Adaptive Channel-State-Information Feedback in Integrated Sensing and Communication Systems

Published

August 28, 2023

Author(s)

Neeraj Varshney, Samuel Berweger, Jack Chuang, Steve Blandino, Jian Wang, Neha Pazare, Camillo Gentile, Nada T. Golmie

Abstract

Efficient design of integrated sensing and communication systems can minimize signaling overhead by reducing the size and/or rate of feedback in reporting channel state information (CSI). To minimize the signaling overhead when performing sensing operations at the transmitter, this paper proposes a procedure to reduce the feedback rate. We consider a threshold-based sensing measurement and reporting procedure, such that the CSI is transmitted only if the channel variation exceeds a threshold. However, quantifying the channel variation, determining the threshold, and recovering sensing information with a lower feedback rate are still open problems. In this paper, we first quantify the channel variation by considering several metrics including the Euclidean distance, time-reversal resonating strength, and frequency-reversal resonating strength. We then design an algorithm to adaptively select a threshold, minimizing the feedback rate, while guaranteeing sufficient sensing accuracy by reconstructing high-quality signatures of human movement. To improve sensing accuracy with irregular channel measurements, we further propose two reconstruction schemes, which can be easily employed at the transmitter in case there is no feedback available from the receiver. Finally, the sensing performance of our scheme is extensively evaluated through real and synthetic channel measurements, considering channel estimation and synchronization errors. Our results show that the amount of feedback can be reduced by 50% while maintaining good sensing performance in terms of range and velocity estimations. Moreover, in contrast to other schemes, we show that the Euclidean distance metric is better able to capture various human movements with high channel variation values.

Citation

IEEE Internet of Things Journal

Volume

10

Issue

24

Pub Type

Journals

Download Paper

https://doi.org/10.1109/JIOT.2023.3304545

Local Download

Keywords

802.11bf, 802.11ay pilots, communication waveform, human motion, sensing, target detection, threshold

Citation

Varshney, N. , Berweger, S. , Chuang, J. , Blandino, S. , Wang, J. , Pazare, N. , Gentile, C. and Golmie, N. (2023), Adaptive Channel-State-Information Feedback in Integrated Sensing and Communication Systems, IEEE Internet of Things Journal, [online], https://doi.org/10.1109/JIOT.2023.3304545, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935568 (Accessed April 29, 2024)