A two-stage approach to estimate CFO and channel with one-bit ADCs

Abstract

In this letter, we propose a two-stage approach to estimate the carrier frequency offset (CFO) and channel with one-bit analog-to-digital converters (ADCs). Firstly, a simple metric which is only a function of the CFO is proposed, and the CFO is estimated via solving the one-dimensional optimization problem.Secondly, the generalized approximate message passing (GAMP) algorithm combined with expectation maximization (EM) method is utilized to estimate the channel. In order to provide a benchmark of our proposed algorithm in terms of the CFO estimation, the corresponding Cramér-Rao bound (CRB) is derived. Furthermore, numerical results demonstrate the effectiveness of the proposed approach when applied to the general Gaussian channel and mmWave channel. keywords: CFO, channel estimation, millimeter wave system, one-bit quantization I. INTRODUCTIONTo provide a high-speed data rate in celluar systems, the mmWave multiple input multiple output (MIMO) system has been proposed as the key technology of the fifth generation (5G) cellular system [1,2]. Because of the larger bandwidths that accompany mmWave, the cost and power consumption are huge due to high precision (e.g., 10-12 bits) analog-to-digital converters (ADCs) [3]. As a result, a low precision (e.g., 1-4 bits) ADC is employed to relieve this ADC bottleneck [4,5]. However, as low precision quantization is severely nonlinear, traditional algorithms designed for high precision systemscan not be applied directly because of significant performance degradation. As a consequence, new signal processing algorithms dealing with channel estimation and transmit precoding have been proposed, which work well in systems with low precision ADCs [6][7][8][9]. For the channel estimation in mmWave systems, it can be regarded as one-bit compressed sensing (CS) problems [10][11][12][13][14], as the mmWave MIMO channel is approximately sparse in angle domain [15]. Therefore, many CS-based algorithms have been proposed to estimate the mmWave MIMO channel. In [16,17], a modified expectation maximization (EM) algorithm

One-Bit LFM Pulse Radar: Harmonic Analysis and Target Reconstruction

“…Because the spectrum of the time window rect(t/T w ) is known, we ignore the term rect(•) for simplicity in the following 3 . Instead of (8), we analyze the spectrum of…”

“…Because the advantages of one-bit quantization, the applications of the one-bit ADC has recently attracted considerable research interest for 5G wireless communications [3]- [8], wireless sensor network (WSN) [9]- [11], radar [12]- [17] and so on. However, as for one-bit radar, how to carry out signal processing and target reconstruction based…”