A Novel Semi-Soft Decision Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks.

Yin Mi,Guangyue Lu,Zhiqiang Bao,Yuxin Li

doi:10.3390/s19112522

Abstract

Spectrum sensing (SS) is an essential part of cognitive radio (CR) technology, and cooperative spectrum sensing (CSS) could efficiently improve the detection performance in environments with fading and shadowing effects, solving hidden terminal problems. Hard and Soft decision detection are usually employed at the fusion center (FC) to detect the presence or absence of the primary user (PU). However, soft decision detection achieves better sensing performance than hard decision detection at the expense of the local transmission band. In this paper, we propose a tradeoff scheme between the sensing performance and band cost. The sensing strategy is designed based on three modules. Firstly, a local detection module is used to detect the PU signal by energy detection (ED) and send decision results in terms of 1-bit or 2-bit information. Secondly, and most importantly, the FC estimates the received decision data through a data reconstruction module based on the statistical distribution such that the extra thresholds are not needed. Finally, a global decision module is in charge of fusing the estimated data and making a final decision. The results from a simulation show that the detection performance of the proposed scheme outperforms that of other algorithms. Moreover, savings on the transmission band cost can be made compared with soft decision detection.

Highlights

With the rapid development of the Internet of Things (IoT) [1] and wireless applications, especially for fifth generation (5G) communication systems and beyond [2], spectrum resources are becoming increasingly strained
The primary user (PU) signal and noise are zero-mean with variance 1
We have proposed a novel semi-soft decision scheme for cooperative spectrum sensing (CSS) in cognitive radio (CR) networks in

Summary

Introduction

With the rapid development of the Internet of Things (IoT) [1] and wireless applications, especially for fifth generation (5G) communication systems and beyond [2], spectrum resources are becoming increasingly strained. The second is Soft-decision detection [10,11], in which each SU sends the sensing data to the FC and the final decision is made by constructing a global test statistic via fusing all of the local sensing information, which increases the local transmission band cost in contrast to 1-bit hard decision detection. In [18], the authors propose a multi-bit fusion rule where the SUs send their 1-bit sensing results to the FC instead of sending multi-bit quantization information, which results in multi-bit reporting and an increase in the energy efficiency. Motivated by the above discussion, this paper proposes a novel semi-soft decision scheme for CSS in CR networks in order to achieve a sufficient tradeoff between the sensing performance and band cost.

Results the simulation of algorithms are provided in Section

The Proposed Semi-Soft Decision Scheme

Local Detection Module

Global Decision Module

Simulation Results

Conclusions