System and apparatus for initializing an algorithm and a method in association thereto

Abstract

System (100), apparatus (102) and a method (300) for initializing an algorithm are disclosed. The method (300) includes an input step (302) which comprises receiving at least one input signal associated with a first signal threshold value, a second signal threshold value and a timer value, the first signal threshold value greater than the second signal threshold value; and a processing step (304) which comprises at least one of: determining whether a current signal value is less than the first signal threshold value; initiating a timer based on the timer value if the current signal value is less than the first signal threshold value; determining whether the current signal value is more than the second signal threshold value upon an expiration of the timer; wherein the algorithm is initialized if the current signal value is greater than the second signal threshold value and a handover procedure is initialized if the current signal value is less than the second signal threshold value.

Description

SYSTEM AND APPARATUS FOR INITIALIZING AN ALGORITHM AND A METHOD IN ASSOCIATION THERETOField Of Invention

[0001] The present disclosure generally relates to one or both of a system and an apparatus for initializing an algorithm in association with, for example, a User Equipment (UE) usable for communication. The present disclosure further relates a method which can be associated with the system and / or the apparatus.Background of Invention

[0002] Generally, energy efficiency and power saving would be helpful in communication networks, for example, a 3rd Generation Partnership Project (3GPP) 5G (fifth generation) New Radio (NR) standard-based telecommunications network.

[0003] Current techniques in determining a handover by a base station from a User Equipment (UE) in a communication network may face problems such as service disruption, delay in the handover and even failure in the handover. Thus, the current techniques may not facilitate efficiency and power saving in an optimal manner.

[0004] The present disclosure contemplates that it would be helpful to address or at least mitigate one or more issues in relation to conventional techniques for facilitating energy efficiency and power saving.Summary 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 which comprises receiving at least one input signal associated with a first signal threshold value, a second signal threshold value and a timer value, wherein the first signal threshold value is greater than the second signal threshold value; and a processing step which comprises at least one of: determining whether a current signal value is less than thefirst signal threshold value; initiating a timer based on the timer value if the current signal value is less than the first signal threshold value; determining whether the current signal value is more than the second signal threshold value upon an expiration of the timer; wherein the algorithm is initialized if the current signal value is greater than the second signal threshold value and a handover procedure is initialized if the current signal value is less than the second signal threshold value.

[0006] Advantageously, the method as described herein having signal thresholds and a timer can prevent service disruption, delay and handover failure.

[0007] In an embodiment, the algorithm is an Artificial Intelligence / Machine Learning (AIML) algorithm.

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

[0009] In an embodiment, the handover procedure is initialized if the current signal value is less than the second signal threshold value.

[0010] In an embodiment, the current signal value, the first signal threshold value and the second signal threshold value correspond to at least one value associable with Reference Signal Received Power (RSRP) and Reference Signal Received Quality (RSRQ).

[0011] In an embodiment, the processing step further comprises monitoring a plurality of signal values if the current signal value is more than the first signal threshold value.

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

[0013] In an embodiment, the at least one base station corresponds to at least one Next Generation Node B (gNB).

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

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

[0016] In an embodiment, there is provided a computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out at least one of the input step and the processing step according to the method of the first aspect.

[0017] In an embodiment, there is provided a computer readable storage medium having data stored therein representing software executable by a computer, the software including instructions, when executed by the computer, to carry out at least one of the input step and the processing step according to the method of the first aspect.

[0018] In an embodiment, there is provided an apparatus for initializing an algorithm comprising: a first module configured to receive at least one input signal associated with a first signal threshold value, a second signal threshold value and a timer value,the first signal threshold value greater than the second signal threshold value; a second module configured to at least one of process and facilitate 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 if the current signal value is greater than the second signal threshold value and initializing a handover procedure if the current signal value is less than the second signal threshold value.

[0019] In an embodiment, the apparatus corresponds to a User Equipment (UE) communicable 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 an embodiment, there is provided a system comprising: at least one apparatus(es); and at least one device(s), wherein the apparatus(es) and the device(s) are capable of being coupled via at least one of wired coupling and wireless coupling.

[0021] Advantageously, the system as disclosed herein can have energy savings at the UE and timely initiation of the transfer of the UE to reduce handover delays.Brief Description of the Drawings

[0022] Embodiments of the disclosure are described hereinafter with reference to the following drawings, in which:

[0023] Fig. 1A shows a schematic diagram illustrating a system for initializing an algorithm which can include at least one apparatus, according to an embodiment of the invention.

[0024] Fig. 1 B to Fig. 1 D show example scenarios in association with the system of Fig. 1A, according to an embodiment of the invention.

[0025] Fig. 2 shows a schematic diagram illustrating the apparatus of Fig. 1A in further detail, according to an embodiment of the invention.

[0026] Fig. 3 shows a method in association with the system of Fig. 1A, according to an embodiment of the invention.

[0027] Fig. 4A and Fig. 4B show schematic diagrams illustrating the flow of information in association with the method of Fig. 3, according to an embodiment of the invention.Detailed Description

[0028] Some portions of the description which follows are explicitly or implicitly presented in terms of algorithms and functional or symbolic representations of operations on data within a computer memory. These algorithmic descriptions and functional or symbolic representations are the means used by those skilled in the data processing arts to convey most effectively the substance of their work to others skilled in the art. An algorithm is here, and generally, conceived to be a self- consistent sequence of steps leading to a desired result. The steps are those requiring physical manipulations of physical quantities, such as electrical, magnetic or optical signals capable of being stored, transferred, combined, compared, and otherwise manipulated.

[0029] The present specification also discloses apparatus for performing the operations of the methods. Such apparatus may be specially constructed for the required purposes, or may comprise a computer or other device selectively activated or reconfigured by a computer program stored in the computer. The algorithms and displays presented herein are not inherently related to any particular computer or other apparatus. Various machines may be used with programs in accordance with the teachings herein. Alternatively, the construction of more specialized apparatus toperform the required method steps may be appropriate. The structure of a computer will appear from the description below.

[0030] In addition, the present specification also implicitly discloses a computer program, in that it would be apparent to the person skilled in the art that the individual steps of the method described herein may be put into effect by computer code. The computer program is not intended to be limited to any particular programming language and implementation thereof. It will be appreciated that a variety of programming languages and coding thereof may be used to implement the teachings of the disclosure contained herein. Moreover, the computer program is not intended to be limited to any particular control flow. There are many other variants of the computer program, which can use different control flows without departing from the spirit or scope of the disclosure.

[0031] 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 interfacing with a computer. The computer readable medium may also include a hard-wired medium such as exemplified in the Internet system, or wireless medium such as exemplified in the mobile telephone system. The computer program when loaded and executed on such a computer effectively results in an apparatus that implements the steps of the preferred method.

[0032] The present disclosure generally contemplates the facilitation and optimization of a network (for example in association with 3GPP based standard / specification etc.) and / or user equipment (UE) efficiency and mobility (for example energy efficiency or power saving), in accordance with an embodiment of the invention. Specifically, the present disclosure contemplates the possibility of initializing Artificial Intelligence and Machine Learning (AIML or AI / ML) of a UE in connection with 3GPP Release 19 (and beyond) standard(s).

[0033] In communication networks, methods or mechanisms are used to define on how to execute a handover (HO). These can include network (NW) triggered HO, lower layer triggered mobility (LTM) HO and Conditional HO (CHO). Executing a good handover is important as it may allow the UE to stay connected within the network and information can be properly transferred from one base station to another base station. 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 methods focus on quick recovery of the UE to the network.

[0034] The present disclosure generally contemplates that such handover mechanisms and failure handling methods can be reactive by design. For example, inaccurate rapid response measurements (RRM) and inaccurate UE location can impair good handover decisions. Moreover, there may be other issues such as radio link failure (RLF), beam failure and handover failure (HOF) due to the mobility of the UE. The complexity, measurement effort, and signaling overhead may also be high and may be unable to eliminate the interruption or bad services caused by a failure event.

[0035] The present disclosure contemplates that Artificial Intelligence I Machine Learning (AI / ML or AIML) can be an important technology in network optimization which can lead to energy-efficient networks. In particular, the application of AIML (or AI / ML) in communication links (e.g. Air Interface) can result in handover optimization by using AIML (or AI / ML) algorithms. If AIML is not executed at a particular time instant, the UE may experience delays in handover. As a result, there may be issues such as service disruption and delay as well as handover failure.

[0036] The present disclosure contemplates the possibility of how AIML (or AI / ML) algorithms can be incorporated in standard network systems, signaling aspects and trigger mechanisms. More specifically, the signaling aspect and the trigger mechanism to execute the AI / ML model can be important in light of having energy efficiency of the UE.

[0037] The present disclosure also contemplates it may be possible to have, for example, AI / ML aided mobility with handover optimization at the network side or UE side. This can include, for example, candidate cell(s) or target cell(s) prediction in a Layer 3(L3)-based mobility as well as candidate or target beam(s) and cell(s) prediction in LTM such as Radio layer 2 and Radio layer 3 Radio Resource Control (RAN2) and UTRAN / E-UTRAN / NG-RAN architecture and related network interfaces (RAN3).

[0038] A base station, for example a Next Generation Node B (gNB), may determine a HO based on UE measurement and prepares for the HO. In the case where the UE is mobile, there can be a delay between UE measurement of the reference signal and the time the actual handover happens. The UE can predict best target cell and other handover parameters related to handover with the use of AIML (or AI / ML). The present disclosure contemplates the possibility of how a UE should optimize the timer of AIML, i.e. when to execute AIML, so that the UE energy consumption is optimized.

[0039] In the above manner, power saving and energy consumption efficiency can possibly be facilitated in the UE or the network, in accordance with an embodiment of the invention.

[0040] The foregoing will be discussed in further detail with reference to Fig. 1 to Fig. 4 hereinafter.

[0041] Referring to Fig. 1A, a schematic diagram illustrating a system 100 for initializing an algorithm is shown, according to an embodiment of the invention. The system 100 can, for example, be suitable for facilitating energy / power efficiency, in accordance with an embodiment of the invention.

[0042] As shown, the system 100 can include one or more apparatuses 102, at least one device 104 and, optionally, a communication network 106, in accordance with an embodiment of the invention.

[0043] The apparatus(es) 102 can be coupled to the device(s) 104. Specifically, the apparatus(es) 102 can, for example, be coupled to the device(s) 104 via the communication network 106, in accordance with an embodiment of the invention.

[0044] In one embodiment, the apparatus(es) 102 can be coupled to the communication network 106 and the device(s) 104 can be coupled to the communication network 106. Coupling can be by manner of one or both of wired coupling and wireless coupling. The apparatus(es) 102 can, in general, be configured to communicate with the device(s) 104 via the communication network 106, according to an embodiment of the invention.

[0045] The apparatus(es) 102 can, for example, be associated with or correspond to or include one or more user equipment (UE) which can carry one or more computers, in accordance with an embodiment of the invention. For example, an apparatus 102 can correspond to a UE carrying at least one computer (e.g. an electronic device or module having computing capabilities such as an electronic mobile device which can be carried into a vehicle or an electronic module which can be installed in a vehicle, in accordance with an embodiment of the invention) which can be configured to perform one or more processing tasks in association with adaptive / dynamic / gradual control, in accordance with an embodiment of the invention.

[0046] In an embodiment, the apparatus(es) 102 can, 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 to generate one or more output signals. The input signal(s) can, for example, be communicated from the device(s) 104 and received by the apparatus(es) 102, in accordance with an embodiment of the invention. The input signal can be associated with a first signal threshold value, a second signal threshold value and a timer value, where the first signal threshold value is greater than the second signal threshold value. As a possible option, the output signal(s) can, forexample, be communicated from the apparatus(es) 102, in accordance with 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 apparatus(es) 102 will be discussed later in further detail with reference to Fig. 2, according to an embodiment of the invention.

[0047] The device(s) 104 can, for example, be associated with / correspond to at least one base station, where the at least one base station can be a Next Generation Node B (gNB). Moreover, the device(s) 104 can, for example, be configured to carry / be associated with / include one or more computers (e.g., an electronic device / module having computing capabilities) which can, for example, be configured to perform one or more processing tasks in association with the base station. The device(s) 104 can be configured to generate one or more input signals which can be communicated to the apparatus(es) 102, in accordance with an embodiment of the invention. This will be discussed later in further detail in the context of an example scenario, in accordance with an embodiment of the invention.

[0048] The communication network 106 can, for example, correspond to an Internet communication network, a cellular-based communication network, a wired-based communication network, a Global Navigation Satellite System (GNSS) based communication network, a wireless-based communication network, or any combination thereof. Communication (e.g., between the apparatuses 102 and / or between the apparatus(es) 102 and the device(s) 104) via the communication network 106 can be by manner of one or both of wired communication and wireless communication.

[0049] As mentioned, the apparatus(es) 102 can, for example, be configured to receive at least one input signal and perform at least one processing task in association with dynamic / adaptive / gradual control on the input signal(s) in a manner so as to generate at least one output signal. Moreover, the device(s) 104 can, for example, be configured to generate (and communicate) the input signal(s) to the apparatus(es) 102, in accordance with an embodiment of the invention. Accordingly, the device(s) 104 can pre-determine the first signal threshold value, the secondsignal threshold value and the timer value and also communicate the first signal threshold value, the second signal threshold value and the timer value to the apparatus(es) 102. This will be discussed, in accordance with an embodiment of the invention, in the context of an example scenario with reference to Fig. 1 B to Fig. 1 D, hereinafter.

[0050] Fig. 1 B to Fig. 1 D show example scenarios in association with the system of Fig. 1A, according to an embodiment of the invention. Specifically, Fig. 1 B to Fig. 1 D show different examples of handover optimization through AIML initialization in the system of Fig. 1A. Fig. 1 B shows an example by training at only one side of the system, either at the device(s) 104 I base station (or network-side, e.g. gNB) or the apparatus(es) 102 (or UE-side). As shown in the figure, a training entity may be provided to each of the device(s) 104 and the apparatus(es) 102. The training entity for each of the device(s) 104 and apparatus(es) 102 can 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 apparatus(es) 102 (UE-side).

[0051] In an alternate embodiment, Fig. 1 C shows an example by joint training to both sides of the system, at the device(s) 104 I base station (or network-side, e.g. gNB) and the apparatus(es) 102 (or UE-side). In this embodiment, training entities may be provided to each of the device(s) 104 (network-side) and the apparatus(es) 102 (UE-side). Each of the training entities can include a respective module (not shown) configured to implement a respective neural network for handover such that the respective neural networks can determine the handover by both the device(s) 104 (network-side) and the apparatus(es) 102 (UE-side). Specifically, the neural network of the network-side (or network-side neural network) is trained and configured to determine handover by the device(s) 104 while the neural network of the UE-side (or UE-side neural network) is trained and configured to determine handover by the apparatus(es) 102. Furthermore, the network-side neural network may perform a backward gradient technique to the apparatus(es) 102 (UE-side) and the UE-side neural network may perform a forward activation technique to thedevice(s) 104 (network-side) to determine and optimize handover by the device(s) 104 and the apparatus(es) 102.

[0052] In another embodiment, Fig. 1 D shows an example by separate training to both sides of the system, at the device(s) 104 I base station (or network-side, e.g. gNB) and the apparatus(es) 102 (or UE-side). In this embodiment, training entities may be provided to each of the device(s) 104 (network-side) and the apparatus(es) 102 (UE-side). Each of the training entities can include a respective module (not shown) configured to implement a respective neural network for handover such that the respective neural networks can be used to determine the handover by both the device(s) 104 (network-side) and the apparatus(es) 102 (UE-side). Specifically, the neural network of the UE-side (or UE-side neural network) may be trained using a first training data set and configured to determine handover by the apparatus(es) 102. Subsequently, the UE-side neural network shares the training data set with the neural network of the network-side (or network-side neural network), which is then trained and configured to determine handover by the device(s) 104. It can be appreciated that the order of training can be opposite, i.e. , the network-side neural network is trained first using a training dataset followed by the UE-side neural network after the network-side neural network shares the training dataset to the UE- side neural network.

[0053] The neural network as described in the present disclosure can be an Artificial Intelligence (Al)-based neural network model such as support vector machines, decision trees, ensemble models, k-nearest neighbours models or Bayesian networks. It can be appreciated that the neural network can also be a multi-modal neural network and may contain other types of models including linear models and / or non-linear models as well as feed-forward neural networks, convolutional neural networks (CNN) or recurrent neural networks (RNN). It can also be appreciated that other types of neural network training may be available and not limited to the examples described herein.

[0054] The above-described aspect(s) of the system 100 of the present invention can also apply analogously (all) the aspect(s) of a below described apparatus 102 of thepresent invention. Likewise, all below described aspect(s) of the apparatus 102 of the invention can also apply analogously (all) the aspect(s) of above-described system 100 of the invention.

[0055] The aforementioned apparatus(es) 102 or User Equipment (UE) will be discussed in further detail with reference to Fig. 2 hereinafter.

[0056] Referring to Fig. 2, a schematic diagram illustrating an apparatus 102 is shown in further detail in the context of an example implementation 200, according to an embodiment of the invention.

[0057] In the example implementation 200, the apparatus 102 can correspond to an electronic module 200a. The electronic module 200a can, in one example, correspond to a mobile device which can, for example, be carried into the vehicle by a user, in accordance with an embodiment of the invention. In another example, the electronic module 200a can correspond to an electronic device which can be installed / mounted in the vehicle, in accordance with an embodiment of the invention. In this regard, the electronic module 200a can be considered to be carried by the vehicle (e.g., either carried into the vehicle by a user or installed / mounted in the vehicle).

[0058] It is contemplated that the electronic module 200a can be capable of performing one or more processing tasks in association with adaptive / dynamic / gradual control related processing, in accordance with an embodiment of the invention.

[0059] The electronic module 200a can, for example, include a casing 200b. Moreover, the electronic module 200a can, for example, carry any one of a first module 202, a second module 204, a third module 206, or any combination thereof.

[0060] In one embodiment, the electronic module 200a can carry a first module 202, a second module 204 and / or a third module 206. In a specific example, theelectronic module 200a can carry a first module 202, a second module 204 and a third module 206, in accordance with an embodiment of the invention.

[0061] In this regard, it is appreciable that, in one embodiment, the casing 200b can be shaped and dimensioned to carry any one of the first module 202, the second module 204 and the third module 206, or any combination thereof.

[0062] The first module 202 can be coupled to one or both of the second module 204 and the third module 206. The second module 204 can be coupled to one or both of the first module 202 and the third module 206. The third module 206 can be coupled to one or both of the first module 202 and the second module 204. In one example, the first module 202 can be coupled to the second module 204 and the second module 204 can be coupled to the third module 206, in accordance with an embodiment of the invention. Coupling between the first module 202, the second module 204 and / or the third module 206 can, for example, be by manner of one or both of wired coupling and wireless coupling. Each of the first module 202, the second module 204 and the third module 206 can correspond to one or both of a hardware-based module and a software-based module, according to an embodiment of the invention.

[0063] In one example, the first module 202 can correspond to a hardware-based receiver which can be configured to receive one or more input signals. The input signal(s) can, for example, be communicated from the device(s) 104 (or base station e.g., a gNB), in accordance with an embodiment of the invention.

[0064] The second module 204 can, for example, correspond to a hardware-based processor which can be configured to perform one or more processing tasks (e.g., in a manner so as to generate one or more output signals) as will be discussed later in further detail with reference to Fig. 3, in accordance with an embodiment of the invention.

[0065] The third module 206 can correspond to a hardware-based transmitter which can be configured to communicate one or more output signals from the electronicmodule 200a. The output signal(s) can, for example, include one or more instructions / commands / control signals in association with the aforementioned dynamic / adaptive / gradual control configuration / determination strategy so as to facilitate efficiency (e.g., power / energy efficiency and / or communication efficiency), in accordance with an embodiment of the invention. For example, the output signal(s) can be a control signal(s) to initialize an algorithm for handover.

[0066] The present disclosure contemplates the possibility that the first and second modules 202, 204 can be an integrated software-hardware based module, for example, an electronic part which can carry a software program or algorithm in association with receiving and processing functions or an electronic module programmed to perform the functions of receiving and processing. The present disclosure further contemplates the possibility that the first and third modules 202, 206 can be an integrated software-hardware based module, for example an electronic part which can carry a software program or algorithm in association with receiving and transmitting functions or an electronic module programmed to perform the functions of receiving and transmitting. The present disclosure yet further contemplates the possibility that the first and third modules 202, 206 can be an integrated hardware module, for example a hardware-based transceiver, capable of performing the functions of receiving and transmitting.

[0067] The UE can, for example, be further configured to process the input signal(s), as will be discussed later in further detail with reference to Fig. 3, in a manner so as to generate one or more output signals in a manner so as to facilitate efficiency, for example power efficiency or energy efficiency, in accordance with an embodiment of the invention. In one specific example, the output signal(s) can include one or more control signals to facilitate some form of dynamic / adaptive / gradual control configuration / determination strategy so as to facilitate efficiency, for example power efficiency or energy efficiency, in accordance with an embodiment of the invention. For example, the output signal(s) can be a control signal(s) to initialize an algorithm for handover.

[0068] The above-described aspect(s) of the apparatus 102 of the present invention can also apply analogously (all) the aspect(s) of a below described processing / communication method of the present invention. Likewise, all below described aspect(s) of the method of the invention can also apply analogously (all) the aspect(s) of above described apparatus 102 of the invention. It is to be appreciated that these remarks apply analogously to the earlier discussed system 100 of the present disclosure.

[0069] Referring to Fig. 3, a method 300 (or a communication method) for initializing an algorithm, for example an Artificial Intelligence / Machine Learning (AIML or AI / ML) algorithm, in association with the system 100 is shown, according to an embodiment of the invention.

[0070] The method 300 can, for example, be suitable for facilitating energy efficiency, network optimization and power saving in accordance with an embodiment of the invention.

[0071] The method 300 can include any one of an input step 302, a processing step 304 and an output step 306, or any combination thereof, in accordance with an embodiment of the invention.

[0072] In an embodiment, the processing method 300 can include the input step 302. In another embodiment, the processing method 300 can include the input step 302 and the processing step 304. In another embodiment, the processing method 300 can include the input step 302, the processing step 304 and the output step 306. In yet another embodiment, the processing method 300 can include the processing step 304 and one or both of the input step 302 and the output step 306. In yet a further embodiment, the processing method 300 can include the input step 302, the processing step 304 and the output step 306. In yet a further additional embodiment, the processing method 300 can include the processing step 304. In yet another further additional embodiment, the processing method 300 can include any one of or any combination of the input step 302, the processing step 304 and the output step 306 (i.e. , the input step 302, the processing step 304 and / or the output step 306).

[0073] With regard to the input step 302, one or more input signal(s) can be received. For example, the input signal(s) can be communicated from the device(s) 104 and can be received by an apparatus 102, in accordance with an embodiment of the invention.

[0074] The input step 302 can include receiving at least one input signal associated with a first signal threshold value, a second signal threshold value and a timer value. The first signal threshold value may be greater than the second signal threshold value and at least one of the first signal threshold value and the second signal threshold value is associable with a conditional handover threshold value. The first signal threshold value and the second signal threshold value may correspond to at least one value associable with Reference Signal Received Power (RSRP) and Reference Signal Received Quality (RSRQ). The first signal threshold value, the second signal threshold value and the timer value may be pre-determined 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) which may communicate the first signal threshold value, the second signal threshold value and the timer value to the apparatus 102 (or UE). The first signal threshold value, the second signal threshold value and the timer value may be received by the UE from the gNB via at least one of System Information Block (SIB) or UE specific message (e.g., Radio Resource Control (RRC) reconfiguration).

[0075] With regard to the processing step 304, at least a processing task can be performed in association with the received input signal(s) in a manner so as to generate one or more output signals, in accordance with an embodiment of the invention.

[0076] The processing step 304 may include at least one of: determining whether a current signal value is less than the first signal threshold value; initiating a timer based on the timer value if the current signal value is less than the first signal threshold value; determining whether the current signal value is more than thesecond signal threshold value upon an expiration of the timer, such that the algorithm is initialized if the current signal value is greater than the second signal threshold value and a handover procedure is initialized if the current signal value is less than the second signal threshold value. The current signal value may correspond to at least one value associable with Reference Signal Received Power (RSRP) and Reference Signal Received Quality (RSRQ).

[0077] The processing step 304 may further include determining whether the current signal value is less than the second signal threshold value, and the timer is stopped if the current signal value is less than the second signal threshold value. Subsequently, the handover procedure is initialized if the current signal value is less than the second signal threshold value. In an example embodiment, the handover may be initiated to a candidate target cell (or a further base station) without executing the AIML algorithm. The processing step 304 may also include monitoring a plurality of signal values if the current signal value is more than the first signal threshold value.

[0078] With regards to the output step 306, the output signal(s) can, for example, be communicated, as an option, in accordance with an embodiment of the invention. For example, the output signal(s) can optionally be communicated from the apparatus 102. In a more specific example, the output signal(s) can optionally be communicated from the apparatus 102 to one or both of at least one device 104 and another apparatus 102, in accordance with an embodiment of the invention. In an embodiment, the apparatus 102 (or UE) may also perform the input step 302, the processing step 304 and the output step 306.

[0079] The present disclosure further contemplates a computer program (not shown) which can include instructions which, when the program is executed by a computer (not shown), cause the computer to carry out the input step 302, the processing step 304 and / or the output step 306 as discussed with reference to the method 300. For example, the computer program can include instructions which, when the program isexecuted by a computer, cause the computer to carry out the input step 302 and / or the processing step 304, in accordance with an embodiment of the invention.

[0080] The present disclosure yet further contemplates a computer readable storage medium (not shown) having data stored therein representing software executable by a computer (not shown), the software including instructions, when executed by the computer, to carry out the input step 302, the processing step 304 and / or the output step 306 as discussed with reference to the method 300. For example, the computer readable storage medium can have data stored therein representing software executable by a computer, the software including instructions, when executed by the computer, cause the computer to carry out the input step 302 and / or the processing step 304, in accordance with an embodiment of the invention.

[0081] Further in view of the foregoing, it is appreciable that the present disclosure generally contemplates an apparatus 102 which can include a first module 202, a second module 204 and / or a third module 206.

[0082] The first module 202 can be configured to receive one or more input signals. The input signal(s) can, for example, be associated a first signal threshold value, a second signal threshold value and a timer value, where the first signal threshold value is greater than the second signal threshold value.

[0083] The second module 204 can be configured to process and / or facilitate processing of the input signal(s) according to the method 300 as discussed earlier to generate one or more output signals.

[0084] The third module 206 can be configured to communicate one or more output signals. The output signal(s) can, for example, correspond to one or more control signals for initializing the algorithm if the current signal value is greater than the second signal threshold value and initializing a handover procedure if the current signal value is less than the second signal threshold value.

[0085] In one embodiment, the apparatus 102 can correspond to a User Equipment (UE) which can communicate with a device 104 corresponding to a base station. The base station can, for example, correspond to a Next generation Node B (gNB) which can be configured to communicate one or more signals (e.g., input signal(s)) to the UE.

[0086] Yet further in view of the foregoing, it is appreciable that the present disclosure generally contemplates a system 100 which can include one or more apparatuses 102 and one or more devices 104. The apparatus(es) 102 and the device(s) 104 can, for example, be capable of being coupled via wired coupling and / or wireless coupling.

[0087] It should be appreciated that the embodiments described above can be combined in any manner as appropriate (e.g., one or more embodiments as discussed in the “Detailed Description” section can be combined with one or more embodiments as described in the “Summary of the Invention” section).

[0088] It should be further appreciated by the person skilled in the art that variations and combinations of embodiments described above, not being alternatives or substitutes, may be combined to form yet further embodiments.

[0089] In one example, the possibility of the output signal(s) being communicated from the apparatus(es) 102 was discussed. It is appreciable that the output signal(s) need not necessarily be communicated from the apparatus(es) 102. Specifically, the possibility that the output signal(s) need not necessarily be communicated outside of the apparatus(es) 102 is contemplated, in accordance with an embodiment of the invention. More specifically, the output signal(s) can, for example, correspond to internal command(s) / instruction(s) (e.g., communicated only within an apparatus 102) for adaptively controlling operational configuration of an apparatus 102, in accordance with an embodiment of the invention.

[0090] In another example, application(s) of the present disclosure in association with / in the context of low power wake up radio and / or ambient loT (Internet of Things) type device(s) can be possible, in accordance with an embodiment of the invention.

[0091] Fig. 4A and Fig. 4B show schematic diagrams illustrating the flow of information in association with the method of Fig. 3, according to an embodiment of the invention.

[0092] In the example context as shown in Fig. 4A, a gNB (or base station) can, for example, be configured to generate / define / (pre)configure / set two or more RSRP / RSRQ signal threshold values defining a RSRP / RSRQ region and / or communicate one or more input signals which can correspond to or be associated with or include the generated / defined / (pre)configured / set RSRP / RSRQ threshold range(s), in accordance with an embodiment of the invention. Moreover, the gNB (or base station) can, for example, be configured to perform or determine one or more processing tasks in association with at least one timer value, in accordance with an embodiment of the invention. Appreciably, the input signal(s) communicable from the gNB (or base station) can, for example, further include or be indicative of the timer value(s), in accordance with an embodiment of the invention.

[0093] In the example context as shown in Fig. 4B, a User Equipment (UE) can be configured to receive one or more input signal(s) communicable from the gNB (or base station) at step 1. The UE can, for example, be further configured to process the input signal(s). The input signal can include or associated with a first signal threshold value, a second signal threshold value and a timer value, where the first signal threshold value is greater than the second signal threshold value. At step 2, the UE can, for example, be configured to evaluate (e.g., detect or measure) a current RSRP / RSRQ signal value and determine if the current RSRP / RSRQ signal value is less than the received first signal threshold value. A timer is initiated or activated based on the received timer value if the current RSRP / RSRQ signal value is less than the received first signal threshold value at step 3. On the other hand, ifthe UE determines that the current RSRP / RSRQ signal value is not less than the received first signal threshold value, the UE continues to evaluate or monitor signal values at step 4.

[0094] At step 5, the UE evaluates if the timer has expired. If the UE evaluates that the timer has expired, the UE further determines whether the current RSRP / RSRQ signal value is more than the received second signal threshold value at step 6. If the UE evaluates that the timer has not expired, the UE further determines whether the current RSRP / RSRQ signal value is less than the received second signal threshold value at step 7.

[0095] At step 8, if the UE determines the current RSRP / RSRQ signal value is more than the received second signal threshold value (step 6), the UE initializes the AI / ML algorithm to predict handover. On the other hand, the UE initializes a handover procedure at step 9 if the UE determines the current RSRP / RSRQ signal value is not more than the second signal threshold value (step 6). In an alternate embodiment, if the UE determines the current RSRP / RSRQ signal value is less than the received second signal threshold value at step 7, the UE may stop the timer and initialize the handover procedure of step 9. If the UE determines the current RSRP / RSRQ signal value is not less than the received second signal threshold value at step 7, the UE continues to evaluate if the timer has expired at step 5.

[0096] In the foregoing manner, various embodiments of the disclosure are described for addressing at least one of the foregoing disadvantages. Such embodiments are intended to be encompassed by the following claims and are not to be limited to specific forms or arrangements of parts so described and it will be apparent to one skilled in the art in view of this disclosure that numerous changes and / or modification can be made, which are also intended to be encompassed by the following claims.

Claims

Claim(s)1 . A method (300) for initializing an algorithm, the method comprising: an input step (302) which comprises receiving at least one input signal associated with a first signal threshold value, a second signal threshold value and a timer value, wherein the first signal threshold value is greater than the second signal threshold value; and a processing step (304) which comprises at least one of: determining whether a current signal value is less than the first signal threshold value; initiating a timer based on the timer value if the current signal value is less than the first signal threshold value; determining whether the current signal value is more than the second signal threshold value upon an expiration of the timer; wherein the algorithm is initialized if the current signal value is greater than the second signal threshold value and a handover procedure is initialized if the current signal value is less than the second signal threshold value.

2. The method (300) according to claim 1 , wherein the algorithm is an Artificial Intelligence / Machine Learning (AIML) algorithm.

3. The method (300) according to claim 1 , wherein at least one of the first signal threshold value and the second signal threshold value is associable with a conditional handover threshold value.

4. The method (300) according to claim 1 , wherein the processing step (304) further comprises determining whether the current signal value is less than the second signal threshold value, wherein the timer is stopped if the current signal value is less than the second signal threshold value.

5. The method (300) according to claim 4, wherein the handover procedure is initialized if the current signal value is less than the second signal threshold value.

6. The method (300) according to claim 1 , wherein the current signal value, the first signal threshold value and the second signal threshold value correspond to at least one value associable with Reference Signal Received Power (RSRP) and Reference Signal Received Quality (RSRQ).

7. The method (300) according to claim 1 , wherein the processing step (304) further comprises monitoring a plurality of signal values if the current signal value is more than the first signal threshold value.

8. The method (300) according to claim 1 , wherein at least one base station is configured to: pre-determine the first signal threshold value, the second signal threshold value and the timer value; and communicate the first signal threshold value, the second signal threshold value and the timer value.

9. The method (300) according to claim 8, wherein the at least one base station corresponds to at least one Next Generation Node B (gNB).

10. The method (300) according to 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 value, the second signal threshold value and the timer value are communicable from the gNB to the UE.

11. The method (300) according to claim 10, wherein the first signal threshold value, the second signal threshold value and the timer value are received by the UE from the gNB via at least one of: System Information Block (SIB) or UE specific message.

12. A computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out at least one of the input step (302) and the processing step (304) according to the method (300) of any of the preceding claims.

13. A computer readable storage medium having data stored therein representing software executable by a computer, the software including instructions, when executed by the computer, to carry out at least one of the input step (302) and the processing step (304) according to the method (300) of claims 1-11.

14. An apparatus (102) for initializing an algorithm comprising: a first module (202) configured to receive at least one input signal associated with a first signal threshold value, a second signal threshold value and a timer value, the first signal threshold value greater than the second signal threshold value; a second module (204) configured to at least one of process and facilitate the processing step (304) according to the method (300) of claim 1 to claim 11 to generate 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 if the current signal value is greater than the second signal threshold value and initializing a handover procedure if the current signal value is less than the second signal threshold value.

15. The apparatus (102) according to claim 14, wherein the apparatus (102) corresponds to a User Equipment (UE) communicable 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. A system (100) comprising: at least one apparatus (102) according to any of claims 14 and 15; and at least one device (104) according to claim 15, wherein the apparatus (102) and the device (104) are capable of being coupled via at least one of wired coupling and wireless coupling.

Images