Symbol-level Integrated Sensing and Communication enabled Multiple Base Stations Cooperative Sensing
Zhiqing Wei, Ruizhong Xu, Zhiyong Feng, Huici Wu, Ning Zhang, Wangjun, Jiang, Xiaoyu Yang

TL;DR
This paper introduces a symbol-level cooperative sensing method for multi-base station mobile communication systems, significantly enhancing target localization accuracy with lower synchronization requirements, suitable for smart city and transportation applications.
Contribution
It proposes a novel symbol-level data fusion approach for cooperative sensing, improving accuracy and reducing synchronization needs compared to existing methods.
Findings
Distance estimation accuracy improved by 40% at -5 dB SNR.
Velocity estimation accuracy improved by 72% at -5 dB SNR.
Outperforms single-BS sensing and data-level fusion in accuracy.
Abstract
With the support of integrated sensing and communication (ISAC) technology, mobile communication system will integrate the function of wireless sensing, thereby facilitating new intelligent applications such as smart city and intelligent transportation. Due to the limited sensing accuracy and sensing range of single base station (BS), multi-BS cooperative sensing can be applied to realize high-accurate, long-range and continuous sensing, exploiting the specific advantages of large-scale networked mobile communication system. This paper proposes a cooperative sensing method suitable to mobile communication systems, which applies symbol-level sensing information fusion to estimate the location and velocity of target. With the demodulation symbols obtained from the echo signals of multiple BSs, the phase features contained in the demodulation symbols are used in the fusion procedure, which…
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Taxonomy
MethodsBalanced Selection
