Improved Information-Theoretic Bound for Multiple-Access Integrated Sensing and Communication Systems

IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM(2023)

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摘要
Integrated sensing and communication (ISAC) is a promising technology for future 6G networks that enables the joint utilization of hardware and spectrum resources for sensing and communication systems. However, the co-sharing of resources leads to a fundamental tradeoff between sensing and communication performance, which is not well understood in multiple-access ISAC scenarios with perfect or imperfect channel state information at the receiver (CSIR). In this paper, we address this challenge by considering a state-dependent multiple access channel model that accounts for correlated sensing and channel states, as well as imperfect CSIR. We propose an achievable scheme that combines message cooperation and joint compression via distributed Wyner-Ziv coding at each user, resulting in unified cooperative communication and sensing. Our scheme always achieves a communication-rate-distortion region which includes that achieved by state-of-the-art coding scheme. In addition, a numerical example is provided to demonstrate strict inclusion. It is found that the compressed information not only enhances communication (especially in scenarios with imperfect CSIR) but also improves sensing performance.
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关键词
Communication Systems,Channel State,Communication Performance,Perfect Channel State Information,Imperfect Channel State Information,6G Networks,Multiple-access Channel,Random Variables,Decoding,Generation Sequencing,Partial Information,Choice Of Variables,Output Channels,Sequence Of States,Independent Random Variables,Codeword,Common Part,Echo Signal,Cramer-Rao Lower Bound,Previous Block,Rate Constraint,Private Messages,Greater Amount Of Information,Binary Random Variable
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