Leveraging Channel Correlation: Prediction Based Multi-Channel Cooperative Sensing

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering

Title: "Leveraging Channel Correlation: Prediction Based Multi-Channel
       Cooperative Sensing"

by

Mr. ZHUO Weipeng

Abstract

Cooperative sensing in Cognitive Radio (CR) Networks has been studied 
extensively in the literature. One challenge of improving cooperative 
sensing is the auto-correlated shadowing problem. Although it can be 
resolved by scattering detectors apart, this is usually not practical in 
suburban areas, where the distance required between detectors should be at 
least 500m.

To solve the problem, in this paper, we leverage the high correlation 
among channels discovered in previous work. We begin by illustrating that 
high correlation in channel states among channels is prevalent and almost 
constant over time. Then we propose a multichannel cooperative sensing 
scheme. This scheme transforms the autocorrelated shadowing problem into a 
cross-correlated shadowing problem, which can be solved by our proposed 
scheme without scattering detectors apart. Therefore, the 
auto-/cross-correlated shadowing problem can be theoretically safely 
avoided. We also show both in theory and in simulation that the 
probability of detection can be greatly increased with an acceptable 
increase in the false alarm rate. Furthermore, when achieving the same 
probability of detection, our scheme can reduce the number of detectors to 
1/4 of the number required by conventional cooperative sensing schemes, 
while still keeping the false alarm rate small.

Date            :       25 May 2011 (Wednesday)

Time            :       10am to 11am

Venue		:       4472 (lift 25-26)

Advisor         :       Dr. Zhang Qian

2nd reader      :	Prof. Bo Li