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Orthogonal frequency division multiplexing (OFDM) technology is the key to evolving telecommunication standards including 3GPP-LTE Advanced and WiMAX. Reliability of any OFDM system increases with improved mean square error performance (MSE) of its channel estimator (CE). Particularly, a least squares (LS) based CE incorporating a time-domain denoising threshold, enables better MSE performance, while avoiding the need for a-priori knowledge of channel statistics (KCS). Existing optimal time-domain thresholds exhibit suboptimal behavior for completely unavailable KCS environments. This is because they involve consistent estimation of one or more KCS parameters, and corresponding estimation errors introduce severe degradation in MSE performance of the CE. To overcome the MSE degradation, this paper proposes a weighted-noise threshold, by introducing a modified hypothesis-testing-problem (HTP) interpretation. Derivation of resulting analytical MSE expression is also provided. Results of OFDM system simulations carried out in rayleigh faded ITU-TU6 and WiMAX-SUI4 channel environments with U-shaped power spectral densities, are presented. The performance results show that, compared to many of the existing thresholds, the proposed threshold renders better MSE performance to the CE and higher reliability to the OFDM system in terms of better bit error rate (BER) performance.

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In reliable orthogonal frequency division multiplexing systems, channel estimator (CE) plays a crucial role. A pilot-aided orthogonal frequency division multiplexing CE often employs denoising thresholds to identify significant and noisy channel impulse response taps. When the knowledge of channel statistics (KCS) is completely unavailable, the existing suboptimal thresholds require consistent estimation of one or more KCS parameters. In this paper, the effect of noise variance parameter estimation on CE's mean square error (MSE) performance is characterized analytically by computing threshold's tap-detection probability. To mitigate MSE degradation due to KCS estimation, an eigen-select threshold, which does not require any KCS estimation, is proposed. It utilizes eigen values of the auto-covariance matrix formed by estimated channel impulse response. The proposed threshold is compared with existing state-of-art alternatives, for CE's MSE performance and system's BER performance, in correlated Rayleigh fading channel environments. Results reveal that, with the proposed threshold, performance plots converge to optimal solution more closely than the others. is concluded in Section 6. Necessary details of derivations are appended in Appendix. EIGEN-SELECT DENOISING THRESHOLDand cyclic prefix is removed. The resultant OFDM symbol is represented as y i;n , 0 6 n 6 N 1, where n is the subcarrier index in time domain. Applying DFT on y i;n , the corresponding frequency domain symbol Y i;k is given by Y i;k D DF T N ¹y i;n º