Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
To achieve
reliable orthogonal frequency division multiplexing (OFDM) communications in
frequency-selective fading channels, accurate channel estimation is critical.
The traditional least squares (LS) estimator enhances noise at pilot locations,
whereas the traditional pilot-only minimum mean square error (MMSE) estimator
adds residual interpolation error that remains independent of signal-to-noise
ratio (SNR). This paper suggests an Adaptive Full-Band Hybrid LS-MMSE channel
estimator which removes both of the limitations by a one-step linear minimum
mean square error (LMMSE) Wiener filter of size NxNP analytically
computed based on the complete channel frequency-domain cross-correlation
matrix using the exponential power delay profile (PDP). The proposed estimator
directly interpolates all pilot measurements to estimates in the entire
frequency band in a single step, ensuring the Hybrid MSE results better than LS
and MMSE results at any SNR. Monte Carlo simulated 16-QAM OFDM system with N =
64 subcarriers, NP = 16 pilots and L = 6 tap Rayleigh fading channel show
consistent performance improvements. The proposed method has a NMSE of -18.21
dB (4.83 dB gain over LS and 3.14 dB gain over MMSE) and a BER of 0.0649, and
spectral efficiency of 8.4 bits/s/Hz at SNR = 28 dB. The estimator is
computationally tractable, and it achieves the Cramer-Rao Lower Bound at high
SNR, making it a high-performance solution to 5G and beyond OFDM systems.
Country : Iraq
IRJIET, Volume 10, Issue 4, April 2026 pp. 276-286