System and device for initializing an algorithm and associated method

Abstract

A system (100), a device (102) and a method (300) for initializing an algorithm are disclosed.The method (300) comprises an input step (302) comprising receiving at least one input signal associated with a first signal threshold, a second signal threshold, and a timer value, wherein the first signal threshold is greater than the second signal threshold; and a processing step (304) comprising at least one of the following: determining whether a current signal value is less than the first signal threshold; starting a timer based on the timer value if the current signal value is less than the first signal threshold; determining whether the current signal value is greater than the second signal threshold upon expiration of the timer; wherein the algorithm is initialized if the current signal value is greater than the second signal threshold, and a handover process is initialized if the current signal value is less than the second signal threshold.

Description

Field of the invention

[0001] The present disclosure generally relates to a system and / or device for initializing an algorithm, for example, in connection with a user equipment (UE) usable for communication. The present disclosure further relates to a method that may be associated with the system and / or device. Background of the invention

[0002] In general, energy efficiency and energy saving would be helpful in communication networks, for example a telecommunications network based on the 3rd Generation Partnership Project (3GPP) fifth generation new radio (5G NR) standard.

[0003] Current techniques for determining a handover by a base station from a user equipment (UE) in a communications network can be fraught with problems such as service interruptions, handover delays, and even handover errors. Thus, current techniques cannot provide optimal efficiency or energy savings.

[0004] The present disclosure contemplates that it would be helpful to address or at least mitigate one or more problems associated with conventional techniques in order to improve energy efficiency and energy conservation. Brief description of the invention

[0005] According to a first aspect of the present invention, there is provided a method for initializing an algorithm, the method comprising: an input step comprising receiving at least one input signal associated with a first signal threshold, a second signal threshold, and a timer value, wherein the first signal threshold is greater than the second signal threshold; and a processing step comprising at least one of the following: determining whether a current signal value is less than the first signal threshold; starting a timer based on the timer value if the current signal value is less than the first signal threshold; determining whether the current signal value is greater than the second signal threshold upon expiration of the timer;wherein the algorithm is initialized when the current signal value is greater than the second signal threshold, and a handover process is initialized when the current signal value is less than the second signal threshold;

[0006] Advantageously, the method as described in this document, which has signal thresholds and a timer, can prevent a service interruption, a delay and a handover error.

[0007] In one embodiment, the algorithm is an artificial intelligence / machine learning (AIML) based algorithm.

[0008] In one embodiment, the processing step further comprises determining whether the current signal value is less than the second signal threshold, wherein the timer is stopped when the current signal value is less than the second signal threshold.

[0009] In one embodiment, the handover process is initialized when the current signal value is less than the second signal threshold.

[0010] In one embodiment, the instantaneous signal value, the first signal threshold value, and the second signal threshold value correspond to at least one value attributable to the received power of the reference signal (RSRP - Reference Signal Received Power) and the received quality of the reference signal (RSRQ - Reference Signal Received Quality).

[0011] In one embodiment, the processing step further comprises monitoring a plurality of signal values ​​when the current signal value is greater than the first signal threshold.

[0012] In one embodiment, at least one base station is configured to: specify the first signal threshold, the second signal threshold, and the timer value; and communicate the first signal threshold, the second signal threshold, and the timer value.

[0013] In one embodiment, the at least one base station corresponds to at least one next generation node B (gNB).

[0014] In one embodiment, a user equipment (UE) is configured to perform the input step and the processing step, and wherein the first signal threshold, the second signal threshold, and the timer value are communicable from the gNB to the UE.

[0015] In one embodiment, the first signal threshold, the second signal threshold, and the timer value are received by the UE from the gNB via at least one of the following: a System Information Block (SIB) or a UE-specific message.

[0016] In one embodiment, a computer program is provided comprising instructions which, when executed by a computer, cause the computer to perform the input step and / or the processing step according to the method of the first aspect.

[0017] In one embodiment, a computer-readable storage medium is provided having stored therein data representing computer-executable software, the software including instructions which, when executed by the computer, cause the input step and / or the processing step to be performed according to the method of the first aspect.

[0018] In one embodiment, a device for initializing an algorithm is provided, comprising: a first module configured to receive at least one input signal associated with a first signal threshold, a second signal threshold, and a timer value, wherein the first signal threshold is greater than the second signal threshold; a second module configured to process and / or enhance the processing step according to the method of the first aspect to generate at least one output signal; and a third module configured to communicate at least one output signal, wherein the output signal corresponds to a control signal for initializing the algorithm when the current signal value is greater than the second signal threshold and for initializing a handover process when the current signal value is less than the second signal threshold.

[0019] In one embodiment, the device corresponds to a user equipment (UE) capable of communication with a device corresponding to a base station, and wherein the base station corresponds to a next generation node B (gNB) configured to communicate the at least one input signal to the UE.

[0020] In one embodiment, a system is provided comprising: at least one device; and at least one apparatus, wherein the device(s) and the apparatus(es) are coupleable via wired coupling and / or wireless coupling.

[0021] Advantageously, the system as disclosed in this document may include energy savings at the UE as well as timely initiation of the UE's transmission to reduce handover delays. Short description of the drawings

[0022] Embodiments of the disclosure are described below with reference to the following drawings, in which: Fig. 1A shows a schematic diagram illustrating a system for initializing an algorithm according to an embodiment of the invention, which may include at least one device. Fig. 1B to Fig. 1D show exemplary scenarios in connection with the system of Fig. 1A according to an embodiment of the invention. Fig. Figure 2 shows a schematic diagram illustrating the setup of Fig. 1A according to an embodiment of the invention. Fig. 3 shows a method in connection with the system of Fig. 1A according to an embodiment of the invention. Fig. 4A and Fig. 4B show schematic diagrams illustrating the information flow associated with the process of Fig. 3 according to an embodiment of the invention. Detailed description

[0023] Some sections of the following description are presented explicitly or implicitly in terms of algorithms and functional or symbolic descriptions of operations on data in a computer memory. These algorithmic descriptions and functional or symbolic representations are the means used by those skilled in the data processing field to most effectively convey the nature of their work to others skilled in the art. An algorithm is understood here and generally as a self-consistent sequence of steps leading to a desired result. The steps are those that require physical manipulations of physical quantities, such as electrical, magnetic, or optical signals, that are storable, transferable, combinable, comparable, and otherwise manipulatable.

[0024] This specification also discloses devices for performing the operations of the methods. Such devices may be specially constructed for the required purposes, or they may comprise a computer or other device that can be selectively activated or reconfigured by a computer program stored in the computer. The algorithms and representations presented in this specification are not tied to any specific computer or other device. Various machines with programs in accordance with the teachings of this specification may be used. Alternatively, the construction of more specialized devices for performing the required method steps may be indicated. The structure of a computer is apparent from the description below.

[0025] Furthermore, the present description also implicitly discloses a computer program, so that it will be apparent to those skilled in the art that the individual steps of the method described in this document can be implemented by computer code. The computer program is not intended to be limited to a specific programming language and its implementation. It is understood that a variety of programming languages ​​and their coding can be used to implement the teachings of the disclosure contained in this document. Furthermore, the computer program is not intended to be limited to a specific control flow. There are many other variations of the computer program that can use different control flows without departing from the spirit or scope of the disclosure.

[0026] Furthermore, one or more of the steps of the computer program may be performed in parallel rather than sequentially. Such a computer program may be stored on any computer-readable medium. The computer-readable medium may include storage devices such as magnetic or optical disks, memory chips, or other storage devices suitable for interoperating with a computer. The computer-readable medium may also comprise a hardwired medium, exemplified by the Internet system, or a wireless medium, exemplified by the mobile telephone system. The computer program, when loaded and executed on such a computer, provides a device implementing the steps of the preferred method.

[0027] According to one embodiment of the invention, the present disclosure generally contemplates the improvement and optimization of a network (e.g., in connection with 3GPP-based standards / specifications, etc.) and / or the efficiency and mobility (e.g., energy efficiency or energy saving) of user equipment (UE). In particular, the present disclosure contemplates the possibility of initiating artificial intelligence and machine learning (AIML or AI / ML) of a UE in connection with the 3GPP Release 19 standard(s) (and beyond).

[0028] In communication networks, procedures or mechanisms are used to define how a handover (HO) should be performed. These can include a network-triggered HO, a lower layer-triggered mobility (LTM), and a conditional HO (CHO). Performing a good handover is important because it can allow the UE to remain connected in the network and information to be properly transmitted from one base station to another. Handover decisions can be made based on historical measurements, rapid response measurements (RRM), and / or UE location. In the event of a failure during a handover, the UE may not be connected to the network, and thus, failure handling procedures focus on quickly reconnecting the UE to the network.

[0029] The present disclosure generally contemplates that such handover mechanisms and error handling methods may be response-based by design. For example, inaccurate rapid response measurements (RRM) and inaccurate UE location may impair good handover decisions. Furthermore, other problems may be present, such as radio link failure (RLF), beam dropout, and handover failure (HOF) due to UE mobility. The complexity, measurement overhead, and signaling overhead may also be high and may not be able to resolve the disruption or inadequate service caused by a fault event.

[0030] The present disclosure contemplates that artificial intelligence / machine learning (AI / ML or AIML) can be an important technology in network optimization, leading to energy-efficient networks. In particular, applying AIML (or AI / ML) to communication links (e.g., an air interface) by using AIML (or AI / ML) algorithms can lead to handover optimization. If AIML is not executed at a specific time, the UE may experience delays during handover. As a result, problems such as service interruption and delay, as well as handover failure, may occur.

[0031] This disclosure considers the possibility of integrating AIML (or AI / ML) algorithms into standard network systems, signaling aspects, and triggering mechanisms. Specifically, the signaling aspect and the triggering mechanism for executing the AI / ML model may be important in light of maintaining UE energy efficiency.

[0032] The present disclosure also contemplates that it may be possible, for example, to have AI / ML-assisted mobility with handover optimization on the network side or on the UE side. This may include, for example, a prediction of candidate cell(s) or target cell(s) in Layer 3 (L3)-based mobility, as well as a prediction of candidate or target beam(s) and cell(s) in LTM, such as the Radio Layer 2 and Radio Layer 3 Radio Resource Control (RAN2) and a UTRAN / E-UTRAN / NG-RAN architecture and related network interfaces (RAN3).

[0033] A base station, such as a next-generation Node B (gNB), may determine an HO based on a UE measurement and prepares for the HO. If the UE is mobile, a delay may occur between the UE measurement of the reference signal and the time at which the actual handover occurs. The UE may predict the best destination cell and other handover-related parameters when using AIML (or AL / ML). The present disclosure considers how a UE should optimize the timer for AIML, i.e., when AIML should be executed, so that the UE's power consumption is optimized.

[0034] In the above manner, according to an embodiment of the invention, energy saving and energy consumption efficiency at the UE or in the network may be improved.

[0035] The above is explained below with reference to Fig. 1 to Fig. 4 is explained in more detail.

[0036] Referring to Fig. 1A, a schematic diagram illustrating a system 100 for initializing an algorithm according to one embodiment of the invention is shown. System 100 may, for example, be adapted to improve energy / power efficiency according to one embodiment of the invention.

[0037] As shown, the system 100 according to an embodiment of the invention may include one or more devices 102, at least one apparatus 104, and optionally a communications network 106.

[0038] The device(s) 102 may be coupled to the device(s) 104. In particular, according to one embodiment of the invention, the device(s) 102 may be coupled to the device(s) 104, for example, via the communications network 106.

[0039] In one embodiment, the device(s) 102 may be coupled to the communications network 106, and the apparatus(es) 104 may be coupled to the communications network 106. The coupling may be via a wired coupling and / or a wireless coupling. The device(s) 102 may be generally configured to communicate with the apparatus(es) 104 via the communications network 106, according to one embodiment of the invention.

[0040] For example, according to one embodiment of the invention, the device(s) 102 may be associated with, correspond to, or include one or more user equipment (UEs) that may carry one or more computers. According to one embodiment of the invention, a device 102 may, for example, correspond to a UE carrying at least one computer (e.g., an electronic device or module with computing capabilities, such as a mobile electronic device that may be carried in a vehicle or an electronic module that may be installed in a vehicle, according to one embodiment of the invention) that may be configured to perform one or more processing tasks associated with adaptive / dynamic / stage-by-stage control.

[0041] In one embodiment, the device(s) 102 may, for example, be configured to receive one or more input signals and perform at least one processing task based on the input signal(s) in a manner that generates one or more output signals. The input signal(s) may, for example, be communicated by the device(s) 104 and received by the device(s) 102 according to an embodiment of the invention. The input signal may be associated with a first signal threshold, a second signal threshold, and a timer value, wherein the first signal threshold is greater than the second signal threshold. As a possible option, the output signal(s) may, for example, be communicated by the device(s) 102 according to an embodiment of the invention.The output signal may correspond to a control signal for initializing an algorithm, for example, an AI / ML algorithm. The device(s) 102 according to an embodiment of the invention will be described later with reference to FIG. Fig. 2 is discussed in more detail.

[0042] The device(s) 104 may, for example, be associated with / correspond to at least one base station, wherein the at least one base station may be a Next Generation Node B (gNB). Furthermore, the device(s) 104 may, for example, be configured to carry / be associated with / contain one or more computers (e.g., an electronic device / module with computing capabilities), which may, for example, be configured to perform one or more processing tasks in conjunction with the base station. The device(s) 104 may, according to an embodiment of the invention, be configured to generate one or more input signals that may be communicated to the device(s) 102. This will be discussed in more detail later in the context of an exemplary scenario according to an embodiment of the invention.

[0043] The communication network 106 may, for example, correspond to an internet communication network, a cellular-based communication network, a wired communication network, a global navigation satellite system (GNSS)-based communication network, a wireless communication network, or any combination thereof. Communication (e.g., between the devices 102 and / or between the device(s) 102 and the device(s) 104) via the communication network 106 may be via wired communication and / or wireless communication.

[0044] As mentioned, the device(s) 102 may, for example, be configured to receive at least one input signal and to perform at least one processing task in connection with dynamic / adaptive / stepwise control on the input signal(s) in such a way that at least one output signal is generated. Furthermore, according to one embodiment of the invention, the device(s) 104 may, for example, be configured to generate (and communicate) the input signal(s) to the device(s) 102. Accordingly, the device(s) 104 may specify the first signal threshold, the second signal threshold, and the timer value and also communicate the first signal threshold, the second signal threshold, and the timer value to the device(s) 102. This will be described below according to one embodiment of the invention in the context of an exemplary scenario with reference to Fig. 1B to Fig. 1D discussed.

[0045] Fig. 1B to Fig. 1D show exemplary scenarios related to the system of Fig. 1A according to an embodiment of the invention. Specifically, Fig. 1B to Fig. 1D various examples of handover optimization by AIML initialization in the system of Fig. 1A. Fig. 1B shows an example with training only on one side of the system: either at the device(s) 104 / base station (or network-side, e.g., gNB) or at the device(s) 102 (or UE-side). As shown in the figure, a training entity may be provided at each of the device(s) 104 and the device(s) 102. The training entity for each of the device(s) 104 and the device(s) 102 may include a module (not shown) configured to implement a respective neural network for handover optimization, such that the neural network determines the handover solely by the device(s) 104 (network-side) or solely by the device(s) 102 (UE-side).

[0046] In an alternative embodiment, Fig. 1C shows an example with joint training on both sides of the system: at the device(s) 104 / base station (or network-side, e.g., gNB) or the device(s) 102 (or UE-side). In this embodiment, training entities may be provided at each of the device(s) 104 (network-side) and the device(s) 102 (UE-side). Each of the training entities may include a respective module (not shown) configured to implement a respective handover neural network, such that the respective neural networks may determine the handover by both the device(s) 104 (network-side) and the device(s) 102 (UE-side).In particular, the network-side neural network (or network-side neural network) is trained and configured to determine a handover by the device(s) 104, while the UE-side neural network (or UE-side neural network) is trained and configured to determine a handover by the device(s) 102. Furthermore, the network-side neural network may perform a backward pass (backward gradient technique) on the device(s) 102 (UE-side), and the UE-side neural network may perform a forward pass (forward activation technique) on the device(s) 104 (network-side) to determine and optimize a handover by the device(s) 104 and the device(s) 102.

[0047] In another embodiment, Fig. 1D shows an example with separate training on both sides of the system: at the device(s) 104 / base station (or network-side, e.g., gNB) and at the device(s) 102 (or UE-side). In this embodiment, training entities may be provided at each of the device(s) 104 (network-side) and the device(s) 102 (UE-side). Each of the training entities may include a respective module (not shown) configured to implement a respective handover neural network, such that the respective neural networks may be used to determine the handover by both the device(s) 104 (network-side) and the device(s) 102 (UE-side). In particular, the UE-side neural network (or the UE-side neural network) may be trained using a first training data set and configured to determine a handover by the device(s) 102.The UE-side neural network then shares the training data set with the network-side neural network (or the network-side neural network), which is then trained and configured to determine a handover by the device(s) 104. It should be understood that the order of training may be reversed, i.e., the network-side neural network is trained first using a training data set, followed by the UE-side neural network after the network-side neural network has shared the training data set with the UE-side neural network.

[0048] The neural network as described in the present disclosure may be an artificial intelligence (AI)-based neural network model, such as support vector machines, decision trees, ensemble models, k-nearest neighbor models, or Bayesian networks. It is understood that the neural network may also be a multimodal neural network and may include other types of models, including linear models and / or nonlinear models, as well as feedforward neural networks, convolutional neural networks (CNNs), or recurrent neural networks (RNNs). It is also understood that other types of neural network training may be available, which are not limited to the examples described herein.

[0049] The above-described aspect(s) of the system 100 of the present invention may also apply analogously to the (all) aspect(s) of a device 102 of the present invention described below. Likewise, the (all) aspect(s) of the device 102 of the invention described below may also apply analogously to the (all) aspect(s) of the system 100 of the invention described above.

[0050] The said device(s) 102 or the user equipment (UE) will be referred to below with reference to Fig. 2 is discussed in more detail.

[0051] Referring to Fig. 2, a schematic diagram illustrating a device 102 is shown in more detail in the context of an exemplary implementation 200 according to an embodiment of the invention.

[0052] In the exemplary implementation 200, the device 102 may correspond to an electronic module 200a. In one example, the electronic module 200a may correspond to a mobile device, for example, that may be brought into the vehicle by a user, according to an embodiment of the invention. In another example, the electronic module 200a may correspond to an electronic device that may be installed / mounted in the vehicle, according to an embodiment of the invention. In this context, the electronic module 200a may be considered to be carried by the vehicle (e.g., either brought into the vehicle by a user or installed / mounted in the vehicle).

[0053] It is contemplated that the electronic module 200a according to an embodiment of the invention may be capable of performing one or more processing tasks associated with adaptive / dynamic / stage-by-stage control-related processing.

[0054] The electronic module 200a may, for example, include a housing 200b. Furthermore, the electronic module 200a may, for example, support a first module 202, a second module 204, a third module 206, or any combination thereof.

[0055] In one embodiment, the electronic module 200a may support a first module 202, a second module 204, and / or a third module 206. In a specific example, the electronic module 200a may support a first module 202, a second module 204, and a third module 206 according to an embodiment of the invention.

[0056] In this regard, it will be appreciated that in one embodiment, the housing 200b may be shaped and sized to support the first module 202, the second module 204, the third module 206, or any combination thereof.

[0057] The first module 202 may be coupled to the second module 204 and / or the third module 206. The second module 204 may be coupled to the first module 202 and / or the third module 206. The third module 206 may be coupled to the first module 202 and / or the second module 204. In one example, according to an embodiment of the invention, the first module 202 may be coupled to the second module 204, and the second module 204 may be coupled to the third module 206. The coupling between the first module 202, the second module 204, and / or the third module 206 may, for example, be via wired coupling and / or wireless coupling. The first module 202, the second module 204, and the third module 206 may correspond to a hardware-based module and / or a software-based module according to an embodiment of the invention.

[0058] In one example, the first module 202 may correspond to a hardware-based receiver that may be configured to receive one or more input signals. The input signal(s) may be communicated, for example, by the device(s) 104 (or a base station, e.g., gNB) according to one embodiment of the invention.

[0059] The second module 204 may, for example, correspond to a hardware-based processor that may be configured to perform one or more processing tasks (e.g., in a manner that generates one or more output signals), as described later with reference to Fig. 3 is discussed in more detail, according to an embodiment of the invention.

[0060] The third module 206 may correspond to a hardware-based transmitter that may be configured to communicate one or more output signals from the electronic module 200a. The output signal(s) may, for example, include one or more instructions / commands / control signals associated with the aforementioned dynamic / adaptive / stage-by-stage control configuration / determination strategy to improve efficiency (e.g., power / energy efficiency and / or communication efficiency) according to one embodiment of the invention. For example, the output signal(s) may be control signals for initializing a handover algorithm.

[0061] The present disclosure contemplates the possibility that the first and second modules 202, 204 may be an integrated software / hardware-based module, for example, an electronic part carrying a software program or algorithm associated with receiving and processing functions, or an electronic module programmed to perform the receiving and processing functions. The present disclosure further contemplates the possibility that the first and third modules 202, 206 may be an integrated software / hardware-based module, for example, an electronic part carrying a software program or algorithm associated with receiving and transmitting functions, or an electronic module programmed to perform the receiving and transmitting functions.The present disclosure further contemplates the possibility that the first and third modules 202, 206 may be an integrated hardware module, such as a hardware-based transceiver, capable of performing the functions of receiving and transmitting.

[0062] For example, according to an embodiment of the invention, the UE may be further configured to process the input signal(s) in a manner as described later with reference to Fig. 3, one or more output signals are generated in a manner to improve efficiency, such as power efficiency or energy efficiency. In a specific example according to an embodiment of the invention, the output signal(s) may include one or more control signals to improve some type of dynamic / adaptive / stage-by-stage control configuration / determination strategy such that efficiency, such as power efficiency or energy efficiency, is improved. For example, the output signal(s) may be a control signal for initializing a handoff algorithm.

[0063] The above-described aspect(s) of the device 102 of the present invention may also apply analogously to the (all) aspect(s) of a processing / communication method of the present invention described below. Likewise, the (all) aspect(s) of the method of the invention described below may also apply analogously to the (all) aspect(s) of the device 102 of the invention described above. It should be appreciated that these statements apply analogously to the previously discussed system 100 of the present disclosure.

[0064] Referring to Fig. 3, a method 300 (or a communication method) for initializing an algorithm, such as an artificial intelligence / machine learning (AIML or AI / ML) based algorithm, is shown in connection with the system 100, according to one embodiment of the invention.

[0065] According to one embodiment of the invention, the method 300 may, for example, be suitable for improving energy efficiency, network optimization and energy savings.

[0066] The method 300 may include an input step 302, a processing step 304, or an output step 306, or any combination thereof, according to one embodiment of the invention.

[0067] In one embodiment, processing method 300 may include input step 302. In another embodiment, processing method 300 may include input step 302 and processing step 304. In another embodiment, processing method 300 may include input step 302, processing step 304, and output step 306. In yet another embodiment, processing method 300 may include processing step 304 and / or input step 302 and / or output step 306. In yet another embodiment, processing method 300 may include input step 302, processing step 304, and output step 306. In yet another additional embodiment, processing method 300 may include processing step 304.In yet another further additional embodiment, the processing method 300 may include the input step 302, the processing step 304, or the output step 306, or any combination thereof (ie, the input step 302, the processing step 304, and / or the output step 306).

[0068] With respect to input step 302, one or more input signals may be received. For example, according to one embodiment of the invention, the input signal(s) may be communicated by device(s) 104 and received by device 102.

[0069] The input step 302 may include receiving at least one input signal associated with a first input signal threshold, a second signal threshold, and a timer value. The first signal threshold may be greater than the second signal threshold, and the first signal threshold and / or the second signal threshold may be associated with a conditional handover threshold. The first signal threshold and the second signal threshold may correspond to at least one value associated with the reference signal received power (RSRP) and the reference signal received quality (RSRQ). The first signal threshold, the second signal threshold, and the timer value may be specified by at least one base station (or device 104).The at least one base station may correspond to at least one next-generation Node B (gNB) that may communicate the first signal threshold, the second signal threshold, and the timer value to the device 102 (or the UE). The first signal threshold, the second signal threshold, and the timer value may be received by the UE from the gNB via a system information block (SIB) and / or a UE-specific message (e.g., a radio resource control (RRC) reconfiguration).

[0070] With regard to processing step 304, according to an embodiment of the invention, at least one processing task may be performed in connection with the received input signal(s) in a manner that generates one or more output signals.

[0071] Processing step 304 may include at least one of the following: determining whether a current signal value is less than the first signal threshold; starting a timer based on the timer value if the current signal value is less than the first signal threshold; determining whether the current signal value is greater than the second signal threshold upon expiration of the timer, such that the algorithm is initialized if the current signal value is greater than the second signal threshold, and a handover process is initialized if the current signal value is less than the second signal threshold. The current signal value may correspond to at least one value attributable to the reference signal received power (RSRP) and the reference signal received quality (RSRQ).

[0072] Processing step 304 may further include determining whether the current signal value is less than the second signal threshold, and stopping the timer if the current signal value is less than the second signal threshold. Subsequently, the handover process is initiated if the current signal value is less than the second signal threshold. In an exemplary embodiment, the handover to a candidate target cell (or another base station) may be initiated without executing the AIML algorithm. Processing step 304 may also include monitoring a plurality of signal values ​​if the current signal value is greater than the first signal threshold.

[0073] With regard to output step 306, the output signal(s) may, for example, be optionally communicated according to one embodiment of the invention. For example, the output signal(s) may optionally be communicated by device 102. In a more specific example, the output signal(s) may, according to one embodiment of the invention, be optionally communicated by device 102 to at least one device 104 and / or to another device 102. In one embodiment, device 102 (or the UE) may also perform input step 302, processing step 304, and output step 306.

[0074] The present disclosure further contemplates a computer program (not shown) that may include instructions that, when executed by a computer (not shown), cause the computer to perform input step 302, processing step 304, and / or output step 306, as discussed with reference to method 300. For example, according to one embodiment of the invention, the computer program may include instructions that, when executed by a computer, cause the computer to perform input step 302 and / or processing step 304.

[0075] The present disclosure further contemplates a computer-readable storage medium (not shown) having stored therein data representing software executable by a computer (not shown), the software including instructions that, when executed by the computer, cause the performance of input step 302, processing step 304, and / or output step 306, as discussed with reference to method 300. For example, according to one embodiment of the invention, the computer-readable storage medium may have stored therein data representing computer-executable software, the software including instructions that, when executed by the computer, cause the computer to perform input step 302 and / or processing step 304.

[0076] Further, in view of the foregoing, it is understood that the present disclosure generally contemplates a device 102 that may include a first module 202, a second module 204, and / or a third module 206.

[0077] The first module 202 may be configured to receive one or more input signals. The input signal(s) may be associated with a first signal threshold, a second signal threshold, and a timer value, wherein the first signal threshold is greater than the second signal threshold.

[0078] The second module 204 may be configured to process and / or enhance the processing of the input signal(s) according to the method 300, as discussed above, to generate one or more output signals.

[0079] The third module 206 may be configured to communicate one or more output signals. The output signal(s) may, for example, correspond to one or more control signals for initializing the algorithm when the current signal value is greater than the second signal threshold and for initiating a handover process when the current signal value is less than the second signal threshold.

[0080] In one embodiment, device 102 may correspond to a user equipment (UE) that can communicate with a device 104 that corresponds to a base station. The base station may, for example, correspond to a next-generation node B (gNB), which may be configured to communicate one or more signals (e.g., an input signal(s)) to the UE.

[0081] Furthermore, in light of the foregoing, it should be understood that the present disclosure generally contemplates a system 100 that may include one or more devices 102 and one or more apparatuses 104. The device(s) 102 and the apparatus(es) 104 may be coupled, for example, via a wired coupling and / or a wireless coupling.

[0082] It should be appreciated that the embodiments described above may be combined in any manner (e.g., one or more embodiments as discussed in the "Detailed Description" section may be combined with one or more embodiments as described in the "Summary of the Invention").

[0083] Furthermore, those skilled in the art should recognize that variations and combinations of embodiments described above that are not alternatives or replacements can be combined to form still further embodiments.

[0084] In one example, the possibility that the output signal(s) is / are communicated by the device(s) 102 was discussed. It should be appreciated that the output signal(s) do not necessarily have to be communicated by the device(s) 102. In particular, according to one embodiment of the invention, the possibility is contemplated that the output signal(s) do not necessarily have to be communicated outside of the device(s) 102. More specifically, according to one embodiment of the invention, the output signal(s) may, for example, correspond to an internal command(s) / instruction(s) (e.g., communicated only within a device 102) for adaptively controlling the operating configuration of a device 102.

[0085] In another example according to an embodiment of the invention, application(s) of the present disclosure may be possible in connection with / in the context of a low-power wake-up radio and / or ambient IoT (Internet of Things) device(s).

[0086] Fig. 4A and Fig. 4B show schematic diagrams illustrating the information flow associated with the process of Fig. 3 according to an embodiment of the invention.

[0087] In the exemplary context as in Fig. For example, as shown in Figure 4A, according to one embodiment of the invention, a gNB (or a base station) may be configured to generate / define / pre-configure / set two or more RSRP / RSRQ signal thresholds defining an RSRP / RSRQ range, and / or communicate one or more input signals that may correspond to, be associated with, or include the generated / defined / pre-configured / set RSRP / RSRQ threshold range(s). Furthermore, according to one embodiment of the invention, the gNB (or the base station) may be configured to perform or determine one or more processing tasks associated with at least one timer value.It is understood that according to an embodiment of the invention, the input signal(s) communicable by the gNB (or the base station) may further include or indicate, for example, the timer value(s).

[0088] In the exemplary context as in Fig.4B, a user equipment (UE) may be configured to receive, at step 1, one or more input signals communicable from the gNB (or the base station). The UE may, for example, be further configured to process the input signals. The input signal may include or be associated with a first signal threshold, a second signal threshold, and a timer value, wherein the first signal threshold is greater than the second signal threshold. At step 2, the UE may, for example, be configured to evaluate (e.g., detect or measure) a current RSRP / RSRQ signal value and determine whether the current RSRP / RSRQ signal value is less than the received first signal threshold.In step 3, if the current RSRP / RSRQ signal value is less than the received first signal threshold, a timer is started or activated based on the received timer value. However, if the UE determines that the current RSRP / RSRQ signal value is not less than the received first signal threshold, the UE proceeds to evaluate or monitor signal values ​​in step 4.

[0089] In step 5, the UE evaluates whether the timer has expired. If the UE evaluates that the timer has expired, the UE further determines in step 6 whether the current RSRP / RSRQ signal value is greater than the received second signal threshold. If the UE evaluates that the timer has not expired, the UE further determines in step 7 whether the current RSRP / RSRQ signal value is less than the received second signal threshold.

[0090] If the UE determines that the current RSRP / RSRQ signal value is greater than the received second signal threshold (step 6), the UE initializes the AI / ML algorithm to predict handover at step 8. On the other hand, if the UE determines that the current RSRP / RSRQ signal value is not greater than the second signal threshold (step 6), the UE initiates a handover process at step 9. In an alternative embodiment, if the UE determines at step 7 that the current RSRP / RSRQ signal value is less than the received second signal threshold, the UE may stop the timer and initiate the handover process of step 9. If the UE determines at step 7 that the current RSRP / RSRQ signal value is not less than the received second signal threshold, the UE proceeds to evaluate whether the timer has expired at step 5.

[0091] In the foregoing, various embodiments of the disclosure have been described to overcome at least one of the aforementioned disadvantages. These embodiments are intended to be encompassed by the following claims and are not limited to the specific forms or arrangements of parts so described, and it will be apparent to those skilled in the art, in light of this disclosure, that numerous changes and / or modifications may be made, which are also intended to be encompassed by the following claims.

Claims

[1] A method (300) for initializing an algorithm, the method comprising: an input step (302) comprising receiving at least one input signal associated with a first signal threshold, a second signal threshold, and a timer value, wherein the first signal threshold is greater than the second signal threshold; and a processing step (304) comprising at least one of the following: Determining whether a current signal value is less than the first signal threshold; Starting a timer based on the timer value when the current signal value is less than the first signal threshold; Determining, upon expiration of the timer, whether the current signal value is greater than the second signal threshold; wherein the algorithm is initialized when the current signal value is greater than the second signal threshold, and a handover process is initialized when the current signal value is less than the second signal threshold. [2] The method (300) of claim 1, wherein the algorithm is an artificial intelligence / machine learning (AIML) based algorithm. [3] The method (300) of claim 1, wherein the first signal threshold and / or the second signal threshold is assignable to a conditional handover threshold. [4] The method (300) of claim 1, wherein the processing step (304) further comprises determining whether the current signal value is less than the second signal threshold, wherein the timer is stopped when the current signal value is less than the second signal threshold. [5] The method (300) of claim 4, wherein the handover process is initialized when the current signal value is less than the second signal threshold. [6] The method (300) of claim 1, wherein the instantaneous signal value, the first signal threshold value, and the second signal threshold value correspond to at least one value attributable to the reception power of the reference signal (RSRP - Reference Signal Received Power) and the reception quality of the reference signal (RSRQ - Reference Signal Received Quality). [7] The method (300) of claim 1, wherein the processing step (304) further comprises monitoring a plurality of signal values ​​when the current signal value is greater than the first signal threshold. [8] The method (300) of claim 1, wherein at least one base station is configured to: Specifying the first signal threshold, the second signal threshold and the timer value; and Communicating the first signal threshold, the second signal threshold, and the timer value. [9] The method (300) of claim 8, wherein the at least one base station corresponds to at least one next generation node B (gNB). [10] The method (300) of claim 9, wherein a user equipment (UE) is configured to perform the input step (302) and the processing step (304), and wherein the first signal threshold, the second signal threshold, and the timer value are communicable from the gNB to the UE. [11] The method (300) of claim 10, wherein the first signal threshold, the second signal threshold, and the timer value are received by the UE from the gNB via at least one of: a system information block (SIB) or a UE-specific message. [12] A computer program comprising instructions which, when executed by a computer, cause the computer to perform the input step (302) and / or the processing step (304) according to the method (300) of any preceding claim. [13] A computer-readable storage medium having stored therein data representing computer-executable software, the software including instructions which, when executed by the computer, cause the input step (302) and / or the processing step (304) to be performed according to the method (300) of any one of claims 1-11. [14] Device (102) for initializing an algorithm, comprising: a first module (202) configured to receive at least one input signal associated with a first signal threshold, a second signal threshold, and a timer value, wherein the first signal threshold is greater than the second signal threshold; a second module (204) configured to perform the processing step (304) according to the method (300) of claim 1 to claim 11 to generate, process and / or enhance at least one output signal; and a third module (206) configured to communicate at least one output signal, wherein the output signal corresponds to a control signal for initializing the algorithm when the current signal value is greater than the second signal threshold and for initializing a handover process when the current signal value is less than the second signal threshold. [15] Device (102) according to claim 14, wherein the device (102) corresponds to a user equipment (UE) capable of communicating with a device (104) corresponding to a base station, and wherein the base station corresponds to a next generation node B (gNB) configured to communicate the at least one input signal to the UE. [16] System (100), comprising: at least one device (102) according to one of claims 14 and 15; and at least one device (104) according to claim 15, wherein the device (102) and the apparatus (104) can be coupled via a wired coupling and / or a wireless coupling.

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