DocumentCode :
1511607
Title :
Optimal Myopic Sensing and Dynamic Spectrum Access in Cognitive Radio Networks with Low-Complexity Implementations
Author :
Li, Yang ; Jayaweera, Sudharman K. ; Bkassiny, Mario ; Avery, Keith A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of New Mexico, Albuquerque, NM, USA
Volume :
11
Issue :
7
fYear :
2012
fDate :
7/1/2012 12:00:00 AM
Firstpage :
2412
Lastpage :
2423
Abstract :
Cognitive radio techniques allow secondary users (SU´s) to opportunistically access underutilized primary channels that are licensed to primary users. We consider a group of SU´s with limited spectrum sensing capabilities working cooperatively to find primary channel spectrum holes. The objective is to design the optimal sensing and access policies that maximize the total secondary throughput on primary channels accrued over time. Although the problem can be formulated as a Partially Observable Markov Decision Process (POMDP), the optimal solutions are intractable. Instead, we find the optimal sensing policy within the class of myopic policies. Compared to other existing approaches, our policy is more realistic because it explicitly assigns SU´s to sense specific primary channels by taking into account spatial and temporal variations of primary channels. Contributions: (1) formulation of a centralized spectrum sensing/access architecture that allows exploitation of all available primary spectrum holes; and (2) proposing sub-optimal myopic sensing policies with low-complexity implementations and performance close to the myopic policy. We show that our proposed sensing/access policy is close to the optimal POMDP solution and outperforms other proposed strategies. We also propose a Hidden Markov Model based algorithm to estimate the parameters of primary channel Markov models with a linear complexity.
Keywords :
cognitive radio; communication complexity; hidden Markov models; parameter estimation; radio spectrum management; wireless channels; SU; access policy; centralized spectrum sensing/access architecture; cognitive radio network; dynamic spectrum access; hidden Markov model based algorithm; linear complexity; low-complexity implementation; optimal POMDP solution; optimal myopic sensing policy; parameter estimation; partially observable Markov decision process; primary channel Markov model; primary channel spectrum hole; primary user; secondary user; spectrum sensing capability; total secondary throughput; Bandwidth; Channel estimation; Hidden Markov models; Markov processes; Sensors; Throughput; Vectors; Cognitive radios; Hidden Markov Model (HMM); Hungarian algorithm; Markov chains; Neyman-Pearson detector; dynamic spectrum access (DSA); myopic sensing; partially observable Markov decision processes (POMDP);
fLanguage :
English
Journal_Title :
Wireless Communications, IEEE Transactions on
Publisher :
ieee
ISSN :
1536-1276
Type :
jour
DOI :
10.1109/TWC.2012.050112.110152
Filename :
6196271
Link To Document :
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