Low-Complexity Joint Azimuth-Range-Velocity Estimation for Integrated Sensing and Communication With OFDM Waveform

Integrated sensing and communication (ISAC) is a main application scenario of the sixth-generation mobile communication systems. Due to the fast-growing number of antennas and subcarriers in cellular systems, the computational complexity of joint azimuth-range-velocity estimation (JARVE) in ISAC sys...

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Vydané v:IEEE transactions on wireless communications Ročník 24; číslo 9; s. 7517 - 7529
Hlavní autori: Zhang, Jun, Yang, Gang, Ye, Qibin, Huang, Yixuan, Hu, Su
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.09.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Antenna arrays
Antennas
Azimuth
Communication
Complexity
Cramer-Rao bounds
Cramér-Rao bounds
Estimation
Integrated sensing and communication
joint azimuth-range-velocity estimation
low-complexity algorithm
Mobile communication systems
Multiple signal classification
OFDM
Orthogonal Frequency Division Multiplexing
Parameter estimation
Receiving antennas
Superresolution
Symbols
Waveforms
Wireless communication
ISSN:1536-1276, 1558-2248
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Popis
Shrnutí:Integrated sensing and communication (ISAC) is a main application scenario of the sixth-generation mobile communication systems. Due to the fast-growing number of antennas and subcarriers in cellular systems, the computational complexity of joint azimuth-range-velocity estimation (JARVE) in ISAC systems is extremely high. This paper studies the JARVE problem for a monostatic ISAC system with orthogonal frequency division multiplexing (OFDM) waveform, in which a base station receives the echoes of its transmitted cellular OFDM signals to sense multiple targets. The Cramér-Rao bounds are first derived for JARVE. A low-complexity algorithm is further designed for super-resolution JARVE, which utilizes the proposed iterative subspace update scheme and Levenberg-Marquardt optimization method to replace the exhaustive search of spatial spectrum in multiple-signal-classification (MUSIC) algorithm. Finally, with the practical parameters of 5G New Radio, simulation results verify that the proposed algorithm can reduce the computational complexity by three orders of magnitude and two orders of magnitude compared to the existing three-dimensional MUSIC algorithm and estimation-of-signal-parameters-using-rotational-invariance-techniques (ESPRIT) algorithm, respectively, and also improve the estimation performance.
Bibliografia:ObjectType-Article-1
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ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2025.3561060