Fundamental Limits of Covert and Non-Covert Communication in a Multiple Access Channel

Core Concepts

The fundamental limits of a communication system with three users (two covert users and one non-covert user) and a single receiver, where communication from the two covert users must remain undetectable to an external warden, are characterized. The presence of the non-covert user can enhance the capacities of the covert users under stringent secret-key constraints.

Abstract

The paper establishes the fundamental limits of a multi-access communication setup with two covert users and one non-covert user communicating to the same receiver in the presence of a warden. Both covert users also share a common secret-key of fixed key rate with the receiver.
The key insights are:

Multiplexing different codes in different phases is crucial to exhaust the entire tradeoff of achievable covert and non-covert rates.
The presence of the non-covert user can potentially improve the covert-capacity under a stringent secret-key rate constraint.

The coding scheme proposed in the paper multiplexes τ different phases and codes to minimize various error probabilities and the divergence between the output distribution observed at the warden under the two hypotheses (covert and non-covert transmission). The combined scheme over all phases then induces an optimal overall-tradeoff between small probabilities of error and small divergences.
The paper also provides a converse proof to establish the fundamental limits of the system. The results can be extended to multiple users with arbitrary finite alphabets.

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Key Insights Distilled From

Covert Multi-Access Communication with a Non-Covert User

by Abde... at arxiv.org 04-23-2024

https://arxiv.org/pdf/2404.14056.pdf

Deeper Inquiries

How can the proposed coding scheme be extended to scenarios with more than three users?

The proposed coding scheme can be extended to scenarios with more than three users by adapting the multiplexing strategy to accommodate additional users. In a multi-user scenario, each user can be assigned specific phases for transmission, similar to how it was done for the three users in the original setup. By increasing the number of phases and designing codebooks for each user in each phase, the scheme can be scaled to include a larger number of users. The key is to ensure that the trade-off between covert and non-covert rates is maintained while allowing for efficient communication among all users.

What are the practical implications and potential applications of the characterized fundamental limits in real-world wireless communication systems?

The fundamental limits characterized in this work have significant practical implications for real-world wireless communication systems, especially in scenarios where security and privacy are paramount. Some potential applications include secure communication in IoT devices, sensor networks, military communications, and any other system where covert communication is essential. By understanding the trade-offs between covert and non-covert rates, system designers can optimize communication protocols to ensure secure and efficient data transmission while minimizing the risk of detection by external parties.

How can the insights from this work be leveraged to design efficient covert communication protocols for emerging applications like Internet of Things (IoT) and sensor networks?

The insights from this work can be leveraged to design efficient covert communication protocols for emerging applications like IoT and sensor networks by incorporating the principles of multiplexing, codebook design, and trade-off analysis into the protocol design. By understanding the fundamental limits of covert communication and the role of non-covert users in enhancing covert capacity, designers can develop protocols that maximize data transmission efficiency while maintaining security and privacy. Additionally, the use of secret-key constraints and divergence analysis can help in creating robust and secure communication protocols that are well-suited for the unique challenges of IoT and sensor networks.