Dynamic Route Optimization System Based on Signal Path Multiplexing and Delay Prediction in 6G Private Campus Networks

Abstract

The invention is a system that enables ultra-low latency by optimizing the signal path in 6G private campus networks. The system includes a signal analysis module (1), an environmental mapping unit (2), a latency estimation engine (3), a dynamic routing unit (4), a 6G radio access unit (5), and a campus control center (6). Signal paths are analyzed and modeled via a digital twin using the signal analysis module (1) and the environmental mapping unit (2). The latency estimation engine (3) calculates risk scores and provides this information to the dynamic routing unit (4), thus optimizing signal routing in real-time via the 6G radio access unit (5). The system provides operational continuity in industrial facilities by offering a proactive transition mechanism before signal loss occurs.

Description

1 TARIFF SIGNAL PATH MULTIPLICATION AND DELAY PREDICTION IN 6G DEDICATED CAMPUS NETWORKS BASED DYNAMIC ROUTE OPTIMIZATION SYSTEM Technical Area 5 The invention is designed for 6G private network infrastructures for industrial facilities and private campus areas. This is particularly relevant by analyzing signal reflections and environmental obstacles in enclosed spaces. It offers a network optimization system that provides low-latency communication. State of the Art Existing industrial dedicated networks typically use fixed scheduling algorithms for signaling. These systems provide transmission. These systems prevent many problems arising from metallic surfaces in the factory environment. It cannot instantly assess signal attenuation and reflection. The current 15 solutions experience high latency in the process of reconnecting when a signal is lost. They are subject to time constraints. This situation makes robotics requiring real-time control problematic. causing data loss or system downtime in systems and critical production lines Furthermore, existing networks respond adaptively to environmental changes. Because it cannot provide this, it cannot offer stable connection quality in dynamic environments. 20 Purpose of the Invention The invention optimizes the signal path in 6G private campus networks, achieving ultra-low latency. The system aims to achieve this. The system consists of 25 environmental obstacles and reflective surfaces. It determines the most suitable transmission route by analyzing signal paths. The main purpose of the invention is: A proactive transition by anticipating potential disruptions before signal loss occurs. The aim is to provide a mechanism that enables submilliseconds of automation in industrial automation systems. Operational continuity is ensured by maintaining delay times. This differs from the current technology. The invention, therefore, focuses not only on signal strength but also on the geometric and environmental characteristics of the signal path. It uses a decision-making mechanism based on its characteristics. The system responds to environmental changes. It maximizes network performance by adapting instantly. 35 2 Figures that will help understand the invention. Figure 1 shows a general representation of the system that is the subject of the invention. Description of Part References 5 1: Signal Analysis Module 2: Environmental Mapping Unit 3: Delay Prediction Engine 4: Dynamic Router 10 5: 6G Radio Access Unit 6: Campus Control Center Detailed Description of the Invention The invention optimizes the signal path in 6G private campus networks, achieving ultra-low latency. It is a system that enables obtaining. The system consists of a signal analysis module (1), environmental mapping. unit (2), delay estimation engine (3), dynamic route router (4), 6G radio access It consists of subunits, namely the unit (5) and the campus control center (6). The signal analysis module (1) analyzes the raw signal data coming through the 6G radio access unit (5) 20 This module processes and calculates the signal-to-noise ratio (SNR) and Doppler shift. Multipath analysis is used to determine which paths the signal reflects and which obstacles it encounters. It runs channel estimation algorithms. The signal analysis module (1) retrieves the data it obtains. It enables the extraction of the instantaneous signal topology by transmitting it to the environmental mapping unit (2). The environmental mapping unit (2) maps the locations of physical objects within the campus and 25 It has a digital twin database containing material properties. This unit performs signal analysis. Using the data from module (1), the surfaces on which the signal is reflected are metallic, glass or It analyzes properties such as concrete. Environmental mapping unit (2), signal paths By creating geometric models, it determines which routes are more stable. The delay estimation engine (3) uses instantaneous data from the signal analysis module (1) and environmental 30 It calculates a risk score by combining the topological data from the mapping unit (2). This risk score takes into account potential obstacles in the signal path (e.g., a moving forklift or metal). The delay estimation engine (3) predicts the increase in delay that a gate will create. If it detects a risk of delay exceeding 5ms on the current route, it will switch to a dynamic route. It sends a warning signal to its router (4). 35 3 The dynamic route guide (4) constitutes the decision mechanism of the system. This unit, According to the risk score from the delay estimation engine (3), the alternative to which the signal will be transmitted It determines the routes. Dynamic route router (4) promises the lowest latency. By choosing the path, it transmits a new routing command to the 6G radio access unit (5). This process, Because this occurs before any signal loss, uninterrupted communication is ensured. 5 The 6G radio access unit (5) enables signal transmission and reception within the campus. This unit is the hardware layer. This unit receives commands from the dynamic route router (4). using beamforming technology to direct the signal to the most suitable angle and direction. It directs the way. The 6G radio access unit (5) also detects environmental changes. It detects this information and transmits it as feedback to the signal analysis module (1). 10 The Campus Control Center (6) is the central unit responsible for managing the entire system. This unit, signal analysis module (1), environmental mapping unit (2), delay estimation engine (3) and It coordinates the data flow between the dynamic route router (4) and the campus control. The central office (6) monitors the overall performance of the network and makes long-term optimization decisions. and updates system parameters. 15 The system operating scenario is as follows: transmitted via 6G radio access unit (5) The signals are continuously monitored by the signal analysis module (1). The signal analysis module (1), detects changes in signal paths and transmits this data to the environmental mapping unit (2) The environmental mapping unit (2) transmits the signal by analyzing changes in the physical environment. Updates the geometric model of the paths. The delay estimation engine (3) uses this updated data to 20 It calculates the delay risk of the current signal path using this method. If the risk exceeds the threshold value, The dynamic route guide (4) is activated and determines an alternative signal path. The newly determined path Route information is transmitted to the 6G radio access unit (5) and the signal direction is changed instantaneously. All these processes are monitored by the campus control center (6) to ensure the stability of the network. 30 35

Claims

4 REQUESTS 1. Dynamic signal path multiplexing and latency estimation based on 6G private campus networks. It is a route optimization system; its feature is: - By processing the raw signal data coming through the 6G radio access unit (5), the signal-to-noise ratio is 5 Signal analysis module (1) which calculates the ratio and Doppler shift. - Using the data from the signal analysis module (1) to analyze the geometric paths of the signal paths environmental modeling and analysis of the material properties of physical objects Mapping unit (2), - Instantaneous data from the signal analysis module (1) and environmental mapping unit (2) 10 by combining incoming topological data, it calculates the potential delay risks in the signal path. delay estimation engine (3), - Lowest delay according to the risk score from the delay estimation engine (3) Dynamic route router (4) which determines alternative signal paths promising a certain duration. - Dynamic route 15, which enables signal transmission and reception within the campus. using beamforming technology in accordance with the commands from its router (4) 6G radio access unit (5) which directs the signal and - Signal analysis module (1), environmental mapping unit (2), delay estimation engine (3) campus control coordinating the data flow between the dynamic route router (4) central (6) 20 It includes. 30 35

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