Sum-Rate Maximization for ISAC Systems With Backscatter RFID Tags

This paper investigates an integrated sensing and communication (ISAC) system incorporating backscattering radio frequency identification (RFID) tag. In this configuration, a base station (BS) simultaneously serves multiple users through a communication beam while utilizing a sensing beam to detect the presence of an RFID tag. A joint beamforming design problem is formulated to maximize the sum-rate for the users while ensuring the minimum quality of service (QoS) for the tag detection and the minimum QoS of all communication users. To tackle the non-convex nature of objective function the Lagrangian dual transform technique is employed. Due to the coupling of variables, an alternating optimization (AO) based algorithm is proposed with guaranteed convergence. Through numerical simulations, we validate the effectiveness of our proposed algorithm. Additionally, we assess the impact of several key parameters on system performance, including the number of transmitting antennas at the BS, the available transmit power at the BS, the minimum QoS for the communication users, and the number of communication users.

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Publication Details

Published
2025-06-08
DOI
https://doi.org/10.1109/icc52391.2025.11161315
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
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Sum-Rate Maximization for ISAC Systems With Backscatter RFID Tags

Raviteja Allu, Saba Al–Rubaye, Keshav Singh, Chih–Peng Li et al.
Energy Harvesting in Wireless Networks
article

Sum-Rate Maximization for ISAC Systems With Backscatter RFID Tags

Raviteja Allu, Saba Al–Rubaye, Keshav Singh, Chih–Peng Li, K Rojith
article en

Abstract

This paper investigates an integrated sensing and communication (ISAC) system incorporating backscattering radio frequency identification (RFID) tag. In this configuration, a base station (BS) simultaneously serves multiple users through a communication beam while utilizing a sensing beam to detect the presence of an RFID tag. A joint beamforming design problem is formulated to maximize the sum-rate for the users while ensuring the minimum quality of service (QoS) for the tag detection and the minimum QoS of all communication users. To tackle the non-convex nature of objective function the Lagrangian dual transform technique is employed. Due to the coupling of variables, an alternating optimization (AO) based algorithm is proposed with guaranteed convergence. Through numerical simulations, we validate the effectiveness of our proposed algorithm. Additionally, we assess the impact of several key parameters on system performance, including the number of transmitting antennas at the BS, the available transmit power at the BS, the minimum QoS for the communication users, and the number of communication users.

National Sun Yat-sen University (TW)
Openalex Percentile: Top 74%
Energy Harvesting in Wireless Networks
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