Title
Chance-constraint optimization of power control in cognitive radio networks
Abstract
In this paper, to minimize the transmission power of cognitive users in underlay cognitive radio networks, a robust power control algorithm is proposed considering the uncertain channel gains. To deal with the uncertainty, we present an opportunistic power control strategy, i.e., the outage probability of all cognitive users and primary users should be reduced below their predefined thresholds. The strategy is the joint design of primary users’ communication protection and cognitive users’ optimal power allocation. A chance constraint robust optimization approach is applied, which can transform the uncertain problem into a deterministic problem. Then, a distributed probabilistic power algorithm is introduced, which ensures the optimization of cognitive users’ power allocation based on the standard interference function and restricts the interference at primary receivers by adjusting the maximum transmission power of cognitive users. Moreover, the admission control is introduced to exploit the network resources more effectively. Numerical results show the convergence and effectiveness of the proposed robust distributed power control algorithm.
Year
DOI
Venue
2016
10.1007/s12083-014-0325-8
Peer-to-Peer Networking and Applications
Keywords
Field
DocType
Cognitive radio networks,Channel gain uncertainty,Chance constraint,Robust optimization,Distributed power allocation
Mathematical optimization,Admission control,Computer science,Robust optimization,Power control,Communication channel,Interference (wave propagation),Probabilistic logic,Constrained optimization,Distributed computing,Cognitive radio
Journal
Volume
Issue
ISSN
9
1
1936-6442
Citations 
PageRank 
References 
3
0.39
19
Authors
5
Name
Order
Citations
PageRank
Zhixin Liu110214.71
Panpan Wang2205.75
Yuanqing Xia33132232.57
Hongjiu Yang470251.23
Xinping Guan52791253.38