BEAM-BASED PREDICTION AND ADAPTIVE WAKE-UP SYSTEM FOR USER EQUIPMENT IN SLEEP MODE ON 6G NETWORKS.

Abstract

The invention is a system that uses artificial intelligence to predict the probability of user equipment (6) being in a beam region while in sleep mode, in order to improve energy efficiency in 6G mobile networks. The system includes a Mobility Data Acquisition Module (1), a Beam Probability Prediction Engine (2), a Dynamic Beam Assignment Unit (3), a Wake-Up Signal Router (4), and an Energy and Resource Monitoring Unit (5). The Beam Probability Prediction Engine (2) analyzes the device's motion data to identify the most likely beam regions, and these regions are prioritized by the Dynamic Beam Assignment Unit (3). The Wake-Up Signal Router (4) sends paging signals only to these regions, eliminating the need to broadcast to the entire cell. In this way, energy consumption and control signaling are minimized, and network efficiency is increased.

Description

1 TARIFF BEAM-BASED FOR USER EQUIPMENT IN SLEEP MODE ON 6G NETWORKS. PREDICTION AND ADAPTIVE WAKE-UP SYSTEM Technical Area The invention aims to increase energy efficiency in 6G mobile networks by utilizing user sleep mode. It relates to the location estimation and wake-up signaling of the equipment. Specifically, sleep The AI ​​determines the probability of user equipment being located in a specific beam region during the mode. By predicting and directing paging signals only to the relevant beam regions. It is a system that provides State of the Art In current mobile network technologies, when a user's equipment goes into sleep mode, the network Paging signals sent by the cell generally cover the entire cell. This is being broadcast. This situation is particularly relevant for high-frequency and narrow beamforming technologies like 6G. This leads to a significant waste of energy in networks. Sending a signal to the entire cell requires both base stations. This increases the station's energy consumption and reduces spectral efficiency. Furthermore, 20 The location information of devices in sleep mode is not updated, therefore the device's location is in a narrow beam. The area cannot be detected, and unnecessary signaling load is created. Existing systems, It takes a static approach based on the last known location of the device, but the device It overlooks mobility trends and environmental factors. These shortcomings, in particular... In dense urban environments and high mobility situations, paging failure rates are 25%. It increases. Purpose of the Invention The invention determines the probability of user equipment being located in a particular beam region while in sleep mode. Predicting energy consumption and control signaling using an AI-powered model. The system aims to reduce [the number of possible cases] by sending paging to only the cell instead of the entire cell. It optimizes radio sources by sending wake-up signals to beam fields. The invention... Its primary purpose is to use the device's historical motion data, environmental context, and network topology. The goal is to create a real-time probability map. This way, wake-up signals are only 35%... The beam is focused on high-probability regions, and unnecessary transmissions are blocked. 2 Unlike existing technology, this invention allows for location estimation even when the device is in sleep mode. It offers a decision-making mechanism that not only provides energy savings. Next, the goal is to improve the user experience by shortening the device's wake-up time. Figures to Help Understand the Invention 5 Figure 1 shows a general representation of the system that is the subject of the invention. Explanation of Part References 1. Mobility Data Collection Module 2. Beam Probability Estimation Engine 3. Dynamic Beam Assignment Unit 4. Wake-up Signal Router 5. Energy and Resource Monitoring Unit 15 6. User Equipment Detailed Description of the Invention The invention describes in which beam region (6) user equipment in sleep mode 20 on 6G networks a system that estimates the probability of being found and optimizes wake-up signals based on that estimate The system is the Mobility Data system which collects the mobility data of the user equipment (6). The Aggregation Module (1) processes this data and calculates the probability of the Beam Probability Estimation Engine. (2), Dynamic Beam Assignment Unit (3) which determines the most suitable beam region, signals to the relevant Wake-up Signal Router (4) which transmits to the region and Energy 25 which measures the energy efficiency of the system and includes Resource Monitoring Unit (5). The Mobility Data Collection Module (1) ensures that the user equipment (6) goes into sleep mode before... It collects previous location information, speed of movement, direction, and environmental context data. This The module creates a dataset by analyzing the device's past movement patterns. The 30 collected data... The data includes parameters such as timestamped location information and signal strength indicators. This The data is stored for use by the Beam Probability Estimation Engine (2) and continuously It is updated accordingly. Beam Probability Estimation Engine (2), artificial intelligence forming the decision mechanism of the system 35 It is a unit based on the Mobility Data Acquisition Module (1). 3 Using the data, determine which beam region the user equipment (6) is in when it is in sleep mode. It calculates the probability of finding it. The prediction process involves the device's movement. a This is done using a scoring algorithm. For example, the device moves in a specific direction. And if it has been determined that it is at a certain speed, then the beam regions in that direction are given a higher 5. A probability score is assigned. Dynamic Beam Assignment Unit (3) is the probability generated by the Beam Probability Estimation Engine (2). It collects the scores and creates a prioritization list based on these scores. This unit has a specific threshold. It identifies beam regions with probability scores above a certain value. If there is more than one 10 If the beam region has a high probability, a ranking is made among these regions. Dynamic The Beam Assignment Unit (3) determines which beam regions should receive the wake-up signal. By making the final decision, it transmits this information to the Wake-Up Signal Router (4) unit. Wake-up Signal Router (4), 15 determined by Dynamic Beam Assignment Unit (3) It directs paging signals to target beam regions. This unit broadcasts to the entire cell. Instead, it protects radio sources by sending signals only to designated narrow beam areas. During signal transmission, the success of the signal delivery and feedback are continuously monitored. If the user equipment (6) is in one of the designated beam regions, it receives the wake-up signal. and it switches to active mode. 20 The Energy and Resource Monitoring Unit (5) monitors the total energy consumption and signaling load of the system. It analyzes. This unit compares the energy that would be expended if the signal were to reach the entire cell. It calculates the difference between the energy consumed and the beam-based wake-up method it offers. Additionally, By tracking paging success rates, feedback for the Beam Probability Estimation Engine (2) 25 If no device is found in the predicted beam regions, the system provides this information. By using this method, the prediction model is updated, leading to more accurate results. The system's operating scenario is as follows: When the user equipment (6) goes into sleep mode The Mobility Data Collection Module (1) records the last location and movement data. Network, user 30 When you want to transmit a call or data to your equipment (6), Beam Probability Prediction Engine (2) It intervenes and calculates the beam regions where the device is most likely to be found. The Dynamic Beam Assignment Unit (3) will send a signal by evaluating these probability scores. It creates the target beam list. The Wake-Up Signal Router (4) only uses this target beam It sends paging signals to its regions. When the user equipment (6) receives the signal, it wakes up and connects with the network 35 4 It communicates with the Energy and Resource Monitoring Unit (5), the energy provided during this process. It reports on energy savings and signaling efficiency. Thanks to this invention, unnecessary signaling traffic is minimized in 6G networks and base The energy consumption of the stations is significantly reduced. Especially in high-frequency bands. 5 The narrow beam technology used is integrated with this system to ensure maximum efficiency.

Claims

REQUESTS 1. In which beam region are user equipment located when in sleep mode on 6G networks? a system that predicts the probability and optimizes wake-up signals based on that prediction and its feature is; 5 - Mobility Data Collection Module which collects mobility data of user equipment (6) (1), - Using the data provided by the Mobility Data Collection Module (1), the user in which beam region is the equipment (6) most likely to be located Beam Probability Estimation Engine (2), which calculates 10 - By evaluating the probability scores generated by the Beam Probability Estimation Engine (2) Dynamic Beam Assignment Unit (3) determines the target beam regions to which the signal will be sent. - Paging to target beam regions determined by Dynamic Beam Assignment Unit (3) Wake-up Signal Router (4) which directs the signals and - Energy and Resource Monitoring 15, which analyzes the system's energy consumption and signal load. Unit (5) It includes.

2. According to Claim 1, beam-based monitoring for user equipment in sleep mode on 6G networks. It is a prediction and adaptive wake-up system, the feature of which is that the user equipment (6) sleep 20 The last location information, speed, direction, and environmental context before switching to this mode. It includes the Mobility Data Collection Module (1) which collects data.

3. According to Claim 1, beam-based monitoring for user equipment in sleep mode on 6G networks. It is a prediction and adaptive wake-up system, the feature of which is; the device's movement trends, the surrounding 25 with a scoring algorithm that takes into account variables such as physical barriers and network topology It includes the Beam Probability Estimation Engine (2) which generates probability maps.

4. According to Claim 1, beam-based monitoring for user equipment in sleep mode on 6G networks. It is a prediction and adaptive wake-up system, its feature is; Beam Probability Prediction Engine (2) 30 By taking the probability scores generated, the probability above a certain threshold value is determined. Dynamic Beam Assignment Unit (3) which prioritizes beam regions with scores It includes.

5. According to Claim 1, beam-based 35 for user equipment in sleep mode on 6G networks. It is a predictive and adaptive wake-up system, and its feature is that instead of broadcasting to the entire cell, 6 only target beam regions determined by the Dynamic Beam Assignment Unit (3) It includes a Wake-Up Signal Router (4) which sends paging signals.

6. According to Claim 1, beam-based monitoring for user equipment in sleep mode on 6G networks. It is a predictive and adaptive wake-up system whose feature is that it tracks paging success rates. 5 Providing feedback for the Beam Probability Estimation Engine (2) and saving energy. It includes the Energy and Resource Monitoring Unit (5) which calculates.

7. According to Claim 1, beam-based monitoring for user equipment in sleep mode on 6G networks. It is a prediction and adaptive wake-up system, the feature of which is that the user equipment (6) sleep 10 Predicting the probability of being in a particular beam region while in this mode, the predicted Prioritization of beam regions and sending wake-up signals only to these regions. It includes a working method that outlines the steps for sending the document.

8. According to Claim 1, beam-based 15 for user equipment in sleep mode on 6G networks. It is a prediction and adaptive wake-up system, the feature of which is that the user equipment (6) is determined If it cannot be found in the beam regions, by the Energy and Resource Monitoring Unit (5) This information is transmitted to the Beam Probability Estimation Engine (2) unit to update the prediction model. It includes a feedback mechanism that provides feedback. 25 35

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