Joint Phase Noise and Transmitter Power Fluctuation Compensation for Sensing via OFDM ISAC Systems

Both phase noise (PN) and transmitter (TX) power fluctuation significantly degrade the sensing performance of orthogonal frequency division multiplexing (OFDM) integrated sensing and communication (ISAC) systems. However, previous studies have primarily focused on compensating for PN, without addressing the compensation for TX power fluctuation. In this paper, we consider the problem of sensing via OFDM ISAC systems affected by both PN and TX power fluctuation. Unlike existing algorithms, we propose an iterative parametric algorithm, referred to as AUTORELAX, to jointly compensate for PN and TX power fluctuation. Numerical examples show that the proposed AUTORELAX algorithm is effective.

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Published
2025-07-12
DOI
https://doi.org/10.1109/icsip65915.2025.11171491
Primary Topic
Power Line Communications and Noise
Type
article
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article

Joint Phase Noise and Transmitter Power Fluctuation Compensation for Sensing via OFDM ISAC Systems

Menglong Wu, Rui Guo
Power Line Communications and Noise
article

Joint Phase Noise and Transmitter Power Fluctuation Compensation for Sensing via OFDM ISAC Systems

Menglong Wu, Rui Guo
article en

Abstract

Both phase noise (PN) and transmitter (TX) power fluctuation significantly degrade the sensing performance of orthogonal frequency division multiplexing (OFDM) integrated sensing and communication (ISAC) systems. However, previous studies have primarily focused on compensating for PN, without addressing the compensation for TX power fluctuation. In this paper, we consider the problem of sensing via OFDM ISAC systems affected by both PN and TX power fluctuation. Unlike existing algorithms, we propose an iterative parametric algorithm, referred to as AUTORELAX, to jointly compensate for PN and TX power fluctuation. Numerical examples show that the proposed AUTORELAX algorithm is effective.

University of Science and Technology of China (CN)
Openalex Percentile: Top 72%
Power Line Communications and Noise
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