Fast two-stage spectrum detector for cognitive radios in uncertain noise channels

An enormous influx of wireless services and devices coupled with inefficient usage of electromagnetic spectrum has led to an apparent scarcity of usable radio bandwidth. Cognitive radio is leading the trend for increasing the spectrum efficiency by utilising the vacancy in the radio spectrum created...

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Bibliographic Details
Main Authors: Nair, P. R., Krishna, A. K., Vinod, Achutavarrier Prasad, Smitha, Kavallur Gopi
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/107333
http://hdl.handle.net/10220/16662
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Institution: Nanyang Technological University
Language: English
Description
Summary:An enormous influx of wireless services and devices coupled with inefficient usage of electromagnetic spectrum has led to an apparent scarcity of usable radio bandwidth. Cognitive radio is leading the trend for increasing the spectrum efficiency by utilising the vacancy in the radio spectrum created by absence of the licensed primary user. This paradigm shift can only take place if the means to detect the primary user are well established so that an ecosystem can be created where both primary and secondary users can co-exist without interfering with each other. In this study the authors propose a two-stage detection mechanism which gives an improved performance over conventional single-stage detectors yet optimises the usage of the second stage, thereby reducing the sensing time as compared to conventional two-stage spectrum sensing algorithms. A hardware implementation of the algorithm has also been done to quantify the area and power consumption values. By utilising the second-stage optimally, the algorithm presented in this study helps in reducing the sensing time by 86% as compared with the conventional two-stage detector. By not activating the second stage at high SNRs, the proposed algorithm saves 0.915%W of dynamic power out of a total of 1.09%W, thus effectively reducing the dynamic power consumption by 84%.