WO2021090101A1 - Sensibilisation à la charge de couche de réseau de transport pour architectures de noeuds de réseau désagrégés - Google Patents

Sensibilisation à la charge de couche de réseau de transport pour architectures de noeuds de réseau désagrégés Download PDF

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Publication number
WO2021090101A1
WO2021090101A1 PCT/IB2020/059945 IB2020059945W WO2021090101A1 WO 2021090101 A1 WO2021090101 A1 WO 2021090101A1 IB 2020059945 W IB2020059945 W IB 2020059945W WO 2021090101 A1 WO2021090101 A1 WO 2021090101A1
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WIPO (PCT)
Prior art keywords
load information
fronthaul
backhaul
link
network node
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PCT/IB2020/059945
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English (en)
Inventor
Andres ARJONA
Subramanya CHANDRASHEKAR
Hakon Helmers
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Nokia Technologies Oy
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Publication of WO2021090101A1 publication Critical patent/WO2021090101A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/08—Configuration management of networks or network elements
    • H04L41/0803—Configuration setting
    • H04L41/0813—Configuration setting characterised by the conditions triggering a change of settings
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/20—Control channels or signalling for resource management
    • H04W72/29—Control channels or signalling for resource management between an access point and the access point controlling device

Definitions

  • FIELD [0001] Some example embodiments may generally relate to mobile or wireless telecommunication systems, such as Long Term Evolution (LTE) or fifth generation (5G) radio access technology or new radio (NR) access technology, or other communications systems.
  • LTE Long Term Evolution
  • 5G fifth generation
  • NR new radio
  • certain embodiments may relate to systems and/or methods for transport network layer load awareness for disaggregated network node architectures.
  • Examples of mobile or wireless telecommunication systems may include the Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (UTRAN), Long Term Evolution (LTE) Evolved UTRAN (E-UTRAN), LTE-Advanced (LTE- A), MulteFire, LTE- A Pro, and/or fifth generation (5G) radio access technology or new radio (NR) access technology.
  • UMTS Universal Mobile Telecommunications System
  • UTRAN Universal Mobile Telecommunications System
  • LTE Long Term Evolution
  • E-UTRAN Evolved UTRAN
  • LTE-A LTE-Advanced
  • MulteFire LTE- A Pro
  • LTE- A Pro LTE- A Pro
  • 5G wireless systems refer to the next generation (NG) of radio systems and network architecture.
  • 5G is mostly built on a new radio (NR), but a 5G (or NG) network can also build on E-UTRA radio.
  • NR may provide bitrates on the order of 10-20 Gbit/s or higher, and may support at least enhanced mobile broadband (eMBB) and ultra-reliable low-latency-communication (URLLC) as well as massive machine type communication (mMTC).
  • eMBB enhanced mobile broadband
  • URLLC ultra-reliable low-latency-communication
  • mMTC massive machine type communication
  • NR is expected to deliver extreme broadband and ultra-robust, low latency connectivity and massive networking to support the Internet of Things (IoT).
  • IoT Internet of Things
  • M2M machine-to-machine
  • the nodes that can provide radio access functionality to a user equipment may be named gNB when built on NR radio and may be named NG-eNB when built on E-UTRA radio.
  • a method may include receiving fronthaul load information associated with one or more distributed units (DUs) associated with the network node and backhaul load information associated with one or more central unit-user planes (CU-UPs) associated with the network node.
  • the method may include providing, to one or more peer nodes, at least one report that includes at least one subset of the fronthaul load information and the backhaul load information.
  • the fronthaul load information and the backhaul load information may be reported separately.
  • the fronthaul load information may identify at least one fronthaul transport network layer (TNL) load for at least one fronthaul link and the backhaul load information may identify at least one backhaul transport network layer (TNL) load for at least one backhaul link.
  • receiving the fronthaul load information may further comprise receiving the fronthaul load information from the one or more distributed units (DUs) via at least one FI interface.
  • receiving the backhaul load information may further comprise receiving the backhaul load information from the one or more central unit-user planes (CU-UPs) via at least one El interface.
  • DUs distributed units
  • receiving the backhaul load information may further comprise receiving the backhaul load information from the one or more central unit-user planes (CU-UPs) via at least one El interface.
  • CU-UPs central unit-user planes
  • the method may further comprise determining the at least one subset of the fronthaul load information and the backhaul load information.
  • determining the at least one subset may comprise determining the at least one subset based on whether one or more cells, with which the fronthaul load information or the backhaul load information is associated, have overlapping coverage with the one or more peer nodes.
  • determining the at least one subset of the fronthaul load information and the backhaul load information may further comprise determining the at least one subset of the fronthaul load information and the backhaul load information using at least one automatic neighbor relation (ANR) table to identify one or more other distributed units (DUs) associated with the peer node and identifying one or more other central unit- user planes (CU-UPs) based on identifying the one or more other distributed units (DUs).
  • ANR automatic neighbor relation
  • the method may further comprise modifying a granularity of the fronthaul load information or the backhaul load information included in the at least one report prior to providing the at least one report to the one or more peer nodes.
  • modifying the granularity may further comprise modifying the granularity to provide at least one aggregated transport network layer (TNL) load per Fl-user plane (Fl-U), Sl-user plane (Sl-U), next generation-user plane (NG-U) link, or to provide details on a per-network slice or a per-cell level.
  • TNL transport network layer
  • the method may further comprise transmitting, to at least one system, at least one other report that includes one or more statistics or counters related to link utilization of at least one backhaul link or at least one fronthaul link.
  • at least one of the one or more peer nodes may be related to mobility or dual connectivity of one or more user equipment (UEs).
  • UEs user equipment
  • a method may include receiving at least one report that includes fronthaul load information and backhaul load information. The fronthaul load information and the backhaul load information may be reported separately. The fronthaul load information may be associated with at least one fronthaul link and the backhaul information may be associated with at least one backhaul link.
  • the at least one fronthaul link and the at least one backhaul link may be associated with at least one cell that overlaps with the network node.
  • the method may include processing the fronthaul load information and the backhaul load information after receiving the fronthaul load information and the backhaul load information.
  • the fronthaul load information may identify at least one fronthaul transport network layer (TNF) load for at least one fronthaul link and the backhaul load information may identify at least one backhaul transport network layer (TNF) load for at least one backhaul link.
  • processing the fronthaul load information and the backhaul load information may further comprise identifying first congestion on at least one fronthaul link based on the fronthaul load information or second congestion on at least one backhaul link based on the backhaul load information.
  • a third embodiment may be directed to an apparatus including at least one processor and at least one memory comprising computer program code.
  • the at least one memory and computer program code may be configured, with the at least one processor, to cause the apparatus at least to perform the method according to the first embodiment or the second embodiment, or any of the variants discussed above.
  • a fourth embodiment may be directed to an apparatus that may include circuitry configured to perform the method according to the first embodiment or the second embodiment, or any of the variants discussed above.
  • a fifth embodiment may be directed to an apparatus that may include means for performing the method according to the first embodiment or the second embodiment, or any of the variants discussed above.
  • a sixth embodiment may be directed to a computer readable medium comprising program instructions stored thereon for performing at least the method according to the first embodiment or the second embodiment, or any of the variants discussed above.
  • a seventh embodiment may be directed to a computer program product encoding instructions for performing at least the method according to the first embodiment or the second embodiment, or any of the variants discussed above.
  • Fig. 1 illustrates an example system including a network node with a disaggregated architecture and a relation of the network node to external peers, according to some embodiments;
  • Fig. 2 illustrates example operations of a network node and a peer node, according to some embodiments;
  • FIG. 3 illustrates an example flow diagram of a method, according to some embodiments
  • FIG. 4 illustrates an example flow diagram of a method, according to some embodiments
  • Fig. 5a illustrates an example block diagram of an apparatus, according to an embodiment
  • Fig. 5b illustrates an example block diagram of an apparatus, according to another embodiment.
  • 4G LTE may include a way to report TNL load between network nodes (e.g., eNBs).
  • this load may refer to resource utilization in the backhaul interface towards the core network, where user traffic is transported and which assumes the network node is a single unit.
  • multiple intra-network node (gNB) interfaces may be introduced, meaning that a bottleneck in transport resources is not limited to backhaul links toward the core network, but may be in fronthaul links within the network node. This is not considered in 4G LTE.
  • a different approach may be needed in 5G in order to provide a way for a network node to assess internal interfaces TNL load, and to provide a representative report to its external peers (e.g., a neighbour gNB or a master node (master gNB) in the case of dual connectivity).
  • a network node e.g., a neighbour gNB or a master node (master gNB) in the case of dual connectivity.
  • master gNB master node
  • 4G LTE may have a way to report TNL load between network nodes (eNBs). This may be useful in order for a source network node to be aware of whether a target network node is able to handle incoming user traffic in a transport network towards the core network (e.g., an Sl-user plane (Sl-U) interface).
  • the transport network in an operator network may be under-dimensioned and may not be able to handle peak throughput in cells associated with a given network node.
  • the TNL load may help to identify whether transport resources are low at the target network node (even if air interface resources are available in some of the network node cells).
  • neighboring network nodes may avoid overloading a network node that is at risk of exhausting its transport resources, and that may lead to throughput degradation, or in worse scenarios, dropped calls.
  • a disaggregated architecture that includes additional interfaces within the network node may be introduced.
  • the network node may no longer be a monolithic unit and, instead, may be split into several logical entities that do not have to be co located or to belong to the same vendor. Lurther, considering virtualized scenarios, a single network node may cover a large geographic area and a high number of cells.
  • a network node may be split to have the following additional intra-network node interfaces: 3GPP based Pl-control plane (Ll-C) (e.g., between a gNB-central unit-control plane (gNB-CU-CP) and gNB distributed unit (gNB-DU) and Ll-user plane (Pl-U) (between a gNB central unit-user plane (gNB-CU-UP) and a gNB-DU) interfaces or 3GPP-based El-control plane (El-C) (e.g., between a gNB-CU-CP and a gNB-CU- UP).
  • Ll-C 3GPP based Pl-control plane
  • El-C El-control plane
  • the problem with the solution existing in 4G LTE is that it may not be directly applicable for the disaggregated architecture of 5G, as bottlenecks may occur in intra-network node fronthaul links utilized to reach a cell, rather than on the backhaul links providing connectivity to the core network.
  • an improved approach may have to be used in 5G in order for informed decisions to be made at peer nodes based on precise load information of the reporting node (since reporting the load in the backhaul TNL towards core network may not discriminate between issues encountered in intra-network node links). That is, reporting a backhaul value may not mean that data can traverse from a user equipment (UE) towards the core network (since a bottleneck can be in an intra-network node interface).
  • UE user equipment
  • the number of internal interfaces may be considerably increased.
  • the problem that may have to be resolved may include how to report, and which links shall be reported, to an external entity.
  • not all backhaul links or fronthaul links may be a bottleneck for user traffic from an external node. For instance, if MeNB cells have an overlap with cells in a gNB-DUl, then the Fl-U fronthaul from a gNB-CU-UPl and a Sl-U/NG-U backhaul link towards a core network may be relevant, as other links may not be involved in a UE’s user plane traffic. Therefore, reporting neither a single backhaul link (as in the existing LTE solution) nor reporting all links may be suitable solutions as the external entity may not have information regarding which gNB interfaces should be considered.
  • 4G LTE may have an existing TNL Load reporting based on backhaul links towards a core network.
  • TNL load at the network node may be reported over an X2 application protocol (X2AP) interface.
  • 5G may include the possibility to copy the same information element (IE) definition and mechanism existing in 4G LTE and may introduce it in 5G to report TNL load at a gNB -DU reported over an FI application protocol (F1AP), to report TNL load at a gNB-CU-UP reported over an El application protocol (E1AP), to report TNL load at a gNB reported over the X2AP, and/or to report TNL load at a gNB reported over a XnAP.
  • IE information element
  • Reporting TNL load over F1AP may not apply to backhaul links toward a core network since the gNB -DU may not be aware of such resources as it has no direct connection to the core network. Instead, reporting TNL load over the F1AP may apply to the link between the gNB -DU and gNB-CU (e.g., the higher layer split fronthaul Fl-U interface). This may only be of limited use for a gNB-CU-CP, as even though it can be used to decide whether to select a different gNB-DU under its control for certain bearer establishment, this bottleneck may not be taken into account when TNL load is reported to an external node.
  • the report from the target node would indicate the backhaul TNL load only if the existing LTE approach is taken. This is misleading, as the backhaul may very well have sufficient resources (as a gNB-CU may host hundreds of cells) despite the network node having transport resource exhaustion in one or multiple fronthaul links used to reach some particular cells.
  • Some embodiments described herein may provide a network node (e.g., a gNB-CU-CP) that is capable of making an explicit discrimination of backhaul and fronthaul TNL load when providing a report to an external peer node (e.g., a Master gNB, a peer gNB, and/or the like) requesting load of the network node.
  • an external peer node e.g., a Master gNB, a peer gNB, and/or the like
  • a network node e.g., a gNB-CU
  • FI load of DUs may not be of any use for the external peers as the external peers may be unaware of which links are used to reach any particular cell.
  • some embodiments described herein may provide a network node (e.g., a gNB- CU-CP) that is capable of reporting the fronthaul and backhaul links (e.g., FI and El interfaces, respectively) that are relevant for an external entity.
  • a network node e.g., a gNB- CU-CP
  • Whether a cell is relevant to an external node may depend on whether the cell has overlapping coverage with that of the external node (e.g., a handover (HO) trigger or a dual connectivity activation trigger).
  • a way to achieve this may include utilizing a automatic neighbor relation (ANR) table at the network node (e.g., the gNB-CU-CP) to decide the fronthaul links to report.
  • ANR automatic neighbor relation
  • the DUs (other network nodes) for which the load information may be reported to the peer node may be identified from the ANR table, while the CU-UPs (other network nodes) may be selected based on the cells/DUs that they serve. This information may be reported by CU-UPs during the El setup procedure.
  • some embodiments described herein may provide an indication to an external peer node that indicates whether there are bottlenecks existing in the gNB (as an example network node) it relates to, which gNBs are experiencing bottlenecks, to what extent the bottlenecks are occurring, and/or the like. With this information, the external peer node may perform a more intelligent decision regarding whether to have user traffic (or only some part of it) directed to such gNB or whether to make a different selection.
  • Fig. 1 illustrates an example system including a network node with a disaggregated architecture and a relation of the network node to external peers, according to some embodiments.
  • Fig. 1 illustrates various networks and network nodes, such as a core network 100 (e.g., a core networkl), a core network 102 (e.g., a core network2), a network node 104 (e.g., a MeNB), a network node 106 (e.g., a gNB), and a network node 108 (e.g., a neighbor gNB/Master node).
  • a core network 100 e.g., a core networkl
  • a core network 102 e.g., a core network2
  • a network node 104 e.g., a MeNB
  • a network node 106 e.g., a gNB
  • a network node 108 e.g., a neighbor gNB/
  • the network node 106 may include a gNB-CU-CP 110, gNB-CU-UPs 112 and 114, and gNB -DUs 116, 118, and 120.
  • the gNB-CU-CP 110, gNB-CU-UPs 112 and 114, and gNB -DUs 116, 118, and 120 may be network nodes as described herein.
  • the gNB-CU-CP 110 may receive fronthaul and backhaul TNL load.
  • the TNL load at one or more backhaul links may be received from gNB-CU-UPs 112, 114 under its control (e.g., related to Sl/NG interfaces) and reported over an El interface.
  • the TNL load at one or more fronthaul links may be received from gNB-DUs 116, 118, 120 under its control (e.g., related to FI interfaces) and reported over an FI interface.
  • the gNB-CU-CP 110 may make an evaluation of the links that are relevant to its external peer network nodes. For example, the gNB-CU-CP 112 may utilize an ANR table to determine which cells under its control are relevant/related to the cells associated with the external peer network nodes and which backhaul and fronthaul links would be involved to transfer user traffic across them. The gNB-CU-CP 110 may report the relevant backhaul and fronthaul TNL loads separately to the external peer network nodes.
  • the gNB-CU-CP 110 may modify (e.g., increase or decrease) a granularity in the reports provided towards the external peer network nodes depending on the information received from gNB- DUs 116, 118, 120 or the gNB-CU-UPs 112, 114.
  • the gNB-CU-CP 110 may provide an aggregated TNL Load per F1-U/S1-U/NG-U link, or may provide more or less granular details on a per-slice or a per-cell level, taking into account for instance, links involved in certain slices and/or cells.
  • the gNB-CU-CP 110 may report statistics and counters on link utilization in both backhaul and fronthaul links towards an operations and maintenance (O&M) system, for purposes of optimization (e.g., longer term optimization), network dimensioning and/or planning purposes (e.g., increasing capacity in certain areas, add more cells in certain areas, etc.), and/or the like.
  • O&M operations and maintenance
  • an external peer may be a node involved in mobility (e.g., a handover (HO) to and/or from) or dual connectivity (e.g., activation, modification, and/or deactivation) related events toward a node with a disaggregated architecture.
  • Certain embodiments described herein may apply to disaggregated architectures for LTE, such as those with a fronthaul interface Wl. Certain embodiments described herein may be based on changes in the 3GPP interfaces from a gNB towards its peer nodes (e.g., Xn, X2 interfaces) to add the above mentioned information while exchanging load reports.
  • a gNB e.g., Xn, X2 interfaces
  • Fig. 1 is provided as an example. Other examples are possible, according to some embodiments.
  • Fig. 2 illustrates example operations of a network node and a peer node, according to some embodiments.
  • Fig. 2 illustrates a network node 106 (e.g., a gNB) that includes one or more gNB CU- UPs 112, 114 and/or gNB DUs 116, 118, 120.
  • Fig. 2 illustrates a gNB CU-CP 110 included in the network node 106.
  • Fig. 2 illustrates a peer network node 204 in communication with the network node 106.
  • the gNB CU-UPs 112, 114 may provide backhaul load information to the gNB CU-CP 110 and the gNB DUs 116, 118, 120 may provide fronthaul load information to the gNB CU-CP 110, as described elsewhere herein.
  • the gNB CU-CP 110 may provide, to the peer network node 204, a report that includes a subset of the fronthaul load information and the backhaul load information (e.g., that is relevant to the peer network node 204), as described elsewhere herein.
  • the fronthaul load information and the backhaul load information may be reported separately (e.g., may be included as separate data sets in the report).
  • the peer network node 204 may process the fronthaul load information and the backhaul load information included in the report after receiving the report. For example, the peer network node 204 may identify congestion on a fronthaul link or a backhaul link.
  • Fig. 2 is provided as an example. Other examples are possible, according to some embodiments.
  • Fig. 3 illustrates an example flow diagram of a method, according to some embodiments.
  • Fig. 3 shows example operations of a network node (e.g., gNB CU-CP 110 and/or apparatus 10). Some of the operations illustrated in Fig. 3 may be similar to some operations shown in, and described with respect to, Figs. 1 and 2.
  • the method may include, at 300, receiving fronthaul load information associated with one or more distributed units (DUs) associated with the network node and backhaul load information associated with one or more central unit-user planes (CU-UPs) associated with the network node.
  • a gNB CU-CP 110 may receive fronthaul load information associated with one or more distributed units (DUs) associated with the gNB CU-CP 110 and backhaul load information associated with one or more central unit-user planes (CU-UPs) associated with the gNB CU-CP 110.
  • DUs distributed units
  • CU-UPs central unit-user planes
  • the method may include, at 302, providing, to one or more peer nodes, at least one report that includes at least one subset of the fronthaul load information and the backhaul load information.
  • the fronthaul load information and the backhaul load information may be reported separately.
  • the gNB CU-CP 110 may provide, to one or more peer network nodes 204, at least one report that includes at least one subset of the fronthaul load information and the backhaul load information.
  • the fronthaul load information and the backhaul load information may be reported separately.
  • the fronthaul load information may identify at least one fronthaul transport network layer (TNL) load for at least one fronthaul link and the backhaul load information may identify at least one backhaul transport network layer (TNL) load for at least one backhaul link.
  • receiving the fronthaul load information may further comprise receiving the fronthaul load information from the one or more distributed units (DUs) via at least one FI interface.
  • receiving the backhaul load information may further comprise receiving the backhaul load information from the one or more central unit-user planes (CU-UPs) via at least one El interface.
  • DUs distributed units
  • receiving the backhaul load information may further comprise receiving the backhaul load information from the one or more central unit-user planes (CU-UPs) via at least one El interface.
  • CU-UPs central unit-user planes
  • the method may further comprise determining the at least one subset of the fronthaul load information and the backhaul load information. In some embodiments, determining the at least one subset may comprise determining the at least one subset based on whether one or more cells, with which the fronthaul load information or the backhaul load information is associated, have overlapping coverage with the one or more peer nodes.
  • determining the at least one subset of the fronthaul load information and the backhaul load information may further comprise determining the at least one subset of the fronthaul load information and the backhaul load information using at least one automatic neighbor relation (ANR) table to identify one or more other distributed units (DUs) associated with the peer node and identifying one or more other central unit-user planes (CU-UPs) based on identifying the one or more other distributed units (DUs).
  • ANR automatic neighbor relation
  • the method may further comprise modifying a granularity of the fronthaul load information or the backhaul load information included in the at least one report prior to providing the at least one report to the one or more peer nodes.
  • modifying the granularity may further comprise modifying the granularity to provide at least one aggregated transport network layer (TNL) load per FI -user plane (Fl-U), Sl-userplane (Sl-U), next generation- user plane (NG-U) link, or to provide details on a per-network slice or a per-cell level.
  • TNL transport network layer
  • the method may further comprise transmitting, to at least one system, at least one other report that includes one or more statistics or counters related to link utilization of at least one backhaul link or at least one fronthaul link.
  • at least one of the one or more peer nodes is related to mobility or dual connectivity of one or more user equipment (UEs).
  • UEs user equipment
  • Fig. 4 illustrates an example flow diagram of a method, according to some embodiments.
  • Fig. 4 shows example operations of a network node (e.g., a peer network node 204 and/or an apparatus 20). Some of the operations illustrated in Fig. 4 may be similar to some operations shown in, and described with respect to, Figs. 1 and 2.
  • the method may include, at 400, receiving at least one report that includes fronthaul load information and backhaul load information.
  • the peer network node 204 may receive at least one report that includes fronthaul load information and backhaul load information.
  • the fronthaul load information and the backhaul load information may be reported separately.
  • the fronthaul load information may be associated with at least one fronthaul link and the backhaul information is associated with at least one backhaul link.
  • the at least one fronthaul link and the at least one backhaul link may be associated with at least one cell that overlaps with the network node.
  • the method may include, at 402, processing the fronthaul load information and the backhaul load information after receiving the fronthaul load information and the backhaul load information.
  • the peer network node 204 may process the fronthaul load information and the backhaul load infor ation after receiving the fronthaul load information and the backhaul load information.
  • the fronthaul load information may identify at least one fronthaul transport network layer (TNL) load for at least one fronthaul link and the backhaul load information may identify at least one backhaul transport network layer (TNL) load for at least one backhaul link.
  • processing the fronthaul load information and the backhaul load information may further comprise identifying first congestion on at least one fronthaul link based on the fronthaul load information or second congestion on at least one backhaul link based on the backhaul load information.
  • Fig. 4 is provided as an example. Other examples are possible according to some embodiments.
  • apparatus 10 may be a node, host, or server in a communications network or serving such a network.
  • apparatus 10 may be a network node (e.g., network node 110), satellite, base station, a Node B, an evolved Node B (eNB), 5G Node B or access point, next generation Node B (NG-NB or gNB), and/or a WLAN access point, associated with a radio access network, such as a LTE network, 5G or NR.
  • apparatus 10 may be an eNB in LTE or gNB in 5G.
  • apparatus 10 may be comprised of an edge cloud server as a distributed computing system where the server and the radio node may be stand-alone apparatuses communicating with each other via a radio path or via a wired connection, or they may be located in a same entity communicating via a wired connection.
  • apparatus 10 represents a gNB
  • it may be configured in a central unit (CU) and distributed unit (DU) architecture that divides the gNB functionality.
  • the CU may be a logical node that includes gNB functions such as transfer of user data, mobility control, radio access network sharing, positioning, and/or session management, etc.
  • the CU may control the operation of DU(s) over a front-haul interface.
  • the DU may be a logical node that includes a subset of the gNB functions, depending on the functional split option. It should be noted that one of ordinary skill in the art would understand that apparatus 10 may include components or features not shown in Fig. 5a.
  • apparatus 10 may include a processor 12 for processing information and executing instructions or operations.
  • processor 12 may be any type of general or specific purpose processor.
  • processor 12 may include one or more of general- purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), and processors based on a multi-core processor architecture, as examples. While a single processor 12 is shown in Fig. 5a, multiple processors may be utilized according to other embodiments.
  • apparatus 10 may include two or more processors that may form a multiprocessor system (e.g., in this case processor 12 may represent a multiprocessor) that may support multiprocessing.
  • processor 12 may represent a multiprocessor
  • the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster).
  • Processor 12 may perform functions associated with the operation of apparatus 10, which may include, for example, precoding of antenna gain/phase parameters, encoding and decoding of individual bits forming a communication message, formatting of information, and overall control of the apparatus 10, including processes related to management of communication resources.
  • Apparatus 10 may further include or be coupled to a memory 14 (internal or external), which may be coupled to processor 12, for storing information and instructions that may be executed by processor 12.
  • Memory 14 may be one or more memories and of any type suitable to the local application environment, and may be implemented using any suitable volatile or nonvolatile data storage technology such as a semiconductor-based memory device, a magnetic memory device and system, an optical memory device and system, fixed memory, and/or removable memory.
  • memory 14 can be comprised of any combination of random access memory (RAM), read only memory (ROM), static storage such as a magnetic or optical disk, hard disk drive (F1DD), or any other type of non-transitory machine or computer readable media.
  • the instructions stored in memory 14 may include program instructions or computer program code that, when executed by processor 12, enable the apparatus 10 to perform tasks as described herein.
  • apparatus 10 may further include or be coupled to (internal or external) a drive or port that is configured to accept and read an external computer readable storage medium, such as an optical disc, USB drive, flash drive, or any other storage medium.
  • an external computer readable storage medium such as an optical disc, USB drive, flash drive, or any other storage medium.
  • the external computer readable storage medium may store a computer program or software for execution by processor 12 and/or apparatus 10.
  • apparatus 10 may also include or be coupled to one or more antennas 15 for transmitting and receiving signals and/or data to and from apparatus 10.
  • Apparatus 10 may further include or be coupled to a transceiver 18 configured to transmit and receive information.
  • the transceiver 18 may include, for example, a plurality of radio interfaces that may be coupled to the antenna(s) 15.
  • the radio interfaces may correspond to a plurality of radio access technologies including one or more of GSM, NB-IoT, LTE, 5G, WLAN, Bluetooth, BT-LE, NFC, radio frequency identifier (RFID), ultrawideband (UWB), MulteFire, and the like.
  • the radio interface may include components, such as filters, converters (for example, digital-to-analog converters and the like), mappers, a Fast Fourier Transform (FFT) module, and the like, to generate symbols for a transmission via one or more downlinks and to receive symbols (for example, via an uplink).
  • transceiver 18 may be configured to modulate information on to a carrier waveform for transmission by the antenna(s) 15 and demodulate information received via the antenna(s) 15 for further processing by other elements of apparatus 10.
  • transceiver 18 may be capable of transmitting and receiving signals or data directly.
  • apparatus 10 may include an input and/or output device (I/O device).
  • memory 14 may store software modules that provide functionality when executed by processor 12.
  • the modules may include, for example, an operating system that provides operating system functionality for apparatus 10.
  • the memory may also store one or more functional modules, such as an application or program, to provide additional functionality for apparatus 10.
  • the components of apparatus 10 may be implemented in hardware, or as any suitable combination of hardware and software.
  • processor 12 and memory 14 may be included in or may form a part of processing circuitry or control circuitry.
  • transceiver 18 may be included in or may form a part of transceiver circuitry.
  • circuitry may refer to hardware-only circuitry implementations (e.g., analog and/or digital circuitry), combinations of hardware circuits and software, combinations of analog and/or digital hardware circuits with software/firmware, any portions of hardware processor(s) with software (including digital signal processors) that work together to case an apparatus (e.g., apparatus 10) to perform various functions, and/or hardware circuit(s) and/or processor(s), or portions thereof, that use software for operation but where the software may not be present when it is not needed for operation.
  • hardware-only circuitry implementations e.g., analog and/or digital circuitry
  • combinations of hardware circuits and software e.g., combinations of analog and/or digital hardware circuits with software/firmware
  • any portions of hardware processor(s) with software including digital signal processors
  • circuitry may also cover an implementation of merely a hardware circuit or processor (or multiple processors), or portion of a hardware circuit or processor, and its accompanying software and/or firmware.
  • the term circuitry may also cover, for example, a baseband integrated circuit in a server, cellular network node or device, or other computing or network device.
  • apparatus 10 may be a network node or RAN node, such as a base station, access point, Node B, eNB, gNB, WLAN access point, or the like.
  • apparatus 10 may be controlled by memory 14 and processor 12 to perform the functions associated with any of the embodiments described herein, such as some operations of flow or signaling diagrams illustrated in Figs. 1-4.
  • apparatus 10 may be controlled by memory 14 and processor 12 to receive fronthaul load information associated with one or more distributed units (DUs) associated with the apparatus 10 and backhaul load information associated with one or more central unit-user planes (CU-UPs) associated with the apparatus 10.
  • apparatus 10 may be controlled by memory 14 and processor 12 to provide, to one or more peer nodes, at least one report that includes at least one subset of the fronthaul load information and the backhaul load information. The fronthaul load information and the backhaul load information may be reported separately.
  • apparatus 20 may be a node, host, or server in a communications network or serving such a network.
  • apparatus 20 may be a network node (e.g., a peer network node 204), satellite, base station, a Node B, an evolved Node B (eNB), 5G Node B or access point, next generation Node B (NG-NB or gNB), and/or a WLAN access point, associated with a radio access network, such as a LTE network, 5G or NR.
  • apparatus 20 may be an eNB in LTE or gNB in 5G.
  • apparatus 20 may be comprised of an edge cloud server as a distributed computing system where the server and the radio node may be stand-alone apparatuses communicating with each other via a radio path or via a wired connection, or they may be located in a same entity communicating via a wired connection.
  • apparatus 20 represents a gNB
  • it may be configured in a central unit (CU) and distributed unit (DU) architecture that divides the gNB functionality.
  • the CU may be a logical node that includes gNB functions such as transfer of user data, mobility control, radio access network sharing, positioning, and/or session management, etc.
  • the CU may control the operation of DU(s) over a front-haul interface.
  • the DU may be a logical node that includes a subset of the gNB functions, depending on the functional split option. It should be noted that one of ordinary skill in the art would understand that apparatus 20 may include components or features not shown in Fig. 5b.
  • apparatus 20 may include a processor 22 for processing information and executing instructions or operations.
  • Processor 22 may be any type of general or specific purpose processor.
  • processor 22 may include one or more of general- purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs), field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), and processors based on a multi-core processor architecture, as examples. While a single processor 22 is shown in Fig. 5b, multiple processors may be utilized according to other embodiments.
  • apparatus 20 may include two or more processors that may form a multiprocessor system (e.g. , in this case processor 22 may represent a multiprocessor) that may support multiprocessing.
  • the multiprocessor system may be tightly coupled or loosely coupled (e.g., to form a computer cluster).
  • Processor 22 may perform functions associated with the operation of apparatus 20, which may include, for example, precoding of antenna gain/phase parameters, encoding and decoding of individual bits forming a communication message, formatting of information, and overall control of the apparatus 20, including processes related to management of communication resources.
  • Apparatus 20 may further include or be coupled to a memory 24 (internal or external), which may be coupled to processor 22, for storing information and instructions that may be executed by processor 22.
  • Memory 24 may be one or more memories and of any type suitable to the local application environment, and may be implemented using any suitable volatile or nonvolatile data storage technology such as a semiconductor-based memory device, a magnetic memory device and system, an optical memory device and system, fixed memory, and/or removable memory.
  • memory 24 can be comprised of any combination of random access memory (RAM), read only memory (ROM), static storage such as a magnetic or optical disk, hard disk drive (F1DD), or any other type of non-transitory machine or computer readable media.
  • the instructions stored in memory 24 may include program instructions or computer program code that, when executed by processor 22, enable the apparatus 20 to perform tasks as described herein.
  • apparatus 20 may further include or be coupled to (internal or external) a drive or port that is configured to accept and read an external computer readable storage medium, such as an optical disc, USB drive, flash drive, or any other storage medium.
  • an external computer readable storage medium such as an optical disc, USB drive, flash drive, or any other storage medium.
  • the external computer readable storage medium may store a computer program or software for execution by processor 22 and/or apparatus 20.
  • apparatus 20 may also include or be coupled to one or more antennas 25 for transmitting and receiving signals and/or data to and from apparatus 20.
  • Apparatus 20 may further include or be coupled to a transceiver 28 configured to transmit and receive information.
  • the transceiver 28 may include, for example, a plurality of radio interfaces that may be coupled to the antenna(s) 25.
  • the radio interfaces may correspond to a plurality of radio access technologies including one or more of GSM, NB-IoT, LTE, 5G, WLAN, Bluetooth, BT-LE, NFC, radio frequency identifier (RFID), ultrawideband (UWB), MulteFire, and the like.
  • the radio interface may include components, such as filters, converters (for example, digital-to-analog converters and the like), mappers, a Fast Fourier Transform (FFT) module, and the like, to generate symbols for a transmission via one or more downlinks and to receive symbols (for example, via an uplink).
  • transceiver 28 may be configured to modulate information on to a carrier waveform for transmission by the antenna(s) 25 and demodulate information received via the antenna(s) 25 for further processing by other elements of apparatus 20.
  • transceiver 28 may be capable of transmitting and receiving signals or data directly.
  • apparatus 20 may include an input and/or output device (I/O device).
  • memory 24 may store software modules that provide functionality when executed by processor 22.
  • the modules may include, for example, an operating system that provides operating system functionality for apparatus 20.
  • the memory may also store one or more functional modules, such as an application or program, to provide additional functionality for apparatus 20.
  • the components of apparatus 20 may be implemented in hardware, or as any suitable combination of hardware and software.
  • processor 22 and memory 24 may be included in or may form a part of processing circuitry or control circuitry.
  • transceiver 28 may be included in or may form a part of transceiver circuitry.
  • apparatus 20 may be a network node or RAN node, such as a base station, access point, Node B, eNB, gNB, WLAN access point, or the like.
  • apparatus 20 may be controlled by memory 24 and processor 22 to perform the functions associated with any of the embodiments described herein, such as some operations of flow or signaling diagrams illustrated in Figs. 1-4.
  • apparatus 20 may be controlled by memory 24 and processor 22 to receive at least one report that includes fronthaul load information and backhaul load information.
  • the fronthaul load information and the backhaul load information may be reported separately.
  • the fronthaul load information may be associated with at least one fronthaul link and the backhaul information is associated with at least one backhaul link.
  • the at least one fronthaul link and the at least one backhaul link may be associated with at least one cell that overlaps with the network node.
  • apparatus 20 may be controlled by memory 24 and processor 22 to process the fronthaul load information and the backhaul load information after receiving the fronthaul load information and the backhaul load information.
  • certain example embodiments provide several technological improvements, enhancements, and/or advantages over existing technological processes.
  • one benefit of some example embodiments is improved decision-making regarding whether to have user traffic (or only some part of it) directed to a gNB, which may conserve processing resources, network resources, and/or the like that would otherwise be consumed due to less intelligent decisions.
  • the use of some example embodiments results in improved functioning of communications networks and their nodes and, therefore constitute an improvement at least to the technological field of network subscription management, among others.
  • any of the methods, processes, signaling diagrams, algorithms or flow charts described herein may be implemented by software and/or computer program code or portions of code stored in memory or other computer readable or tangible media, and executed by a processor.
  • an apparatus may be included or be associated with at least one software application, module, unit or entity configured as arithmetic operation(s), or as a program or portions of it (including an added or updated software routine), executed by at least one operation processor.
  • Programs also called program products or computer programs, including software routines, applets and macros, may be stored in any apparatus-readable data storage medium and may include program instructions to perform particular tasks.
  • a computer program product may include one or more computer-executable components which, when the program is run, are configured to carry out some example embodiments.
  • the one or more computer-executable components may be at least one software code or portions of code. Modifications and configurations required for implementing functionality of an example embodiment may be performed as routine(s), which may be implemented as added or updated software routine(s). In one example, software routine(s) may be downloaded into the apparatus.
  • software or a computer program code or portions of code may be in a source code form, object code form, or in some intermediate form, and it may be stored in some sort of carrier, distribution medium, or computer readable medium, which may be any entity or device capable of carrying the program.
  • Such carriers may include a record medium, computer memory, read-only memory, photoelectrical and/or electrical carrier signal, telecommunications signal, and/or software distribution package, for example.
  • the computer program may be executed in a single electronic digital computer or it may be distributed amongst a number of computers.
  • the computer readable medium or computer readable storage medium may be a non-transitory medium.
  • the functionality may be performed by hardware or circuitry included in an apparatus (e.g., apparatus 10 or apparatus 20), for example through the use of an application specific integrated circuit (ASIC), a programmable gate array (PGA), a field programmable gate array (FPGA), or any other combination of hardware and software.
  • the functionality may be implemented as a signal, such as a non tangible means that can be carried by an electromagnetic signal downloaded from the Internet or other network.
  • an apparatus such as a node, device, or a corresponding component, may be configured as circuitry, a computer or a microprocessor, such as single-chip computer element, or as a chipset, which may include at least a memory for providing storage capacity used for arithmetic operation(s) and/or an operation processor for executing the arithmetic operation(s).
  • Example embodiments described herein apply equally to both singular and plural implementations, regardless of whether singular or plural language is used in connection with describing certain embodiments. For example, an embodiment that describes operations of a single network node equally applies to embodiments that include multiple instances of the network node, and vice versa.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

Systèmes, procédés, appareils et produits programmes d'ordinateur pour la sensibilisation à la charge de couche de transport pour des architectures de nœuds de réseau désagrégés pouvant fournir un noeud de réseau (par exemple, un gNB-CU-CP) qui est capable de réaliser une discrimination explicite de la charge TNL backhaul et fronthaul lors de la fourniture d'un rapport à un noeud homologue externe (par exemple, un gNB maître, un gNB homologue, et/ou similaire) demandant la charge du noeud de réseau. Ainsi, certains modes de réalisation de la présente invention peuvent fournir un noeud de réseau (par exemple, un gNB-CU-CP) qui est capable de rapporter les liaisons fronthaul et backhaul (par exemple, des interfaces F1 et E1, respectivement) qui sont pertinentes pour une entité externe.
PCT/IB2020/059945 2019-11-06 2020-10-22 Sensibilisation à la charge de couche de réseau de transport pour architectures de noeuds de réseau désagrégés WO2021090101A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114615708A (zh) * 2022-05-11 2022-06-10 广州世炬网络科技有限公司 一种将终端均衡接入集中单元用户面的方法及装置

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018229299A1 (fr) * 2017-06-16 2018-12-20 Telefonaktiebolaget Lm Ericsson (Publ) Gestion de contexte d'équipement utilisateur dans un nœud d'accès radio désagrégé
US20180368109A1 (en) * 2017-06-16 2018-12-20 Kt Corporation Methods for managing resource based on open interface and apparatuses thereof
US20190075023A1 (en) * 2017-11-07 2019-03-07 Intel IP Corporation Transport network layer associations on the f1 interface
US20190075552A1 (en) * 2017-11-07 2019-03-07 Intel Corporation Enabling network slicing in a 5g network with cp/up separation

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018229299A1 (fr) * 2017-06-16 2018-12-20 Telefonaktiebolaget Lm Ericsson (Publ) Gestion de contexte d'équipement utilisateur dans un nœud d'accès radio désagrégé
US20180368109A1 (en) * 2017-06-16 2018-12-20 Kt Corporation Methods for managing resource based on open interface and apparatuses thereof
US20190075023A1 (en) * 2017-11-07 2019-03-07 Intel IP Corporation Transport network layer associations on the f1 interface
US20190075552A1 (en) * 2017-11-07 2019-03-07 Intel Corporation Enabling network slicing in a 5g network with cp/up separation

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114615708A (zh) * 2022-05-11 2022-06-10 广州世炬网络科技有限公司 一种将终端均衡接入集中单元用户面的方法及装置

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