A novel approach for energy‐efficient resource allocation in double threshold‐based cognitive radio network. (27th October 2016)

• Record Type: Journal Article
• Authors: Das, Deepa; Das, Susmita
• Is Part Of: International journal of communication systems. Volume 30:Number 9(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-10-27
• Subjects: double threshold -- energy efficiency -- iterative Dinkelbach method -- power allocation -- sensing time -- soft decision fusion; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.3198
• Languages: English
• ISSNs: 1074-5351

Abstract

Summary: This paper mainly focuses on solving the energy efficiency (EE) maximization problem in double threshold‐based soft decision fusion (SDF) cooperative spectrum sensing (CSS) in the cognitive radio network (CRN). The solution to this objective problem starts with the selection of suitable secondary users (SUs) both for the spectrum sensing and data transmission. Here, energy efficiency is maximized under the constraints of interference to the primary user (PU), an acceptable outage of SUs, the transmission power of the SUs and the probability of false alarm. We propose a novel algorithm called iterative Dinkelbach method (IDM) which jointly optimizes the sensing time and transmission power allocation to the SUs. Further, Lagrangian duality theorem is employed to find the exact power assigned to the SUs. Finally, simulation results are carried out to validate the effectiveness of our proposed scheme by comparing with the other existing schemes. The performance is also analyzed for different system parameters. Abstract : This paper proposes selection of secondary users (SUs) on the basis of the number of sensing rounds and channel gains in double threshold‐based soft decision fusion cooperative spectrum sensing. The energy efficiency maximization problem is formulated under the constraints of interference to the primary user, outage of SUs, maximum transmission power of SUs and minimum achievable data rate. Further, a novel iterative Dinkelbach method algorithm is proposed for joint optimization of sensing time and power allocation.