Conventional symbol time (ST) synchronization algorithms for orthogonal frequency-division multiplexing (OFDM) systems are mostly based on the maximum correlation result of the cyclic prefix. Due to the channel effect, the estimated ST is not accurate enough. Hence, one needs to further identify the channel impulse response (CIR) so as to obtain a better ST estimation. Overall, the required computational complexity is high because it involves time-domain (TD) correlation operations, as well as the fast Fourier transform (FFT) and inverse FFT (IFFT) operations. In this work, without the FFT/IFFT operations and the knowledge of CIR, a low-complexity TD ST estimation is proposed. We first characterize the frequency-domain (FD) interference effect. Based on the derivation, the new method locates the symbol boundary at the sampling point with the minimum interference in the FD (instead of the conventional maximum TD correlation result). Moreover, to reduce the computational complexity, the proposed FD minimum-interference (MI) metric is converted to a low-complexity TD metric by utilizing Parseval's theorem and the sampling theory. Simulation results exhibit good performance for the proposed algorithm in multipath fading channels.

Based on our previous work, this work presents a complete method for time-domain processing of frequency-domain data with evenly-spaced frequency indices, together with its application. The proposed method can be used to calculate the cross spectral and power spectral densities for the frequency indices of interest. A promising application for the time-domain processing of frequency-domain data, particularly for calculating the summation of frequency-domain cross- and auto-correlations in orthogonal frequency-division multiplexing (OFDM) systems, is studied. The advantages of the time-domain processing of frequency-domain data are 1) the ability to rapidly acquire the properties that are readily available in the frequency domain and 2) the reduced complexity. The proposed fast algorithm directly employs time-domain samples, and hence, does not need the fast Fourier transform (FFT) operation. The proposed algorithm has a lower complexity (required complex multiplications ∼ O(N)) than conventional techniques.

In OFDM receivers, an accurate signal-to-noise ratio (SNR) estimation is desirable for all sorts of operations involved in high-performance baseband demodulation. In this work, conventional SNR estimation techniques are investigated. Next, a blind SNR estimation scheme for the phase-shift keying (PSK) signals based on the coherence function is proposed. The proposed method is non-data-aided (NDA) and hence bandwidth-efficient. Simulations confirm that the proposed method has the best performance from moderate to high SNRs both in AWGN and dispersive channels; however, the proposed method has worse performance when SNRs are low.

This letter introduces a blind minimum interference symbol synchronization for orthogonal frequency-division multiplexing (OFDM) systems based on the cyclic prefix (CP). The basic idea of our contribution is to obtain an estimate of the channel-tap powers from the correlation characteristics of the CP. Based on the estimate of the channel-tap powers, a minimum interference metric is proposed. The proposed algorithm has low complexity and can be used to cope with long inter-symbol-interference (ISI) channels with length up to twice the CP length.