize the normalized throughput, we employ the no-regret learning algorithm. However, this algorithm requires information exchange. Therefore, we propose a modified no-regret learning algorithm that does not require information exchange. Through simulations, we evaluate our proposal and compare its performance with other algorithms, and the results obtained are close to the no regret learning algorithm and superior to random selection algorithm.

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  - Li-Wang Li
AU  - Jin-Cheng Ge
PY  - 2016/12
DA  - 2016/12
TI  - Channel Sensing Order for Distributed Cognitive Radio Networks Using No-Regret Learning
BT  - Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
PB  - Atlantis Press
SP  - 674
EP  - 679
SN  - 2352-538X
UR  - https://doi.org/10.2991/icwcsn-16.2017.138
DO  - 10.2991/icwcsn-16.2017.138
ID  - Li2016/12
ER  -