E-HFWN: Design and performance test of a communication and sensing integrated network for enhanced 5G mmWave

Abstract

Communication and sensing integrated networks (CSINs) refer to the ability of physical digital space perception and ubiquitous intelligent communication at the same time. These networks realize the perception and cooperative communication of multidimensional resources through the cooperative work of communication and sensing resources and have the ability of intelligent interaction and processing of new information flow. First, this study proposes the technical architecture of an enhanced CSIN (E-HFWN), studies its key technologies and performance indicators, and explains the air interface technology, including frame structure design, carrier aggregation, channel detection, physical skyline mapping, beamforming and management, resource allocation and scheduling. In the resource allocation scheme, an actor-critic reinforcement learning (RL) framework is used to divide the wireless resources. The goal is to maximize the amount of mutual information (MI) and minimize the end-to-end delay of the sensing terminal. Then, the performance of the E-HFWN is tested, including numerical simulation of wireless resource management, system peak rate, capacity, end-to-end delay and communication perception waveform sidelobe ratio. Finally, from the results of the E-HFWN index test, the E-HFWN is further enhanced on the basis of 5G mmWave. The enhanced sensing function can provide a priori information for the optimal and rapid scheduling of distributed computing power and provide richer data sources for artificial intelligence (AI) services and applications to enhance the robustness of the training model. The E-HFWN can contribute to the development of technologies related to 6G synaesthesia computing integrated networks, promote the consensus between academia and industry.