This paper presents a novel two-step method for channel estimation in millimeter wave hybrid MIMO systems over doubly (time and frequency) selective channels. In the first step, the dominant delay taps of the channel are selected by using an energy detector. In the second step, utilizing the basis expansion model (BEM) for effectively representing doubly selective channels, a BEM-based block orthogonal matching pursuit algorithm is proposed for estimating the gains of the selected delay taps. The proposed method benefits from exploiting the entire available training sequence to estimate all channel parameters, is capable of capturing channel variations across the whole training frames and does not require any feedback. Computer simulations and complexity evaluations show that the proposed approach can significantly improve the mean squared error performance compared with the existing techniques without increasing the computational complexity.

In this paper, we present novel methods for signal detection in single carrier zero-padded spatial modulation under high mobility conditions. By expressing the doubly selective channel in terms of the basis expansion model (BEM), first a maximum likelihood (ML) method is presented as a processing framework. To reduce the complexity of the exhaustive ML search, two novel methods, respectively the BEM-based partial interference cancellation (BPIC) and BPIC with successive interference cancellation (BPIC-SIC), are then proposed. The complexity of the new methods are compared and their performance is evaluated by simulations in terms of bit error rate. The results indicate that the new schemes can remarkably improve the performance compared with the conventional methods.

In this paper, a novel pilot-aided algorithm is proposed for the detection of integer frequency offset (IFO) in orthogonal frequency division multiplexing (OFDM) systems. By transforming the IFO into two new integer parameters, the proposed method can largely reduce the number of trial values for the true IFO. The two new integer parameters are detected using two different pilot sequences, a periodic pilot sequence and an aperiodic pilot sequence. It is shown that the new scheme can significantly reduce the computational complexity while achieving almost the same performance as compared to previous methods.

In this paper, we investigate new methods for preamble-aided coarse timing estimation in orthogonal frequency division multiplexing systems. Two novel timing metrics using high-order statistics-based correlation and differential normalization functions are first proposed. The performance of the new timing metrics is then evaluated using different criteria, including class separability, robustness to the carrier frequency offset, and computational complexity. It is shown that the new timing metrics can considerably increase the class separability due to their more distinct values at correct and wrong timing instants, and thus give a significantly better detection performance as compared with the existing timing metrics. Furthermore, a new method for coarse estimation of the start of the frame is proposed, which remarkably reduces the probability of intersymbol interference (ISI). The improved performances of the new schemes in multipath fading channels are shown by the probabilities of false alarm, missed detection, and ISI obtained through computer simulations.

This paper addresses the estimation of the integer part of the carrier frequency offset (CFO) in orthogonal frequency division multiplexing (OFDM) systems. A novel method is presented based on the maximum likelihood (ML) approach that jointly estimates the channel impulse response (CIR) and the integer CFO. The new scheme estimates the CIR by using pilots and obtains the estimate of the integer CFO by taking advantage of the effect of the CFO on the CIR and data symbols. The performance of the new method is evaluated in Rayleigh fading channels. The results demonstrate that the proposed scheme significantly outperforms the previous methods.