Mehran University Research Journal Of Engineering &
Technology (HEC Recognized In Category "X")
Publishing Since 1982.



For Authors
For Readers
Article Information
A Modified Energy Detection Based Spectrum Sensing Algorithm for Green Cognitive Radio Communication

Keywords: Spectrum Sensing, Cognitive Radios, Green Communication, Energy Detection

Mehran University Research Journal of Engineering & Technology

Volume 34 ,  Issue 4

Sidra  Rajput,Nafeesa  Bohra,Hafiz Muhammad  Haris

Abstract

Spectrum Sensing is the first and fundamental function of Cognitive Cycle which plays a vital role in the success of CRs (Cognitive Radios). Spectrum Sensing indicate the presence and absence of PUs (Primary Users) in RF (Radio Frequency) spectrum occupancy measurements. In order to correctly determine the presence and absence of Primary Users, the algorithms in practice include complex mathematics which increases the computational complexity of the algorithm, thus shifted the CRs to operate as ?green? communication systems. In this paper, an energy efficient and computationally less complex, energy detection based Spectrum Sensing algorithm have been proposed. The design goals of the proposed algorithm are to save the processing and sensing energies. At first, by using less MAC (Multiply and Accumulate) operation, it saves the processing energy needed to determine the presence and absence of PUs. Secondly, it saves the sensing energy by providing a way to find lowest possible sensing time at which spectrum is to be sensed. Two scenarios have been defined for testing the proposed algorithm i.e. simulate detection capability of Primary Users in ideal and noisy scenarios. Detection of PUs in both of these scenarios have been compared to obtain the probability of detection. Energy Efficiency of the proposed algorithm has been proved by making performance comparison between the proposed (less complex) algorithm and the legacy energy detection algorithm. With reduced complexity, the proposed spectrum sensing algorithm can be considered under the paradigm of Green Cognitive Radio Communication