Integrated Sensing and Communications for Unsourced Random Access: Fundamental Limits

2024-04-30

Global Communications Conference

AI Summary

To address the challenge of supporting massive passive, uncoordinated users, this paper proposes UNISAC—a short-frame shared integrated sensing and communication (ISAC) system that operates without base station scheduling. UNISAC simultaneously achieves communication message decoding, passive user activity detection, and sub-degree angle-of-arrival (AoA) estimation. We establish, for the first time, a theoretical framework for passive ISAC, breaking from the conventional paradigm that treats communication multiple access and sensing as separate tasks, and derive a joint achievability bound. A unified receiver is designed based on random coding and joint message-parameter detection, with performance validated via asymptotic information-theoretic analysis and numerical simulations. Compared to benchmark schemes—including ALOHA, TDMA, treating interference as noise (TIN), and MUSIC—UNISAC achieves reliable message decoding and sub-degree AoA estimation even under strong multiuser interference, thereby significantly enhancing communication-sensing synergy.

Technology Category

• Multiagent Systems: Agent Communication
• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Reasoning under Uncertainty: Stochastic Optimization

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

This work considers the problem of integrated sensing and communications (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 simultaneously 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 detecting active sensing users and estimating their angles of arrival, regardless of the identity of the senders. In this paper, we derive an approximate achievable result 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 effectiveness of UNISAC’s sensing and communication capabilities for a large number of users.

Problem

• Integrate sensing and communication in massive unsourced systems
• Decode messages and detect sensing users despite interference
• Validate UNISAC model performance against conventional methods

Innovation

• Massive unsourced ISAC system (UNISAC)
• Simultaneous decoding and angle estimation
• Outperforms conventional methods like ALOHA