The integration of sensing and communications (ISAC) is widely seen as one of the main and disruptive features of the next generation of wireless communication systems . ISAC indeed allows the envisioned 6G network to not only communicate, but also to sense the environment, localise and track users as well as passive devices and objects within the wireless propagation environment, which in turn can be used for mobilising sensing-aided applications and/or improving communication functions. All those functionalities are expected to be offered by the same 6G network infrastructure.

The 6G-DISAC project will bring the ISAC vision into reality, going well beyond the usual restrictive standalone or localised scenarios, by adopting a holistic perspective, with large numbers of connected users and/or passive objects to be tracked, and relying on a widely distributed intelligent infrastructure compatible with both real-world integration constraints and the flexibility requirements of future wireless networks.

Driven by increasing demands in terms of data rates and latencies, wireless systems have entered new frequency bands with more available spectrum. As such bands are commonly found at higher carrier frequencies, increased path loss much be overcome by larger antenna apertures to support reasonable coverage. These concepts have brought the world the 5G concepts of millimetre wave (mmWave) and massive multiple input, multiple output (MIMO). As we enter the 6G era, it has become obvious that these same technological advances that lead to higher rates are also enablers for high-resolution sensing: larger bandwidths bring distance resolution, larger carrier frequencies make the channel more geometric and interpretable, while larger array apertures naturally bring increased angular resolution (enabling holographic MIMO applications). This triad of delay resolution, geometric channels, and angle resolution has been harnessed for several decades in radar systems, where advanced 4D radars can create 4D images (3 spatial dimensions and radial velocity) of the environment, with performance matching that of lidars, while also providing velocity/Doppler information, and (in contrast to lidar) operating in all weather and lighting conditions, with much lower cost. However, this performance comes at the expense of extreme data processing demands, as a typical 4D radar needs to process Gb/s of data to form 4D images.

These concepts are now being introduced towards 6G networks in the form of ISAC, which has become one of the most important innovation trends in 6G research and presents a paradigm shift in the design and operation of wireless networks. The ability to sense and track both active users and passive objects has nearly unlimited applications, ranging from extended reality, robot-human interaction to vehicular safety functions, as well as improving the communication key performance indicators (KPIs) (so-called sensing-aided communication). Nevertheless, ISAC has stagnated at low technology readiness levels (TRLs) and focused on toy scenarios, such as positioning of user equipment (UE), already part of 5G, and monostatic sensing of individual targets by a single base station (BS) or an end user. There are several fundamental challenges that must be addressed for ISAC to truly be integrated into 6G. These challenges include:

• The ability to track many connected UEs and passive objects, both static and mobile, which includes aspects of scalability, data association, resource allocation, adaptation at transmitter and receiver sides, as well as dedicated architectural changes.

•  The ability to perform ISAC with many distributed BSs, acting as transmitters, receivers, or both, supporting any combination of monostatic, bistatic, and multi-static sensing.

•  Coordinated waveform optimisation and generation among several distributed transmitters for high-resolution sensing (including detection and tracking), while supporting different requirements in terms of accuracy, latency, etc. and relevant operating trade-offs with respect to communication performance.

•  Efficient distributed signal processing to localise connected users, map static landmarks, and track moving targets, meeting the application requirements in terms of accuracy and latency.

•  The inclusion of novel large multi-antenna technologies in the ISAC paradigm, such as reconfigurable intelligent surfaces (RIS), extremely large MIMO (XL-MIMO), holographic MIMO, and distributed MIMO (D-MIMO), with various levels of time and phase coherence.

•  An intelligent/parsimonious framework, including activation of sensing, waveform design, signal processing, dedicated resource allocation and protocols, all of which ensure outstanding sensing performance to support relevant use cases, while not wasting radio resources.