The rapid evolution of wireless communication technologies has ushered in a new era of connectivity, transforming the way we think about the purpose of radio signals. 6G wireless networks have brought about a fundamental rethinking, blurring the lines between communication and sensing, and introducing the concept of Integrated Sensing and Communications (ISAC). ISAC promises to connect the physical and digital worlds, enabling a seamless exchange of information and intelligence.
However, the current vision for ISAC has faced challenges and limitations. It often lacks support for widely distributed deployments, a comprehensive perspective that incorporates both Key Performance Indicators (KPIs) and Key Value Indicators (KVIs), and the fusion of heterogeneous sensors beyond the 6G signal itself. Unlocking the full potential of ISAC requires a more extended vision, one that addresses these critical components – and that vision is known as Distributed and Intelligent Integrated Sensing and Communications (DISAC).
The DISAC Framework: A Transformative Approach
The DISAC framework represents a transformative vision for wireless communications, combining the fusion of heterogeneous and distributed sensors with a highly adaptive and efficient semantic-native approach. This innovative approach aims to enable energy-efficient, high-resolution tracking of connected User Equipments (UEs) and objects, revolutionizing the fundamental fabric of wireless networks.
At the heart of DISAC are three interrelated cornerstones:
1. The DISAC Architecture:
This distributed architecture serves as the foundation for both sensing and communications, supporting intelligent operations and distributed functions. By enabling large-scale tracking of connected UEs and passive objects, the DISAC architecture revolutionizes the way wireless networks are designed and operated. It supports distributed Artificial Intelligence (AI) operations, balancing local data processing and fusion, while also incorporating novel multi-antenna technologies and an exposure framework for external sensors.
2. The Semantic and Goal-Oriented Framework:
Powered by Machine Learning (ML) and AI, this intelligent and parsimonious framework encompasses sensing activation, waveform design, signal processing, dedicated resource allocation, robust protocols, and semantic reasoning about multi-modal sensed information. This framework ensures exceptional sensing performance for a myriad of use cases while optimizing resource utilization.
3. Advanced High-Resolution Processing:
By exploiting multi-site and multi-band processing and leveraging a combination of ML and model-based signal processing, DISAC aims to develop efficient methods that can support the goal-oriented semantic framework while running over the DISAC architecture. This balances computational and storage requirements, enabling the deployment of DISAC on a global scale.
Unlocking the Potential of ISAC through DISAC
The DISAC vision addresses the limitations of existing ISAC approaches by introducing several key enablers:
1. Semantic Framework for ISAC:
The semantic and goal-oriented communications approach in DISAC allows diverse information from various sensing modalities to be aggregated, facilitating the transition from traditional data fusion to the composition of semantically selected information and the pragmatic generation of AI-based reasoning stimuli. This semantic awareness enhances interoperability, contextual understanding, and the effectiveness of activating sensing functions.
2. Optimized and Parsimonious Physical Layer:
The DISAC physical layer involves waveform optimization, channel parameter estimation, detection, data association, and estimation of objects, as well as the tracking of UEs and objects over time. By leveraging a combination of ML and model-based methods, DISAC aims to tailor these processes to the instantaneous application needs, leading to more parsimonious and efficient ISAC operation.
3. Intelligent Resource Allocation:
Unlike traditional resource allocation strategies focused on bandwidth and power constraints, DISAC-oriented resource allocation must account for the unique demands of high-resolution sensing, leading to potentially large volumes of sensor data and semantic processing. Efficient resource allocation schemes must be inherently goal-oriented, exploiting contextual information to strike a balance in the time, frequency, and energy resources allocated for sensing and communications.
4. Evolved Architecture for DISAC Support:
The DISAC architecture departs from the conventional cellular network architecture, introducing new network functions, protocols, and interfaces to fully integrate sensing within 3GPP-compliant systems. This includes support for distributed intelligent signal processing, new functions for tracking and handover of objects, and the management of Sensor-Receiver-Network (SRN) groups, as well as the integration of external sensors.
Driving Innovation in Sensor Networks and IoT
The DISAC framework holds immense potential for transforming the landscape of sensor networks and IoT applications. By seamlessly integrating sensing with communications and harnessing the power of distributed AI, DISAC addresses the limitations of existing ISAC approaches and unlocks new possibilities for resource-efficient, accurate, and semantic network operations.
Some key areas where DISAC can drive innovation include:
1. Digital Twins:
DISAC is particularly well-suited for digital twin applications, where a dynamic, user-centric sensor network on roadways is complemented by sensors connected to the 5G/6G urban infrastructure and non-3GPP sensors, enabling the seamless exchange of information and the symbiotic interplay of distributed sensing and communication.
2. Autonomous Vehicles and Robotics:
The DISAC framework can enhance applications such as UAV trajectory tracing, intrusion detection, collision avoidance, and seamless XR streaming, by leveraging the distributed and intelligent sensing capabilities to optimize resource utilization and provide actionable insights.
3. Smart Cities and Infrastructure Monitoring:
DISAC can enable innovative use cases like highway and railway intrusion detection, rainfall monitoring, and sensing for flooding, by harnessing the power of distributed sensing and semantic-aware processing to enhance situational awareness and decision-making.
4. Health and Wellness Monitoring:
The DISAC framework can revolutionize applications like sleep and health monitoring, facilitating the fusion of multi-modal sensed information and providing personalized insights to improve individual and public well-being.
As the industry and research community continue to explore and develop ISAC-related standards, the DISAC vision stands as a transformative approach that can unlock new possibilities for sensor networks and IoT applications, ultimately paving the way for a more intelligent, efficient, and integrated future.
Overcoming Challenges and Driving Standardization
While the DISAC vision holds immense promise, it also presents several challenges that must be addressed to realize its full potential. These challenges can be categorized as follows:
1. Semantic Framework Design and Implementation:
Designing and executing the semantic framework outlined in DISAC represents a formidable challenge, as it significantly departs from the standard approach and architecture for ISAC. Extensive research and collaboration between industry and academia will be required to tackle this complex task.
2. Distributed ISAC Signal Processing and Fusion:
The distributed approach for ISAC will necessitate new methods for shaping the wireless signal, processing it, and fusing the resulting information with external sensors over extended space and time. Overcoming the raw computational and communication constraints will be a key priority, requiring the development of lightweight processing methods.
3. Hardware and Integration Considerations:
The use of multi-functional Reconfigurable Intelligent Surfaces (RISs) and the seamless integration of heterogeneous hardware components operating in different frequency ranges add another layer of complexity that must be addressed.
4. Real-world Demonstration and Standardization:
Implementing the semantic framework and demonstrating its performance in real-world scenarios present significant challenges. Additionally, the standardization of DISAC-related aspects, such as waveforms, distributed architectures, and new functional elements, protocols, and interfaces, will be crucial for its widespread adoption.
To address these challenges and drive the standardization of DISAC, collaborative efforts between industry, academia, and standards development organizations (SDOs) will be essential. Key SDOs, such as ETSI, 3GPP, and ITU-R, have already begun exploring and developing work on the ISAC topic, incorporating AI-based approaches.
As these standardization efforts progress, the DISAC vision and its underlying principles will need to be closely integrated and aligned with the ongoing work. This will ensure that the unique requirements and capabilities of DISAC are properly addressed and incorporated into the evolving 6G ecosystem, paving the way for its seamless deployment and adoption.
Conclusion: Unlocking the Future of Sensor Networks and IoT
The Distributed and Intelligent Integrated Sensing and Communications (DISAC) framework represents a transformative vision for wireless communications, one that holds the potential to revolutionize the way sensor networks and IoT applications are designed and deployed. By seamlessly integrating sensing with communications and harnessing the power of distributed AI, DISAC addresses the limitations of existing ISAC approaches and unlocks new possibilities for resource-efficient, accurate, and semantic network operations.
As the industry and research community continue to explore and develop ISAC-related standards, the DISAC vision stands as a crucial catalyst for innovation, driving advancements in areas such as digital twins, autonomous vehicles, smart cities, and health monitoring. Through collaborative efforts and a steadfast commitment to overcoming the challenges, the DISAC framework has the potential to shape the future of sensor networks and IoT, ushering in a new era of connectivity, intelligence, and optimization.
Embrace the transformative power of DISAC and stay at the forefront of the evolving sensor network and IoT landscape. The future is distributed, intelligent, and ready to be unleashed.