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ZTE Communications ›› 2024, Vol. 22 ›› Issue (3): 48-55.DOI: 10.12142/ZTECOM.202403007

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  • 收稿日期:2024-07-30 出版日期:2024-09-25 发布日期:2024-09-29

Low-Complexity Integrated Super-Resolution Sensing and Communication with Signal Decimation and Ambiguity Removal

DAI Qianglong1, ZHOU Zhiwen1, XIAO Zhiqiang1,2, ZENG Yong1,2(), YANG Fei3, CHEN Yan3   

  1. 1.National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
    2.Purple Mountain Laboratories, Nanjing 211111, China
    3.Wireless Technology Lab. , 2012 Lab, Shanghai Huawei Technologies Co. , Ltd, Shanghai 201206, China
  • Received:2024-07-30 Online:2024-09-25 Published:2024-09-29
  • About author:DAI Qianglong received his BS degree in electronic and information engineering from Nanjing University of Posts and Telecommunications, China in 2023. He is currently pursuing his MS degree with the National Mobile Communications Research Laboratory, Southeast University, China. His research interests include ISAC and OFDM.
    ZHOU Zhiwen received his BS degree in electronic and information engineering from Nanjing University of Posts and Telecommunications, China in 2022. He is currently pursuing his MS degree with the National Mobile Communications Research Laboratory, Southeast University, China. His research interests include ISAC and XL-arrays.
    XIAO Zhiqiang received his BS and MS degrees from Nanjing University of Posts and Telecommunications, China in 2017 and 2020, respectively. He is currently pursuing his PhD degree with the National Mobile Communication Research Laboratory, Southeast University, China, and Purple Mountain Laboratories. His research interests include ISAC, waveform design and optimization, massive MIMO communications, and wireless localization.
    ZENG Yong ( yong_zeng@seu.edu.cn) is a full professor with the National Mobile Communications Research Laboratory, Southeast University, China, and also with the Purple Mountain Laboratories. He received both the BE (First-Class Honours) and PhD degrees from Nanyang Technological University, Singapore. From 2013 to 2018, he was a research fellow and senior research fellow at the Department of Electrical and Computer Engineering, National University of Singapore. From 2018 to 2019, he was a lecturer at the School of Electrical and Information Engineering, the University of Sydney, Australia. Dr. ZENG was a highly cited researcher by Clarivate Analytics for five consecutive years (2019–2023). He is the recipient of the Australia Research Council (ARC) Discovery Early Career Researcher Award (DECRA), 2020 and 2024 IEEE Marconi Prize Paper Awards in Wireless Communications, 2018 IEEE Communications Society Asia-Pacific Outstanding Young Researcher Award, 2020 and 2017 IEEE Communications Society Heinrich Hertz Prize Paper Awards, 2021 IEEE ICC Best Paper Award, and 2021 China Communications Best Paper Award. He has published more than 170 papers, which have been cited by more than 26 000 times based on Google Scholar.
    YANG Fei received his BS and PhD degrees in communication and information system in 2009 and 2014, respectively, both from University of Science and Technology of China (USTC). He joined Huawei Technologies Co., Ltd. since 2014. He has worked in departments of radio access network (RAN) chipset algorithm R&D and cell-phone communication protocol and technology. He is now a principal engineer in Wireless Technology Laboratory. His research interests include 6G channel modeling and integrated communication and sensing (ISAC) and their RAN simulation methodologies.
    CHEN Yan is a senior expert of wireless communication at Huawei Technologies Co., Ltd. She received her BS and PhD degrees from Chu Kochen Honored College and Institute of Information and Communication Engineering, Zhejiang University, China in 2004 and 2009, respectively. Her research interests include 6G vision and enabling technology study (e.g., use cases, key capabilities, evaluation methodologies, and emerging technologies such as ISAC and collaborative robotics enabled by integrated sensing, artificial intelligence, and communications).
  • Supported by:
    the National Natural Science Foundation of China(62071114)

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Abstract:

Integrated sensing and communication (ISAC) is one of the main usage scenarios for 6G wireless networks. To most efficiently utilize the limited wireless resources, integrated super-resolution sensing and communication (ISSAC) has been recently proposed to significantly improve sensing performance with super-resolution algorithms for ISAC systems, such as the Multiple Signal Classification (MUSIC) algorithm. However, traditional super-resolution sensing algorithms suffer from prohibitive computational complexity of orthogonal-frequency division multiplexing (OFDM) systems due to the large dimensions of the signals in the subcarrier and symbol domains. To address such issues, we propose a novel two-stage approach to reduce the computational complexity for super-resolution range estimation significantly. The key idea of the proposed scheme is to first uniformly decimate signals in the subcarrier domain so that the computational complexity is significantly reduced without missing any target in the range domain. However, the decimation operation may result in range ambiguity due to pseudo peaks, which is addressed by the second stage where the total collocated subcarrier data are used to verify the detected peaks. Compared with traditional MUSIC algorithms, the proposed scheme reduces computational complexity by two orders of magnitude, while maintaining the range resolution and unambiguity. Simulation results verify the effectiveness of the proposed scheme.

Key words: ISSAC, sparse decimation, range ambiguity, two-stage approach