Cognitive Radio with Reinforcement Learning Applied to Multicast Downlink Transmission with Power Adjustment

Authors:
Mengfei Yang;David Grace
Affiliations:
Communication Research Group, Department of Electronics, University of York, York, UK YO10 5DD;Communication Research Group, Department of Electronics, University of York, York, UK YO10 5DD
Venue:
Wireless Personal Communications: An International Journal
Year:
2011

Citing 9
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Abstract

This paper shows how channel assignment in multicast terrestrial communication systems with distributed channel occupancy detection can be improved using intelligence based on reinforcement learning and transmitter power adjustment. It is shown how such schemes greatly reduce the number of reassignments and improve the dropping probability, at the expense of increased blocking. It is found that using different minimum quality of service threshold percentages can partly control and improve the performance, in place of the more traditional SINR threshold levels. The paper also shows how a power adjustment technique is developed which significantly reduces the level of overlap between adjacent base stations, and further reduces interference and transmitter power.