Article (Scientific journals)
Constrained Bayesian Active Learning of Interference Channels in Cognitive Radio Networks
Tsakmalis, Anestis; Chatzinotas, Symeon; Ottersten, Björn
2017In IEEE Journal of Selected Topics in Signal Processing
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Keywords :
Cognitive Radio Networks; Expectation Propagation; Active Learning
Abstract :
[en] In this paper, a sequential probing method for interference constraint learning is proposed to allow a centralized Cognitive Radio Network (CRN) accessing the frequency band of a Primary User (PU) in an underlay cognitive scenario with a designed PU protection specification. The main idea is that the CRN probes the PU and subsequently eavesdrops the reverse PU link to acquire the binary ACK/NACK packet. This feedback indicates whether the probing-induced interference is harmful or not and can be used to learn the PU interference constraint. The cognitive part of this sequential probing process is the selection of the power levels of the Secondary Users (SUs) which aims to learn the PU interference constraint with a minimum number of probing attempts while setting a limit on the number of harmful probing-induced interference events or equivalently of NACK packet observations over a time window. This constrained design problem is studied within the Active Learning (AL) framework and an optimal solution is derived and implemented with a sophisticated, accurate and fast Bayesian Learning method, the Expectation Propagation (EP). The performance of this solution is also demonstrated through numerical simulations and compared with modified versions of AL techniques we developed in earlier work.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SIGCOM
Disciplines :
Electrical & electronics engineering
Author, co-author :
Tsakmalis, Anestis ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Chatzinotas, Symeon  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Ottersten, Björn ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
External co-authors :
no
Language :
English
Title :
Constrained Bayesian Active Learning of Interference Channels in Cognitive Radio Networks
Publication date :
21 December 2017
Journal title :
IEEE Journal of Selected Topics in Signal Processing
ISSN :
1941-0484
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), New York, United States - New York
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Security, Reliability and Trust
European Projects :
H2020 - 742648 - AGNOSTIC - Actively Enhanced Cognition based Framework for Design of Complex Systems
Funders :
FNR - Fonds National de la Recherche [LU]
CE - Commission Européenne [BE]
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