Statistics – Applications
Scientific paper
2011-11-21
Statistics
Applications
Scientific paper
We propose a new framework for cooperative spectrum sensing in cognitive radio networks, that is based on a novel class of non-uniform samplers, called the event-triggered samplers, and sequential detection. In the proposed scheme, each secondary user computes its local sensing decision statistic based on its own channel output; and whenever such decision statistic crosses certain predefined threshold values, the secondary user will send one (or several) bit of information to the fusion center. The fusion center asynchronously receives the bits from different secondary users and updates the global sensing decision statistic to perform a sequential probability ratio test (SPRT), to reach a sensing decision. We provide an asymptotic analysis for the above scheme, and under different conditions, we compare it against the cooperative sensing scheme that is based on traditional uniform sampling and sequential detection. Simulation results show that the proposed scheme, using even 1 bit, can outperform its uniform sampling counterpart that uses infinite number of bits under changing target error probabilities, SNR values, and number of SUs.
Moustakides George
Wang Xiaodong
Yilmaz Yasin
No associations
LandOfFree
Cooperative Sequential Spectrum Sensing Based on Level-triggered Sampling does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Cooperative Sequential Spectrum Sensing Based on Level-triggered Sampling, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Cooperative Sequential Spectrum Sensing Based on Level-triggered Sampling will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-551882