PERFORMANCE OF COUNTING RULES FOR PRIMARY USER DETECTION

In this dissertation we consider the problem of cooperative sensing for secondary user access to primary user spectrum in cognitive radio systems. Using a fusion center or an access point, the cooperative users decide on the availability of spectrum for their use. Both Neyman-Pearson and Bayes criterion are considered for performance assessment. Our work on the asymptotic performance of counting rules with a very large number of sensors in decentralized detection problem shows that majority logic fusion rule has the same order of performance when compared to the best fusion rule based on the binary decisions received from the observing sensors in a network. In cognitive radio context, very large number of sensors may not be realistic and hence we would like to examine the performance of majority logic and counting rules involving a finite and small number of sensors. Uniformly most powerful test for decentralized detection for testing parameter θ when the observation is a sample from uniform (0,θ) distribution is investigated and it is shown that OR rule has the best performance among all counting rules in error free channel. The numerical study for reporting channel as a binary symmetric channel (BSC) with probability of bit error is also investigated and the results show that 2-out-of-5 or 2-out-of-10 has better performance among other k-out-of-n rules, whenever OR rule is not able to provide a probability of false alarm at the sensor, that lies over (0,1) at a given probability of bit error.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Campus Only Dissertation

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Year

2015

Author dc:creator

• Ahsant, Babak

Contributors dc:contributor

• Sayeh, Mohammad
• Viswanathan, Ramanarayanan

• Asymptotic Performance
• Cognitive Radio
• Cooperative Sensing
• Counting Rules
• Decentralized Detection

Repository record dc:identifier

https://opensiuc.lib.siu.edu/dissertations/1062

OAI identifier oai:identifier

oai:opensiuc.lib.siu.edu:dissertations-2066