TY - GEN
T1 - Thompson sampling for opportunistic spectrum access with Markovian rewards
AU - Alnatheer, Suleman
AU - Man, Hong
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/24
Y1 - 2014/11/24
N2 - This paper considers the problem of multi- channels opportunistic access in stationary wireless environments, where an intelligent and unlicensed agent uses the existing licensed spectrum to maximize it's throughput while not causing harm to existing licensed users. Each channel is modeled as unknown and never ending stream of binary data generated by first order discrete time Markov process with two states Gilbert-Elliot model. This problem is classified as restless bandit, where optimal solution is intractable. An on-line approximation algorithm is proposed based on Thompson Sampling Algorithm, which acts as heuristic search for best channel in the spectrum.
AB - This paper considers the problem of multi- channels opportunistic access in stationary wireless environments, where an intelligent and unlicensed agent uses the existing licensed spectrum to maximize it's throughput while not causing harm to existing licensed users. Each channel is modeled as unknown and never ending stream of binary data generated by first order discrete time Markov process with two states Gilbert-Elliot model. This problem is classified as restless bandit, where optimal solution is intractable. An on-line approximation algorithm is proposed based on Thompson Sampling Algorithm, which acts as heuristic search for best channel in the spectrum.
UR - http://www.scopus.com/inward/record.url?scp=84919444269&partnerID=8YFLogxK
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U2 - 10.1109/VTCFall.2014.6966204
DO - 10.1109/VTCFall.2014.6966204
M3 - Conference contribution
AN - SCOPUS:84919444269
T3 - IEEE Vehicular Technology Conference
BT - 2014 IEEE 80th Vehicular Technology Conference, VTC2014-Fall, Proceedings
T2 - 80th IEEE Vehicular Technology Conference, VTC 2014-Fall
Y2 - 14 September 2014 through 17 September 2014
ER -