Method and system for managing multiple bandwidth portions in wireless communication system

Abstract

A method performed by a base station is provided. The method includes, for a first time window in a corresponding BWP among the plurality of BWPs, identifying at least one of a plurality of BWP level metrics and a plurality of user equipment (UE) level metrics for each of the plurality of BWPs. The method includes determining a BWP allocation policy based on the identified at least one of the plurality of BWP level metrics and the plurality of UE level metrics. The method includes allocating each of the plurality of UEs to each of the BWPs based on the determined BWP allocation policy for a second time window subsequent to the first time window.

Description

Technical Field

[0001] This disclosure relates to wireless communication systems. More specifically, this disclosure relates to systems and methods for managing multiple bandwidth components (BWPs) in a wireless communication system. Background Technology

[0002] Since the deployment of fourth-generation (4G) networks, the demand for wireless data services has increased with advancements in wireless technology and communication systems. Efforts have been underway to develop fifth-generation (5G) networks to meet this demand.

[0003] 5G networks have become the next generation of cellular networks, offering higher data speeds, lower latency, and increased capacity compared to previous generations. To further enhance the capabilities of 5G, the 3rd Generation Partnership Project (3GPP) proposed extending the New Radio (NR) to the 5 and 6 GHz bands in NR-unlicensed (NR-U) spectrum and to millimeter wave (mmWave) operation above 60 GHz.

[0004] Energy efficiency is a key performance indicator for 5G and beyond, crucial for supporting various use cases such as enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable and low-latency communications (URLLC). Furthermore, battery life plays a vital role in user experience, and enhancing user equipment (UE) performance without compromising battery life is a challenging task.

[0005] In Release 15 (e.g., TS 38.300 and TS 38.211), 3GPP introduced the Bandwidth Part (BWP) in NR to meet different UE requirements (e.g., power saving) and different service requirements (e.g., higher / lower data rates, latency sensitivity, service type, etc.) at a more granular level. A BWP is a set of contiguous resource blocks (RBs) within a wider total carrier bandwidth, with specific parameters such as parameter set, subcarrier spacing, RB size width, etc. Summary of the Invention

[0006] Technical solution This summary is provided to present, in a simplified format, the selected concepts further described in the detailed description of the invention. This summary is not intended to identify key or fundamental inventive concepts of the invention, nor is it intended to define the scope of the invention.

[0007] According to one embodiment of the disclosure, a method for managing multiple bandwidth parts (BWPs) in a wireless communication system is disclosed. The method includes calculating, by a base station of the wireless communication system, at least one of a plurality of BWP-level metrics and a plurality of user equipment (UE)-level metrics for each of the plurality of BWPs for a current time window in a corresponding BWP among the plurality of BWPs. The method also includes determining, by the base station, a BWP allocation policy based on the calculated at least one of the plurality of BWP-level metrics and the plurality of UE-level metrics. Thereafter, the method includes allocating, by the base station, each of a plurality of UEs to each of the BWPs based on the determined BWP allocation policy for a time window subsequent to the current time window.

[0008] According to another embodiment of the disclosure, a system for managing multiple bandwidth parts (BWPs) in a wireless communication system is disclosed. The system includes a memory and a processor coupled to the memory. The processor is configured to calculate at least one of a plurality of BWP-level metrics and a plurality of user equipment (UE)-level metrics for each of the plurality of BWPs for a current time window in a corresponding BWP among the plurality of BWPs. The processor is also configured to determine a BWP allocation policy based on the calculated at least one of the plurality of BWP-level metrics and the plurality of UE-level metrics. The processor is further configured to allocate each of a plurality of UEs to each of the BWPs based on the determined BWP allocation policy for a time window subsequent to the current time window.

[0009] In order to further clarify the advantages and features of the present application, a more particular description of the application will be rendered by reference to specific embodiments thereof, which are illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the application and are therefore not to be considered limiting of its scope. The application will be described and explained with additional specificity and detail through the use of the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0010] These and other features, aspects, and advantages of the present application will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings.

[0011] Figure 1 An exemplary bandwidth part (BWP) allocation is shown; Figure 2 An LBT protocol for a shared channel is shown; Figure 3 A multi-path reception of a signal at a g NodeB (gNB) is shown; Figure 4 A time-varying impulse response of a multi-path channel is shown; Figure 5Different BLER performance in each BWP in a New Radio (NR) licensed system is shown; Figure 6 BWP allocation in a wireless communication unlicensed system is shown; Figure 7 An example of a wireless communication system that supports managing multiple bandwidth parts (BWPs) according to embodiments of the disclosure is shown; Figure 8 A method for managing multiple BWPs in a wireless communication system according to embodiments of the disclosure is shown; Figure 9 A timing diagram for managing multiple BWPs in a wireless communication system according to embodiments of the disclosure is shown; Figure 10 An exemplary AI model for managing multiple BWPs in a wireless communication system according to embodiments of the disclosure is shown; Figure 11 An exemplary BWP allocation for a wireless communication licensed system according to embodiments of the disclosure is shown; Figure 12 An exemplary BWP allocation for a wireless communication unlicensed system according to embodiments of the disclosure is shown; Figure 13 A block diagram of a system for managing multiple BWPs in a wireless communication system according to embodiments of the disclosure is shown; Figure 14A And Figure 14B A comparison of BWP allocation in an unlicensed wireless communication system according to embodiments of the disclosure is shown; Figure 15A And Figure 15B A comparison of BWP allocation in a licensed wireless communication according to embodiments of the disclosure is shown.

[0012] Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and that that they can not have been necessarily drawn to scale. For example, flow diagrams set forth in the figures, which illustrate the processes of methods in accordance with the preferred embodiments of the present disclosure, are provided by way of example, and are not limiting. Further, one or more of the components of the devices can have been represented by conventional symbols in the drawings, and the drawings can show only those specific details that are necessary to appreciate the embodiments of the present disclosure and that set the present disclosure apart from other designs. Thus, the drawings can show conventional elements that are common between devices and are often labeled with a common numeral. DETAILED DESCRIPTION

[0013] For the purposes of promoting an understanding of the principles of the present disclosure, reference will now be made to the embodiments illustrated in the drawings, and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the disclosure is intended by the specification of these embodiments, which alteration and further modifications in the illustrated system, and such further applications of the principles of the present disclosure illustrated therein are contemplated by persons skilled in the art to which the present disclosure pertains.

[0014] Those skilled in the art will appreciate that the foregoing General Description and the following Detailed Description are explanatory of the disclosure and are not intended to be limiting thereof.

[0015] Reference throughout this specification to "an aspect", "another aspect" or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Accordingly, appearances of the phrases "in an embodiment", "in another embodiment", and similar language in the specification, throughout the specification, can but do not necessarily all refer to the same embodiment.

[0016] The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but can include other steps not expressly listed or inherent to such process or method. Similarly, one or more systems or subsystems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices or other subsystems or other elements or other structures or other components or additional devices or additional subsystems or additional elements or additional structures or additional components.

[0017] The term “connection” and its derivatives refer to any direct or indirect communication between two or more elements, regardless of whether these elements are physically in contact with each other. The terms “send,” “receive,” and “communicate,” and their derivatives include both direct and indirect communication. The term “or” is an inclusive term, meaning “and / or.” The phrase “associated with” and its derivatives refer to including, being included in, interconnected with, containing, being contained within, connected to or linked to, coupled to or connected to, able to communicate with, cooperate with, interleave, juxtapose, proximate, bound to or bound to, having, possessing the attributes of, having a relationship with, or having a relationship to. The term “controller” refers to any device, system, or part thereof that controls at least one operation. The functionality associated with any particular controller can be centralized or distributed, local or remote. The phrase “at least one of” when used with a list of items means that different combinations of one or more of the listed items can be used, and it is possible that only one item from the list is needed. For example, "at least one of A, B, and C" includes any of the following combinations: A, B, C, A and B, A and C, B and C, and A and B and C, and any variations thereof. As an additional example, the expression "at least one of a, b, or c" can indicate only a, only b, only c, both a and b, both a and c, both b and c, all of a, b, and c, or variations thereof. Similarly, the term "set" means one or more. Therefore, a set of items can be a single item or a collection of two or more items.

[0018] like Figure 1 As shown, the entire carrier 101 is divided into BWP0, BWP1, etc. Each parameter can be set according to the type of service that a BWP can provide to the UE. At a given time, in both the uplink (UL) and downlink (DL), the UE can have / be assigned to an active BWP. NR also supports BWP adaptation, where the UE can switch to / be reassigned to a different BWP upon request. For example, when the UE is already connected and active, the primary method for BWP switching / reassignment is based on downlink control information (DCI) handover. Compared to other handover methods (3GPP TS 38.133), this has low overhead (one time slot handover delay for a 15kHz subcarrier spacing (SCS) and two time slot handover delay for a 30kHz SCS).

[0019] 5G networks have become the next generation of cellular networks, offering higher data speeds, lower latency, and increased capacity compared to previous generations. NR licensed (NR-L) spectrum is reserved only for a given operator and there is no coexistence with any other kind of traffic from other operators / technologies. To enhance 5G capabilities, 3GPP Release 16 proposes to extend NR to shared unlicensed spectrum (NR-U) at 5 GHz and 6 GHz bands and millimeter wave operations above 60 GHz. NR-U is a cost-effective (no license cost) option with many use cases that can greatly improve network performance by increasing data rates, reducing latency, improving quality of service (QoS) for users, increasing coverage, etc. There are challenges compared to the licensed NR scenario because NR-U has to coexist with existing technologies (such as Wi-Fi, LTE-LAA, traffic from other operators, etc.) that also use the same unlicensed channel. The method for accessing shared spectrum based on Long Term Evolution (LTE) License Assisted Access (LAA) (3GPP TR 36.889 (V13.0.0)), whenever NR wants to gain access to the channel for transmission, NR also has to follow a similar Listen-Before-Talk (LBT) protocol. Figure 2 An LBT protocol for shared channels according to the prior art is shown. As shown in Figure 2 The UE performs an initial clear channel assessment (ICCA) (delay time in Figure 2 , which is a fixed period of time for which the channel is sensed. Once the channel is sensed to be clear during ICCA, a backoff counter value c is sampled from the range [0, CW], CW being the contention window size. The UE performs an extended clear channel assessment (ECCA), i.e., senses the channel for c slots, and when the counter reaches 0, starts NR transmission and occupies the channel for a period of time called maximum channel occupancy time (MCOT). This is considered as LBT success.

[0020] If the retransmission / negative acknowledgement (NACK) percentage is above a threshold, the CW is updated to 2 x CW, i.e., the contention window size is doubled, and the steps are repeated. This way of accessing the channel results in scheduling uncertainty and greatly reduces network performance, affecting throughput and latency. This degradation is mainly dependent on the collisions / congestion due to coexistence traffic.

[0021] Therefore, with the introduction of BWPs, a BWP allocation problem occurs in NR-L. For example, in urban environments, there can or can not be a line-of-sight (LOS) propagation path between a UE and a g-NodeB (gNB) in a 5G network. Therefore, the radio waves transmitted from the UE arrive at the gNB after reflection (also known as multipath reception), as Figure 3from different directions have different propagation delays. This multipath reception results in a frequency selective channel. Due to frequency selective fading, certain sub-channels can be in deep fading in orthogonal frequency division multiplexing (OFDM) and the information carried by these sub-carriers is lost. The signal strength can also be reduced due to destructive interference caused by phase offsets. These factors can result in increased block error rate (BLER) in certain BWPs, which directly impacts the performance of the UE in that BWP. Therefore, due to frequency selective fading, the performance of the UE can vary in different BWPs. Furthermore, due to the time varying nature of the multipath channel, the frequency selective performance varies over time, as Figure 4 Therefore, a BWP that gave good performance earlier can give poor performance after a period of time. Therefore, it is difficult and uncertain to predict the BWP that gives the best performance due to the randomness of the environment.

[0022] Furthermore, UE positioning (e.g., cell edge UE) is also an important factor that can cause performance variation in each BWP. Due to environmental factors and UE positioning, a UE can perform better in one BWP compared to other BWPs. Low performance in a BWP can result in higher BLER, which results in packet retransmission. Packet retransmission results in resource wastage and lower spectral utilization. As Figure 5 As shown in FIG. 2, for a time window t w = 1, if UE1 is assumed to be allocated to each of the BWPs simultaneously, the performance of UE1 in BWP2 will be better compared to BWP0 or BWP1 allocation.

[0023] The current system of selecting BWPs for a UE is based on fixed rules, such as power saving, data rate requirement, etc., and does not consider how it can impact the overall system level key performance indicators (KPIs). Optimally allocating a UE to the most suitable BWP can improve KPIs, such as system throughput and latency. However, the impact on the overall system KPIs is not considered in the conventional system.

[0024] Similar to NR licensed spectrum, BWP can also be defined and used in NR-U to get similar BWP benefits as in licensed case. In addition, defining BWP in NR-U can improve the number of NR transmission opportunities in the shared channel, resulting in better network KPIs. Unlike the licensed case, BWP has an important factor that can determine to a large extent the performance that the BWP can serve, i.e., the collision / congestion due to coexisting traffic in the channel of each BWP. However, the existing system for selecting a BWP for a UE is based on fixed rules such as power saving, data rate requirements, etc., and does not take into account how it can affect overall system-level KPIs. Optimally assigning UEs to the most suitable BWP can improve KPIs such as system throughput and latency. However, the impact on overall system KPIs is not considered in traditional systems. For example, as shown in Figure 6 a given BWP can have more congestion, e.g., BWP0. If this is not taken into account and some other rule such as the width of the BWP is used or a random / arbitrary assignment is used, it can result in a UE 601 being assigned to a BWP with a large amount of traffic from other radio access technologies (RATs) (e.g., Wi-Fi node 603). For example, the UE 601 has been assigned to BWP0, which has more congestion than BWP1. This results in very few NR transmission opportunities due to high LBT failures. In another example, if all UEs are assigned to the same given BWP, then each UE can get fewer scheduled opportunities if there are too many UEs in that BWP, increasing their latency. Therefore, various factors need to be considered when deciding BWP assignment, and the prior art does not consider all factors.

[0025] Therefore, solving this complex problem of BWP assignment can help greatly improve NR-U system KPIs and end-user experience. It can also better enable NR-U to utilize BWP for flexible service provisioning, get more NR transmission opportunities, etc. The Wi-Fi problem can be defined as follows: consider a set of UEs that are all served by the same gNB in the NR system. In the licensed case, only gNB and UE traffic can be considered, while in the unlicensed case, the spectrum is shared with other radio access technologies (RATs) such as Wi-Fi nodes. The gNB's spectrum is configured as N BWPs, given by N = {0, 1, 2, (N-1)}. Each BWP can consist of multiple NR-U UEs, and each UE is assigned to a BWP (one BWP per UE for downlink (DL) and uplink (UL), respectively). According to the prior art, the BWP assignment strategy can be considered as i.e., UE u belongs to BWP n at time t, which provides a mapping of the BWP ID to which each UE should be assigned.

[0026] Therefore, in addition to power saving, other factors and congestion caused by coexisting traffic, such as system throughput, delay, UE level traffic parameters, channel conditions, and BWP level parameters, need to be considered in order to decide BWP allocation in a better way.

[0027] Therefore, there is a need to provide techniques for BWP allocation that overcome the above and other related problems.

[0028] The present disclosure provides techniques for managing multiple BWPs in a wireless communication system. Optimal BWP allocation per UE is necessary to better meet varying quality of service (QoS) requirements of all UEs, which helps to provide a better end-user experience. It also becomes more critical in unlicensed scenarios, as there is inherent performance degradation due to the shared nature of the spectrum. Therefore, in embodiments, the present disclosure discloses techniques that adapt to the dynamic environment of UEs in a wireless communication system and provide efficient BWP allocation that maximizes the performance of the system and UEs. The disclosed techniques also ensure proper distribution of available UEs among the available BWPs to maximize spectrum usage. Reference is made to Figures 7 to 15B The disclosed techniques are explained in further detail.

[0029] It should be noted that the wireless communication system has been illustrated for simplicity and clarity as a New Radio (NR) / 5G system Figures 7 to 15B However, the techniques discussed with respect to Figures 7 to 15B are applicable to other wireless communication systems such as beyond 5G, 6G, etc. Therefore, throughout the present disclosure and the accompanying drawings, the terms “unlicensed NR (NR-U) system” and “licensed NR (NR-L) system” have been used interchangeably with “unlicensed wireless communication system” and “licensed wireless communication system”, respectively.

[0030] Figure 7 An example of a wireless communication system that supports managing multiple bandwidth parts (BWPs) is shown in accordance with embodiments of the present disclosure. The wireless communication system 700 can include one or more UEs 701, a core network 703, and base stations 705. In some examples, the wireless communication system 700 can be a New Radio (NR) network, a 5G Ultra network, a 6th Generation (6G) network, etc. In some examples, the wireless communication system 700 can support enhanced broadband communications, ultra-reliable (e.g., mission critical) communications, low latency communications, communications with low-cost and low-complexity devices, or any combination thereof.

[0031] The base stations 705 can be dispersed throughout the geographic region to form the wireless communications system 700 and can be of different forms or have different capabilities. The base stations 705 and the UEs 701 can wirelessly communicate via one or more communication links 707. Each base station 705 can provide communication coverage for one or more cells, and a cell can be an example of a geographic area within which the base station 705 can establish one or more communication links 707 with the UEs 701.

[0032] The UEs 701 can be dispersed throughout the coverage areas of the wireless communications system 700, and each UE 701 can be stationary, moving, or both at different times. The UEs 701 can be examples of different forms of wireless devices, which can be referred to as Internet of Things (IoT) devices, in some examples.

[0033] One or more of the base stations 705 described herein can include or can be referred to as a base transceiver station, a radio base station, an access point, a radio transceiver, a NodeB, an eNodeB (eNB), a next-generation NodeB or giga-NodeB (either of which can be referred to as a gNB), a Home NodeB, or a Home eNodeB, among other examples. The UEs 701 described herein can be able to communicate with various types of base stations 705 and network equipment including macro eNBs or gNBs, small cell eNBs or gNBs, or relay base stations, among other examples, as

[0034] The UEs 701 described herein can include or can be referred to as mobile devices, wireless devices, remote devices, handheld devices, subscriber devices, electronic devices, or some other suitable terminology, where the “device” can also be referred to as a unit, a station, a terminal, or a client, among other examples. The UEs 701 can also include or can be referred to as personal electronic devices such as a cellular phone, a personal digital assistant (PDA), a tablet computer, a laptop computer, or a personal computer, among other examples. In some examples, the UEs 701 can include or be referred to as a wireless local loop (WLL) station, an Internet of Things (IoT) device, an Internet of Everything (IoE) device, or a machine type communications (MTC) device, among other examples, which can be implemented in various objects such as appliances or vehicles, among other examples.

[0035] One or more of the UEs 701 described herein can be capable of communicating with various types of devices, such as other UEs 701, which can sometimes act as relays as well as base stations 705 and network equipment including macro eNBs or gNBs, small cell eNBs or gNBs, or relay base stations, among other examples, as shown in FIG. 1. Figure 7

[0036] Also, it should be noted that although for illustrative purposes, the description herein is in the context of a 5G system, the teachings herein can be applicable to other multi-access technologies and the 5G implementations are only one example. Figure 7 ​Only three UEs 701 and one base station 705 are depicted, but the wireless communication system 700 may include Figure 7 Additional UEs and base stations are not shown in the diagram.

[0037] Figure 8 A method 800 (operation) for managing multiple bandwidth portions (BWPs) in a wireless communication system (e.g., an NR system) according to embodiments of the present disclosure is illustrated. In an embodiment, method 800 may be embedded in base station 705. For example, method 800 may be performed by base station 705. Therefore, in an embodiment, it has been incorporated Figure 7 Explained Figure 8 .

[0038] like Figure 8 As shown, at step 801, method 800 may include: the base station 705 of the NR system 700 calculating at least one of a plurality of BWP-level metrics and a plurality of User Equipment (UE)-level metrics for each of the plurality of BWPs within a current time window of a corresponding BWP among the plurality of BWPs. For example, the base station 705 may perform identification of at least one of the plurality of BWP-level metrics and a plurality of User Equipment (UE)-level metrics for each of the plurality of BWPs within a current time window of a corresponding BWP among the plurality of BWPs. In an embodiment, the NR system 700 may be an NR unlicensed (NR-U) system and may include a plurality of UEs. The plurality of UEs may belong to a plurality of multiple RATs operating in the same unlicensed frequency band of the NR-U system. In another embodiment, the NR system 700 may be an NR licensed (NR-L) system and may include a plurality of UEs belonging to a single RAT operating in the NR-L system. Furthermore, in an embodiment, the current time window may consist of a predefined number (W) of consecutive time slots in the corresponding BWP. For example, as Figure 9 As shown, in BWP0, the current time window can refer to time window 1, i.e., t w =1. Therefore, time window 1 can include consecutive time slots, i.e., 0, 1, 2, ..., W. It should be noted that a predefined number of consecutive time slots can be configured by base station 705. Therefore, the time window index... Indicator time interval Where W is the window size. Furthermore, multiple UEs can exist within each BWP. For example, multiple UEs (such as 4 UEs) can exist in BWP0. Therefore, UE-level metrics can be calculated for each of the 4 UEs.

[0039] In this embodiment, when the NR system is an unlicensed NR (NR-U) system, multiple UE-level metrics may include, but are not limited to, the UE service queue size metric. Head of the queue (HoL) latency metric , incoming packet size metric , outgoing packet size metric , and encoding metric , and UE channel condition metric . In an example embodiment, let us consider the multiple UE level metrics computed for the current time window 1 (such as t w =1) for the corresponding BWP (i.e., BWP0). Then, the base station 705 can compute the multiple UE level metrics for the current time window t w =1. Thus, the UE traffic queue size metric may refer to a metric that includes the average traffic queue size of each of the multiple UEs present in the current time window t w =1. Similarly, the incoming packet size metric may refer to a metric that includes the average size of the incoming packets of each of the multiple UEs present in the current time window t w =1. The outgoing packet size metric may refer to a metric that includes the average size of the outgoing packets of each of the multiple UEs present in the current time window t w =1. The HoL delay metric may refer to a metric that includes the average HoL delay of each of the multiple UEs present in the current time window t w =1. The HoL delay can be defined as the average difference between the time at which the packet is scheduled and the arrival time in the queue. The encoding metric may refer to a metric that includes the encoding scheme of each UE-BWP allocation in the current time window t w =1. For example, in the current time window t w =1, each of the multiple UEs can be allocated to a different BWP. Thus, the allocation information is encoded using a predefined encoding scheme such as one-hot encoding scheme. It should be noted that the base station 705 can use any other encoding scheme to encode the allocation information. Further, the UE channel condition metric represents the average number of bits allowed to be transmitted by the UE using a resource block (RB) in the current time window.

[0040] In another embodiment, when the NR system is a licensed NR (NR-L) system, the multiple UE level metrics can include, but are not limited to, the UE traffic queue size metric , HoL delay metric , incoming packet size metric , outgoing packet size metric , encoding metric , and channel condition metric and a plurality of block error rate (BLER) metrics . UE traffic queue size metrics , HoL delay metrics , incoming packet size metrics , outgoing packet size metrics , encoding metrics and UE channel condition metrics Similar to the metrics of the NR-U system. Therefore, for the sake of brevity of the present disclosure, the explanation of these metrics is not provided again. BLER metrics may refer to metrics that include the BLER of each of the plurality of UEs in the current time window t w = 1.

[0041] In an embodiment, when the NR system is an NR-U system, the plurality of BWP level metrics can include, but are not limited to, a listen-before-talk (LBT) protocol failure rate metric (F n [t]), a BWP size metric (N RB n ), an average contention window size metric (CW n [t w ]), an average in-network channel occupancy metric (M n [t w ]) and a channel condition metric C n [t]. Continuing the above example, the channel condition metric C n [t] represents the average number of bits allowed to be transmitted by each of the plurality of UEs using a resource block (RB) in the current time window t w = 1. Further, the LBT protocol failure rate metric (F n [t]) can refer to metrics that include the average failure rate of the LBT protocol for each of the plurality of UEs present in the current time window t w = 1. Each time the base station 705 attempts LBT in the time window t w = 1, the number of attempts is incremented. Each time a pre-existing traffic is detected during the ICCA or ECCA during the LBT, then the failure count is incremented. Thus, the LBT failure rate can be defined as

[0042] Similarly, the BWP size metric can refer to metrics that include the size of the corresponding BWP for each of the plurality of UEs present in the current time window t w = 1. The average contention window size metric (CW n [t w ]) represents the average of the contention window size during the LBT attempts initiated in the current time window. Further, the average in-network channel occupancy metric (M w [t]) can refer to metrics that include the average number of bits allowed to be transmitted by each of the plurality of UEs using a resource block (RB) in the current time window t n = 1.n [t w ]) represents an average duration of time that the channel is occupied by contention technology traffic during the ECCA when the backoff counter of the NR-U is interrupted during the ECCA in the corresponding BWP.

[0043] In another embodiment, when the NR system is an NR-L system, the plurality of BWP level metrics can include, but are not limited to, a plurality of block error rate (BLER) metrics (E n [t]) in the corresponding BWP and a number of active UEs (A n [t]) in the corresponding BWP. The BLER represents an average value of BLERs obtained across a plurality of UEs in the corresponding BWP.

[0044] It should be noted that each of the UE level and BWP level metrics can be computed by the base station 705 using techniques known to those skilled in the art. In another embodiment, some of the UE level metrics can be computed at the UE 701 and the base station 705 can receive them accordingly from the UE 701.

[0045] Referring back to Figure 8 , at step 803, the method 800 can include determining, by the base station 705, a BWP allocation policy based on at least one of the computed (or identified) plurality of BWP level metrics and the plurality of UE level metrics. In an embodiment, the BWP allocation policy can be determined to optimize a plurality of key performance indicators (KPIs) of the NR system. In an embodiment, the plurality of KPIs can include throughput, HoL latency, UE power, spectral efficiency, packet delay violation, and the like. Thus, in an exemplary embodiment, the BWP allocation policy can be determined to maximize the throughput of the NR system while minimizing the HoL latency. Thereafter, at step 805, the method 800 can include allocating, by the base station 705, each of the plurality of UEs to each of the BWP based on the determined BWP allocation policy for a time window subsequent to a current time window. For example, the current time window can be referred to as a first time window and the time window subsequent to the current time window can be referred to as a second time window. Referring to Figures 10 to 15B The method 800 is further explained.

[0046] In an embodiment, the BWP allocation policy can be determined using an artificial intelligence (AI) model. Figure 10An exemplary AI model for managing multiple BWPs in a wireless communication system, such as an NR system, according to embodiments of the present disclosure is shown. The base station 705 computes an exponentially weighted average of each of the plurality of UE-level metrics and the plurality of BWP-level metrics for the current time window. The AI model 1000 then receives the exponentially weighted average of each of the plurality of UE-level metrics and the plurality of BWP-level metrics from the base station 705. The AI model 1000 then determines a BWP allocation policy 1001 based on the exponentially weighted average of each of the plurality of UE-level metrics, the exponentially weighted average of each of the plurality of BWP-level metrics, and a reward function. In embodiments, the reward function is defined to maximize the throughput of the NR system and minimize the HoL delay. In embodiments, as shown in Figure 10 the AI model 1000 can receive the exponentially weighted average of each of the plurality of UE-level metrics and the plurality of BWP-level metrics at slot W-1 in the current time window t w =1. In particular, the base station 705 computes the exponentially weighted average of each of the plurality of UE-level metrics and the plurality of BWP-level metrics for the current time window t w =1 from slot 0 to W-2. The AI model 1000 then determines the BWP allocation policy for the next time window (i.e., t w =2) at slot W-1. It should be noted that the plurality of UEs will be allocated to the corresponding BWPs according to the determined BWP allocation policy in the next time window t w =2.

[0047] In exemplary embodiments, when the NR system is an NR-L system, the plurality of UE-level metrics includes and and In addition, the plurality of BWP metrics includes and Accordingly, the base station 705 can compute the exponentially weighted value of each of the plurality of UE-level metrics and the plurality of BWP metrics for the current time window t w =1, i.e., as defined below :

[0048] The respective gamma factor (γ) in each equation determines the weight to be given to the historical values of the corresponding metric. After receiving the exponentially weighted value of each of the plurality of UE-level metrics and the BWP-level metrics, the AI model 1000 determines the BWP allocation policy 1001. Accordingly, the AI model 1000 allocates each of the plurality of UEs to the corresponding BWP in the next time window t w =2. For example, as Figure 10As shown in the middle, UEs 0, 1, 4, and 6 have been assigned to BWP 0, while UEs 2, 3, 5, and 7 have been assigned to BWP 1. In example embodiments, the AI model 1000 can be a reinforcement learning (RL) model. In this scenario, the AI model 1000 can use state metrics to determine a BWP assignment policy. An example state metric can be defined as:

[0049] wherein,

[0050] Further, a reward function may be defined as:

[0051] where T max is the maximum achievable throughput of the NR-L system. a and represent the weights of HoL delay and throughput, respectively, and (a, > 0). In embodiments, R[t w ] is determined such that a UE is assigned to only one BWP at any given time.

[0052] Further, it should be noted that the reward function is defined to optimize KPIs of a wireless communication system, such as the NR-L system. For example, the reward function described above has been configured to maximize throughput while minimizing HoL delay. However, the reward function can be easily modified to prioritize other KPIs. In embodiments, other KPIs can include UE power, spectral efficiency, packet delay violation, etc.

[0053] Thus, multiple UEs can be assigned to corresponding BWPs using the AI model 1000, as Figure 11is shown. During initial access, the UE acquires a synchronization signal block (SSB) containing a master information block (MIB). The UE decodes a system information block 1 (SIB1) using parameters in the MIB. The SIB1 contains information for an initial BWP (BWP_0) for both downlink and uplink. The UE uses the initial BWP for uplink and the base station uses the initial BWP for downlink until a radio resource control (RRC) connection between the UE and the base station. Thus, after a UE attaches to the NR-L system, the initial BWP (i.e., BWP0) is assigned to each UE, and after an RRC connection is established between the UE and the base station of the NR-L system, the UE can be configured with a UE-specific BWP. The assigned BWP remains active for a current time window. Thus, the base station accumulates multiple UE-level metrics and multiple BWP-level metrics for the current time window. In particular, the base station tracks the performance of each UE in its assigned initial BWP and keeps collecting UE-level and BWP-level metrics. At the end of the current time window, the base station passes the accumulated metrics to the AI model 1000 to determine a BWP allocation strategy. If the AI model 1000 predicts the same BWP, no switching is needed. The UE is assigned to BWP_y using a switching method such as DCI-based BWP switching. For example, as shown, the UE is assigned to BWP1 in the current time window. However, the AI model 1000 determines that BWP2 is better for the UE, and then switches the UE to BWP2 using DCI switching. The base station continues to accumulate multiple UE-level metrics and BWP-level metrics until the UE is actively transmitting / receiving data with the base station. Thus, the AI model 1000 keeps determining a BWP allocation strategy for the UE until the UE is actively transmitting / receiving data with the base station. Once the UE becomes inactive and the BWP inactivity timer expires, the UE is assigned back to the default BWP (BWP_0). Figure 11

[0054] Referring back to Figure 10 In an example embodiment, when the NR system is an NR-U system, the multiple UE-level metrics include and In addition, the multiple BWP-level metrics include: (F n [t]), BWP size metric (N RB n ), (CW n [t w ]), (M n [t w ]) and C n [t]. In an embodiment, the exponentially weighted value of N RB n is equal to N RB n In other words, the base station 705 does not calculate N​RB n exponentially weighted values of the N RB n forwarded to the AI model 1000. Thus, the AI model 1000 determines the BWP allocation policy using the N RB n exponentially weighted values of the N w = 1. In addition, similar to the NR-L system, the exponentially weighted values of each of the plurality of UE-level metrics and each of the plurality of BWP metrics for the current time window t and (M n [t w ]) are calculated. It should be noted that the exponentially weighted values of and may be determined using Equations (2), (3), (4), (5), (6), and (7), respectively. are defined as follows:

[0055] The respective gamma factor (γ) in each equation determines the weight to be given to the historical values of the corresponding metric. After receiving the exponentially weighted values of each of the plurality of UE-level metrics and BWP-level metrics, the AI model 1000 determines the BWP allocation policy 1003. Thus, the AI model 1000 allocates each of the plurality of UEs to a corresponding BWP in the next time window t w = 2. For example, as shown in Figure 10 , the UEs 0, 1, 4, and 6 have been allocated to BWP0, while the UEs 2 and 7 have been allocated to BWP1, and the UEs 3 and 5 have been allocated to BWP2. As discussed with reference to the NR-L system, the AI model 1000 can be an RL model. Thus, the state metric can be defined as:

[0056] wherein,

[0057] Further, the reward function R[t w ] can be defined as:

[0058] wherein, T max is the maximum achievable throughput of the NR-U system. a and represent the weights of HoL delay and throughput, respectively, and (a, > 0). In an embodiment, R[t wsuch that the UE is assigned to only one BWP at any given time. Further, it should be noted that the reward function is defined to optimize the KPIs of the wireless communication system, such as the NR-U system. For example, the reward function described above has been configured to maximize the throughput while minimizing the HoL delay. However, the reward function can be easily modified to prioritize other KPIs. In an embodiment, the other KPIs can include the UE power, the spectral efficiency, the packet delay violation, and the like. Further, multiple UEs can be assigned to the corresponding BWPs using the AI model 1000, as shown in Figure 11

[0059] In an alternative embodiment, the BWP allocation in the NR-U system can be performed directly by the base station 705 without using the AI model 1000. This approach is referred to as the least collision allocation (LCA). However, the base station 705 can perform the LCA for a predefined cell coverage area only when the total number of active UEs in the predefined cell coverage area is less than or equal to the maximum number of UEs allowed to be scheduled in each time slot in the corresponding BWP. In an embodiment, the predefined cell coverage area and the maximum number of UEs can be configured by the base station 705. For example, the predefined cell coverage area can be defined as the coverage area covered by one cell associated with the base station 705. In another example, the predefined cell coverage area can be defined as the coverage area covered by two cells associated with the base station 705. Further, the LCA can be performed only when the multiple UEs are homogeneous UEs having similar channel conditions to each other. For example, let us consider that the maximum number of UEs allowed to be scheduled in each time slot in the corresponding BWP is 5. In this case, the LCA can be performed only when the total number of active UEs in the predefined cell coverage is 5 or less and the signal quality between each of these UEs 705 is similar to each other. In the LCA approach, the base station 705 can calculate the channel average weighted value of the channel conditions based on the channel condition metrics w for the current time window t w = 1. Then, the base station 705 can calculate the LBT average weighted value of the LBT failure rate based on the LBT failure rate metrics for the current time window t = 1. Then, the base station 705 can determine the BWP allocation strategy based on , the BWP size corresponding to the BWP, and

[0060] It should be noted that and ​​​​Equations (11) and (12) can be used to determine, respectively. In an embodiment, the BWP allocation strategy can be determined to maximize the throughput of the NR-U system.

[0061] Thus, multiple UEs can be allocated to corresponding BWPs using the LCA method, as Figure 12 shown. As Figure 12 shown, when multiple UEs initially attach to the base station 705, an initial BWP for each UE is selected based on a round-robin manner. For example, for the current time window t w = 1, one of the multiple UEs has been allocated to each of the BWPs, i.e., BWP0, BWP1, and BWP2. However, from Figure 12 it can be seen that BWP2 is congested by wi-fi nodes. In an embodiment, the base station 705 can compute multiple BWP-level metrics for each BWP. At the end of the current time window, the base station 705 can determine a BWP allocation strategy, i.e., the optimal BWP (bwp ), and can perform BWP reallocation based on the optimal BWP (bwp ). For example, as Figure 12 shown, in the next time window t w = 2, all UEs have been allocated to BWP0. The base station 705 can determine the BWP allocation strategy for each new UE entering the NR-U system. For example, at time window t w = 3, two new UEs 1201, 1203 enter the NR-U system. Thus, they are initially allocated to BWP1 and BWP2 for this time window t w = 3. During this time window, the base station 705 can determine the BWP allocation strategy for the next window t w = 4. In the case where all UEs have been attached and allocated BWPs, the LCA method is used if the LBT failure rate of the current optimal BWP exceeds its original value by some predefined delta value. The predefined delta value can be configured by the base station 705. For example, as Figure 12 shown, the LBT failure rate of BWP0 exceeds its original value, thus, in the next time window t w = 4, all UEs have been allocated to BWP1.

[0062] Figure 13 A block diagram of a system for managing multiple BWPs in a wireless communication, such as an NR system, according to an embodiment of the disclosure is shown.

[0063] Figure 13The configuration of the system 1300 can be understood as part of the configuration of the base station 705. Further, according to another embodiment, the method 800 as disclosed above can be implemented in the system 1300. In an embodiment, the system 1300 corresponds to the UE 701. In other words, the system 1300 can be referred to as a base station 705, a UE 701, a device, a network node (e.g., a distributed unit (DU), a near- real-time RAN intelligent controller (near-RT-RIC)). With reference to Figure 13 The system 1300 can include a processor 1302, a communication circuit 1304 (e.g., a communicator or a communication interface), and a memory 1306.

[0064] As an example, the processor 1302 can be a single processing unit or multiple units, all of which can include multiple computing units. The processor 1302 can be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and / or any devices that manipulate signals based on operational instructions. Among other capabilities, the processor 1302 is configured to fetch and execute computer-readable instructions and data stored in the memory 1306. The processor 1302 can include one or more processors. At this time, the one or more processors 1302 can be a general-purpose processor such as a central processing unit (CPU), an application processor (AP), etc., a graphics-only processor such as a graphics processing unit (GPU), a visual processing unit (VPU), and / or an AI-dedicated processor such as a neural processing unit (NPU). The processor or processors 1302 can control the processing of input data according to a pre-defined operation rule or an artificial intelligence (AI) model stored in a non-volatile memory and a volatile memory (i.e., the memory 1306). The pre-defined operation rule or the AI model is provided through training or learning. In another embodiment, the processor 1302 can perform the method 800. For example, the processor 1302 can be referred to as at least one processor (including a processing circuitry).

[0065] The processor 1302 of the system 1300 can include various processing circuitry and / or multiple processors. For example, the term “processor” as used throughout this document (including the claims) can include various processing circuitry including at least one processor, and one or more of the at least one processor can be configured to perform, individually and / or collectively, the various functions described below in a distributed scheme. When the “processor,” “at least one processor,” and “one or more processors” are described as being configured to perform various functions as used below, these terms are not limited to the example and include cases where one processor performs part of the referenced function and another processor performs another part of the referenced function, as well as cases where one processor can perform all of the referenced function. In addition, for example, the at least one processor can include a combination of processors that perform various functions listed / disclosed in a distributed scheme. The at least one processor can execute program instructions to implement or perform various functions.

[0066] The communication circuitry 1304 can perform functions for transmitting and receiving signals via a wireless channel. In an embodiment, the communication circuitry 1304 can allocate a plurality of UEs to corresponding BWPs according to the techniques disclosed in this disclosure. In another embodiment, the processor 1302 can perform the method 800 via the communication circuitry 1304.

[0067] The memory 1306 can include any non-transitory computer-readable medium known in the art including, for example, volatile memory such as static random access memory (SRAM) and dynamic random access memory (DRAM), and / or non-volatile memory such as read-only memory (ROM), erasable programmable ROM, flash memory, hard disks, optical disks, and magnetic tapes. For example, the memory 1306 can include one or more storage media.

[0068] Embodiments are exemplary in nature and the system 1300 can include additional components needed to implement the desired functionality of the system 1300 according to the present disclosure.

[0069] In an embodiment, the system 1300 can be part of a centralized unit (CU) of an NR system. In another embodiment, the system 1300 can be part of a distributed unit (DU) of an NR system. In such scenarios, the system 1300 can be implemented as part of a near real-time RAN intelligent controller (near RT-RIC) module of the DU. The near RT RIC leverages embedded intelligence and is responsible for per-UE RB management, interference detection, quality of service (QoS) management, etc. In addition, as Figure 10The above disclosed AI model 1000 shown can be deployed as part of the “trained model” module of the near-RT-RIC, where UE / cell KPI metrics and system management information are readily available about a broader visibility across multiple-RATs. Additionally, the AI model 1000 can be deployed in a separate container group (pod) within the same worker node of the DU. Since the worker node can handle inter-node communication easily, the DU node can pass all the statistics to the AI model 1000, where the AI model 1000 can form the state and provide appropriate actions in each time window. These actions can then be communicated back to the DU node for BWP reallocation.

[0070] Figure 14A and Figure 14B A comparison of BWP allocation in unlicensed wireless communication, such as a NR-U system, is shown according to embodiments of the disclosure. As Figure 14A shown, in the prior art, BWP-level or UE-level metrics are not considered during BWP allocation for a UE, resulting in suboptimal results. For example, the UE can be allocated to a BWP with higher congestion (such as BWP1) due to other coexistence technologies. As a result, NR transmission opportunities are reduced, and the QoS requirements of the UE are not met. In contrast, as Figure 14B shown, in embodiments of the disclosure, both BWP-level and UE-level metrics are considered during BWP allocation for a UE, resulting in more optimal allocation. For example, the UE can be allocated to a BWP with lower congestion from other coexistence technologies (such as BWP0). This results in enhanced NR transmission opportunities and ensures that the QoS requirements of the UE are met.

[0071] Figure 15A and Figure 15B A comparison of BWP allocation in licensed wireless communication systems, such as a NR-L system, is shown according to embodiments of the disclosure. As Figure 15A shown, in the prior art, BWP-level or UE-level metrics are not considered during BWP allocation for a UE, resulting in suboptimal results. For example, the UE can be allocated to a BWP with more BLER, such as BWP1. This results in more packet retransmissions, indicating resource waste and reduced spectral efficiency. Furthermore, the QoS requirements of the UE are not met. In contrast, as Figure 15B shown, in embodiments of the disclosure, both BWP-level and UE-level metrics are considered during BWP allocation for a UE, resulting in more optimal allocation. For example, the UE can be allocated to a BWP with lower BLER (such as BWP0). This results in fewer packet retransmissions, indicating less resource waste and improved spectral efficiency. Furthermore, the QoS requirements of the UE are met.

[0072] Accordingly, the present disclosure provides techniques for managing multiple BWPs in a NR system.

[0073] Accordingly, the present disclosure provides various advantages. For example, the present disclosure provides techniques for optimizing unlicensed channel access for NR while reducing average HoL latency for UEs and increasing cell throughput. Further, by using AI-based models for BWP allocation, the disclosed techniques help in jointly optimizing and producing BWP allocation recommendations at each time window. Moreover, the present disclosure provides a mechanism for adapting to the dynamic environment of UEs in NR and provides efficient BWP allocation that maximizes the performance of the NR system as well as the UEs. The disclosed techniques also ensure fairness in spectrum usage and do not hinder the performance of coexistence techniques. The disclosed techniques improve KPIs such as throughput and latency of the overall NR system and individual UEs. In exemplary embodiments, the disclosed techniques reduce HoL latency by 35-70% and increase throughput by 15-75%. The disclosed techniques also result in increased customer satisfaction, better SLA compliance, improved quality of service, and reduced network maintenance costs. The disclosed techniques also ensure regulatory compliance as fairness is maintained in coexistence.

[0074] According to an embodiment, a method (800) for managing multiple bandwidth parts (BWPs) in a wireless communication system can include calculating (801), by a base station of the wireless communication system, for a current time window in a corresponding BWP among the multiple BWPs, at least one of multiple BWP-level metrics and multiple user equipment (UE)-level metrics for each of the multiple BWPs. The method (800) can include determining (803), by the base station, a BWP allocation policy based on the calculated at least one of the multiple BWP-level metrics and the multiple UE-level metrics. The method (800) can include allocating, by the base station, each of the multiple UEs to each of the BWPs for a time window subsequent to the current time window based on the determined BWP allocation policy.

[0075] In an embodiment, the BWP allocation policy can be determined to optimize multiple key performance indicators (KPIs) of the wireless communication system.

[0076] In an embodiment, when the wireless communication system is an unlicensed wireless communication system, the multiple UE-level metrics can include a UE traffic queue size metric, a head-of-line (HoL) latency metric, an incoming packet size metric, an outgoing packet size metric, a UE channel condition metric, and a coding metric. The UE channel condition metric can represent an average number of bits allowed to be transmitted by the UE using resource blocks (RBs) in the current time window. The coding metric can represent a coding scheme used to encode the allocation of each UE to the corresponding BWP.

[0077] In an embodiment, when the wireless communication system is a licensed wireless communication system, the plurality of UE-level metrics can include a UE traffic queue size metric, a head-of-line (HoL) delay metric, an incoming packet size metric, an outgoing packet size metric, a coding metric, a UE channel condition metric, and a plurality of block error rate (BLER) metrics.

[0078] In an embodiment, when the wireless communication system is a licensed wireless communication system, the plurality of BWP-level metrics can include a plurality of block error rate (BLER) metrics in a corresponding BWP and a number of active UEs in the corresponding BWP.

[0079] In an embodiment, determining the BWP allocation policy can include calculating an exponentially weighted average of each of the plurality of UE-level metrics and the plurality of BWP-level metrics for a current time window. Determining the BWP allocation policy can include determining the BWP allocation policy based on the exponentially weighted average of each of the plurality of UE-level metrics, the exponentially weighted average of each of the plurality of BWP-level metrics, and a reward function.

[0080] In an embodiment, the reward function can be defined to optimize a plurality of KPIs of the wireless communication system. The wireless communication system can be one of an unlicensed wireless communication system and a licensed wireless communication system.

[0081] In an embodiment, determining the BWP allocation policy can include using an artificial intelligence (AI) model to determine the BWP allocation policy.

[0082] In an embodiment, when the wireless communication system is an unlicensed wireless communication system, the plurality of BWP-level metrics can include a listen-before-talk (LBT) protocol failure rate metric, a BWP size metric, an average contention window size metric, an average in-network channel occupancy metric, and a channel condition metric. The channel condition metric can represent an average number of bits allowed to be transmitted by each of the plurality of UEs using a resource block (RB) in a current time window of a corresponding BWP.

[0083] In an embodiment, when the wireless communication system is an unlicensed wireless communication system, determining the BWP allocation policy can include calculating a channel average weighted value of a channel condition based on the channel condition metric of the current time window. When the wireless communication system is an unlicensed wireless communication system, determining the BWP allocation policy can include calculating an LBT average weighted value of an LBT failure rate based on the LBT failure rate metric of the current time window. When the wireless communication system is an unlicensed wireless communication system, determining the BWP allocation policy can include determining the BWP allocation policy based on the channel average weighted value, the LBT average weighted value, and a BWP size corresponding to the BWP. The BWP allocation policy can be determined to optimize a plurality of KPIs of the unlicensed wireless communication system.

[0084] In an embodiment, the plurality of BWP level metrics can include a listen before talk (LBT) protocol failure rate metric, a BWP size metric, and a channel condition metric. The channel condition metric can represent an average number of bits allowed to be transmitted by each of the plurality of UEs using a resource block (RB) in a current time window of the corresponding BWP.

[0085] In an embodiment, determining the BWP allocation policy can include determining the BWP allocation policy when a total number of active UEs in a predefined cell coverage area of the base station is less than or equal to a maximum number of UEs allowed to be scheduled per slot in the corresponding BWP.

[0086] In an embodiment, determining the BWP allocation policy can include determining the BWP allocation policy when the plurality of UEs are homogeneous UEs having similar channel conditions to each other.

[0087] In an embodiment, the current time window can consist of a predefined number of consecutive slots in the corresponding BWP.

[0088] In an embodiment, the plurality of UEs can belong to one of a plurality of radio access technologies (RATs) operating in a same unlicensed frequency band of an unlicensed wireless communication system and a single RAT operating in a licensed wireless communication system.

[0089] According to an embodiment, a system (1300) for managing a plurality of bandwidth parts (BWPs) in a wireless communication system can include a memory (1306). The system (1300) can include a processor (1301) coupled to the memory (1306). The processor (1301) can be configured to compute, for a current time window in a corresponding BWP among the plurality of BWPs, at least one of a plurality of BWP level metrics and a plurality of user equipment (UE) level metrics for each BWP in the plurality of BWPs. The processor (1301) can determine a BWP allocation policy based on the computed at least one of the plurality of BWP level metrics and the plurality of UE level metrics. The processor (1301) can allocate each UE in the plurality of UEs to each BWP based on the determined BWP allocation policy for a time window subsequent to the current time window.

[0090] In an embodiment, the BWP allocation policy can be determined to optimize a plurality of key performance indicators (KPIs) of the wireless communication system.

[0091] In an embodiment, when the wireless communication system is an unlicensed wireless communication system, the plurality of UE-level metrics can include a UE traffic queue size metric, a head-of-line (HoL) delay metric, an incoming packet size metric, an outgoing packet size metric, a UE channel condition metric, and a coding metric. The UE channel condition metric can represent an average number of bits allowed to be transmitted by a UE using a resource block (RB) in a current time window. The coding metric can represent a coding scheme used to encode an allocation of each UE to a corresponding BWP.

[0092] In an embodiment, when the wireless communication system is a licensed wireless communication system, the plurality of UE-level metrics can include a UE traffic queue size metric, a head-of-line (HoL) delay metric, an incoming packet size metric, an outgoing packet size metric, a coding metric, a UE channel condition metric, and a plurality of block error rate (BLER) metrics corresponding to each of the plurality of UEs.

[0093] In an embodiment, when the wireless communication system is a licensed wireless communication system, the plurality of BWP-level metrics can include a plurality of block error rate (BLER) metrics in the corresponding BWP and a number of active UEs in the corresponding BWP.

[0094] In an embodiment, to determine the BWP allocation policy, the processor (1301) is configured to compute an exponentially weighted average of each of the plurality of UE-level metrics and the plurality of BWP-level metrics for a current time window. To determine the BWP allocation policy, the processor (1301) is configured to determine the BWP allocation policy based on the exponentially weighted average of each of the plurality of UE-level metrics, the exponentially weighted average of each of the plurality of BWP-level metrics, and a reward function.

[0095] In an embodiment, the reward function can be defined to optimize a plurality of KPIs of the wireless communication system. The wireless communication system can be one of an unlicensed wireless communication system and a licensed wireless communication system.

[0096] In an embodiment, the processor (1301) can be configured to determine the BWP allocation policy using an artificial intelligence (AI) model.

[0097] In an embodiment, when the wireless communication system is an unlicensed wireless communication system, the plurality of BWP-level metrics can include a listen-before-talk (LBT) protocol failure rate metric, an average contention window size metric, an average in-network channel occupancy metric, and a channel condition metric. The channel condition metric can represent an average number of bits allowed to be transmitted by each of the plurality of UEs using a resource block (RB) in a current time window of the corresponding BWP.

[0098] In an embodiment, when the wireless communication system is an unlicensed wireless communication system, to determine the BWP allocation strategy, the processor (1301) is configured to calculate a channel average weighted value of channel conditions based on a channel condition metric for a current time window. When the wireless communication system is an unlicensed wireless communication system, to determine the BWP allocation strategy, the processor (1301) is configured to calculate a LBT failure rate average weighted value of LBT failure rate based on a LBT failure rate metric for the current time window. When the wireless communication system is an unlicensed wireless communication system, to determine the BWP allocation strategy, the processor (1301) is configured to determine the BWP allocation strategy based on the channel average weighted value, a BWP size corresponding to the BWP, and the LBT failure rate average weighted value. The BWP allocation strategy can be determined to optimize a plurality of KPIs of the unlicensed wireless communication system.

[0099] In an embodiment, the plurality of BWP level metrics can include a listen before talk (LBT) protocol failure rate metric, a BWP size metric, and a channel condition metric. The channel condition metric can represent an average number of bits allowed to be transmitted by each of the plurality of UEs using resource blocks (RBs) in a current time window of the corresponding BWP.

[0100] In an embodiment, the processor (1301) can be configured to determine the BWP allocation strategy when a total number of active UEs in a predefined cell coverage area of the base station is less than or equal to a maximum number of UEs allowed to be scheduled per slot in the corresponding BWP.

[0101] In an embodiment, the processor (1301) can be configured to determine the BWP allocation strategy when the plurality of UEs are homogeneous UEs having similar channel conditions to each other.

[0102] In an embodiment, the current time window can consist of a predefined number of consecutive slots in the corresponding BWP.

[0103] In an embodiment, the plurality of UEs can belong to a plurality of radio access technologies (RATs) operating in one of the same unlicensed frequency bands of the unlicensed wireless communication system and a single RAT operating in the licensed wireless communication system.

[0104] According to an embodiment, a method performed by a base station in a wireless communication system can include identifying, for a first time window in a corresponding bandwidth part (BWP) of a plurality of BWPs, at least one of a plurality of BWP level metrics and a plurality of user equipment (UE) level metrics for each of the plurality of BWPs. The method can include determining a BWP allocation strategy based on the identified at least one of the plurality of BWP level metrics and the plurality of UE level metrics. The method can include allocating each of a plurality of UEs to each of the BWPs based on the determined BWP allocation strategy for a second time window after the first time window.

[0105] In an embodiment, the BWP allocation strategy can be determined to optimize a plurality of key performance indicators (KPIs) of the wireless communication system.

[0106] In an embodiment, in a case where the wireless communication system is an unlicensed system, the plurality of UE-level metrics can include a UE traffic queue size metric, a head-of-line (HoL) delay metric, an incoming packet size metric, an outgoing packet size metric, a UE channel condition metric, and a coding metric. The UE channel condition metric can represent an average number of bits allowed to be transmitted by each of the plurality of UEs using a resource block (RB) in a first time window. The coding metric can represent a coding scheme used to encode an allocation of each of the plurality of UEs to a corresponding BWP.

[0107] In an embodiment, in a case where the wireless communication system is a licensed system, the plurality of UE-level metrics can include a UE traffic queue size metric, a head-of-line (HoL) delay metric, an incoming packet size metric, an outgoing packet size metric, a coding metric, a UE channel condition metric, and a plurality of block error rate (BLER) metrics.

[0108] In an embodiment, in a case where the wireless communication system is a licensed system, the plurality of BWP-level metrics can include a plurality of block error rate (BLER) metrics in the corresponding BWP and a number of active UEs in the corresponding BWP.

[0109] In an embodiment, determining the BWP allocation strategy can further include calculating an exponentially weighted average of each of the plurality of UE-level metrics and the plurality of BWP-level metrics for the first time window. Determining the BWP allocation strategy can further include determining the BWP allocation strategy based on the exponentially weighted average of each of the plurality of UE-level metrics, the exponentially weighted average of each of the plurality of BWP-level metrics, and a reward function.

[0110] In an embodiment, the reward function can be defined to optimize a plurality of KPIs of the wireless communication system. The wireless communication system can be one of an unlicensed system and a licensed system.

[0111] In an embodiment, determining the BWP allocation strategy can further include determining the BWP allocation strategy using an artificial intelligence (AI) model.

[0112] In an embodiment, in a case where the wireless communication system is an unlicensed system, the plurality of BWP-level metrics can include a listen-before-talk (LBT) protocol failure rate metric, a BWP size metric, an average contention window size metric, an average in-network channel occupancy metric, and a channel condition metric. The channel condition metric can represent an average number of bits allowed to be transmitted by each of the plurality of UEs using a resource block (RB) in a first time window of the corresponding BWP.

[0113] In an embodiment, in a case that the wireless communication system is an unlicensed system, determining the BWP allocation strategy can further include calculating a channel average weighted value of channel conditions based on the channel condition metric of the first time window. In a case that the wireless communication system is an unlicensed system, determining the BWP allocation strategy can further include calculating a LBT average weighted value of LBT failure rate based on the LBT failure rate metric of the first time window. In a case that the wireless communication system is an unlicensed system, determining the BWP allocation strategy can further include determining the BWP allocation strategy based on the channel average weighted value, the LBT average weighted value, and a BWP size of the corresponding BWP. The BWP allocation strategy can be determined to optimize a plurality of KPIs of the unlicensed system.

[0114] In an embodiment, the plurality of BWP level metrics can include a listen before talk (LBT) protocol failure rate metric, a BWP size metric, and a channel condition metric. The channel condition metric can represent an average number of bits allowed to be transmitted by each of the plurality of UEs using resource blocks (RBs) in the first time window of the corresponding BWP.

[0115] In an embodiment, determining the BWP allocation strategy can further include determining the BWP allocation strategy when a total number of active UEs in a predefined cell coverage area of the base station is less than or equal to a maximum number of UEs allowed to be scheduled per slot in the corresponding BWP.

[0116] In an embodiment, the first time window can consist of a predefined number of consecutive slots in the corresponding BWP.

[0117] According to an embodiment, a base station can include a memory storing instructions. The base station can include at least one processor. The instructions, when executed by the at least one processor individually or collectively, can cause the base station to identify, for a first time window in a corresponding bandwidth part (BWP) among a plurality of BWPs, at least one of a plurality of BWP level metrics and a plurality of user equipment (UE) level metrics for each of the plurality of BWPs. The instructions, when executed by the at least one processor individually or collectively, can cause the base station to determine a BWP allocation strategy based on the identified at least one of the plurality of BWP level metrics and the plurality of UE level metrics. The instructions, when executed by the at least one processor individually or collectively, can cause the base station to allocate each of a plurality of UEs to each of the BWPs based on the determined BWP allocation strategy for a second time window after the first time window.

[0118] According to an embodiment, a non-transitory computer-readable storage medium can store one or more programs including instructions, which when executed by at least one processor of a base station, alone or in combination, cause the base station to identify, for a first time window in a corresponding BWP among a plurality of BWPs, at least one of a plurality of bandwidth part (BWP) level metrics and a plurality of user equipment (UE) level metrics for each BWP among the plurality of BWPs. The non-transitory computer-readable storage medium can store one or more programs including instructions, which when executed by the at least one processor, alone or in combination, cause the base station to determine a BWP allocation policy based on the identified at least one of the plurality of BWP level metrics and the plurality of UE level metrics. The non-transitory computer-readable storage medium can store one or more programs including instructions, which when executed by the at least one processor, alone or in combination, cause the base station to allocate each UE among a plurality of UEs to each BWP among the plurality of BWPs based on the determined BWP allocation policy for a second time window after the first time window.

[0119] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The singular forms "a," "an," and "the" include plural referents unless otherwise stated.

[0120] Benefits, other advantages, and solutions to problems have been described above with regard to specific embodiments. However, the benefits, advantages, solutions to problems and any elements that cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature or element of any or all the claims.

[0121] Although the subject matter has been described in language specific to structural features, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features described. Rather, the specific features are disclosed as example implementations of the inventive subject matter. One skilled in the art will understand that the elements of the described embodiments can be combined, divided, or omitted, and that the functions of one element can be performed by another element.

Claims

1. A method performed by a base station in a wireless communication system, the method comprising: For a first time window in a corresponding BWP among multiple bandwidth portion BWPs, identify at least one of multiple BWP-level metrics and multiple UE-level metrics for each BWP among the multiple BWPs. A BWP allocation strategy is determined based on at least one of the identified multiple BWP-level metrics and multiple UE-level metrics. as well as For the second time window following the first time window, each UE among the multiple UEs is assigned to each BWP based on the determined BWP allocation strategy.

2. The method according to claim 1, wherein, The BWP allocation strategy was determined to optimize several key performance indicators (KPIs) of the wireless communication system.

3. The method according to claim 1, wherein, In the case that the wireless communication system is an unlicensed system, the multiple UE-level metrics include: UE traffic queue size metric, queue head HoL delay metric, incoming packet size metric, outgoing packet size metric, UE channel condition metric, and coding metric. Wherein, the UE channel condition metric represents the average number of bits that each of the plurality of UEs is allowed to transmit using resource block RB within the first time window, and The encoding metric represents the encoding scheme used to encode the allocation of each of the plurality of UEs to the corresponding BWP.

4. The method according to claim 1, wherein, When the wireless communication system is a licensed system, the multiple UE-level metrics include: UE service queue size metric, queue head HoL delay metric, incoming packet size metric, outgoing packet size metric, coding metric, UE channel condition metric, and multiple block error rate (BLER) metrics.

5. The method according to claim 1, wherein, When the wireless communication system is a licensed system, the multiple BWP-level metrics include multiple block error rate (BLER) metrics in the corresponding BWP and the number of active UEs in the corresponding BWP.

6. The method according to claim 1, wherein, Determining the BWP allocation strategy further includes: Calculate the exponentially weighted average of each of the plurality of UE-level metrics and the plurality of BWP-level metrics for the first time window; and The BWP allocation strategy is determined based on the exponentially weighted average of each UE-level metric among the plurality of UE-level metrics, the exponentially weighted average of each BWP-level metric among the plurality of BWP-level metrics, and the reward function.

7. The method according to claim 6, wherein, The reward function is defined as optimizing multiple KPIs of the wireless communication system, and The wireless communication system is either an unlicensed system or a licensed system.

8. The method according to claim 6, wherein, Determining the BWP allocation strategy further includes: The BWP allocation strategy is determined using an artificial intelligence (AI) model.

9. The method according to claim 6, wherein, In the case that the wireless communication system is an unlicensed system, the multiple BWP-level metrics include the Listen-Before-Talk (LBT) protocol failure rate metric, BWP size metric, average contention window size metric, average on-network channel occupancy metric, and channel condition metric, and The channel condition metric represents the average number of bits that each of the plurality of UEs is allowed to transmit using resource block RB within the first time window corresponding to BWP.

10. The method according to claim 1, wherein, In the case that the wireless communication system is an unlicensed system, determining the BWP allocation strategy further includes: Based on the channel condition metric of the first time window, calculate the channel average weighted value of the channel condition; Based on the LBT failure rate metric of the first time window, calculate the LBT average weighted value of the LBT failure rate; and Based on the channel average weighting value, the LBT average weighting value, and the corresponding BWP size, the BWP allocation strategy is determined. The BWP allocation strategy is determined to optimize multiple KPIs of the unauthorized system.

11. The method according to claim 10, wherein, The multiple BWP-level metrics include a Listen-After-Speak (LBT) protocol failure rate metric, a BWP size metric, and a channel condition metric, wherein the channel condition metric represents the average number of bits that each of the multiple UEs is allowed to send using a resource block (RB) within the first time window corresponding to the BWP.

12. The method according to claim 10, wherein, Determining the BWP allocation strategy further includes: The BWP allocation strategy is determined when the total number of active UEs in the predefined cell coverage area of ​​the base station is less than or equal to the maximum number of UEs that can be scheduled in each time slot of the corresponding BWP.

13. The method according to claim 1, wherein, The first time window consists of a predefined number of consecutive time slots in the corresponding BWP.

14. A base station, the base station comprising: A memory, wherein the memory stores instructions; as well as At least one processor, Wherein, when the instructions are executed individually or jointly by the at least one processor, the base station: For a first time window in a corresponding BWP among multiple bandwidth portion BWPs, identify at least one of multiple BWP-level metrics and multiple UE-level metrics for each BWP among the multiple BWPs. Based on at least one of the identified multiple BWP-level metrics and multiple UE-level metrics, a BWP allocation strategy is determined; and For the second time window following the first time window, each UE among the multiple UEs is assigned to each BWP based on the determined BWP allocation strategy.

15. A non-transitory computer-readable storage medium storing one or more programs comprising instructions that, when executed individually or jointly by at least one processor of a base station, cause the base station to: For a first time window in a corresponding BWP among multiple bandwidth portion BWPs, identify at least one of multiple BWP-level metrics and multiple UE-level metrics for each BWP among the multiple BWPs. A BWP allocation strategy is determined based on at least one of the identified multiple BWP-level metrics and multiple UE-level metrics. as well as For the second time window following the first time window, each UE among the multiple UEs is assigned to each BWP based on the determined BWP allocation strategy.

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