Improve Radar Sensing Performance of Multiple Roadside Units Cooperation via Space Registration

Jiang, Wangjun; Wei, Zhiqing; Li, Bin; Zhang, Feng; Fang, Zixi

doi:10.1109/tvt.2022.3184182

Cited by 10 publications

(3 citation statements)

References 32 publications

(21 reference statements)

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“…By exploiting networked collaboration capabilities, multiple distributed sensors (including MUEs and APs that use ISAC) can cooperatively sense the same physical area, effectively reducing blind spots caused by obstruction and random deep fading in the single-sensor scenario [16]. Using distributed computing such as FL, collaborative MUEs can conduct distributed training, where they only need to exchange model parameters to share semantic information, thereby improving the efficiency of the sensing network and ensuring the security of data.…”

Section: Computing-empowered Networked Isacmentioning

confidence: 99%

Integrated Communication, Sensing, and Computation Framework for 6G Networks

Chen,

Feng,

Zhang

et al. 2024

Sensors

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In the sixth generation (6G) era, intelligent machine network (IMN) applications, such as intelligent transportation, require collaborative machines with communication, sensing, and computation (CSC) capabilities. This article proposes an integrated communication, sensing, and computation (ICSAC) framework for 6G to achieve the reciprocity among CSC functions to enhance the reliability and latency of communication, accuracy and timeliness of sensing information acquisition, and privacy and security of computing to realize the IMN applications. Specifically, the sensing and communication functions can merge into unified platforms using the same transmit signals, and the acquired real-time sensing information can be exploited as prior information for intelligent algorithms to enhance the performance of communication networks. This is called the computing-empowered integrated sensing and communications (ISAC) reciprocity. Such reciprocity can further improve the performance of distributed computation with the assistance of networked sensing capability, which is named the sensing-empowered integrated communications and computation (ICAC) reciprocity. The above ISAC and ICAC reciprocities can enhance each other iteratively and finally lead to the ICSAC reciprocity. To achieve these reciprocities, we explore the potential enabling technologies for the ICSAC framework. Finally, we present the evaluation results of crucial enabling technologies to show the feasibility of the ICSAC framework.

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Section: Computing-empowered Networked Isacmentioning

confidence: 99%

Integrated Communication, Sensing, and Computation Framework for 6G Networks

Chen,

Feng,

Zhang

et al. 2024

Sensors

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“…2) Cooperative signal processing: The networked mobile communication system is applied to realize cooperative sensing using multiple BSs, which can significantly improve the sensing accuracy and range [147]. Correspondingly, the signal processing for cooperative sensing needs to be studied.…”

Section: ) Isac Signal Processing With High Accuracy and Low Complexitymentioning

confidence: 99%

“…For signal-level fusion, space registration realizes the matching of sensing areas of multiple BSs. To solve this problem, we propose an adjustable beam enabled space registration algorithm (AB-SRA) based on beamwidth adjustable beamforming algorithm (BABA) [8], which flexibly adjusts the side length of the sensing area of different BSs to achieve the matching of sensing areas by generating the sensing beam with adjustable beamwidth.…”

Section: Cooperative Sensing Algorithmmentioning

confidence: 99%

Integrated Sensing and Communication Signals Toward 5G-A and 6G: A Survey

Wei

Wang

et al. 2023

IEEE Internet Things J.

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Integrated sensing and communication (ISAC) has the advantages of efficient spectrum utilization and low hardware cost. It is promising to be implemented in the fifth-generationadvanced (5G-A) and sixth-generation (6G) mobile communication systems, having the potential to be applied in intelligent applications requiring both communication and high-accurate sensing capabilities. As the fundamental technology of ISAC, ISAC signal directly impacts the performance of sensing and communication. This article systematically reviews the literature on ISAC signals from the perspective of mobile communication systems, including ISAC signal design, ISAC signal processing algorithms and ISAC signal optimization. We first review the ISAC signal design based on 5G, 5G-A and 6G mobile communication systems. Then, radar signal processing methods are reviewed for ISAC signals, mainly including the channel information matrix method, spectrum lines estimator method and super resolution method. In terms of signal optimization, we summarize peak-to-average power ratio (PAPR) optimization, interference management, and adaptive signal optimization for ISAC signals. This article may provide the guidelines for the research of ISAC signals in 5G-A and 6G mobile communication systems.

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