System and method for 5G and WLAN private network convergence for improved QOS and QOE

Abstract

System and method embodiments for 5G and WLAN private network convergence are described in the present disclosure to improve quality of service (QoS) and quality of experience (QoE) by using cognitive layer handover, boot or split traffic. The cognitive layer may sense signal conditions and learn user preferences for traffic allocation between available Wi-Fi and 5G networks. In embodiments, the cognitive layer may include an artificial intelligence (AI) or machine learning (ML) module, a signal condition sensor, and a user QoS / QoE aware scheduler. A cloud-based service controller may be incorporated to make decisions regarding user QoS and QoE assignments based on cognitive layer inputs. Implementations of network convergence embodiments may improve QoS / QoE.

Description

Cross-references to related patent applications

[0001] This application claims priority to commonly owned U.S. Patent Application No. 17 / 832,593, filed on June 4, 2022, entitled “SYSTEM AND METHODS FOR 5G AND WLAN PRIVATENETWORK CONVERGENCE FOR IMPROVED QOS AND QOE,” listing Gururaj Padaki, Sriram Rajagopal, Harpriya Surampudi, Hersh Vardhan Shukla, and Venkatesh Sukuman as inventors. Each of the foregoing patent documents is incorporated herein by reference in its entirety. Technical Field

[0002] The present disclosure generally relates to systems and methods for wireless network convergence. More specifically, the present disclosure relates to systems and methods for 5G and WLAN dedicated network convergence for improved quality of service (QoS) and quality of experience (QoE). Background Art

[0003] Wireless communication transfers information between multiple points without using electrical conductors as a transmission medium. Wireless communication can be implemented using different technologies or protocols (such as 5G, Wi-Fi, etc.).

[0004] Wi-Fi communications have been widely used to provide local network and Internet access to devices within the Wi-Fi range of one or more routers. Given the high popularity of Wi-Fi, Wi-Fi networks may be congested with surrounding networks (such as another Wi-Fi network, a cellular communication network, etc.) that may operate in a close or similar frequency band. These surrounding networks may cause interference or disruption to users of Wi-Fi network services, thereby affecting user QoS. In addition, given that some applications have high QoE requirements, users may require dedicated and predictable QoS to run those applications.

[0005] Therefore, there is a need for systems, devices, and methods for QoS and QoE improvements when multiple wireless networks coexist. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Reference will be made to embodiments of the present disclosure, examples of which may be shown in the accompanying drawings. These drawings are intended to be illustrative and not restrictive. Although the attached disclosure is generally described in the context of these embodiments, it should be understood that the scope of the present disclosure is not intended to be limited to these specific embodiments. The items in the drawings may not be drawn to scale.

[0007] Figure 1 A block diagram of a wireless network convergence system is depicted in accordance with an embodiment of the present disclosure.

[0008] Figure 2 A block diagram of a cognitive layer is depicted in accordance with an embodiment of the present disclosure.

[0009] Figure 3 A process for QoS / QoE-aware scheduling according to an embodiment of the present disclosure is depicted.

[0010] Figure 4 Depicted is a schematic diagram of a UE connected to a radio unit across different wireless links according to an embodiment of the present disclosure.

[0011] Figure 5 A process for redirecting traffic across different wireless links according to an embodiment of the present disclosure is depicted. DETAILED DESCRIPTION

[0012] In the following description, for the purpose of explanation, specific details are set forth in order to provide an understanding of the present disclosure. However, it will be apparent to those skilled in the art that the present disclosure may be practiced without these details. In addition, those skilled in the art will recognize that the embodiments of the present disclosure described below may be implemented in various ways, such as a process, device, system / equipment, or a method on a tangible computer-readable medium.

[0013] The components or modules shown in the accompanying drawings are illustrations of exemplary embodiments of the present disclosure and are intended to avoid obscuring the present disclosure. It should also be understood that throughout the discussion, components may be described as separate functional units, which may include subunits, but those skilled in the art will recognize that various components or parts thereof may be separated into separate components or may be integrated together, including, for example, being located in a single system or component. It should be noted that the functions or operations discussed herein may be implemented as components. Components may be implemented in software, hardware, or a combination thereof.

[0014] In addition, the connection between the components or systems in the drawings is not intended to be limited to direct connection. On the contrary, the data between these components can be modified, reformed or otherwise changed by intermediate components. Moreover, more or less connections can be used. It should also be noted that the terms "coupled", "connected", "communicatively coupled", "interfaced", "interface" or any derivatives thereof should be understood to include direct connection, indirect connection through one or more intermediate devices, and wireless connection. It should also be noted that any communication such as signal, response, reply, confirmation, message, inquiry, etc. can include one or more information exchanges.

[0015] References in the specification to "one or more embodiments," "preferred embodiments," "embodiments," "embodiments," etc., mean that a particular feature, structure, characteristic, or function described in conjunction with the embodiment is included in at least one embodiment of the present disclosure, and may be present in more than one embodiment. Furthermore, the appearance of the above phrases in various places in the specification do not necessarily refer to the same embodiment or embodiments.

[0016] Certain terms are used in various places in the specification for the purpose of explanation and should not be interpreted as limiting. The terms "include, including", "comprise, comprising" should be understood as open terms, and any examples are provided by way of illustration and are not intended to limit the scope of the present disclosure.

[0017] Services, functions or resources are not limited to a single service, function or resource; the use of these terms may refer to the grouping of several related services, functions or resources that may be distributed or aggregated. The use of memory, database, information base, data storage, table, hardware, cache, etc. may be used herein to refer to one or more system components into which information may be input or otherwise recorded. The terms "data", "information" and similar terms may be replaced by other terms referring to a group of one or more bits and may be used interchangeably. The terms "packet" or "frame" should be understood to mean a group of one or more bits. The terms "frame" or "packet" should not be interpreted as limiting the embodiments of the present invention to 5G networks. The terms "packet", "frame", "data" or "data service" may be replaced by other terms (such as "datagram" or "unit") referring to a group of bits. The words "optimal", "optimization", "optimization" and the like refer to improvements in results or processes, and do not require that the specified results or processes have reached an "optimal" or peak state.

[0018] It should be noted that: (1) some steps may be performed optionally; (2) the steps may not be limited to the specific order described herein; (3) some steps may be performed in a different order; and (4) some steps may be performed simultaneously.

[0019] With the development of wireless communication technology, most user devices (such as smartphones) can currently support both Wi-Fi and 4G / 5G communication protocols. The convergence of the two protocols at the access point may not be very common because different chipsets may be used. It is expected that the processing chip has processing capabilities on the chip that supports both protocol stacks and implements QoS / QoE-aware scheduling to improve system performance. The following describes system and method embodiments of a system for 5G and WLAN dedicated network convergence for improved QoS and QoE.

[0020] Figure 1 A block diagram of a wireless network convergence system according to an embodiment of the present disclosure is depicted. A UE or customer premises equipment (CPE) 110 is coupled to a first wireless station 122 via a first wireless link 121 and to a cellular base station 124 via a second wireless link 123. The first wireless station 122 may be a Wi-Fi access point and the first wireless link 121 may be a Wi-Fi connection. The second wireless station 124 may be a 5G-NR base station, such as a gNodeB (gNB), and the second wireless link 123 may be a 5G NR cellular link. A cognitive layer 126 is coupled to both the first wireless station 122 and the second wireless station 124. The cognitive layer 126 senses the signal conditions of the first and second wireless links and learns the user's preference for traffic allocation between the first and second wireless links.

[0021] In one or more embodiments, the wireless network convergence system may include a protocol converter 128 coupled to both the first wireless station 122 and the second wireless station 124 to redirect traffic to / from the UE between the first wireless station 122 and the second wireless station 124 through IP packet conversion. Such traffic redirection may involve re-splitting 5G data into 5G data plane data and 5G control plane data. In the case where a 5G data flow for traffic management or a portion of the 5G data flow is redirected to / from Wi-Fi, the protocol converter 128 may potentially separate and / or enhance one (or more) control protocols for the 5G data flow. The protocol converter 128 may be coupled to an Internet service server 140 and a core network (CN) 150 (e.g., 5GCN) via a cloud connection 130 for communication. The wireless network convergence system may also include an Internet service controller 130 that makes decisions about QoS and QoE aware allocations based at least on cognitive layer inputs.

[0022] Figure 2A block diagram of a cognitive layer according to an embodiment of the present disclosure is depicted. The cognitive layer 126 includes one or more channel condition sensors 210 for a first wireless link, and one or more channel condition sensors 220 for a second wireless link. The channel condition sensors are configured to determine one or more channel conditions of the first and second wireless links based on one or more measurements. The channel conditions may include one or more of the following: signal strength, signal-to-noise ratio (SNR), data ratio, throughput, current load information, signal (e.g., Wi-Fi) interference from the same channel used by neighboring APs, cellular interference from other macro cells or nearby small cells, traffic / channel congestion on each wireless link, error rate (e.g., hybrid automatic repeat request (HARQ) measurement), etc. The current load information may include the size allocated for the current load, data rate, one (or more) frequency bands, and one (or more) bandwidths, etc.

[0023] The cognitive layer 126 may include an operation module 230 to perform artificial intelligence (AI) or machine learning (ML)-based operations for QoS / QoE-aware scheduling for at least one of the first wireless link 121 and the second wireless link 123. The cognitive layer 126 may be deployed in a single node (the first wireless station 122 or the second wireless station 124) or in two nodes with software / hardware acceleration. QoS / QoE-aware scheduling may be scheduling of downlink traffic or uplink traffic for the first wireless link 121 and / or the second wireless link 123. QoS / QoE-aware scheduling may be deployed for TDD / FDD in different frequency bands and for simultaneous or alternative operation of the first wireless link 121 and / or the second wireless link 123. The cognitive layer 126 may also implement various forms of control for QoS / QoE-aware scheduling, such as traffic management, power control, modulation type, etc. across Wi-Fi / 5G. These QoS / QoE-aware scheduling and / or control forms may be different for each user or client.

[0024] In one or more embodiments, the operation module 230 performs QoS / QoE-aware scheduling based on the channel conditions of the first wireless link and the second wireless link and historical data. The historical data may include: user preferences for traffic allocation between available Wi-Fi and 5G networks, and historical traffic allocation for the UE and other UEs served by the first wireless station 122 and the second wireless station 124. User preferences may be general preferences or application-specific preferences. For example, a user may prefer Wi-Fi (e.g., IEEE 802.11be) communications to meet QoS standards for applications with high traffic and requiring low latency and high bandwidth. The historical data can be stored in a memory accessible to the operation module 230, such as a cloud database or an internal memory.

[0025] Figure 3 A process for QoS / QoE-aware scheduling according to an embodiment of the present disclosure is depicted. In step 305, one or more channel conditions of a first wireless link coupling a UE to a first wireless station (e.g., a Wi-Fi access point) and a second wireless link coupling the UE to a second first wireless station (e.g., a 5G gNB) are determined based on one or more measurements. The first wireless station and the second wireless station can be separate devices or integrated together as a single station capable of supporting two wireless links. The first wireless link is established using a first wireless technology (e.g., Wi-Fi), and the second wireless link is established using a second wireless technology different from the first wireless technology (e.g., 5G NR).

[0026] In step 310, historical data about the first wireless station and the second wireless station is retrieved. The historical data may include user preferences for traffic allocation between the first wireless station and the second first wireless station. The user preferences may be general preferences or application specific preferences.

[0027] In step 315, QoS / QoE-aware scheduling for services involving the UE is performed at the cognitive layer for at least one of the first radio link and the second radio link based at least on one or more channel conditions of the first radio link and the second radio link and historical data. The service may be downlink service to the UE or uplink service from the UE. QoS / QoE-aware scheduling may be scheduling for simultaneous operation or alternative operation of the first radio link and the second radio link. In one or more embodiments, QoS / QoE-aware scheduling is also based on load information of the services to be scheduled, which may include: load type (audio, video, streaming, text, etc.), size, data rate, latency requirements, required or preferred one (or more) frequency bands and bandwidths, etc.

[0028] Currently, both 5G-NR base stations (e.g., gNBs) and Wi-Fi networks can be deployed in the unlicensed 5G New Radio Unlicensed (NR-U) band, resulting in coexistence between two different wireless access technologies at the same or similar NR-U band. Figure 4A schematic diagram of a UE connected to a radio unit across different wireless links in accordance with an embodiment of the present disclosure is depicted. A radio unit (RU) 435 in a wireless station 430 (e.g., a small cell or gNB) may be coupled to a UE 405 via a first wireless link 410 (e.g., a Wi-Fi link) and / or a second wireless link 420 (e.g., a cellular link), depending on the configuration of the RU and the capabilities of the UE. The wireless station 430 may include a RU, a distributed unit (DU), and a centralized unit (CU). The RU may include multiple antenna elements that may be configured to support signal reception / transmission using a first wireless link, a second wireless link, or both.

[0029] In one or more embodiments, QoS / QoE-aware scheduling may include traffic redirection across a first wireless link and a second wireless link by a protocol converter through IP packet conversion. Such traffic redirection may involve re-splitting the 5G data into 5G data plane data and 5G control plane data. For example, in the case where a 5G data flow or a portion of a 5G data flow is redirected to / from a Wi-Fi wireless link, the protocol converter may separate and / or enhance one (or more) control protocols for the 5G data flow. Alternatively, to redirect a Wi-Fi data downlink flow, traffic redirection may involve: separating Wi-Fi data from Wi-Fi frames in the Wi-Fi data downlink flow, and adding a 5G preamble to the Wi-Fi data to form a 5G downlink flow for sending to the UE. In one or more embodiments, the cognitive layer and the protocol converter may be integrated within the radio unit 430 of the wireless station 430.

[0030] Figure 5A process for traffic redirection across different wireless links according to an embodiment of the present disclosure is depicted. In step 505, the cognitive layer identifies the UE as connected on both the first wireless link and the second wireless link. In step 510, at the cognitive layer, based at least on one or more channel conditions of the first wireless link and the second wireless link, user preferences, and information about the data stream, traffic redirection of at least a portion of the data stream is scheduled at one or more scheduled time slots across the first wireless link and the second wireless link. In one example, when a Wi-Fi access point is stressed by a large amount of traffic and therefore has very limited bandwidth available for additional traffic, and the 5G link is only slightly used when relatively high bandwidth is available, the cognitive layer can schedule traffic redirection for downlink traffic of a video stream that was originally scheduled to be sent via the Wi-Fi link, so that at least a portion of the video stream is redirected to be sent to the UE via the 5G link using the 5G NR-U band. In another example, the user is running an application that requires low latency (e.g., an online meeting). The data stream of the application was originally sent via the Wi-Fi link. However, when the Wi-Fi link suffers from some interference and has higher latency than expected, the cognitive layer senses the higher latency on the Wi-Fi link and can schedule traffic redirection for the data flow or part of the data flow for the application to be sent on the current 5G link with low latency.

[0031] In step 515, the protocol converter converts the at least a portion of the data stream into a converted data stream to be sent via the redirected wireless link, which may be a first wireless link or a second wireless link, depending on the wireless link originally scheduled. Referring to the above example of video streaming, the protocol converter may convert a portion of the video streaming from a Wi-Fi protocol to a 5G protocol so that the converted portion of the video streaming may be sent via the 5G wireless link. In one or more embodiments, the protocol converter may separate the original preamble (e.g., a Wi-Fi preamble) from the at least a portion of the data stream and add an alternative preamble (e.g., a 5G preamble) required for data transmission on the redirected wireless link. In the case where the original wireless link is a Wi-Fi link and the redirected wireless link is a 5G NR link, the protocol converter may also add control plane data to the at least a portion of the data stream.

[0032] In step 520, the converted data stream is sent via the redirected wireless link at one or more scheduled time slots. In the case where the data stream is partially redirected to be via the converted redirected wireless link, the receiving party (UE for downlink data stream or wireless station for uplink data stream) may need to reassemble the services received from the original wireless link and the redirected wireless link to recover the complete data stream. In the above example of video streaming for downlink transmission, the UE can receive a first part of the video streaming transmission via the Wi-Fi link and a second part of the video streaming transmission via the 5G cellular link. The first part and the second part are then reassembled into a complete stream transmission at the UE, for example by frame numbers in the video streaming transmission.

[0033] In one or more embodiments, the cognitive layer can be a separate entity and can be merged with the protocol converter in a common core for Internet services. This deployment is applicable considering that not all access points provide an aggregation solution. In some embodiments, when the density of Wi-Fi access points is high (e.g., multiple access points in a shopping mall / office), but not all Wi-Fi access points have 5G cellular connectivity capabilities, the cognitive layer can be deployed to address problems caused by high congestion on Wi-Fi channels. 5G cellular connections can have higher coverage and can be used to redirect those services or portions of those services on the Wi-Fi link by scheduling requests for services to be sent on one (or more) 5G channels. Such service redirection can effectively relieve Wi-Fi congestion.

[0034] Aspects of the present disclosure may be encoded on one or more non-transitory computer-readable media with instructions for one or more processors or processing units to cause the steps to be performed. It should be noted that the non-transitory computer-readable medium should include volatile and / or non-volatile memory. It should be noted that alternative implementations are possible, including hardware implementations or software / hardware implementations. The functions of hardware implementations can be implemented using ASICs, programmable arrays, digital signal processing circuits, etc. Therefore, the term "unit" in any claim is intended to cover both software implementations and hardware implementations. Similarly, the term "computer-readable medium" as used herein includes software and / or hardware or a combination thereof on which an instruction program is embodied. In view of these implementation alternatives, it should be understood that the drawings and the accompanying descriptions provide functional information that those skilled in the art will need to write program code (i.e., software) and / or manufacture circuits (i.e., hardware) to perform the desired processing.

[0035] It should be noted that embodiments of the present disclosure may also relate to computer products having non-transitory tangible computer-readable media having computer code thereon for performing various computer-implemented operations. The media and computer code may be those specifically designed and constructed for the purposes of the present disclosure, or they may be of a type known or available to those skilled in the relevant art. Examples of tangible computer-readable media include, for example: magnetic media such as hard disks, floppy disks, and tapes; optical media such as CDs and holographic devices; magneto-optical media; and hardware devices specifically configured to store or configured to store and execute program code, such as ASICs, PLDs, flash memory devices, other non-volatile memory devices, and ROM and RAM devices. Examples of computer code include machine code such as produced by a compiler, and files containing higher-level code executed by a computer using an interpreter. Embodiments of the present disclosure may be implemented in whole or in part as machine executable instructions, which may be in program modules executed by one or more processing devices. Examples of program modules include libraries, programs, routines, objects, components, and data structures. In a distributed computing environment, program modules may be physically located in local, remote, or both locations.

[0036] Those skilled in the art will recognize that no computing system or programming language is critical to the practice of the present disclosure. Those skilled in the art will also recognize that the above-mentioned several elements can be physically and / or functionally separated into modules and / or sub-modules or combined together.

[0037] Those skilled in the art will appreciate that the foregoing examples and embodiments are illustrative and do not limit the scope of the present disclosure. It is intended that all permutations, enhancements, equivalents, combinations, and improvements that are apparent to those skilled in the art upon reading the specification and studying the drawings are included within the true spirit and scope of the present disclosure. It should also be noted that the elements of any claim may be arranged differently, including having multiple dependencies, configurations, and combinations.

Claims

1. A method for wireless network convergence, comprising: determining one or more channel conditions of a first wireless link coupling a user equipment (UE) to a first wireless station and a second wireless link coupling the UE to a second first wireless station based on the one or more measurements; retrieving historical data regarding the first wireless station and the second wireless station; as well as Based at least on the one or more channel conditions of the first radio link and the second radio link and the historical data, quality of service (QoS) aware scheduling for traffic involving the UE is performed at a cognitive layer for at least one of the first radio link and the second radio link.

2. The method according to claim 1, wherein: The first wireless link is established using a first wireless technology, and the second wireless link is established using a second wireless technology different from the first wireless technology.

3. The method according to claim 2, wherein: The first wireless link is a Wi-Fi link and the second wireless link is a 5G New Radio (NR) link, the first wireless station is a Wi-Fi access point, and the second wireless station is a 5G gNodeB (gNB).

4. The method according to claim 1, wherein: The one or more channel conditions for the first wireless link and the second wireless link include one or more of the following: Signal strength; Signal-to-noise ratio (SNR); Data ratio; Throughput; Current load information; Signal interference from neighboring wireless access points using the same channel; Cellular interference from other macro cells or nearby small cells; Traffic or channel congestion on the first radio link and the second radio link; as well as Error rate.

5. The method according to claim 1, wherein: The historical data includes historical user preferences for traffic allocation, historical traffic allocation for the UE and other UEs served by the first wireless station and the second wireless station.

6. The method according to claim 1, wherein: The first wireless station and the second wireless station are separate devices or are integrated together as a single wireless station capable of supporting both the first wireless link and the second wireless link.

7. The method according to claim 1, wherein: The QoS-aware scheduling is further based on load information of the service to be scheduled, wherein the load information includes load type, size, data rate, delay requirement, and bandwidth required or preferred for service transmission.

8. The method according to claim 1, further comprising: converting, using a protocol converter, at least a portion of the traffic involving the UE into a converted data stream to be sent via a redirected radio link, the redirected radio link being different from an initial radio link originally scheduled for traffic transmission, the redirected radio link and the initial radio link being from the first radio link and the second radio link; as well as The converted data stream is transmitted via the redirected wireless link at one or more scheduled time slots.

9. The method according to claim 8, wherein: Converting the at least part of the service involving the UE includes: separating an original preamble from said at least a portion of said traffic; and A substitute preamble required for data transmission over the redirected wireless link is added.

10. A method for wireless network convergence, comprising: identifying, at a cognitive layer, a user equipment (UE) connected on a first wireless link to a first wireless station and a second wireless link to a second wireless station; At the cognitive layer, scheduling, across the first radio link and the second radio link, traffic redirection of at least a portion of the data flow at one or more scheduled time slots based at least on one or more channel conditions of the first radio link and the second radio link, user preferences, and information of the data flow, the data flow being scheduled to be sent or being sent on an initial radio link, the initial radio link being one of the first radio link and the second radio link; converting, using a protocol converter, the at least a portion of the data stream into a converted data stream to be sent via a redirected wireless link, the redirected wireless link being one of the first wireless link and the second wireless link and different from the initial wireless link; as well as The converted data stream is transmitted via the redirected wireless link at the one or more scheduled time slots.

11. The method according to claim 10, wherein: The first wireless link is a Wi-Fi link and the second wireless link is a 5G New Radio (NR) link, the first wireless station is a Wi-Fi access point, and the second wireless station is a 5G gNodeB (gNB).

12. The method according to claim 10, wherein: The first wireless link is a first Wi-Fi link, and the second wireless link is a second Wi-Fi link at a different frequency band than the first Wi-Fi link.

13. The method according to claim 10, wherein: The data flow is a downlink data flow or an uplink data flow, and the information of the data flow includes a load type, size, data rate, delay requirement, and required or preferred bandwidth.

14. The method according to claim 10, wherein: Converting the at least part of the service involving the UE includes: separating an original preamble from said at least a portion of said data stream; A substitute preamble required for data transmission over the redirected wireless link is added.

15. The method according to claim 10, wherein: Converting the at least part of the service involving the UE includes: When the data stream is a 5G data stream scheduled to be sent or being sent, at least a portion of the 5G data stream is re-split into 5G data plane data and 5G control plane data.

16. A non-transitory computer readable medium comprising one or more instruction sequences, which when executed by at least one processor, cause steps for wireless network convergence to be performed, including: determining one or more channel conditions of a first wireless link coupling a user equipment (UE) to a first wireless station and a second wireless link coupling the UE to a second first wireless station based on the one or more measurements; retrieving historical data regarding the first wireless station and the second wireless station; as well as Quality of service (QoS)-aware scheduling of a service involving the UE is performed for at least one of the first radio link and the second radio link based at least on the one or more channel conditions of the first radio link and the second radio link, the historical data, and load information of the service to be scheduled.

17. The non-transitory computer readable medium of claim 16, wherein: The one or more channel conditions of the first wireless link and the second wireless link include one or more of the following: Signal strength; Signal-to-noise ratio (SNR); Data ratio; Throughput; Current load information; Signal interference from neighboring wireless access points using the same channel; Cellular interference from other macro cells or nearby small cells; Traffic or channel congestion on the first radio link and the second radio link; as well as Error rate.

18. The non-transitory computer readable medium of claim 16, wherein: The historical data includes: historical user preferences for traffic allocation, historical traffic allocation for the UE and other UEs served by the first wireless station and the second wireless station.

19. The non-transitory computer readable medium of claim 16, wherein: The load information includes: load type, size, data rate, delay requirement, and bandwidth required or preferred for service transmission.

20. The non-transitory computer readable medium of claim 15, further comprising one or more sequences of instructions that, when executed by at least one processor, cause execution of the steps comprising: converting, using a protocol converter, at least a portion of the traffic involving the UE into a converted data stream to be sent via a redirected radio link, the redirected radio link being different from an initial radio link originally scheduled for traffic transmission, the redirected radio link and the initial radio link being from the first radio link and the second radio link; and The converted data stream is transmitted via the redirected wireless link at one or more scheduled time slots.

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