Channel Impulse Response-Based Sensing Algorithm for Localization Using Downlink Pilots in 5G NR: Theory and Applications

Abstract

Environmental sensing is a pivotal technology that utilizes sensor data to enable vehicles, robots, and drones to accurately perceive their surroundings. The emergence of 5G New Radio (NR) networks as specialized sensors for environmental sensing has become a promising research direction, particularly within the context of integrated sensing and communication (ISAC) systems. One category of ISAC research in 5G NR primarily focus on radar signal modeling to create range-Doppler imaging maps. However, the generation of range-Doppler maps demands a significant amount of continuous data in the time-frequency domain, which is usually unavailable in localization tasks that rely on time domain data. This paper focuses on utilizing the downlink pilots in 5G NR without modifying the existing communication functions, aiming to propose an implementation algorithm for sensing from the perspective of the channel model. Firstly, we investigate the performance of an inverse discrete Fourier transform (IDFT)-based channel impulse response (CIR) ranging scheme. Secondly, a CIR-based back projection (BP) algorithm for sensing is proposed, which exploits the downlink pilots of 5G NR. In this algorithm, the transceiver pair consisting of a gNB and user equipment (UE) is treated as a subaperture, and the subapertures from all gNBs are combined to emulate the effect of a synthetic aperture. Finally, the performance of the CIR-based BP sensing algorithm is demonstrated through simulations. Notably, the advantage of the proposed method is that it does not require redesigning 5G NR signals, does not interfere with communication functions, and only requires the pilot from a single orthogonal frequency division multiplexing (OFDM) symbol for sensing, thereby offering an innovative approach to environmental sensing and localization.