Article Per Year (5 Year)
p-Index From 2019 - 2024
0.444
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Samson Iyanda Ojo
LADOKE AKINTOLA UNIVERSITY OF TECHNOLOGY
Computer Science & IT Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
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.
On the applicability of some existing tropospheric scintillation prediction models for Ikeja and Abuja, Nigeria Zachaeus Kayode Adeyemo; Ridwan Olalekan Yusuf; Hammed Oyebamiji Lasisi; Samson Iyanda Ojo; Rebecca Olufunmilayoa Omowaiye; Adebukola Ayoade Adedeji
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5084-5092

Abstract

Tropospheric scintillation which causes rapid fluctuation of signal due to the turbulence in the atmosphere is of significance in satellite link budget design. Existing models that predict the intensity of scintillation such as Karasawa, International Telecommunication Union Radiocommunication (ITU-R) Sector, Otung, Van de Kamp and Ortgies are not appropriate for predicting scintillation intensity (SI) in Nigeria due to localization of the models to particular regions. The monthly average air temperature and relative humidity for Ikeja and Abuja, Nigeria, retrieved from the Nigerian Meteorological Centre data bank were used for the investigation. An elevation angle of 5° was used as look angle, antenna diameter of 0.3 m, 40 GHz and 45 GHz frequencies were considered in this study. The existing scintillation model values were then compared with the measured values for the two locations to determine the best performance model. The SI results at 40 GHz and 45 GHz were obtained for each of the existing models. It could be deduced from the results obtained that orgies model values were the most closet to the measured values. Therefore, Orgies-N model was the most appropriate for SI prediction in Ikeja and Abuja.
Co-Authors Adebukola Ayoade Adedeji Hammed Oyebamiji Lasisi Oluwatobi Omolola Oyedokun Rebecca Olufunmilayoa Omowaiye Rebeccah Oluwafunmilayo Omowaiye Ridwan Olalekan Yusuf Zachaeus Kayode Adeyemo Zachaeus Kayode Adeyemo