  This work considers the problem of integrated sensing and communication
(ISAC) with a massive number of unsourced and uncoordinated users. In the
proposed model, known as the unsourced ISAC system (UNISAC), all active
communication and sensing users share a short frame to transmit their signals,
without requiring scheduling with the base station (BS). Hence, the signal
received from each user is affected by significant interference from numerous
interfering users, making it challenging to extract the transmitted signals.
UNISAC aims to decode the transmitted message sequences from communication
users while simultaneously detect active sensing users, regardless of the
identity of the decoded and detected users. In this paper, we derive an
achievable performance limit for UNISAC and demonstrate its superiority over
conventional approaches such as ALOHA, time-division multiple access, treating
interference as noise, and multiple signal classification. Through numerical
simulations, we validate the UNISAC's effectiveness in detecting and decoding a
large number of users.
