Communication systems face challenges from high-power adjacent
channel signals, or blockers, inducing nonlinear behavior in RF front
ends. Ensuring robust performance in the presence of blockers is
crucial for IoT and other spectrum-consuming devices coexisting with
advanced transceivers. This paper proposes a flexible, data-driven
solution using a Deep Belief Network (DBN) to mitigate third-order
intermodulation distortion (IMD) during demodulation. Numerical
evaluations of AI-enhanced receivers employing DBN as an IMD
canceler and demodulator show significant improvements in bit error
rate (BER) performance. The effectiveness of DBN varies with RF
front end characteristics, notably the third-order intercept point (IP3).
E. Shamsudeen1, B. Suganthi2, P. Ramesh3, C. Saravanakumar4
EMEA College of Arts and Science, India1, Dhanalakshmi Srinivasan University, India2, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India3, SRM Valliammai Engineering College, India4
Deep Belief Network, IMD Cancellation, Nonlinear Receivers, RF Front End, Bit Error Rate
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| Published By :
ICTACT
Published In :
ICTACT Journal on Communication Technology
( Volume: 15 , Issue: 2 , Pages: 3179 - 3184 )
Date of Publication :
June 2024
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243
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