One-to-Many Relationship Based Kullback Leibler Divergence against Malicious Users in Cooperative Spectrum Sensing

Noor Gul,Muhammad Kamran,Imtiaz Rasool,Sadiq Akbar,Ijaz Mansoor Qureshi

doi:10.1155/2018/3153915

Abstract

The centralized cooperative spectrum sensing (CSS) allows unlicensed users to share their local sensing observations with the fusion center (FC) for sensing the licensed user spectrum. Although collaboration leads to better sensing, malicious user (MU) participation in CSS results in performance degradation. The proposed technique is based on Kullback Leibler Divergence (KLD) algorithm for mitigating the MUs attack in CSS. The secondary users (SUs) inform FC about the primary user (PU) spectrum availability by sending received energy statistics. Unlike the previous KLD algorithm where the individual SU sensing information is utilized for measuring the KLD, in this work MUs are identified and separated based on the individual SU decision and the average sensing statistics received from all other users. The proposed KLD assigns lower weights to the sensing information of MUs, while the normal SUs information receives higher weights. The proposed method has been tested in the presence of always yes, always no, opposite, and random opposite MUs. Simulations confirm that the proposed KLD scheme has surpassed the existing soft combination schemes in estimating the PU activity.

Highlights

The rapid evolution in wireless communication demands new wireless services in both the used and unused parts of the radio spectrum [1]
fusion center (FC) takes sensing data from all secondary users (SUs) and determines Kullback Leibler Divergence (KLD) score based on the energy statistics of individual user with the average statistics received from all other users
Out of the total cooperative SUs, four users are intentionally selected as always yes (AY), always opposite (AO), random opposite (RO), and AO nature of malicious user (MU)

Summary

Introduction

The rapid evolution in wireless communication demands new wireless services in both the used and unused parts of the radio spectrum [1]. An improved energy detector scheme is suggested in [14] to maximize the throughput of a CRN network with minimum interference to the PUs. Individual SU faces a number of restrictions to sense the PU spectrum accurately. In the soft fusion combination schemes proposed in [30,31,32] sensing energies from different SUs are combined to take accurate decision about the PU spectrum holes. FC takes sensing data from all SUs and determines KLD score based on the energy statistics of individual user with the average statistics received from all other users. The outcome shows that these MUs in CSS increase the false alarm and misdetection, resulting in an increased interference to the primary transmission and reduced throughput of the network.

System Model

The Proposed One-to-Many Relations Based KLD

Numerical Results and Discussion

Conclusion