Integrating Sensing and Communication-Based Target Detection and Speed Estimation for Beyond-Generation Networks

Tracking high-speed users becomes one of the most important issues for the generation networks that enhance developer's completion towards exploring existing methods and technologies to sense, track, and estimate users’ mobility. To do that, integrating and sensing is a very important method to measure the quality of service (QoS) as well as the signal-to-noise ratio (SNR). QoS localization, and resource allocation (RA) with integrating sensing and communication (ISAC) are based on orthogonal multiple access (NOMA) and SNR for moving objects. This paper proposes a model, using ISAC, for tracking user equipment (UE) and flying objects (Drones). ISAC techniques can utilize the communication networks to afford the capability of signal sensing, and tracking moving or flying objects nearby. In this paper, an ISAC model-based outdoor moving target detection, tracking, and speed estimation is proposed and simulated in 5G networks. The proposed system comprises two 5G base stations (BSs) that serve many pedestrians and moving users while simulating detection and speed estimation of moving objects only (Drones). Simulation evaluation and results demonstrate the relatively high accuracy of the proposed model in an outdoor environment when tracking flying targets.