IRS Aided Millimeter-Wave Sensing and Communication: Beam Scanning, Beam Splitting, and Performance Analysis

Author:

Renwang Li, Xiaodan Shao, Shu Sun, Meixia Tao, Rui Zhang

Keyword:

Computer Science, Information Theory, Information Theory (cs.IT), Signal Processing (eess.SP)

journal:

date:

2024-01-27 00:00:00

Abstract

Integrated sensing and communication (ISAC) has attracted growing interests for enabling the future 6G wireless networks, due to its capability of sharing spectrum and hardware resources between communication and sensing systems. However, existing works on ISAC usually need to modify the communication protocol to cater for the new sensing performance requirement, which may be difficult to implement in practice. In this paper, we study a new intelligent reflecting surface (IRS) aided millimeter-wave (mmWave) ISAC system by exploiting the distinct beam scanning operation in mmWave communications to achieve efficient sensing at the same time. First, we propose a two-phase ISAC protocol aided by a semi-passive IRS, consisting of beam scanning and data transmission. Specifically, in the beam scanning phase, the IRS finds the optimal beam for reflecting signals from the base station to a communication user via its passive elements. Meanwhile, the IRS directly estimates the angle of a nearby target based on echo signals from the target using its equipped active sensing element. Then, in the data transmission phase, the sensing accuracy is further improved by leveraging the data signals via possible IRS beam splitting. Next, we derive the achievable rate of the communication user as well as the Cram\'er-Rao bound and the approximate mean square error of the target angle estimation Finally, extensive simulation results are provided to verify our analysis as well as the effectiveness of the proposed scheme.

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