Integrated Sensing and Communication for RIS Assisted Backscatter Systems

To facilitate the development of Internet of Things (IoT) services, future networks are expected to simultaneously provide sensing functionality and support low-power communications. In this paper, we investigate the system sum rate maximization problem in an integrated sensing and RIS backscatter c...

Full description

Saved in:
Bibliographic Details
Published in:IEEE internet of things journal 2023-08, Vol.10 (15), p.1-1
Main Authors: Wang, Xinyi, Fei, Zesong, Wu, Qingqing
Format: Article
Language:English
Subjects:
Algorithms
Array signal processing
Backscatter
backscatter communication
Backscattering
Beamforming
Channel estimation
Communication
Communication systems
Communications systems
Cramer-Rao bounds
Integrated sensing and communications
Internet of Things
Mathematical programming
Optimization
reconfigurable intelligent surface
Sensors
Target tracking
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:To facilitate the development of Internet of Things (IoT) services, future networks are expected to simultaneously provide sensing functionality and support low-power communications. In this paper, we investigate the system sum rate maximization problem in an integrated sensing and RIS backscatter communication system, where the base station (BS) simultaneously detects backscattered signals from multiple IoT devices and senses targets based on the echo signals. We formulate a joint transmit beamforming, RIS phase shifts and receive beamforming design problem under the Cramér-Rao bound (CRB) constraint for target angle estimation. To solve the non-convex problem, we then propose a fractional programming based alternating optimization algorithm. In particular, the fractional programming technique is firstly employed to transform the formulated problem into a more tractable form, and the exact penalty method and manifold optimization are then utilized to address the CRB constraint and constant-modulus constraint, respectively. Numerical results have shown that the proposed design significantly improves the system sum rate and illustrate the trade-off between the communication and sensing performance.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2023.3262867