Integrated sensing and communications (ISAC) has been proposed to significantly improve the performance of applications through highly-efficient spectrum/hardware sharing between channel-sensing and data-communications. However, how to apply the ISAC technique to accurately sense and estimate the wireless channel state while transmitting the information to mobile users to support massive ultra-reliable and low-latency communications (mURLLC) has imposed many new challenges not encountered before. To address these challenges, in this paper we investigate the channel capacity-distortion tradeoff for ISAC-enabled mURLLC over massive multiple-input multiple-output (MIMO) mobile networks using finite blocklength coding (FBC). First, we establish system models for ISAC-based architectures using massive-MIMO. Second, we define the capacity-distortion function under the distortion constraint for the estimated channel state. Third, we develop a new statistical quality of service (QoS) metric, termed ISAC-based <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\epsilon$</tex>-effective capacity, to simultaneously guarantee statistical-delay and error-rate bounded QoS by optimizing the sensing-communication power splitting ratio of ISAC. Finally, we use numerical analyses to validate and evaluate our developed ISAC schemes in supporting mURLLC.
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