Adaptive topology selection method for 5g nr

Abstract

A method for common signal transmission in a system comprising plurality of base stations (200) where base stations (200) are capable of transmitting common signal and information signal, plurality of user equipment (300) which are capable of communicate communicating with the base stations (200) and a network controller (100) for controlling the operation of base stations (200) characterized in that comprising the steps of: receiving, by user equipment, information signals comprising instructions on how and when to trigger the base stations; selecting, by the network controller (100), operation mode of base stations (200) among an inactive mode where the base station (200) hold operation of transmitting common signals until a user equipment (300) or the network controller (100) triggers common signaling; an active mode where common signaling is realized and where base stations' (200) transmitting and receiving capabilities are adjusted for covering the coverage area of the base stations (200) that operate in inactive mode; monitoring, by the network controller (100), network conditions; performing selection of operation mode based on monitoring results.

Description

[0001] DESCRIPTION

[0002] ADAPTIVE TOPOLOGY SELECTION METHOD FOR 5G NR

[0003] TECHNICAL FIELD

[0004] Invention relates to a method for common signal transmission in a system, in particular a 5G NR system, comprising plurality of base stations where base stations are capable transmitting common signal and information signal, plurality of user equipment which are capable of communicate with the base stations and a network controller for controlling the operation of base stations.

[0005] PRIOR ART

[0006] Current 5thgeneration new radio (5G NR) networks use periodic transmission of synchronization signals and system information, which consumes significant energy, even when the network is idle. The primary goal is to reduce unnecessary transmissions and conserve energy in 5G NR networks.

[0007] Previous solutions have primarily focused on adjusting the periodicity of common signals and random access opportunities to save energy. This involves adapting the transmission / reception of common channels / signals, such as SSB (synchronization signal block) and System Information Block Type 1 (SIB1 ), by modifying their periodicities. For instance, some companies have explored extending the periodicity of SSB and SIB1 to reduce the frequency of transmissions.

[0008] Another approach introduced in Rel-19 is on-demand SSB transmission, which enables sporadic SSB transmissions for specific purposes like secondary cell (SCell) activation, measurements, and beam management, thereby reducing unnecessary transmissions and conserving energy. However, this approach is currently limited to Secondary Cells (SCells) and not applicable to Primary Cells (PCells).

[0009] Additionally, US20240251345A1 proposes a method for determining when a cell should enter or exit a power saving mode based on predicted future load and network performance. This method involves using machine learning to analyze historical load data and predict future load conditions, and then dynamically adjusting thresholds for switching cells or carriers on / off to achieve energy savings without compromising user experience.

[0010] Previous documents propose various energy-saving solutions for 5G NR networks, primarily focused on time-domain adaptation and on-demand SSB transmission.

[0011] Time-domain adaptation methods involve adjusting the periodicity or skipping the transmission of common signals and random access opportunities to reduce energy consumption.

[0012] While the proposed solutions offer promising approaches to energy saving in 5G NR networks, they also present certain disadvantages:

[0013] Time-domain adaptation methods:

[0014] • Limited granularity: Adjusting periodicities offers limited granularity in controlling transmissions, potentially leading to unnecessary SSBs or delayed access for user equipment (UEs).

[0015] • Network-wide impact: Changes in SSB or SIB1 periodicities affect all UEs in the network, potentially impacting those who require frequent access or updates.

[0016] • Complexity: Determining optimal periodicities for different network conditions and traffic patterns can be complex and require significant overhead.

[0017] On-demand SSB transmission:

[0018] • Limited applicability: Currently limited to SCells, leaving the energy consumption of PCells unaddressed.

[0019] • Triggering challenges: Efficiently triggering on-demand SSBs while minimizing latency and ensuring timely access for UEs can be challenging.

[0020] • UE capability: Requires UE support for on-demand SSB operation, potentially limiting its benefits for legacy UEs

[0021] All the problems mentioned above have made it necessary to make an innovation in the relevant technical field as a result.

[0022] BRIEF DESCRIPTION OF THE INVENTION

[0023] The present invention relates to a method to eliminate the above-mentioned disadvantages and bring new advantages to the relevant technical field. An object of the invention is to save energy in base stations of 5G new radio (NR) while maintaining improved user equipment experience.

[0024] Another object of invention is to reduce signaling overhead.

[0025] Another object of the invention is to maintain coverage while saving energy.

[0026] To achieve all the objects mentioned above and that will emerge from the following detailed description, the present invention relates to a method for common signal transmission in a system comprising plurality of base stations where base stations are capable of transmitting common signal and information signal, plurality of user equipment which are capable of communicating with the base stations and a network controller for controlling the operation of base stations. Accordingly, it is characterized in that comprising the steps of:

[0027] - receiving, by user equipment, information signals comprising instructions on how and when to trigger the base stations;

[0028] - selecting, by the network controller, operation mode of base stations among an inactive mode where the base station hold operation of transmitting common signals until a user equipment or the network controller triggers common signaling; an active mode where common signaling is realized and where base stations’ transmitting and receiving capabilities are adjusted for covering the coverage area of the base stations that operate in inactive mode;

[0029] - monitoring, by the network controller, network conditions;

[0030] - performing selection based on monitoring results. Thus, energy efficiency is significantly increased while maintaining service to user equipment and maintaining substantially same coverage. On-demand SSB ensures faster access to synchronization signals for UEs in inactive cells, reducing latency and improving performance compared to delayed access due to extended periodicities or handover overhead from cell switching. Further, signaling overhead is reduced.

[0031] The invention addresses a critical challenge in 5G NR networks: the high energy consumption associated with the continuous transmission of SSBs, even during periods of low or no user activity. This persistent signaling, while necessary for UE to access the network, contributes significantly to operational costs and carbon footprint.

[0032] A possible embodiment of the invention is characterized in that network conditions are at least one of network load, user equipment locations, user equipment requirements. Wherein the common signal is synchronization signal block (SSB). Another possible embodiment of the invention is characterized in that comprising the steps of:

[0033] - accessing, by the network controller, an Al model vtrained to determine optimal network configurations based on inputs comprising network status, user equipment locations, and user equipment requirements;

[0034] - applying monitored network status, including user equipment locations, load, and requirements, to the model and performing selection of operation mode based on Al model’s output.

[0035] Another possible embodiment of the invention is characterized in that comprising the steps of:

[0036] - accessing, by the network controller, Deep Q-Network with Long Short-Term Memory (DQN- LSTM) model trained to determine optimal network configurations based on inputs comprising network status, user equipment locations, and user equipment requirements;

[0037] - applying monitored network status, including user equipment locations, load, and requirements, to the model and performing selection of operation mode based on Al model’s output.

[0038] - iteratively refining the DQN-LSTM model by incorporating feedback from monitored network performance metrics to improve subsequent configurations. Thus, improved topology is realized.

[0039] Another possible embodiment of the invention is, network conditions are at least one of network load, user equipment locations, user equipment requirements.

[0040] In summary, this invention offers a comprehensive solution to the energy efficiency challenges in 5G NR networks. By strategically controlling SSB transmissions, optimizing power usage, and ensuring responsiveness to user needs and network dynamics, the invention achieves a balance between energy conservation and quality of service.

[0041] BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 is a drawing illustrating top schematic view of the system.

[0043] Figure 2a is a drawing illustrating a selected topology all base stations operating in active mode. Figure 2b is a drawing illustrating a selected topology where some of the base station operate in active mode and some of them operate in inactive mode. The base stations operating in active mode are boosted in order to cover the coverage area of inactive base stations.

[0044] REFERENCE NUMBERS GIVEN IN THE FIGURE

[0045] 100 Network controller

[0046] 200 Base station

[0047] 300 User equipment

[0048] DETAILED DESCRIPTION OF THE INVENTION

[0049] In this detailed description, the subject matter is explained with references to examples without forming any restrictive effect only in order to make the subject more understandable.

[0050] Referring to figure 1 , invention relates to a method realized by a system comprising plurality of base stations (200) and a network controller (100) controlling the base station (200). Base stations (200) are capable of transmitting common signals to user equipment (300).

[0051] The base station (200) is configured to perform common signaling by broadcasting synchronization signals, system information, and reference signals to all user equipment (300) within its coverage area, while simultaneously executing control signaling to manage resource allocation, scheduling, and communication with individual user equipment (300).

[0052] The base stations (200) are configured to boost its coverage area by dynamically adjusting its transmission power, modifying the tilt angle of its antennas, or altering beamforming parameters to extend signal reach and enhance connectivity in designated regions. Network controller (100) may command base stations (200) to adjust their coverage area.

[0053] The method provides an adaptive topology for base stations (200) so that they save energy. This topology is controlled by the network controller (100) and decided by monitoring network conditions.

[0054] Network commands base stations (200) to operate in an active mode and inactive mode. In inactive mode base stations (200) operate in low power consuming mode and do not transmit common signals. In active mode, base stations (200) operate in normal operation mode and transmit common signals. Further, base stations (200) operate in varying transmission and receiving strengths. For instance, active base stations (200) may be boosted in order to cover coverage area of inactive base stations (200). Inactive base stations (200) are triggered by user equipment (300) entering to coverage area or by the network station. Triggered inactive base stations (200) start to operate in active mode.

[0055] User equipment access (300) to an information signal comprising instructions on how and when to trigger base stations (200). This information signal may be transmitted by network elements such as base stations (200).

[0056] The network controller (100) selects the topology based on monitoring network conditions. Network conditions may be network load, user equipment (300) locations and user equipment (300) requirements.

[0057] Figure 2a gives an exemplary condition where all base stations (200) are in active mode. Figure 2b gives an example where some of the base stations (200) are in inactive mode and some are in active mode. Base stations (200) who are in active mode are boosted in order to cover the coverage areas of inactive base stations (200). When a user equipment (300) enters to inactive base stations’ (200) coverage area and demands common signaling, it may be triggered to operate in active mode.

[0058] In a possible embodiment network controller (100) selects the topology using an Al model, model trained to determine optimal network configurations based on inputs comprising network status, user equipment (300) locations, and user equipment (300) requirements. The Al model is trained with network status, user equipment (300) locations, user equipment (300) requirements and network performance data and network topology data. It decides a network topology consisting of active base stations (200), inactive base stations (200) and the level of base stations (200) transmission and receiving amplification.

[0059] The Al model may be a Deep Q-Network with Long Short-Term Memory (DQN-LSTM) model.

[0060] Network controller (100) then monitors network performance. Network performance can be monitored by using tools and techniques that track key metrics to ensure the network operates efficiently and reliably. Examples of performance parameters include throughput, which measures the amount of data transmitted; latency, which is the delay in data transfer; packet loss, which shows how many data packets are lost during transmission; and jitter, which measures variations in delay that can affect real-time applications. Other metrics include bandwidth utilization, error rates, and availability (uptime). Network (100) controller then feeds back the performance metrics to the Al model, which the Al model reconfigures itself in order to provide better decisions in the future. A reward is calculated, taking into account factors like energy saving, latency reduction, and throughput improvement. This reward is then used to update the DRL model, allowing it to learn and make better decisions in the future. This cyclical process ensures continuous optimization of the network topology based on real-time conditions and feedback.

[0061] The scope of protection of the invention is specified in the attached claims and cannot be limited to those explained for sampling purposes in this detailed description. It is evident that a person skilled in the art may exhibit similar embodiments in light of the above-mentioned facts without drifting apart from the main theme of the invention.

Claims

CLAIMS1. A method for common signal transmission in a system comprising plurality of base stations (200) where base stations (200) are capable of transmitting common signal and information signal, plurality of user equipment (300) which are capable of communicating with the base stations (200) and a network controller (100) for controlling the operation of base stations (200) characterized in that comprising the steps of:- receiving, by user equipment (300), information signals comprising instructions on how and when to trigger the base stations (200);- selecting, by the network controller (100), operation mode of base stations (200) among an inactive mode where the base station (200) hold operation of transmitting common signals until a user equipment (300) or the network controller (100) triggers common signaling; an active mode where common signaling is realized and where base stations’ (200) transmitting and receiving capabilities are adjusted for covering the coverage area of the base stations (200) that operate in inactive mode;- monitoring, by the network controller (100), network conditions;- performing selection of operation mode based on monitoring results.

2. The method according to claim 1 , wherein network conditions are at least one of network load, user equipment (300) locations, user equipment (300) requirements.

3. The method according to claim 2, characterized in that comprising the steps of:- accessing, by the network controller (100), an Al model vtrained to determine optimal network configurations based on inputs comprising network status, user equipment (300) locations, and user equipment (300) requirements;- applying monitored network status, including user equipment (300) locations, load, and requirements, to the model and performing selection of operation mode based on Al model’s output.

3. The method according to claim 3, characterized in that comprising the steps of:- accessing, by the network controller (100), Deep Q-Network with Long Short-Term Memory (DQN-LSTM) model trained to determine optimal network configurations based on inputs comprising network status, user equipment (300) locations, and user equipment (300) requirements;- applying monitored network status, including user equipment (300) locations, load, and requirements, to the model;- performing selection of operation mode based on N-LSTM model’s output;- iteratively refining the DQN-LSTM model by incorporating feedback from monitored network performance metrics to improve subsequent configurations4. The method according to claim 1 , wherein said common signal is Synchronization Signal Block (SSB).

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