METHODS FOR OPTIMIZING THE USE OF FREQUENCY AGGREGATION IN WI-FI 7 TO MINIMIZE LATENCY AND PACKET LOSS IN IOT SYSTEMS WITH LIDAR AND VIDEO CAMERAS

Abstract

The article investigates the influence of frequency aggregation mechanisms and Multi-Link Operation in wireless networks of the IEEE 802.11be standard (Wi-Fi 7) on the delay and packet loss indicators in heterogeneous IoT systems that integrate video cameras and LiDAR sensors. The relevance of the study is due to the rapid growth of sensor data volumes in smart city systems, autonomous transport, industrial automation and intelligent video surveillance, for which the stability of information delivery, minimization of marginal delays and preservation of time consistency of multi-channel streams are critical. The aim of the work is to provide theoretical justification and applied analysis of the effectiveness of Wi-Fi 7 multi-link mechanisms in reducing latency and packet loss in scenarios with a combination of video and LiDAR traffic, as well as to develop an adaptive model for distributing flows between frequency links taking into account the requirements of different data classes. The object of the study is the processes of transmitting heterogeneous sensor traffic in multi-frequency wireless networks, and the subject is the regularities of the influence of frequency aggregation and Multi-Link Operation on the quality of service indicators of real-time IoT systems. The methodological basis of the study is the methods of queuing theory, multi-criteria optimization, stochastic analysis of wireless networks and system modeling. A model for adaptive link selection, which is based on the assessment of the predicted delay, probability of loss and the level of channel congestion and is implemented in the form of a weighted decision-making criterion, is proposed. The model weights are adjusted according to the priorities of video and LiDAR traffic, achieving a balance between time stability, reliability and efficient use of the radio resource. The analysis shows that the use of Multi-Link Operation allows to significantly reduce the average and marginal data transmission delay by distributing the load between several partially independent access environments, reducing the frequency of retransmissions and the time of air occupation. It is shown that the greatest gain is achieved in high-load scenarios with a large number of clients, where single-frequency networks are characterized by QoS fluctuations. The proposed packet routing model provides a reduction in tail-latency and loss coefficient, which is critically important for maintaining sensor data synchronization and video stream stability. The scientific novelty of the work lies in the formalization of an adaptive model of traffic distribution between multi-frequency Wi-Fi 7 links, taking into account the specifics of heterogeneous sensor load and in establishing quantitative dependencies between multi-link architecture parameters and quality of service indicators. The practical significance of the results obtained lies in the possibility of their use in the design and optimization of wireless infrastructures for video surveillance systems, autonomous navigation, industrial Internet of Things, and sensor data fusion complexes operating in real time. Prospects for further research are related to the development of intelligent Multi-Link Operation control algorithms based on machine learning methods, the integration of multi-link mechanisms with edge computing technologies and next-generation mobile networks, as well as experimental verification of the proposed approaches in large-scale multi-cell environments with real sensor load