Autocorrelation Based White Space Detection in Energy Harvesting Cognitive Radio Network

Samson Iyanda Ojo,Rebeccah Oluwafunmilayo Omowaiye,Oluwatobi Omolola Oyedokun,Zachaeus Kayode Adeyemo

doi:10.52549/ijeei.v9i4.3179

Abstract

Accurate detection of White Space (WS) is of paramount importance in a Cognitive Radio Network (CRN) to prevent authorized users from harmful interference. However, channel impairment such as multipath fading and shadowing affects accurate detection of WS resulting in interference. The Existing Feature Detection (EFD) technique used to address the problem is faced with computational complexity and synchronization resulting in long sensing time, bandwidth inefficiency, energy constrain and poor detection rate. Hence, this paper proposes autocorrelation based multiple antenna with energy harvesting for WS detection in a CRN using Radio Frequency (RF) energy harvesting and autocorrelation of the received signal with a modified Equal Gain Combiner (mEGC). Antenna Switching (AS) RF energy harvesting with mEGC are used to harvest energy and information from the received PU signal in a multiple antenna configuration. Autocorrelation is then obtained and compared with the set threshold of zero to determine the presence or absence of WS. The proposed technique is evaluated using Spectral Efficiency (SE), Probability of Detection (PD) and Sensing Time (ST) by comparing with EFD technique. The results obtained revealed that the proposed technique shows better performance than EFD.

Highlights

The extensive increase in the demand of wireless communication services due to their functions in many facets of human endeavor has led to exponential increase in the demand of radio spectrum
The results obtained reveal that the proposed technique has higher detection rate than the existing technique at all the SNR considered due to the combining nature of the modified Equal Gain Combiner (mEGC) used for the proposed technique that reduces variability in Primary User (PU) signal strength
The proposed technique does not require synchronization, thereby reducing the hardware complexity leading to reduction of power consumption and sensing rate

Summary

INTRODUCTION

The extensive increase in the demand of wireless communication services due to their functions in many facets of human endeavor has led to exponential increase in the demand of radio spectrum. The results obtained confirmed better performance of the technique when compared with ED but suffers from long sensing time and high bandwidth consumption due to Hilbert transform theory and synchronization required, respectively. Feature detection based blind approach for SS and classification technique was proposed in [22] to solve the problem of harmful interference in a CR network In this technique, unauthorized multiple antenna received the multiple copies of authorized user’s signal over Rayleigh fading channel. The contributions of this paper are as follows: 1) proposes an energy efficient multiple antenna white space detection that reduces operational expenditure thereby making the services affordable to every user This is achieved by using RF energy harvesting to power the licensed user node during spectrum sensing, while reserving its own energy for signal transmission.

PROPOSED WHITE SPACE DETECTION TECHNIQUE

Combined Fading Channel

CONCLUSION