Robust Channel Estimation and Performance Evaluation of OFDM Through AWGN Channel

Orthogonal frequency division multiplexing (OFDM) is a widely adopted modulation technique in modern communication systems, offering high data rates and spectral efficiency. Robust channel estimation in OFDM plays a critical role in mitigating the impact of wireless channel impairments. This paper presents a comprehensive study of various channel estimation techniques in OFDM systems, with a focus on their robustness in the presence of Additive White Gaussian Noise (AWGN) and fading channels. The research explores the robust channel estimation techniques such as; least square estimation (LS) and minimum mean square error estimation (MMSE) under AWGN noise channel. A thorough performance evaluation is conducted under simulated AWGN and fading conditions, utilizing metrics such as Mean Square Error (MSE), and Bit Error Rate (BER) by varying FFT size and different modulation orders of QAM. The results provide insights into the MSE and BER for both estimation techniques. In the case of MSE, the MMSE estimation achieves 98.5% improvement (reduction in MSE) when compared to LS estimation. When the order of modulation and FFT size increases, the MMSE shows an efficient improvement (92.8%) when compared to LS (65%). Whereas, in the case of BER, the MMSE estimation achieves a 64% improvement (reduction in BER) when compared to LS estimation. When the order of modulation and FFT size increases, the MMSE shows an efficient improvement (68%) when compared to LS (44%)