Variable Step-Size LMS-Based Anti-Jamming Algorithm for Industrial IoT Communications over 2.4 GHz ISM Band
Year: 2026
Type: article
Abstract: Industrial Internet of Things (IIoT) systems deployed in factory environments face severe narrowband interference in the 2.4 GHz ISM band, where ZigBee-based sensor networks coexist with Wi-Fi and Bluetooth devices operating under strong electromagnetic interference from industrial machinery. Conventional adaptive filters employing fixed step-size Least Mean Squares (LMS) algorithms fail under high Jammer-to-Noise Ratio (JNR) conditions, exhibiting numerical instability and bit error rates (BER) approaching 0.5. This paper proposes a Variable Step-Size LMS (VS-LMS) algorithm integrated with Direct Sequence Spread Spectrum (DSSS) modulation to address this limitation. The proposed step-size update rule adaptively scales the learning rate according to instantaneous filter error: μ(n)=μ min +(μ max -μ min ) · exp(-α·e 2 (n)) , enabling large step-sizes during convergence and small step-sizes under strong interference to maintain numerical stability. Python-based simulations under AWGN plus sinusoidal narrowband interference (JNR=25 dB) demonstrate that the proposed VS-LMS scheme reduces BER by 76.1% compared to conventional fixed-step LMS, recovering communication quality (BER=0.12) in scenarios where fixed-step LMS completely fails. The results confirm that the proposed software-layer approach provides a practical, hardware-agnostic solution for reliable IIoT communications in electromagnetically hostile factory environments.
Author: Haoxin Chen
Institution: South China University of Technology
Language: English
Subfield: Computational Mechanics
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7225168588