13 May 2024 | Kaitao Meng, Member, IEEE, Christos Masouros, Fellow, IEEE Athina P. Petropulu, Fellow, IEEE, and Lajos Hanzo, Life Fellow, IEEE
The paper "Cooperative ISAC Networks: Opportunities and Challenges" by Kaitao Meng, Christos Masouros, Athina P. Petropulu, and Lajos Hanzo explores the integration of sensing and communication (ISAC) as a cornerstone technology for the sixth generation era. The authors highlight the main challenges in efficient ISAC, including limited sensing and communication coverage and severe inter-cell interference. They propose network-level ISAC, where multi-cell cooperation can effectively expand both sensing and communication (S&C) coverage and provide extra degrees of freedom (DoF) for increased integration gains. The paper discusses new metrics, optimization of DoF, cooperation regimes, and S&C tradeoffs, and presents a suite of cooperative S&C architectures at the task, data, and signal levels. It also investigates the interplay between S&C at the network level and outlines promising research directions. Key considerations include network-level performance metrics, optimization of DoF, resource constraints, cooperation frameworks, and tradeoffs. The paper further explores new opportunities in space-air-ground ISAC networks, multi-modal sensing information transmission and fusion, and vehicular ISAC networks. Challenges addressed include network synchronization requirements, limited backhaul constraints, and security and privacy concerns. The authors categorize ISAC cooperation into four levels: coordinated cell association, collaborative data fusion, cooperative interference management, and joint cooperative S&C arrangements. They also discuss the synergies between network sensing and communication, including sensing-assisted communication and communication-assisted sensing. Finally, the paper presents a case study on interference management and cooperation schemes, demonstrating the effectiveness of cooperative ISAC through simulations. The authors conclude by outlining future research directions, such as smart propagation engineering, semantically aware ISAC networks, and self-adaptive AI in ISAC networks.The paper "Cooperative ISAC Networks: Opportunities and Challenges" by Kaitao Meng, Christos Masouros, Athina P. Petropulu, and Lajos Hanzo explores the integration of sensing and communication (ISAC) as a cornerstone technology for the sixth generation era. The authors highlight the main challenges in efficient ISAC, including limited sensing and communication coverage and severe inter-cell interference. They propose network-level ISAC, where multi-cell cooperation can effectively expand both sensing and communication (S&C) coverage and provide extra degrees of freedom (DoF) for increased integration gains. The paper discusses new metrics, optimization of DoF, cooperation regimes, and S&C tradeoffs, and presents a suite of cooperative S&C architectures at the task, data, and signal levels. It also investigates the interplay between S&C at the network level and outlines promising research directions. Key considerations include network-level performance metrics, optimization of DoF, resource constraints, cooperation frameworks, and tradeoffs. The paper further explores new opportunities in space-air-ground ISAC networks, multi-modal sensing information transmission and fusion, and vehicular ISAC networks. Challenges addressed include network synchronization requirements, limited backhaul constraints, and security and privacy concerns. The authors categorize ISAC cooperation into four levels: coordinated cell association, collaborative data fusion, cooperative interference management, and joint cooperative S&C arrangements. They also discuss the synergies between network sensing and communication, including sensing-assisted communication and communication-assisted sensing. Finally, the paper presents a case study on interference management and cooperation schemes, demonstrating the effectiveness of cooperative ISAC through simulations. The authors conclude by outlining future research directions, such as smart propagation engineering, semantically aware ISAC networks, and self-adaptive AI in ISAC networks.