학술논문

Comparison of the Mixed Norm(LMMN) and LMMN Algorithm with Sign-Regressor in Channel Equalization
Document Type
Conference
Source
2023 IEEE 3rd International Conference on Applied Electromagnetics, Signal Processing, & Communication (AESPC) Applied Electromagnetics, Signal Processing, & Communication (AESPC), 2023 IEEE 3rd International Conference on. :1-4 Nov, 2023
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Fields, Waves and Electromagnetics
Power, Energy and Industry Applications
Signal Processing and Analysis
Simulation
Bit error rate
Adaptive equalizers
Behavioral sciences
Convergence
LMMN
Sign Regressor LMMN
convergence analysis
BER
Language
Abstract
This paper gives an insight of equalization technique for a channel adapting itself to the changing environment and the framework is used to compare the performance of the mixed norm (LMMN) algorithm and the sign regressor mixed norm (SRLMMN) algorithm both in mean sense. According to the simulation results, the bit error rate (BER) performance of the LMMN and the SRLMMN algorithms is comparable. Additionally, the outcomes demonstrate that the Sign Regressor algorithm performs slightly worse than its original counterpart in terms of convergence behavior.