Joint Communication and Sensing Design for Beyond 5G System

Abstract

Joint communication and sensing (JCAS) is an emerging research topic aiming to integrate radio communications and radar systems in time and frequency domains along with the spatial domain. Integration in the spatial domain relies on a suitable beamforming technique for acquiring desired detection performance levels for both operations. Beamforming methods in the context of JCAS systems, with an emphasis on convex optimization, are studied in this thesis. A previously established work on beamformer design for optimum antenna selection is reviewed and duplicated to establish the groundwork for the main research. The novel beamforming algorithm proposed in this work maximizes the detection performance for the radar function in a JCAS system while maintaining the communication performance at an acceptable level. This is accomplished in the presence of clutter and with no assumption of a direct path between the transmitter and the communication user. A mathematical groundwork is presented for acquiring a valid convex optimization problem to represent the beamforming objective and constraints, along with using rank one decomposition to convert the result into a beamforming weight vector usable in practical application. The tests performed on a simulation environment showed that performance tradeoffs between radar and communication functions are observable on acquired results, in addition to assurance about the validity of assumptions made during problem definition.