CFP last date
03 June 2024
Reseach Article

Comparative Analysis of Performance of a Developed Energy-efficient Optimal Frequency System Versus Existing Overlay and Underlay Approaches

by Oluwaseun S. Adewuyi, Matthew I. Ehikhamenle, Samson I. Ojo, Benjamin O. Akinloye
Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
Volume 7 - Number 39
Year of Publication: 2023
Authors: Oluwaseun S. Adewuyi, Matthew I. Ehikhamenle, Samson I. Ojo, Benjamin O. Akinloye
10.5120/cae2023652901

Oluwaseun S. Adewuyi, Matthew I. Ehikhamenle, Samson I. Ojo, Benjamin O. Akinloye . Comparative Analysis of Performance of a Developed Energy-efficient Optimal Frequency System Versus Existing Overlay and Underlay Approaches. Communications on Applied Electronics. 7, 39 ( Aug 2023), 16-25. DOI=10.5120/cae2023652901

@article{ 10.5120/cae2023652901,
author = { Oluwaseun S. Adewuyi, Matthew I. Ehikhamenle, Samson I. Ojo, Benjamin O. Akinloye },
title = { Comparative Analysis of Performance of a Developed Energy-efficient Optimal Frequency System Versus Existing Overlay and Underlay Approaches },
journal = { Communications on Applied Electronics },
issue_date = { Aug 2023 },
volume = { 7 },
number = { 39 },
month = { Aug },
year = { 2023 },
issn = { 2394-4714 },
pages = { 16-25 },
numpages = {9},
url = { https://www.caeaccess.org/archives/volume7/number39/892-2023652901/ },
doi = { 10.5120/cae2023652901 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-09-04T20:03:01.721354+05:30
%A Oluwaseun S. Adewuyi
%A Matthew I. Ehikhamenle
%A Samson I. Ojo
%A Benjamin O. Akinloye
%T Comparative Analysis of Performance of a Developed Energy-efficient Optimal Frequency System Versus Existing Overlay and Underlay Approaches
%J Communications on Applied Electronics
%@ 2394-4714
%V 7
%N 39
%P 16-25
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper proposed an effective switching technique between Overlay Cognitive Radio (OCR) and Underlay Cognitive Radio (UCR) in a wireless communication system. The availability of white or brown space is achieved using energy detector and the system switches to overlay approach when there is presence of white space, and instantly switches to underlay approach when there is presence of brown space based on the switching algorithm. Also, Hybrid Decode Amplify and Forward (H-DAF) cooperative relay technique is incorporated to enhance the coverage area of the cognitive user. During the underlay approach, the received signal at the relay node is decoded, amplified, and coded using CDMA before forwarding to the CU receiver. The proposed spectrum management system is simulated using MATLAB R2021a and evaluated using Throughput (TP) and Spectral Efficiency (SE) by comparing with the existing overlay and underlay CR approach. The simulated outcomes showed the designed system demonstrated improved switching system and performances than the existing techniques with highest TP and SE values and can be adopted in wireless communication designs for effective frequency spectrum usage.

References
  1. Barnes, S. D., Van Vuuren, P. J., & Maharaj, B. T. (2013). Spectrum occupancy investigation: measurements in South Africa. Measurement, 46(9), 3098-3112.
  2. Yuan, Y., Bahl, P., Chandra, R., Chou, P. A., Ferrell, J. I., Moscibroda, T., and Wu, Y. (2007, April). KNOWS: Cognitive radio networks over white spaces. In 2007 2nd IEEE international symposium on new frontiers in dynamic spectrum access networks (pp. 416-427).
  3. Act, E., & No, E. D. (2008). Second report and order and memorandum opinion and order. ET Docket, (08-260).
  4. Garrido, H. A. A., Rivero-Angeles, M. E., and Flores, I. Y. O. (2016, March). Performance analysis of a wireless sensor network for seism reporting in an overlay cognitive radio system. In 2016 30th international conference on advanced information networking and applications workshops (WAINA) (pp. 565-570).
  5. Naik, G., Singhal, S., Kumar, A., and Karandikar, A. (2014, February). Quantitative assessment of TV white space in India. In 2014 Twentieth National Conference on Communications (NCC) (pp. 1-6). IEEE.
  6. Akyildiz, I. F., Lee, W. Y., Vuran, M. C., & Mohanty, S. (2006). NeXt generation/ dynamic spectrum access/ cognitive radio wireless networks: A survey. Computer networks, 50(13), 2127-2159.
  7. Nikhil, A., and Rita, M. (2017). Cooperative spectrum sensing using hard-soft decision fusion scheme. International Journal of open Information Technologies, 5(5), 36-39.
  8. Dong, X. J., Chen, Y. B., Yang, G. Y., Pang, X. S., and Yang, J. X. (2015, June). The optimization of improved energy detector in Cognitive Radio network. In International Conference on Computer Information Systems and Industrial Applications (pp. 87-90). Atlantis Press.
  9. Adeyemo, Z. K., Ojo, S. I., Abolade, R. O., & Oladimeji, O. B. (2019). Modification of a Square-Law Combiner for Detection in a Cognitive Radio Network. International Journal of Wireless and Microwave Technologies, 9(2), 32-45.
  10. Chang, K. (2012). Spectrum Sensing, Detection and Optimization in Cognitive Radio for Non- Stationary Primary User Signals, unpublished Ph.D. Thesis submitted to Queensland University of Technology, Network and Communication, Faculty of Science and Engineering, pp 23-189.
  11. Kachroo, A., & Ekin, S. (2018, August). Impact of secondary user interference on primary network in cognitive radio systems. In 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall) (pp. 1-5).
  12. Alizadeh, A., Bahrami, H. R., & Maleki, M. (2016). Performance analysis of spatial modulation in overlay cognitive radio communications. IEEE Transactions on Communications, 64(8), 3220-3232.
  13. Abdou, A., Abdo, A., & Jamoos, A. (2019). Overlay cognitive radio based on OFDM with channel estimation issues. Wireless Personal Communications, 108, 1079-1096.
  14. Odeyemi, K. O., Owolawi, P. A., & Olakanmi, O. O. (2020). On the performance of underlay cognitive radio system with random mobility under imperfect channel state information. International Journal of Communication Systems, 33(15), e4561.
  15. Kumar, B., Kumar Dhurandher, S., and Woungang, I. (2018). A survey of overlay and underlay paradigms in cognitive radio networks. International Journal of Communication Systems, 31(2), e3443.
  16. Do, D. T., Le, A. T., and Lee, B. M. (2020). NOMA in cooperative underlay cognitive radio networks under imperfect SIC. IEEE Access, 8, 86180-86195.
  17. Rashid, R. A., Aripin, N. M., Hamzah, A. E., Ahmad, N., Fisal, N., & Yusof, S. K. S. (2008). Cross Layer Design of Cognitive Radio MB-OFDM Systems. In 3rd International Conference on Postgraduate Studies (ICPE3), Penang.
  18. Obayiuwana, E., Ayodele, P., & Fisusi, A. (2022). Power Minimization in Dual-Hop Underlay Cooperative Cognitive Radio Relay Networks for Optimal Resource Allocation. FUOYE Journal of Engineering and Technology, 7(1), 32-38.
  19. Singh, K. K., Yadav, P., Singh, A., Dhiman, G., & Cengiz, K. (2021). Cooperative spectrum sensing optimization for cognitive radio in 6 G networks. Computers and Electrical Engineering, 95, 107378.
  20. Lu, M., Zhou, B., Bu, Z., & Zhao, Y. (2022, April). A learning approach towards power control in full-duplex underlay cognitive radio networks. In 2022 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 2017-2022).
  21. Jia, X., Zheng, K., Chi, K., and Liu, X. (2022). DDPG-Based Throughput Optimization with AoI Constraint in Ambient Backscatter-Assisted Overlay CRN. Sensors, 22(9), 3262.
  22. Nigam, R., Pawar, S., & Sharma, M. (2021). Modified Bayesian algorithm‐based compressive sampling for wideband spectrum sensing in cognitive radio network using wavelet transform. International Journal of Communication Systems, 34(1), e4635.
  23. Ustok, R. F. (2010). Spectrum Sensing Techniques for Cognitive Radio Systems with Multiple Antennas, unpublished Master thesis in Electronics and communication Engineering, Graduate School of Engineering and Sciences, Izmir Institute of Technology, Turkey.
  24. Goldsmith, A.J. (2004). Wireless Communication” first Edition. Cambridge University press. Cambridge, England. pp 23-45.
  25. Mo, Z., Su, W., and Matyjas, J. D. (2016, November). Amplify and forward relaying protocol design with optimum power and time allocation. In MILCOM 2016-2016 IEEE Military Communications Conference (pp. 412-417).
  26. Liu, R., Guo, K., An, K., Zhu, S., and Shuai, H. (2022). Joint decoding order and power allocation design for a NOMA-based overlay cognitive integrated satellite-terrestrial relay network. Wireless Communications and Mobile Computing, 2022.
  27. AUTHORS’ PROFILE
  28. Oluwaseun S. Adewuyi/ has B.Tech. degree in Electrical/Electronic Engineering, M.Eng. in Communications Engineering from LAUTECH, Nigeria in 2008 and FUTA, Nigeria in 2013, respectively. He is currently a Doctoral student at Centre for Information and Telecommunication Engineering (CITE), University of Port-Harcourt (UNIPORT), Nigeria and a Manager at the Nigerian Communications Commission, NCC (an independent telecoms regulatory agency in Nigeria). His area of research includes Communication En
  29. Matthew I. Ehikhamenle has B.Eng., Electrical/Electronic Engineering from AAU, Ekpoma in 2007 and M.Eng. degree in Electrical/Electronic Engineering from UNIBEN in 2010, Nigeria. He obtained his Ph.D. degree specializing in Electronics and Communications from MOUAU, Nigeria. He is presently a Senior lecturer in the Electrical and Electronic Engineering Department, UNIPORT, Nigeria, where he is the Assistant Director of the Centre for information and telecommunication Engineering (CITE). His rese
  30. Samson I. Ojo received his B. Tech and M. Tech degrees in Electronic and Electrical Engineering in 2011 and 2018, respectively, from Ladoke Akintola University of Technology (LAUTECH), Ogbomoso, Nigeria. He is a registered member of Council for the Regulation of Engineering in Nigeria (COREN). He obtained his Ph.D. in mobile communication in the year 2021. His research interests are signal processing, diversity, and cognitive radio.
  31. Benjamin O. Akinloye received his B.Tech from LAUTECH, Nigeria in 2009 and M.Eng. degrees in Electronic and Electrical Engineering in 2014 from FUTA, Nigeria. He completed his PhD in Electrical Engineering from the UNN, Nigeria in 2023. He is a lecturer at the Federal University of Petroleum Resources, Nigeria. His research interests are electrical machine design and smart grids.
Index Terms

Computer Science
Information Sciences

Keywords

Cognitive radio; Dynamic Spectrum Access; white space; brown space; signal to interference ratio; Spectrum Utilization Efficiency.