Machine learning, and more specifically deep learning, have shown remarkable
performance in sensing, communications, and inference. In this paper, we consider the …

We consider the problem of sinusoidal parameter estimation using signed observations
obtained via one-bit sampling with fixed as well as time-varying thresholds. In a previous …

One-bit radar, performing signal sampling and quantization by a 1-bit analog-to-digital
converter, is a promising technology for many civilian applications due to its low-cost and …

Millimeter wave (mmWave) massive MIMO cellular systems will be characterized by
increased bandwidths and the ability to handle a large number of users. To cope with the …

We propose a novel mixed analog-to-digital converter (ADC) architecture for direction-of-
arrival (DOA) estimation using a uniform linear array, where the in-phase and quadrature …

Multi-user millimeter wave (mmWave) massive multi-input multi-output (MIMO) is a
promising technology for the next generation mobile communication systems. However …

Much effort has been devoted to recovering sparse signals from one-bit measurements in
recent years. However, it is still quite challenging to recover signals with high fidelity, which …

We consider a mixed analog-to-digital converter (ADC) based architecture consisting of high-
precision and one-bit ADCs with the antenna-varying threshold for direction of arrival (DOA) …

We consider angular-domain channel estimation in massive MIMO systems using one-bit
analog-to-digital converters (ADCs) with various thresholding schemes at the receivers. We …

In this paper, we consider the problem of signal recovery from 1-bit noisy measurements. We
present an efficient method to obtain an estimation of the signal of interest when the …