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All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Zachaeus Kayode Adeyemo
Ladoke Akintola University of Technology, Ogbomoso
Computer Science & IT Electrical & Electronics Engineering

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Autocorrelation Based White Space Detection in Energy Harvesting Cognitive Radio Network Samson Iyanda Ojo; Zachaeus Kayode Adeyemo; Rebeccah Oluwafunmilayo Omowaiye; Oluwatobi Omolola Oyedokun
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 4: December 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | 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.
Improvement of Multiple Antenna Sensing Technique for Detecting the White Space in a Spectrum Sharing System Zachaeus Kayode Adeyemo; Samson Iyanda Ojo; Saheed Abiona Abolude; Damilare Oluwole Akande; Hammed O. Lasisi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3802

Abstract

Exact detection of White Space (WS) is one of the actions in a Spectrum Sharing System (SSS) to determine unused spectrum for proper utilization. However, exact detection of WS is being affected by channel impairments, resulting in harmful interference. The Existing Multiple Antenna Spectrum Sensing (EMASS) technique used in addressing this effect is characterized with noise uncertainty leading to low detection rate due to setting of thresholds that is based on noise variance. Hence, this paper proposes an Improved Multiple Antenna Spectrum Sensing (IMASS) for detecting the WS in a SSS. Various copies of licensed user’s signals are received through the unlicensed user antennas over different antenna configuration. The received signals are combined using a modified equal gain combiner and energy of the combined signal is determined using Parseval’s relation for a discrete time signal. The received signal is used to form a square matrix which is converted to covariance matrix. Characteristic equation is obtained from covariance matrix to determine the minimum eigenvalue. The ratio of energy to minimum eigenvalue of the received signal is obtained and used as test statistics. The IMASS technique is evaluated using Probability of Detection (PD) and Total Error Probability (TEP) by comparing with EMASS. The proposed IMASS technique gives better performance with higher PD and lower TEP values than EMASS at all different antenna configurations.
Co-Authors Damilare Oluwole Akande Hammed O. Lasisi Oluwatobi Omolola Oyedokun Rebeccah Oluwafunmilayo Omowaiye Saheed Abiona Abolude Samson Iyanda Ojo Samson Iyanda Ojo