Article (Scientific journals)
Cooperative cognitive networks: Optimal, distributed and low-complexity algorithms
Zheng, Gan; Song, Shenghui; Wong, Kai-Kit et al.
2013In IEEE Transactions on Signal Processing, 11 (61), p. 2778-2790
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Abstract :
[en] This paper considers the cooperation between a cognitive system and a primary system where multiple cognitive base stations (CBSs) relay the primary user's (PU) signals in exchange for more opportunity to transmit their own signals. The CBSs use amplify-and-forward (AF) relaying and coordinated beamforming to relay the primary signals and transmit their own signals. The objective is to minimize the overall transmit power of the CBSs given the rate requirements of the PU and the cognitive users (CUs). We show that the relaying matrices have unity rank and perform two functions: Matched filter receive beamforming and transmit beamforming. We then develop two efficient algorithms to find the optimal solution. The first one has a linear convergence rate and is suitable for distributed implementation, while the second one enjoys superlinear convergence but requires centralized processing. Further, we derive the beamforming vectors for the linear conventional zero-forcing (CZF) and prior zero-forcing (PZF) schemes, which provide much simpler solutions. Simulation results demonstrate the improvement in terms of outage performance due to the cooperation between the primary and cognitive systems.
Disciplines :
Computer science
Author, co-author :
Zheng, Gan 
Song, Shenghui
Wong, Kai-Kit
Ottersten, Björn ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Language :
English
Title :
Cooperative cognitive networks: Optimal, distributed and low-complexity algorithms
Publication date :
2013
Journal title :
IEEE Transactions on Signal Processing
ISSN :
1053-587X
Publisher :
IEEE
Volume :
11
Issue :
61
Pages :
2778-2790
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBilu :
since 14 January 2014

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