Reduction of Destructive Multipath Signal Effects in Radio Propagation Using Adaptive Equalization Technique
Article Sidebar
Page Numbers:
1586-1602
Digital Object Identifier:
10.58578/ajstea.v3i5.7051
Viewed: 196 times
Downloaded: 132 times
LYAS Publisher cordially invites qualified professionals to serve as Editors or Reviewers. Your expertise will make an important contribution to maintaining and strengthening the academic quality of our publications. Interested applicants are kindly requested to complete the application form at the following link: Editors & Reviewers
Please feel free to contact us if you need any further information about the submission process or if you have any additional questions.
Authors:Nwanoruo M. N.1*, Okoye J. A.2, Mbachu C. B.3
Copyright :Authors retain copyright and grant the journal right of first publication.
Main Article Content
Abstract
Radio signals transmitted through propagation channels are subject to fading, dispersion, and distortion, often resulting in communication errors such as inter-symbol interference. These impairments, largely influenced by atmospheric conditions and physical obstructions, alter signal behavior during transmission. This study evaluates the effectiveness of adaptive equalization techniques in mitigating the adverse effects of destructive multipath signals in wireless and radio communication systems. A Rayleigh fading channel model was employed, and an adaptive algorithm was implemented to approximate the desired filter by minimizing the least mean square error (MSE) of the output signal. System performance was assessed using source recovery error as a cost function to correct delays and recover the transmitted information. Two equalization strategies—decision-directed and dispersion minimization algorithms—were developed to reduce multipath-induced errors. Results showed that adaptive equalization significantly reduced signal ripple. The decision-directed equalizer exhibited faster convergence but higher steady-state error, achieving an optimal MSE value of 10⁻² and outperforming the dispersion minimization approach. These findings confirm the effectiveness of adaptive equalization in enhancing communication reliability under fading channel conditions.
Citation Metrics:
Downloads
Article Details
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
References
Achebe, P. N. and Muoghalu, C. N. (2024). Capacity analysis of multiple antenna wireless system under different array and channel configurations. International Journal of Advanced Networking and Applications, 15(4), 6063-6068.
Garima, M. and Amandeep, S.S. (2021). Adaptive equalization algorithm: An overview. International Journal of Advanced Computer Science and Applications vol. 2, No.3.
Jina, K. (2023). Area and power conscious rake receiver design for third generation WCDMA systemS’.
Mahdin, M. and Sittul, M. (2017). Comparison of different models for the analysis of rayleigh fading channels.
Osuagwu, I. C., Nwabueze, C. A., & Muoghalu, C. N. (2024). Investigating the quality of service at receiver end due to multipath fading on signal strength. International Journal of Progressive Research in Engineering Management and Science, 4(6), 2552-2557.
Osuagwu, I. C., Nwabueze, C. A., & Muoghalu, C. N., Ajere, I. U. (2025). Adaptive equalization technique for mitigating effect of multi terrain multipath signal quality. International Journal of Advanced Networking and Applications, 16(5), 6533-6543.
Prachi, S., Piush, G. and Pradeep, K. S. (2024). Performance comparison of ZF, LMS and RLS algorithms for linear adaptive equalizer. Advance in Electronic and Electric Engineering. ISSN 2231-1297, 587-592.
Richard, C., North, R. A., and James, R. Z. (2021). The performance of adaptive equalization for digital communication systems corrupted by interference. ASILOMAR Conf. on Signals, Systems and Computers10/93, pp 3.
William, C. L. (2016). Mobile communication engineering, McGraw-Hill book company, New York. www.navymars.org/national/training/nmo.14182_ch2.pdf, “Radio Wave PropagatioN”.
Yahong, R., Zheng, J., and Jing, P. (2020). Simulation model with correct statistical properties of rayleigh fading channels