Work

Enhanced nonlinear equalization for OFDM systems in IoT-based intelligent transportation using CGLS algorithms

Year: 2025

Type: article

Abstract: The rapid development of intelligent transportation systems and the Internet of Things (IoT) has increased the need for robust and efficient wireless communication in high-mobility environments, such as vehicle-to-everything networks. Orthogonal frequency division multiplexing is widely used due to its high data rates and resistance to multipath fading. However, in fast-moving scenarios, Doppler effects cause interference between subcarriers, reducing signal quality. This paper proposes a practical nonlinear equalization framework based on the conjugate gradient least squares (CGLS) method to tackle this problem. Two advanced designs—a CGLS-based block decision feedback equalizer and a regularized least squares CGLS sliding window equalizer—are introduced and tested. Simulation results show that the proposed methods significantly reduce bit error rates and achieve up to a 5 dB performance improvement over traditional approaches, while keeping computational costs low enough for real-time IoT applications. This work supports the development of safer, more reliable, and energy-efficient communication systems for smart and sustainable transportation. These contributions align with the United Nations Sustainable Development Goals (SDGs), specifically SDG 9 (Industry, Innovation, and Infrastructure), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action) by supporting the development of resilient, energy-efficient, and scalable digital communication infrastructures for smart mobility and urban sustainability.

Source: EURASIP Journal on Wireless Communications and Networking

DOI: 10.1186/s13638-025-02492-7