Towards Integrated Communications and Sensing

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Integrated Communications and Sensing (ICS) has been recently proposed as the design paradigm and corresponding enabling technologies to combine communications and sensing systems for efficient spectrum utilization and for potential mutual benefits, e.g., sharing common hardware infrastructure, balancing dual-functional performance, performing mutual assistance. We propose a research plan to study and develop efficient ICS transmission and resource allocation techniques applicable to heterogeneous wireless access networks through the notion of cognitive cooperation. Furthermore, efficient use of multiple-antenna techniques among nodes can bring benefits from the collaborative advantages in a distributed manner via massive multiple-input multiple-output (mMIMO), full-duplex (FD) operation. On one hand, it can provide spatial multiplexing required for high-capacity multi-user communications links. On the other hand, it can facilitate super-resolution sensing receiver. FD-mMIMO with simultaneous transmission and reception over the same frequency slot can allow communications and sensing to share not only the spectrum but also the common hardware infrastructure. In particular, we plan to consider a multi-user (MU) FD-mMIMO system using hybrid RF-beamformer/baseband-precoder for ICS. Interference is the major performance-limiting factor and interference mitigation can be more effectively done in a collaborative interference control manner via multiple-objectives optimization. For communications, sum-rate maximization is widely used as an objective function. For sensing, its estimation performance can be represented in different parameters to be jointly optimized with its spectral efficiency. We propose to investigate three inter-related topics: (i) efficient multi-dimensional transmission schemes for ICS, (ii) cooperative hybrid precoding & dynamic resource allocation in ICS networks, and (iii) integrated communication, sensing and localization. Effective MIMO/m-MIMO operation needs fast and accurate channel-state information (CSI) acquisition. We will explore the sensing and learning capabilities to acquire knowledge of the propagation environment and user locations, to derive the CSI with significantly less resources and power than aimless and exhaustive beam sweeping. We will consider the assistance of Intelligent Reflective Surfaces (IRS) in enriching the propagation conditions and scenarios, which can enhance both the communications and sensing performance, as well as the integrated communication, sensing and localization operation. The proposed approach and methodology will involve various aspects, including system modeling and analysis, development of efficient ICS techniques, performance evaluation by analysis and simulation, implementation of proposed schemes. The proposed research is significant and should be undertaken to enhance Canada's competitive position in providing advanced intelligent communications systems.