Title
Power Versus Spectrum 2-D Sensing in Energy Harvesting Cognitive Radio Networks
Abstract
AbstractEnergy harvester-based cognitive radio is a promising solution to address the shortage of both spectrum and energy. Since the spectrum access and power consumption patterns are interdependent, and the power value harvested from certain environmental sources are spatially correlated, the new power dimension could provide additional information to enhance the spectrum sensing accuracy. In this paper, the Markovian behavior of the primary users is considered, based on which we adopt a hidden input Markov model to specify the primary versus secondary dynamics in the system. Accordingly, we propose a 2-D spectrum and power (harvested) sensing scheme to improve the primary user detection performance, which is also capable of estimating the primary transmit power level. Theoretical and simulated results demonstrate the effectiveness of the proposed scheme, in term of the performance gain achieved by considering the new power dimension. To the best of our knowledge, this is the first work to jointly consider the spectrum and power dimensions for the cognitive primary user detection problem.
Year
DOI
Venue
2015
10.1109/TSP.2015.2464191
Periodicals
Keywords
Field
DocType
Cognitive radio, energy harvesting, spectrum sensing, hidden Markov model, power sensing, 2-D sensing
Mathematical optimization,Transmitter power output,Markov process,Energy level,Simulation,Markov model,Energy harvesting,Electronic engineering,Hidden Markov model,Economic shortage,Mathematics,Cognitive radio
Journal
Volume
Issue
ISSN
63
23
1053-587X
Citations 
PageRank 
References 
4
0.42
22
Authors
5
Name
Order
Citations
PageRank
Yanyan Zhang114923.51
Weijia Han281.90
Di Li34814.30
Ping Zhang4758105.08
Shuguang Cui55382368.45