Automotive radar using IEEE 802.11p signals

Autonomous vehicles have led to a surge in research on automotive radar both in academia and industry during the last few years. In this report, we develop a framework for using the dedicated short range communication (DSRC) waveform for the purposes of automotive radar. Our approach operates on the frequency domain channel estimates generated by the OFDM physical layer used in DSRC. We consider a two path channel model, with the first cluster corresponding to direct signal interference and the second cluster corresponding to the signal reflected from the target. The target ranging, direction of arrival and velocity information is encoded in the parameters of the reflected path. We estimate the parameters of the direct and reflected path using a variant of least squares matching pursuit algorithm by exploiting their relative power difference. The performance of the algorithm is evaluated through numerical simulations assuming low power omnidirectional 5 dBi antennas, Swerling type 0 and type 3 target models, 10 MHz transmission bandwidth and different analog-to-digital quantization resolutions. Simulations results show sub-meter accuracy in location estimation for a significant range of target distances. The results are also compared with the Cramer-Rao lower bound which is a theoretical performance benchmark.Electrical and Computer Engineerin

Multi-user Downlink Beamforming using Uplink Downlink Duality with CEQs for Frequency Selective Channels

High-resolution fully digital transceivers are infeasible at millimeter-wave (mmWave) due to their increased power consumption, cost, and hardware complexity. The use of low-resolution converters is one possible solution to realize fully digital architectures at mmWave. In this paper, we consider a setting in which a fully digital base station with constant envelope quantized (CEQ) digital-to-analog converters on each radio frequency chain communicates with multiple single antenna users with individual signal-to-quantization-plus-interference-plus-noise ratio (SQINR) constraints over frequency selective channels. We first establish uplink downlink duality for the system with CEQ hardware constraints and OFDM-based transmission considered in this paper. Based on the uplink downlink duality principle, we present a solution to the multi-user multi-carrier beamforming and power allocation problem that maximizes the minimum SQINR over all users and sub-carriers. We then present a per sub-carrier version of the originally proposed solution that decouples all sub-carriers of the OFDM waveform resulting in smaller sub-problems that can be solved in a parallel manner. Our numerical results based on 3GPP channel models generated from Quadriga demonstrate improvements in terms of ergodic sum rate and ergodic minimum rate over state-of-the-art linear solutions. We also show improved performance over non-linear solutions in terms of the coded bit error rate with the increased flexibility of assigning individual user SQINRs built into the proposed framework.Comment: arXiv admin note: text overlap with arXiv:2206.1442

Signal processing and bounds for fully digital mmWave architectures with low-resolution converters

Low-resolution analog to digital converters (ADCs) and digital to analog converters (DACs) are the key to power-efficient fully digital massive multiple input multiple output transceivers operating at large bandwidths. The use of low-resolution converters, however, results in severe distortion in the signal model which requires significantly different analysis and signal processing techniques compared to high-resolution systems. In this dissertation, we analyze the performance and design algorithms for sensing and wireless communication systems equipped with low-resolution converters. In the first half of this dissertation, we focus on the sensing application where we consider a fully digital architecture with 1-bit ADCs on each radio-frequency chain. We characterize the effect of the 1-bit ADCs on the radar parameter estimation by the Cramér-Rao bound and show that at low per-antenna signal-to-noise ratios the 1-bit converters result in a loss of 2 dB compared to a system with ideal ∞-resolution ADCs. We then design a low-complexity analog preprocessing unit, realizable through low-cost low-resolution phase-shifters, that reduces the performance gap of the 1-bit system from the ∞-resolution system to 1.16 dB. Our numerical results demonstrate the potential of the proposed architecture to meet the requirements of high-resolution sensing under the low-resolution hardware constraints. In the second half of this dissertation, we focus on the communication application and consider the multi-user (MU) downlink (DL) beamforming (BF) problem under constant envelope quantizer (CEQ) constraints at the base station. We provide a linear precoding based solution to the MU-DL-BF problem by extending the well known uplink-downlink duality principle for ∞-resolution systems to systems constrained by CEQs for both flat and frequency selective channels. Our results show that the proposed formulation significantly outperforms state of the art linear precoding strategies in terms of the ergodic sum rate and ergodic minimum rate. The proposed solution further reduces the performance gap of linear precoding strategies from non-linear precoding methods and actually outperforms them in terms of the coded bit error rate over a wide range of system parameters.Electrical and Computer Engineerin