Methods and systems for faster service acquisition in wireless communication systems

Abstract

The present invention relates to a system and method for faster service acquisition in wireless communication systems The system comprises a user equipment (UE) (102) having multiple radio frequency (RF) chains (104) and multiple mobile subscriber identity modules (MSIM) (106), configured to determine available RF chains (104) and MSIM modules (106) for prioritizing the parallel frequency band and RAT scanning when service acquisition is required due to initial acquisition, out of service, PLMN search or radio link failure scenarios. The method involves prioritizing scanning based on location-based RAT prioritization, RF chains capability, and neighboring cell information and thereafter performing parallel frequency band scanning. The UE camps on first available service while continuing parallel scanning for better options, then moves to optimal RAT and cell once identified. This parallel scanning significantly reduces scanning and service acquisition time in mixed RAT deployment environments, thereby addressing sequential scanning delays while optimizing power consumption.

Description

METHODS AND SYSTEMS FOR FASTER SERVICE ACQUISITION IN WIRELESS COMMUNICATION SYSTEMSFIELD OF THE INVENTION

[0001] The present disclosure relates to wireless communication technology for service acquisition in mixed network Radio Access Technology (RAT) deployment environments, and more particularly to systems and methods for faster service acquisition using parallel frequency band scanning with multiple mobile subscriber identity modules and location-based prioritization.BACKGROUND OF THE INVENTION

[0002] Wireless communication systems are extensively utilized for delivering a wide array of telecommunications services including telephony, video streaming, data transmission, messaging, and broadcasting. These systems commonly employ multiple-access technologies to facilitate communication with numerous users by efficiently sharing available system resources such as bandwidth and transmit power. Examples of such multiple-access technologies encompass code division multiple access (CDMA), time division multiple access (TDMA), frequency-division multiple access (FDMA), orthogonal frequency-division multiple access (OFDMA), single-carrier frequency-division multiple access (SC-FDMA), time division synchronous code division multiple access (TD-SCDMA), and long-term evolution (LTE).

[0003] LTE / LTE-Advanced represents a suite of enhancements to the universal mobile telecommunications system (UMTS) mobile standard, as standardized by the Third Generation Partnership Project (3GPP). New Radio (NR), often referred to as 5G, represents further enhancements to the LTE mobile standard and is engineered to advance mobile broadband Internet access by enhancing spectral efficiency, reducing costs, improving services, harnessing new spectrum bands, and fostering better integration with other open standards. NR achieves these goals through the utilization of advanced techniques such as orthogonal frequency division multiplexing (OFDM) with a cyclic prefix (CP) on the downlink, along with CP-OFDM and single-carrier frequency-division multiplexing (SC-FDM) on the uplink, while supporting cutting-edge technologies including beamforming, multiple-input multiple-output (MIMO) antenna systems, and carrier aggregation.

[0004] In a wireless communication network, multiple base stations are deployed to facilitate communication for various user equipment (UEs). A UE interacts with a base stationvia two communication channels: the downlink and the uplink. The downlink denotes the communication pathway from the base station to the UE, whereas the uplink signifies the communication pathway from the UE back to the base station. Base stations may be referred to by different names including Node B, gNB, access point (AP), radio head, transmit and receive point (TRP), new radio (NR) base station, 5GNode B, and similar designations.

[0005] In current designs, user equipment scans device-supported frequency bands for a supported Radio Access Technology (RAT) in a defined order to camp on a cell to receive network service. When user equipment does not detect service on available or supported bands for a RAT on a device, the device moves to another RAT to scan the frequency bands supported. This process may take time to identify the appropriate cell for service and service may be delayed to the user in many use cases, such as initial acquisition service, out-of-service scenarios, radio link failure, and other situations. Advanced methods involve the device scanning the last service frequency or last service frequency bands to expedite acquisition, but this approach sometimes does not provide assistance in many cases, particularly with the growing number of RATs and variants of network types, such as Terrestrial Network (TN) and Non-Terrestrial Network (NTN) RATs.

[0006] In mixed RAT deployment environments, there are multiple RATs deployed to an area, including Terrestrial Network (TN) and Non-Terrestrial Network (NTN) with 4G, 5G and 6G RATs and other combinations. There may be a need for techniques to select the available RAT and frequency for service while achieving faster acquisition to avoid delays in services. There may be opportunities for optimized radio frequency scanning by prioritizing the cell or frequency which are more suitable for a UE current service or based on lactation proximity to the UE. There is need to reduce the service camping time by scanning multiple cells frequencies or bands in parallel to achieve faster service acquisition to camp on service.OBJECTIVES OF THE INVENTION

[0007] The objectives described herein are merely exemplary and are not intended to be limiting. It will be apparent to those skilled in the art that various modifications and variations can be made to the disclosed embodiments without departing from the scope of the invention.

[0008] The primary objective of the present invention is to provide systems and methods for faster service acquisition in wireless communication systems, particularly in mixed network Radio Access Technology (RAT) deployment environments where multiple RATsincluding Terrestrial Network (TN) and Non-Terrestrial Network (NTN) with 4G, 5G and 6G RATs.

[0009] Another objective of the present invention is to implement optimal parallel frequency band scanning capabilities using multiple radio frequency (RF) chains and multiple mobile subscriber identity modules (MSIM) to significantly reduce service acquisition time during initial acquisition, out-of-service scenarios, Public Land Mobile Network (PLMN) search, and radio link failure situations. The optimal parallel frequency search where device may take the frequency bands to parallel scanning in optimal order based on UE current requirements.

[0010] Yet another objective of the present invention is to optimize service acquisition through location-based RAT prioritization and frequency bands prioritization, enabling user equipment to avoid unnecessary scanning of non-deploy ed RATs and frequency bands in a current UE area, thereby saving significant device power and reducing acquisition delays.

[0011] Yet another objective of the present invention is to incorporate database server integration, in internal UE database server and external database server or both, containing real-time frequency and band deployment information for various locations to enhance the efficiency and accuracy of service acquisition decisions in diverse network environments.

[0012] Yet another objective of the present invention is to implement a predictive location module that anticipate potential UE movement patterns and user schedule calendar information, enabling proactive retrieval of neighboring cell information to improve service continuity and faster reacquisition across network environments.

[0013] Yet another objective of the present invention is to provide intelligent RAT selection and prioritization scanning, where RAT prioritization based on running applications on the UE, including high bandwidth applications, latency-sensitive applications, real-time applications, and emergency applications, ensuring optimal network selection based on application requirements.

[0014] Yet another objective of the present invention is to enable continuous service optimization by allowing UEs to camp on first available service while maintaining parallel scanning using free available RF chains for better RAT and cell options, ensuring uninterrupted service while seeking optimal network conditions.

[0015] Yet another objective of the present invention is to optimize Public Land Mobile Network (PLMN) search processes and reduce signaling overhead by implementing proximity -based neighbor cell frequency bands or measurement techniques using approximate cell originating location and coverage range information, improving the speed and reliability of service acquisition across multiple RATs.SUMMARY OF THE INVENTION

[0016] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

[0017] The present invention relates to the field of wireless communication systems, particularly to methods and systems for faster service acquisition and reacquisition in mixed network RAT deployment environments.

[0018] According to an aspect of the present disclosure, a wireless communication system for faster service acquisition is provided. The system comprises a user equipment (UE) having multiple radio frequency (RF) chains and multiple mobile subscriber identity modules (MSIM). The UE is configured to determine available RF chains and MSIM modules at the UE for parallel frequency band and RAT scanning capability when the UE service acquisition or reacquisition is required due to initial acquisition, out of service, public land mobile network (PLMN) search or radio link failure scenarios. The UE prioritizes frequency band scanning based on at least one of: location -based RAT prioritization and frequency bands prioritization, RF chains capability, RF distribution optimization, and neighboring cell information with location and area coverage data. Accordingly, the UE performs parallel frequency band scanning using available multiple RF chains to scan different frequency bands simultaneously in optimal prioritized order. The UE camps on first available service found through the parallel frequency band or RAT scanning while continuing parallel scanning for better RAT and better cell options if first service band or RAT is not optimal for UE service, and moves to optimal RAT, frequency bands, and cell for service once a better option is identified.

[0019] According to another aspect of the present disclosure, a method for faster service acquisition in a wireless communication system is provided. The method comprises determining, by a user equipment (UE) having multiple radio frequency (RF) chains and multiple mobile subscriber identity modules (MSIM), for parallel scanning capability when service acquisition or reacquisition is required due to initial acquisition, out of service, PLMN search scenarios or radio link failure scenarios. The method includes prioritizing frequencyband scanning based on at least one of: location -based RAT prioritization and frequency bands prioritization, RF chains capability, RF distribution optimization, and neighboring cell information with location and area coverage data, performing parallel frequency band scanning using multiple RF chains to scan different frequency bands on same or different RAT simultaneously, camping on first available service found through the parallel frequency band or RAT scanning while continuing parallel scanning for better RAT and better cell options if first service band or RAT is not optimal for UE service, and moving to optimal RAT, frequency bands, and cell for service once a better option is identified.

[0020] The present invention addresses the challenge of reducing service acquisition time when user equipment prioritizes parallel scanning of supported frequency bands for available RATs to camp on a cell in mixed RAT deployment environments. By prioritizing the parallel scanning process in the user equipment using multiple RF chains corresponding to the mobile subscriber identity modules (MSIM), internal or external database servers for location-based frequency prioritization, and a predictive location module, the system provides a solution to the problem of sequential scanning delays that occur in growing mixed RAT deployments including Terrestrial Network (TN) or Non-Terrestrial Network (NTN) with 4G,5G, 6GRATs.

[0021] This innovative approach offers several advantages, including enhanced service acquisition speed, improved user experience through reduced connection delays, optimized Public Land Mobile Network (PLMN) search processes, and significant power savings by avoiding unnecessary scanning of non-deploy ed RATs and frequency bands in specific areas. Additionally, the system’s location-based prioritization and predictive capabilities ensure optimal performance across various network conditions and deployment scenarios.

[0022] The foregoing general description of the illustrative embodiments and the following detailed description thereof are merely exemplary aspects of the teachings of this disclosure and are not restrictive.BRIEF DESCRIPTION OF FIGURES

[0023] Non-limiting and non-exhaustive examples are described with reference to the following figures.

[0024] FIG. 1 illustrates a block diagram of a wireless communication system 100 with multiple RF chains 104 and MSIM modules 106, according to aspects of the present disclosure.

[0025] FIG. 2A illustrates a block diagram of a service acquisition system 200 with a database server 204 and predictive location module components 210, according to aspects of the present disclosure.

[0026] FIG. 2B illustrates a block diagram of the service acquisition system 200 with the database server 204 in external configuration connected to network infrastructure 220, according to aspects of the present disclosure.

[0027] FIG. 3 illustrates a flowchart of a method 300 for faster service acquisition using parallel scanning capability, according to aspects of the present disclosure.

[0028] FIG. 4 illustrates a flowchart of a method 400 for service acquisition utilizing location-based frequency information, according to aspects of the present disclosure.

[0029] FIG. 5 illustrates a block diagram of an artificial intelligence and machine learning processing system for predictive location module, according to aspects of the present disclosure.DETAILED DESCRIPTION

[0030] The following description describes various features and functions of the disclosed invention with reference to the accompanying figures. In the figures, similar symbols identify similar components, unless context dictates otherwise. The illustrative aspects described herein are not meant to be limiting. It may be readily understood that certain aspects of the disclosed invention can be arranged and combined in a wide variety of different configurations, all of which are contemplated herein.

[0031] Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope of the invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.

[0032] Features that are described and / or illustrated with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments and / or in combination with or instead of the features of the other embodiments.

[0033] The terms and words used in the following description and claims are not limited to the bibliographical meanings but are merely used to enable a clear and consistent understanding of the invention. Accordingly, it should be apparent to those skilled in the artthat the following description of exemplary embodiments of the present invention are provided for illustration purposes only and not to limit the invention.

[0034] It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.

[0035] While this invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.

[0036] The present disclosure relates to wireless communication systems and methods for faster service acquisition in mixed radio access technology (RAT) deployment environments. Modem wireless communication networks may include multiple RATs deployed simultaneously in a geographical area, such as 4G, 5G, next generation 6G with network type of Terrestrial Network (TN), or Non-Terrestrial Network (NTN) technologies. In such environments, user equipment may experience delays when attempting to acquire or reacquire service due to sequential scanning processes across different frequency bands, network types and RATs. In such environments, User equipment may also scan frequency bands or network types cell in a priority order which may not align with user equipment requirements and such a scanning takes more time and consumes battery power as well and camping on such cell may further reduce the UE performance.

[0037] The disclosed wireless communication system addresses challenges associated with service acquisition or reacquisition time by implementing optimize prioritized parallel scanning techniques using multiple radio frequency (RF) chains and mobile subscriber identity modules (MSIM). The system may utilize location-based prioritization methods to optimize frequency band scanning processes. In some cases, the system may employ external database servers containing real-time frequency and band deployment information for various locations to enhance service acquisition efficiency.

[0038] The disclosed methods may provide faster service acquisition and reacquisition capabilities for mobile devices operating in mixed network environments. The system may implement predictive location module to anticipate user movement patterns and prepare neighboring cell information in advance. In some cases, the system may optimize Public LandMobile Network (PLMN) search processes and reduce power consumption by avoiding unnecessary scanning of non-deploy ed RATs and frequency bands in specific areas.

[0039] The wireless communication system may incorporate multiple approaches for parallel frequency band scanning, including multi-MSIM parallel scanning and external database server integration. The system may prioritize frequency band scanning based on location-based RAT prioritization, RF chains capability, RF distribution optimization, and neighboring cell information with location and area coverage data. In some cases, the system may enable user equipment to camp on the first available service while continuing parallel scanning using free available RF chain for better RAT and cell options.

[0040] Referring to FIG. 1, a wireless communication system 100 may be configured to provide faster service acquisition capabilities in mixed radio access technology deployment environments. The wireless communication system 100 may include a user equipment (UE) 102 that contains multiple radio frequency (RF) chains 104 and multiple mobile subscriber identity modules (MSIM) 106. The MSIM module 106 may include multiple RF chains 104. The multiple RF chains 104 may enable the UE 102 to perform simultaneous scanning operations across different frequency bands of a RAT, while the multiple MSIM modules 106 may provide parallel processing capabilities for different RAT scanning operations. In some cases, the UE 102 may distribute frequency band groups across different RF chains of available MSIM modules to enhance service acquisition speed.

[0041] The UE 102 may incorporate several internal processing modules that work together to implement faster service acquisition methods. A parallel scanning module 108 may be connected to both the multiple RF chains 104 and the multiple MSIM modules 106 to coordinate simultaneous scanning operations across different frequency bands and RATs. The parallel scanning module 108 may schedule different RAT or different frequency bands scanning operations on different MSIM modules simultaneously, allowing the UE 102 to scan multiple frequency bands in parallel rather than sequentially. In some cases, the parallel scanning module 108 may group frequency bands based on RF chains capability available to the UE 102 and may utilize available free RF chains for service acquisition based on RF design and RF capability of the device.

[0042] A prioritization module 110 may provide input to the parallel scanning module 108 and may be configured to prioritize frequency band scanning based on various factors including location-based RAT prioritization, frequency bands prioritization, RF chains capability, RFdistribution optimization, and neighboring cell information with location and area coverage data. The prioritization module 110 may process real-time network requirements of the UE 102, including network type requirements based on the UE current application types suitable for Terrestrial Network or Non-Terrestrial Network service options. In some cases, the prioritization module 110 may implement RAT selection and prioritization based on running applications on the UE 102, considering application requirements such as high bandwidth applications requiring enhanced data throughput, latency-sensitive applications requiring low- latency communication, real-time applications requiring continuous connectivity, and emergency applications requiring priority network access.

[0043] As further shown in FIG. 1, a service camping module 112 may be configured to enable the UE 102 to camp on the first available service found through parallel frequency band or RAT scanning operations. The service camping module 112 may allow the UE 102 to establish service connectivity while continuing parallel scanning for better RAT and better cell options in the background if first service camped is not optimal for UE current requirements. A service optimization module 114 of the wireless communication system 100 may be further connected to the service camping module 112 and may be configured to move the UE 102 to optimal RAT, frequency bands, and cell for service once a better option is identified. The service optimization module 114 may continuously evaluate available service options and may facilitate seamless transitions to improved network connections without interrupting ongoing service.

[0044] The wireless communication system 100 may operate within a network environment 120 that encompasses various types of wireless communication networks and technologies. The network environment 120 may include 4G / 5G / 6G RAT networks that provide traditional cellular communication services across different generations of mobile technology standards. 5G and 6G RATs may be implemented in the network environment 120 with network type of Terrestrial Network (TN) or Non-Terrestrial Network (NTN) technologies. The Terrestrial Network (TN) may be included within the network environment 120 to provide ground-based wireless communication infrastructure, while a Non-Terrestrial Network (NTN) may provide satellite-based or aerial communication capabilities to 5G and 6G RAT networks. In some cases, the network environment 120 may represent mixed RAT deployment environments where multiple radio access technologies are deployed simultaneously in the same geographical area, creating opportunities for the UE 102 to select among different network options based on service requirements and availability.

[0045] The interconnections between the internal modules of the UE 102 may form a processing chain that enables coordinated service acquisition operations. The parallel scanning module 108 may provide scanning results based on the priority order received from the prioritization module 110, where the prioritization of frequency bands or RAT scanning are based on location-based deployment prioritization to reduce scanning of non-deployed RATs and frequency bands in the current area. The parallel scanning module 108 may pass prioritized scanning results to the service camping module 112, which may establish initial service connections while maintaining scanning operations for better options. The service optimization module 114 may receive information from the service camping module 112 and may implement transitions to improved network connections when available, thereby optimizing Public Land Mobile Network search processes and saving power of the UE 102 by avoiding unnecessary scanning operations.

[0046] Referring to FIG. 2A, a service acquisition system 200 may be configured to enhance service acquisition capabilities through database integration and predictive modeling techniques. The service acquisition system 200 may include a UE location module 202 that may be configured to determine the current location of user equipment and may provide location-based information for service acquisition optimization. The UE location module 202 may establish communication connections with multiple system components to facilitate coordinated location-aware service acquisition operations. A database server 204 may be connected to the UE location module 202 and may contain comprehensive information about frequency deployments and network configurations across various geographical areas. The database server 204 may be implemented as an internal UE database server where neighboring frequency and RAT information may be stored locally within the user equipment, eliminating external server queries in some deployment scenarios. This UE data base server may keep updated by the UE services on different cells and frequency bands based on the recent history or it may be updated by the network operator over the air configuration.

[0047] The database server 204 may incorporate multiple information storage components that may provide detailed network deployment data for service acquisition optimization. Realtime frequency info 206 may be contained within the database server 204 and may store current frequency allocation information for different network operators and geographical locations. Band deployment info 208 may also be contained within the database server 204 and may provide detailed information about frequency band deployments across different areas and network types. The database server 204 may be configured as OEM-specific implementationstailored to particular original equipment manufacturers’ requirements and deployment strategies, allowing customization based on device capabilities and manufacturer specifications. In some cases, the database server 204 may be configured as operator-specific implementations customized for particular network operators’ business needs and coverage areas, enabling targeted optimization for specific network environments.

[0048] A predictive location module 210 may be connected to both the UE location module 202 and the database server 204 to provide advanced location prediction capabilities for service acquisition optimization. The predictive location module 210 may analyze user movement patterns and may predict future locations based on user schedular activities calendar, where user equipment may require service acquisition or reacquisition operations. The predictive location module 210 may utilize artificial intelligence and machine learning algorithms to process historical movement data as daily activities and future visits planning based on the user schedule calendar in system and may generate predictions about areas where user equipment may move based on established patterns and scheduled activities. In some cases, the predictive location module 210 may incorporate user schedule calendar information to enhance prediction accuracy and may provide neighboring cell information for anticipated movement areas in advance of actual user movement. The network operator may update the frequency bands or RAT information of predicted location to the database based on the UE predicted location in near future which is provided by the predictive location module.

[0049] As further shown in FIG. 2A, a neighbor cell prioritization 212 module may be connected to both the database server 204 and the predictive location module 210 and may be configured to prioritize neighboring cell measurements and scanning operations based on proximity calculations and coverage area analysis. The neighbor cell prioritization 212 may include approximate range coverage information in addition to cell originating location to help devices prioritize measurements based on proximity calculations. The neighbor cell prioritization 212 may process approximate cell originating location data and approximate range coverage information to determine which neighboring cells may provide stronger connectivity or signal strength based on geographical proximity to user equipment. A RAT selection optimizer 214 may be connected to the neighbor cell prioritization 212 and may be configured to optimize radio access technology selection based on application requirements and network availability. The RAT selection optimizer 214 may analyze running applications on user equipment and may select appropriate RAT options based on bandwidth requirements, latency sensitivity, and connectivity needs to set priority order for RAT for UE at that time.

[0050] The service acquisition system 200 may interface with network infrastructure 220 that may provide the underlying wireless communication framework for service acquisition operations. The network infrastructure 220 may include base stations 222 that may provide wireless communication coverage across different geographical areas and may support multiple radio access technologies including the 4G / 5G / 6G networks with network types of the Terrestrial Network (TN) or the Non-Terrestrial Network (NTN). Geographical locations 224 may be incorporated within the network infrastructure 220 and may provide location-based reference points for service acquisition optimization and network deployment mapping. In one implementation, the database server 204 may maintain real-time updates from the base stations 222 to ensure frequency cells deployment information remains current and accurate for field devices, enabling dynamic adaptation to changing network conditions and deployment configurations.

[0051] The interconnections between components within the service acquisition system 200 may enable coordinated information flow and processing for enhanced service acquisition capabilities. The UE location module 202 may provide current location information to both the database server 204 and the predictive location module 210, enabling location-aware processing and prediction operations. The database server 204 may provide data traffic mean value status information of different geographical locations, enabling traffic-aware network selection decisions based on current network loading conditions and performance characteristics. The predictive location module 210 may receive location data from the UE location module 202 and network deployment information from the database server 204, and UE schedule visit by accessing the UE scheduler calendar, processing this information to generate predictions about future service acquisition requirements and neighboring cell availability for anticipated movement patterns.

[0052] Referring to FIG. 2B, an alternative configuration of the service acquisition system 200 may implement an external database server architecture where the database server 204 may be positioned external to the service acquisition system 200 and may interface with the network infrastructure 220. In this configuration, the database server 204 may be connected to the base stations 222 within the network infrastructure 220 to collect real-time frequency and band deployment information from multiple geographical locations 224. The external database server 204 may contain the real-time frequency info 206 and band deployment info 208 components and may provide centralized network deployment data to multiple user equipment devices operating across different coverage areas. The UE location module 202 maycommunicate with the external database server 204 to retrieve location-specific frequency bands and RAT deployment information based on current geographical position. The predictive location module 210 may receive network deployment data from the external database server 204 to enhance location prediction accuracy and neighboring cell information preparation. This external database server configuration may enable centralized data collection and distribution across multiple network operators and geographical regions, providing comprehensive network deployment information for enhanced service acquisition optimization.

[0053] Referring to FIG. 3, a method 300 may be implemented to provide faster service acquisition capabilities through parallel scanning operations in wireless communication systems. The method 300 may begin with a step 302 where user equipment may determine parallel scanning capability of the user equipment (UE) by evaluating available radio frequency chains and mobile subscriber identity modules for concurrent frequency band and RAT scanning operations. The step 302 may involve assessing RF design characteristics and RF capability of the UE to identify free RF chains that may be utilized for service acquisition processes. In some cases, the step 302 may evaluate device hardware configurations to determine optimal distribution strategies for parallel scanning operations across multiple MSIM modules and RF chains.

[0054] Following the determination of parallel scanning capability, the method 300 may proceed to a step 304 where frequency band or RAT scanning may be prioritized based on various factors including location-based RAT prioritization, frequency bands prioritization, RF chains capability, RF distribution optimization, and neighboring cell information with location and area coverage data. The step 304 may implement location-based frequency bands or RAT deployment prioritization to reduce scanning of non-deploy ed RATs and frequency bands in the current area, thereby optimizing Public Land Mobile Network search processes and conserving power consumption. The step 304 may analyze real-time network requirements of the UE, including network type requirements based on available Terrestrial Network or NonTerrestrial Network service options, and may implement RAT selection optimization based on running applications on the user equipment

[0055] The method 300 may continue to a step 306 where parallel frequency bands / RATs scanning operations are planned which are performed using available multiple RF chains / MSIM modules to scan different frequency bands / RATs simultaneously. The step 306 may enable the UE to plan scan frequency bands across the same RAT or different RATs concurrently, reducing the time associated with sequential scanning processes. The step 306plan simultaneous scanning operations across multiple frequency bands, allowing UEs to evaluate service availability across different network technologies including the 4G / 5G / 6G networks of the Terrestrial Network (TN) or the Non-Terrestrial Network (NTN).

[0056] The method 300 may proceed to step 308 where UE supported frequency bands may be grouped based on RF chains capability of individual RF chain of the UE. The step 308 may analyze RF design characteristics and hardware limitations to determine optimal frequency band grouping strategies that maximize parallel scanning efficiency. The step 318 may consider factors such as RF chain bandwidth capabilities, frequency range limitations, and simultaneous operation constraints when grouping frequency bands for parallel scanning operations.

[0057] The method 300 may continue to the step 310 where different bands / RAT scanning operations are planned on different RF chains of the corresponding MSIM modules. The step 310 may coordinate planning for parallel RAT scanning operations across multiple MSIM modules to enhance service discovery capabilities and reduce acquisition time. The step 310 may plan scheduling algorithms that distribute RAT scanning operations across available MSIM modules based on device capabilities and network deployment characteristics.

[0058] Further, in step 312, frequency band groups may be distributed across different RF chains of available MSIM modules based on RF chains capability. The step 312 may implement distribution strategies that optimize utilization of available RF chains and MSIM modules for continued parallel scanning operations. The step 312 may group frequency bands based on RF chains capability available to user equipment and may allocate scanning resources to maximize coverage of potential service options.

[0059] In step 314, available free RF chains may be utilized for scanning as distributed frequencies. The step 314 may implement resource utilization strategies that maximize the use of available RF hardware for service acquisition operations. In some cases, the method 300 may be controlled through a user interface that allows users to enable or disable the faster service acquisition mode according to their preferences, providing user control over power consumption and scanning intensity. The location terminology used by the method 300 may not be limited to coordinate-based location only but may include any wireless protocol form such as tracking area or other location descriptors used in wireless communication systems.

[0060] At step 316, the UE may camp on the first available service found through parallel frequency band or RAT scanning operations. In some cases, step 316 may enable the UE to establish service connectivity without waiting for completion of all scanning operations,providing immediate service availability while background scanning continues to identify improved network options in case first service camp is not optimal for UE. In such a case, step 316 may maintain service connectivity while parallel scanning operations continue on free available RF chain to evaluate alternative RAT and cell combinations that may provide enhanced performance characteristics.

[0061] The method 300 may include a step 318 that represents a decision point where the UE may determine whether better RAT or cell options have been identified through the parallel scanning operations. The step 318 may evaluate scanning results to identify service options that may provide improved performance characteristics compared to the current service connection established in the step 316. The step 318 may analyze factors such as signal strength, preferred RAT, preferred frequency band, network capacity, application compatibility, and service quality metrics to determine whether alternative RAT or cell options may provide enhanced user experience.

[0062] When the step 318 determines that better RAT or cell options have been identified, the method 300 may proceed to the final step 320 where the UE has moved to the optimal RAT, frequency bands, and cell for service. Alternatively, if the step 318 determines that the first available service is not an optimal network service, the method 300 may proceed to step 322 to continue scanning in parallel on free RF chains to achieve better service as described in steps 302 to 320 until camping on an optimal service is achieved. Once a better or improved service is determined which is different from the camped current service connection, the method 300 may implement transition procedures that enable seamless migration from the current service connection to the improved network option without interrupting ongoing communications or data transfers. During transition procedure, handover operations may be coordinated between different RATs or cells to maintain service continuity while optimizing network performance characteristics.

[0063] Referring to FIG. 4, a method 400 may be implemented to provide location-based service acquisition capabilities through database server integration and real-time frequency information processing. The method 400 may begin with a step 402 where a user equipment (UE) may query a database server for real-time frequency and band information corresponding to various geographical locations including the current location and predicted near future location of user equipment. The step 402 may involve transmitting location-specific requests to database servers that may contain comprehensive frequency deployment data need for different network operators and coverage areas. The database server queried in the step 402may be configured as an external database server which may have collected information from various devices in the field, or may be implemented as an internal UE database server where neighboring frequency and RAT information may be stored locally within the UE. In some cases, the step 402 may involve querying database servers that may be configured as OEM- specific implementations or as operator-specific implementations customized for particular network operators' business needs and coverage areas.

[0064] Following the database server query operation, the method 400 may proceed to a step 404 where user equipment may receive location-based frequency bands and RAT deployment information from the queried database server. The step 404 may involve processing comprehensive deployment data that may include neighboring location frequency bands and RAT deployment information for the current UE location and surrounding areas. The location-based frequency bands deployment information received in the step 404 may encompass details about the 4G / 5G / 6G networks RAT with the Terrestrial Network (TN) or the Non-Terrestrial Network (NTN) for 5G and 6G RAT deployments across different geographical regions. The step 404 may process neighboring cells type information including Terrestrial Network or Non-Terrestrial Network RAT coverage data, signal strength measurements, and data traffic mean value status information. In some cases, the step 404 may receive neighboring cell information organized in order of frequency bands and signal strength from stronger to weaker signal strength cells based on the UE current location request.

[0065] The method 400 may continue to a step 406 where real-time frequency bands deployment information may be downloaded for the current location area and neighboring areas. The step 406 may involve retrieving detailed network deployment data that may enable location-aware service acquisition optimization and may provide comprehensive coverage information for anticipated movement areas. The step 406 may download frequency bands deployment information that may include approximate cell originating location data and approximate range coverage information for neighboring cells in the vicinity of user equipment. The real-time frequency bands deployment information downloaded in the step 406 may be updated dynamically from base stations to ensure accuracy and currency of network deployment data for field devices. In some cases, the step 406 may download deployment information that may cover multiple RATs simultaneously, providing comprehensive network availability data for mixed RAT deployment environments.

[0066] The method 400 may continue to a step 408 where a predictive location module may be utilized to map neighboring cell information for areas where the UE may move basedon user movement patterns and anticipated geographical transitions. The step 408 may implement artificial intelligence and machine learning algorithms to analyze historical movement data and may generate predictions about future locations where the UE may require service acquisition or reacquisition operations. The predictive location module utilized in the step 408 may incorporate user schedule calendar information to predict areas where the UE may move based on scheduled appointments and activities, enabling proactive preparation of neighboring cell information for anticipated movement areas. The step 408 may process user movement patterns to identify recurring geographical transitions and may prepare neighboring cell information in advance of actual user movement to reduce service acquisition delays.

[0067] As further shown in FIG. 4, the method 400 may proceed to the final step 410 where neighbor cells measurement or scanning operations may be prioritized based on proximity calculations and real-time network requirements. The step 410 may utilize approximate cell originating location and approximate range coverage information to determine which neighboring cells or frequency bands may provide stronger connectivity or signal strength based on geographical proximity to user equipment. The step 410 may process real-time network requirements of the UE, including network type requirements based on available Terrestrial Network or Non-Terrestrial Network service options, and may implement RAT selection optimization based on running applications on the user equipment. The prioritization operations performed in the step 410 may consider application requirements such as high bandwidth applications, latency-sensitive applications, real-time applications, and emergency applications requiring priority network access. In some cases, the step 410 may prioritize neighbor cells measurement operations to provide faster measurement reports to base stations by focusing on cells that may offer superior signal characteristics based on proximity computations.

[0068] In an embodiment, the present invention incorporates signal fluctuation detection capabilities where a user equipment may experience signal fluctuations or abnormal radio connectivity issues on the current serving cell. When such conditions are detected with configured threshold values, the user equipment may query the external database server for neighboring cells information corresponding to RAT and frequency bands supported at the current location. The user equipment may utilize the predictive location module to obtain neighboring cell information in advance, enabling proactive preparation for service acquisition scenarios. In cases where abnormal radio connectivity or issues occur on the serving cell, the user equipment may initiate service acquisition or reacquisition operations based on location-centric bands and RAT supported sets, prioritizing frequency bands and RAT options deployed in the current geographical area to reduce scanning time and power consumption while ensuring rapid service recovery.

[0069] Referring to FIG. 5, the predictive location module 210 may implement an artificial intelligence and machine learning processing system to analyze user movement patterns and generate location predictions. The system may receive multiple input parameters (XI, X2, X3...Xn) that may include historical UE movement data, user schedule calendar information, and established patterns of geographical transitions, UE current applications requirements such as TN connectivity preference and 6G or 5G connectivity Preference, latency requirements. Each input parameter may be processed through corresponding weight parameters (Wl, W2, W3...Wn) that may determine the relative importance of different factors in the prediction algorithm. The weight for each parameter is dynamic and may depend on multiple real time factors such as network load conditions, UE battery power and UE priority service application on the device where no compromise in service quality. The weighted inputs may be processed through a processing engine that may implement machine learning algorithms to generate output predictions (Y) about future locations where user equipment may require service acquisition operations. The artificial intelligence processing may enable proactive preparation of neighboring cell information for anticipated movement areas, allowing the wireless communication system to optimize service acquisition based on predicted user movement patterns and scheduled activities.

[0070] The present invention offers a significant technical advancement by addressing the problem of service acquisition delays and sequential scanning through an innovative approach that reduces service acquisition or requisition delays and power consumption associated with RF scanning activities, thereby enhancing faster and power optimized PLMN search and service recovery procedure. Wireless communication systems operating in mixed radio access technology deployment environments may encounter technical challenges related to service acquisition delays when user equipment attempts to establish or reestablish network connectivity. Traditional service acquisition methods may implement sequential scanning processes where user equipment scans supported frequency bands for available RATs in a predetermined order, moving from one RAT to another when service may not be detected on available or supported bands. This sequential approach may result in extended service acquisition times, particularly in environments where multiple RATs including 4G, 5G, 6G with Terrestrial Network or Non-Terrestrial Network technologies may be deployedsimultaneously across overlapping geographical areas. The sequential scanning process may consume substantial time and power resources as user equipment evaluates each frequency band individually before proceeding to alternative RAT options, potentially causing service delays during initial acquisition scenarios, out of service conditions, or radio link failure recovery operations.

[0071] The technical problem may be compounded by the increasing complexity of mixed RAT deployment environments where network operators deploy multiple radio access technologies concurrently. User equipment operating in such environments may lack efficient mechanisms to identify which RATs and frequency bands may be deployed in specific geographical locations, leading to unnecessary scanning of non-deployed network technologies. This inefficient scanning approach may result in wasted power consumption and extended service acquisition times as user equipment attempts to evaluate network options that may not be available in the current area.

[0072] The disclosed wireless communication system may address these technical challenges through parallel scanning techniques with prioritized scanning order that enable simultaneous evaluation of multiple frequency bands and RATs in priority order. The optimal parallel scanning approach may utilize multiple radio frequency chains and mobile subscriber identity modules to perform concurrent scanning operations, reducing service acquisition time and eliminating delays associated with sequential scanning methods.

[0073] Location-based prioritization techniques may provide additional technical solutions by enabling user equipment to focus scanning operations on RATs and frequency bands that may be deployed in the current geographical area. The location-based approach may utilize database servers containing real-time frequency and band deployment information to prioritize scanning operations based on actual network deployment characteristics, reducing power consumption and service acquisition time.

[0074] The technical solution may implement predictive location module that analyze user movement patterns to anticipate future service acquisition requirements and prepare neighboring cell information in advance. This predictive approach may enable proactive service acquisition preparation and incorporate artificial intelligence and machine learning algorithms to process historical movement data, enabling optimized resource allocation and enhanced service continuity.

[0075] The technical effects achieved through these solutions may include substantial reductions in service acquisition time compared to traditional sequential scanning methods. The parallel scanning approach may enable user equipment to identify available services across multiple RATs simultaneously, while location-based prioritization may enhance acquisition speed by eliminating scanning operations for non-deployed network technologies. This process may also reduce the service resumption time after out of service recovery or reduce time in connection reestablishment procedure.

[0076] Power consumption reductions may represent another technical effect achieved through the disclosed solutions. The location-based prioritization approach may eliminate unnecessary scanning operations for RATs and frequency bands not deployed in the current geographical area, reducing power consumption associated with RF scanning activities. The parallel scanning techniques may optimize utilization of available RF chains and MSIM modules for efficient resource allocation. This disclosure also ensure the faster and power optimized PLMN search and service recovery procedure.

[0077] Enhanced user experience may result from the combination of reduced service acquisition time and improved service continuity provided by the technical solutions. User equipment may establish service connectivity more rapidly during initial acquisition scenarios, out of service recovery operations, and radio link failure conditions. The predictive location module may enable seamless service transitions as user equipment moves between different coverage areas, while the ability to camp on first available service while continuing parallel scanning may provide immediate connectivity.

[0078] The disclosed wireless communication system may provide substantial advantages in service acquisition performance through parallel scanning techniques and intelligent network selection mechanisms. The parallel scanning approach may enable user equipment to evaluate multiple frequency bands and radio access technologies simultaneously, resulting in reduced service acquisition times across initial acquisition, out of service recovery, and radio link failure conditions. The parallel processing approach may utilize multiple radio frequency chains and mobile subscriber identity modules to maximize scanning efficiency and optimize service discovery performance.

[0079] Power consumption reductions may represent another advantage achieved through location-based prioritization mechanisms. The location-aware scanning approach may focus scanning operations on radio access technologies and frequency bands deployed in the currentgeographical area, avoiding unnecessary evaluation of non-deployed network options. The intelligent prioritization may utilize real-time frequency and band deployment information to enable targeted scanning strategies that minimize power consumption while maintaining comprehensive service discovery capabilities.

[0080] Public Land Mobile Network search optimization may be enhanced through the combination of parallel scanning techniques and location-based deployment prioritization mechanisms. The optimized search processes may focus on network operators and technologies that provide service in the current geographical location, reducing search duration and resource consumption. The predictive location module may further enhance search optimization by anticipating future service requirements based on user movement patterns and preparing neighboring cell information in advance of geographical transitions.

[0081] Enhanced user experience may result from the combination of faster service acquisition, reduced power consumption, and improved service continuity provided by the wireless communication system. User equipment may establish service connectivity more rapidly during various operational scenarios, reducing service interruption periods and maintaining communication capabilities across different network environments. The ability to camp on first available service while continuing parallel scanning for better options may provide immediate connectivity while background optimization continues to identify improved network alternatives.

[0082] The technical benefits achieved through intelligent prioritization mechanisms may include optimized resource allocation and enhanced network selection accuracy. The prioritization approach may consider multiple factors including proximity calculations, signal strength characteristics, application requirements, and real-time network conditions to identify optimal service options. The application-aware radio access technology selection may match network capabilities with specific application requirements such as high bandwidth applications, latency-sensitive applications, real-time applications, and emergency applications requiring priority network access.

[0083] The predictive location module capabilities may provide additional advantages through proactive service acquisition preparation and enhanced mobility management. The artificial intelligence and machine learning algorithms may analyze historical movement data to generate predictions about future locations where user equipment may require service acquisition operations. The predictive approach may incorporate user schedule calendarinformation to enhance prediction accuracy and provide comprehensive coverage data for various potential movement scenarios.

[0084] The database server integration capabilities may provide comprehensive network deployment information that enhances service acquisition accuracy and efficiency across different geographical areas and network operators. The real-time frequency and band deployment information may enable location-aware service acquisition optimization and provide current network availability data for mixed radio access technology deployment environments. The database server implementations may be configured as operator-specific or original equipment manufacturer-specific solutions tailored to particular business needs and deployment strategies.

[0085] The description provides examples, and is not limiting of the scope, applicability, or examples set forth in the claims. Changes may be made in the function and arrangement of elements discussed without departing from the scope of the disclosure. Various examples may omit, substitute, or add various procedures or components as appropriate. For instance, the methods described may be performed in an order different from that described, and various steps may be added, omitted, or combined. Also, features described with respect to some examples may be combined in some other examples. For example, the apparatus may be implemented or a method may be practiced using any number of the aspects set forth herein. In addition, the scope of the disclosure is intended to cover such an apparatus or method which is practiced using other structure, functionality, or structure and functionality in addition to, or other than, the various aspects of the disclosure set forth herein. It should be understood that any aspect of the disclosure disclosed herein may be embodied by one or more elements of a claim. The word “exemplary” is used herein to mean “serving as an example, instance, or illustration." Any aspect described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other aspects.

[0086] The terminology used herein describes particular aspects only and should not be construed to limit any aspects disclosed herein. As used herein, the terms "user equipment" (UE) and "base station" are not intended to be specific or otherwise limited to any particular Radio Access Technology (RAT), unless otherwise noted. In general, such UEs may be any wireless communication device (e.g., a mobile phone, router, tablet computer, laptop computer, tracking device, Internet of Things (loT) device, etc.) used by a user to communicate over a wireless communications network. A UE may be mobile or may (e.g., at certain times) bestationary, and may communicate with a Radio Access Network (RAN). Network and base station terminology in this specification may be used interchangeable in this specification.

[0087] It should be noted that while aspects may be described using terminology commonly associated with 5G and later wireless technologies including next generation 6G, aspects of the present disclosure can be applied in other generation-based communications systems, such as and including 3G and / or 4G technologies.

[0088] A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the disclosure. Accordingly, other implementations are within the scope of the following claims.

Claims

WE CLAIM:

1. A wireless communication system (100) for faster service acquisition, the system comprising: a user equipment (UE) (102) having multiple radio frequency (RF) chains (104) and multiple mobile subscriber identity modules (MSIM) (106); wherein the UE (102) is configured to: determine available RF chains (104) and MSIM modules (106) at the UE (102) for parallel frequency band and RAT scanning capability when the UE (102) service acquisition or reacquisition is required due to initial acquisition, out of service, Public land mobile network (PLMN) search or radio link failure scenarios; prioritize frequency band scanning based on at least one of: location-based RAT prioritization and frequency bands prioritization, RF chains capability, RF distribution optimization, UE current requirement and neighboring cell information with location and area coverage data; perform parallel frequency band scanning using available multiple RF chains (104) to scan different frequency bands simultaneously in order of prioritization; camp on first available service found through the parallel frequency band or RAT scanning while continuing parallel scanning for better RAT and better cell options if first camped service is not optimal for UE service; and move to optimal RAT, frequency bands, and cell for service once a better option is identified.

2. The wireless communication system (100) as claimed in claim 1, wherein the UE (102) is configured to perform parallel frequency band or parallel RAT scanning using multiple MSIM modules (106) by: grouping frequency bands based on RF chains capability available to the UE (102); scheduling different RAT scanning on different MSIM modules (106) simultaneously; distributing different frequency band groups across different RF chains (104) of available MSIM modules (106); andutilizing available free RF chains (104) for service acquisition based on RF design and RF capability of the UE (102).

3. The wireless communication system (100) as claimed in claim 1, wherein the parallel frequency bands scanning reduces scanning of non-deploy ed RATs and frequency bands in a current area based on location-based deployment prioritization, thereby optimizing Public Land Mobile Network (PLMN) search process and saving power of the UE (102).

4. The wireless communication system (100) as claimed in claim 1, wherein the RATs include at least one of: Terrestrial Network (TN) and Non-Terrestrial Network (NTN) of 4G, 5G and 6G RATs in mixed RAT deployment environments (120).

5. The wireless communication system (100) as claimed in claim 1, wherein the UE (102) is configured to perform parallel frequency band scanning using a database server (204) by: querying a database server (204) containing real-time frequency and band deployment information for various locations; receiving location-based frequency bands deployment information including neighboring location frequency bands and RAT deployment from the server; downloading real-time frequency bands deployment information for current area and neighboring areas; prioritizing neighbor cells measurement or scanning based on proximity to the UE (102) using approximate cell originating location and approximate range coverage information, and real time network requirements of the UE (102) including network type requirements based on available Terrestrial Network (TN) or Non-Terrestrial Network (NTN) service and RAT selection optimization based on running applications on the UE (102); and utilizing a predictive location module (210) to obtain neighboring cell information for areas where the UE (102) moves based on user movement patterns.

6. The wireless communication system (100) as claimed in claim 5, wherein the RAT selection optimization is based on application requirements of running applications on the UE (102) toavoid selection of higher RAT or lower RAT based on application needs include at least one of: high bandwidth applications requiring enhanced data throughput; latency-sensitive applications requiring low-latency communication; real-time applications requiring continuous low latency connectivity; and emergency applications requiring priority network access.

7. The wireless communication system (100) as claimed in claim 5, wherein the database server (204) is at least one of: an internal UE database server where neighboring frequency and RAT information is stored within the UE (102); and an external database server which has collected information from various devices in the field.

8. The wireless communication system (100) as claimed in claim 7, wherein the external database server is configured to connect with different location base stations (222) and provides neighboring cell information in order of frequency bands, signal strength from stronger to weaker signal strength cells based on the UE's (102) current location request.

9. The wireless communication system (100) as claimed in claim 5, wherein the database server (204) is at least one of OEM-specific and operator-specific for particular locations or areas, and provides neighboring cell information, neighboring cells type including Terrestrial Network (TN), and Non-Terrestrial Network (NTN) RAT coverage, signal strength and data traffic mean value status of different geographical locations (224).

10. The wireless communication system (100) as claimed in claim 5, wherein the locationbased measurement or scanning configuration is applied for one or more RATs, and wherein neighboring cells information is provided with location and coverage range information for at least one specific RAT based on implementation requirements.

11. The wireless communication system (100) as claimed in claim 5, wherein when the UE (102) experiences signal fluctuations or abnormal radio connectivity issues or PLMN search request, the UE (102) is configured to: query the database server (204) for neighboring cells for RAT and frequency bands supported at the current location; utilize the predictive location module (210) to obtain neighboring cell information in advance; and initiate service acquisition or reacquisition based on location-centric bands and RAT supported set in priority when abnormal radio connectivity occurs on a serving cell.

12. A method (300) for faster service acquisition in a wireless communication system, the method comprising: determining (302), by a user equipment (UE) having multiple radio frequency (RF) chains and multiple mobile subscriber identity modules (MSIM), for parallel scanning capability when service acquisition or reacquisition is required due to initial acquisition, out of service, PLMN search scenarios or radio link failure scenarios; prioritizing (304) frequency band scanning based on at least one of: location -based RAT prioritization and frequency bands prioritization, RF chains capability, RF distribution optimization, and neighboring cell information with location and area coverage data; performing (306) parallel frequency band scanning using multiple RF chains to scan different frequency bands on same or different RAT simultaneously; camping (316) on first available service found through the parallel frequency band or RAT scanning while continuing parallel scanning for better RAT and better cell options if first available service camped is not optimal for UE; and moving (320) to optimal RAT, frequency bands, and cell for service once a better option is identified.

13. The method (300) as claimed in claim 12, comprising performing parallel frequency band scanning using multiple MSIM modules by:grouping (308) frequency bands based on RF chains capability available to the UE; planning (310) different RAT scanning on different MSIM modules simultaneously; distributing (312) different frequency band groups across different available free RF chains of available MSIM modules; and utilizing (314) available free RF chains for service acquisition based on RF design and RF capability of the UE.

14. The method (400) as claimed in claim 12, comprising performing parallel frequency band scanning using a database server by: querying (402) a database server containing real-time frequency and band deployment information for various locations; receiving (404) location-based frequency bands deployment information including neighboring location bands and RAT deployment from the database server for the current UE location; downloading (406) real-time frequency bands deployment information for current location area and neighboring areas; utilizing (408) a predictive location module to obtain neighboring cell information for areas where the UE may move based on user movement patterns and user schedule calendar; and prioritizing (410) neighbor cells measurement or scanning based on proximity to the UE using approximate cell originating location and approximate range coverage information, and real time network requirements including network type requirements such as Terrestrial Network (TN) or Non-Terrestrial Network (NTN) service and RAT selection optimization based on running applications on the UE.

15. The method (400) as claimed in claim 14, wherein the location -based measurement configuration is applied for one or more RATs, and wherein neighboring cells information is provided with location and coverage range information for at least one specific RAT based on implementation requirements.

16. The method (400) as claimed in claim 14, comprising: when experiencing signal fluctuations or abnormal radio connectivity issues below threshold signal connectivity, querying the database server for neighboring cells for RAT and frequency bands supported at the current location; utilizing the predictive location module to obtain neighboring cell information in advance; and initiating service acquisition or reacquisition based on location-centric bands and RAT supported set when abnormal radio connectivity occurs on a serving cell.

17. The method (300) as claimed in claim 12, wherein the faster service acquisition is controlled by a user interface, and the method comprises optimizing Public Land Mobile Network (PLMN) search and saving the UE power by avoiding unnecessary scanning of RAT s or frequency bands not deployed in an area, wherein the RATs include at least one of: Terrestrial Network (TN) or Non-Terrestrial Network (NTN) of 4G, 5G and 6G RATs.

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