Doppler shift estimation of MIMO-OFDM systems based on auto-correlation function of channel estimate

Multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) techniques have been considered as a strong candidate for the next-generation - wireless communication systems, due to their well-known advantages in high data-rate wireless transmission as well as high frequency spectrum efficiency. In the mean time, channel state information (CSI) is required for precise detection and recovery of signals. Therefore, channel estimation plays a significant role in MIMO-OFDM systems. On the other hand, due to the high mobility of wireless terminals, Doppler shift (DS) can be one of the major side-effects of utilizing MIMO-OFDM techniques, which may lead to severe performance loss. Many schemes on DS estimation have been developed for broadband single-input single-output (SISO) systems. A commonly used method is to exploit the auto-correlation property of the channel impulse response (CIR) estimated by well-developed channel estimation approaches, which not only has high accuracy but also moderate computational complexity. Hence, we first investigate an efficient channel estimation method in this thesis. We will then focus on Jakes' model based DS estimation schemes, and further extend to independently identically distributed (i.i.d.) MIMO-OFDM fading channels with both Rayleigh and Rician distributions. In the first part of the thesis, a training-sequence (TS) based least square (LS) channel estimation scheme is presented for MIMO-OFDM systems along with plenty of computer simulations and corresponding analyses. Experimental study shows that the CIR estimates obtained by the LS method are reliable under moderate channel conditions, and can efficiently be utilized for DS estimation. The second part of the thesis first studies the auto-correlation function (ACF) based DS estimation schemes for SISO-OFOM systems in Rayleigh fading channels, and then extends it to Rician fading channels by developing a new approach along with the analysis of its accuracy and complexity. Thereafter, we apply those approaches to MIMO-OFOM systems and present a few enhanced methods by using non-linear interpolation under certain circumstances. Detailed computer simulations and comparisons are performed, confirming that the proposed ACF based schemes give satisfactory estimation performance over i.i.d. Rayleigh or Rician fading channels with various channel conditions

Robust massive MIMO Equilization for mmWave systems with low resolution ADCs

Leveraging the available millimeter wave spectrum will be important for 5G. In this work, we investigate the performance of digital beamforming with low resolution ADCs based on link level simulations including channel estimation, MIMO equalization and channel decoding. We consider the recently agreed 3GPP NR type 1 OFDM reference signals. The comparison shows sequential DCD outperforms MMSE-based MIMO equalization both in terms of detection performance and complexity. We also show that the DCD based algorithm is more robust to channel estimation errors. In contrast to the common believe we also show that the complexity of MMSE equalization for a massive MIMO system is not dominated by the matrix inversion but by the computation of the Gram matrix.Comment: submitted to WCNC 2018 Workshop

Estimation of Sparse MIMO Channels with Common Support

We consider the problem of estimating sparse communication channels in the MIMO context. In small to medium bandwidth communications, as in the current standards for OFDM and CDMA communication systems (with bandwidth up to 20 MHz), such channels are individually sparse and at the same time share a common support set. Since the underlying physical channels are inherently continuous-time, we propose a parametric sparse estimation technique based on finite rate of innovation (FRI) principles. Parametric estimation is especially relevant to MIMO communications as it allows for a robust estimation and concise description of the channels. The core of the algorithm is a generalization of conventional spectral estimation methods to multiple input signals with common support. We show the application of our technique for channel estimation in OFDM (uniformly/contiguous DFT pilots) and CDMA downlink (Walsh-Hadamard coded schemes). In the presence of additive white Gaussian noise, theoretical lower bounds on the estimation of SCS channel parameters in Rayleigh fading conditions are derived. Finally, an analytical spatial channel model is derived, and simulations on this model in the OFDM setting show the symbol error rate (SER) is reduced by a factor 2 (0 dB of SNR) to 5 (high SNR) compared to standard non-parametric methods - e.g. lowpass interpolation.Comment: 12 pages / 7 figures. Submitted to IEEE Transactions on Communicatio