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An Enhanced Pilot-Assisted Channel Estimation Framework for OFDM Systems Using Linear Predictive Coding Techniques
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Keywords
OFDM systems
Channel estimation
Pilot-assisted estimation
Linear predictive coding
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Abstract
Orthogonal Frequency-Division Multiplexing (OFDM) systems are highly susceptible to channel impairments, particularly in fast time-varying and frequency-selective wireless environments. Accurate channel estimation is therefore essential to ensure reliable data transmission and improved spectral efficiency. This paper proposes an enhanced pilot-assisted channel estimation framework that integrates linear predictive coding (LPC) techniques to improve estimation accuracy in dynamic wireless conditions. The proposed framework leverages temporal correlation in channel variations and combines pilot-based estimation with predictive modeling to mitigate noise and interpolation errors. A comprehensive analytical and simulation-based evaluation demonstrates that the proposed method significantly outperforms conventional least squares (LS), minimum mean square error (MMSE), and adaptive filtering approaches in terms of mean square error (MSE) and bit error rate (BER). The framework is particularly effective in high-mobility scenarios, where traditional estimation methods exhibit performance degradation. The findings contribute to the advancement of robust channel estimation strategies for next-generation wireless communication systems.
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