DocumentCode
3433475
Title
Energy efficient transmissions in MIMO cognitive radio networks
Author
Fu, Liqun ; Zhang, Ying Jun ; Huang, Jianwei
Author_Institution
Inst. of Network Coding, Chinese Univ. of Hong Kong, Hong Kong, China
fYear
2012
fDate
21-23 March 2012
Firstpage
1
Lastpage
6
Abstract
In this paper, we consider energy efficient transmissions for MIMO cognitive radio networks in which the secondary users coexist with the primary users. We want to optimize the proper time allocations and the beamforming vectors for the secondary users, in order to minimize the total energy consumption of the secondary users while satisfying secondary users´ rate requirements and the primary receivers´ received interference constraints. The joint time scheduling and beamforming optimization is non-convex and is often highly complex to solve. Fortunately, we show that the optimal time allocation and the optimal beamforming vectors can be found very efficiently in polynomial-time through a proper decomposition. The simulation results show that compared with a simplistic maximum rate transmission policy, our proposed energy-optimal-transmission algorithm can achieve an energy-saving of 26% to 91%, depending on the traffic load of the secondary system.
Keywords
MIMO communication; array signal processing; cognitive radio; computational complexity; concave programming; radio networks; radiofrequency interference; scheduling; MIMO cognitive radio networks; energy efficient transmissions; energy-optimal-transmission algorithm; energy-saving; joint time scheduling; maximum rate transmission policy; nonconvex optimization; optimal beamforming vectors; optimal time allocation; polynomial-time; primary receiver received interference constraints; secondary user rate requirements; total energy consumption; traffic load; Array signal processing; Receivers; Cognitive radio networks; Energy-efficiency; MIMO;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Sciences and Systems (CISS), 2012 46th Annual Conference on
Conference_Location
Princeton, NJ
Print_ISBN
978-1-4673-3139-5
Electronic_ISBN
978-1-4673-3138-8
Type
conf
DOI
10.1109/CISS.2012.6310707
Filename
6310707
Link To Document