Detection of Primary Users with Distributed Spectrum Sensors over Rayleigh Fading Channel

Abstract

This study addresses detection of primary users (PUs) for cognitive radio system (CRS) with distributed spectrum sensors (DSSs) in Rayleigh fading environment. Two sensing schemes using DSSs that employ energy detection (ED) are investigated as cooperative sensing and collaborative sensing. For the cooperative sensing, each DSS makes hard decision after sensing and transmits the information by on-off keying (OOK) singling to a secondary user (SU) that performs data fusion. In collaborative sensing DSSs exchange the hard decision information after sensing and make data fusion at a selected DSS. Then, the selected DSS transmits the decision information to the SU with OOK signaling. In this paper, a closed-form expression for the probability of detection (PD) of ED with selective combining (SC) in Rayleigh fading environment is derived. Applying this expression to the PU detection problem, analytical models for evaluating the two sensing schemes are obtained. Results show that at 5-dB signal- to-noise ratio (SNR) and using 3 DSSs, the PD is increased from 0.02 to 0.3 and 0.4 by collaborative sensing and collaborative sensing, respectively. I. INTRODUCTION Many existing wireless systems are regulated by a fixed spectrum assignment strategy. The policy partitions the whole spectrum into a large number of different ranges. Each piece is specified for a particular system. This leads to undesirable situations where a large portion of frequency bands is unoc- cupied or only partially occupied (1). Cognitive radio system (CRS) (2) has the potential to boost the evolution of wireless communication by allowing unlicensed users or secondary users (SUs) to dynamically access those temporally unused frequency spectrum in licensed band of primary users (PUs). The functionalities of the CRS can be classified into cognitive engine (CE), sensing and interface. Sensing as a key functional entity measures the radio frequency environment. Then, the sensing information is passed from the sensing entity to CE through the interface. Based on the sensing information, the CE residing in SUs determines the presence of PUs and makes spectrum access decision. Currently, the IEEE P1900.6 working group is ac- tively developing the standard of sensing interface and data structure required for sensing information exchange among CEs and sensing entities (3). The standard supports the sensing functionality to be realized by distributed spectrum sensors (DSSs) (4). This promotes innovation of sensing technologies. In this study, we consider two sensing schemes, cooperative sensing and collaborative sensing, for PU detection using DSSs where there are N number of spectrum sensors, Si,