OTFS-based Integrated Positioning and Communication Systems with Low-Resolution ADCs

TL;DR

This paper introduces an OTFS-based integrated positioning and communication system that operates effectively with low-resolution ADCs, combining channel estimation, user positioning, and beamforming to enhance performance despite quantization limitations.

Contribution

It presents a novel two-phase OTFS framework with algorithms for channel and position estimation under low-resolution ADC constraints, including theoretical bounds and simulation validation.

Findings

Enhanced downlink bit error rate with better uplink positioning

Low-resolution ADCs cause performance degradation

Proposed algorithms effectively estimate channel and position

Abstract

This paper proposes a two-phase orthogonal time frequency space (OTFS)-based integrated positioning and communication (IPAC) framework under realistic low-resolution analog-to-digital converters (ADCs). In the uplink phase, the positioning signal is used to estimate channel parameters, which are subsequently used to determine the user's position. The spatial smoothing-multiple signal classification algorithm is introduced to estimate the angle-of-arrival, whereas an iterative interference cancellation scheme is conceived for the remaining parameters' estimation. The corresponding Cramer-Rao lower bounds of channel parameters and user position are also derived. During the downlink communication phase, the estimated parameters are exploited to improve beamforming at the base station. Simulation results evaluate the impact of ADC quantizer resolutions. Specifically, it is shown that enhanced downlink bit error rate performance can be achieved with improved uplink positioning, while the use of low-resolution ADCs induces noticeable performance degradation in the OTFS-IPAC system.