Automated cloud ran deployment with latency constraints

Abstract

Methods and systems are described for a fast, sustainable, and automatic method to meet Cloud RAN service run-time requirements with the usage of Cloud Affinity methods. In some embodiments, for each installed RU a telecom operator can instantiate a special set of virtual functions, referred as Radio Affinity POD (RAPD), correlated with the RU in all the Cloud clusters that have compatible Cloud and Transport characteristics to host the RU relevant Distributed Unit (DU) services. The special RAPD images can contain the identification of the RU, microservices to expose the RU identity and affinity labels and, optionally, microservices to continuously monitor the communication status between the RU and the Cloud server to validate the expected latency assumptions. In certain embodiments, the RAPD can also provide additional telemetry and observability services.

Description

AUTOMATED CLOUD RAN DEPLOYMENT WITH LATENCY CONSTRAINTSTECHNICAL FIELD

[0001] The present disclosure generally relates to systems and methods to automate the deployment of Cloud Radio Access Network, Cloud RAN, while accommodating service runtime requirements.BACKGROUND

[0002] RAN deployments will eventually evolve towards Cloud RAN (Radio Access Network) for many mobile network operators, in particular in the most advanced 5G markets. Historically Packet Core is largely deployed on Cloud architectures, while RAN is typically deployed on purpose-built hardware where the Baseband Units and the Radio Units are quite close (e.g., 200 meters in Distributed RAN). Mobile RAN backhaul, between the Baseband Units and the Packet Core, is typically in the range of 40 km or more (round trip time up to 5ms) thanks to the characteristics of their 3 GPP standard interfaces.

[0003] Instead, Cloud RAN poses new challenges to the customer network infrastructures as it extends the distance between the Radio Units (RUs) (geographically distributed) and the Baseband Unit processes (referred as “BBU” or “RAN Compute”) that can be hosted on the Cloud Execution Environment.

[0004] The traditional Cloud Data Center model is not optimized for Cloud RAN since its execution environment is too far from the RU’s from latency perspective. Cloud RAN will require a Distributed Cloud architecture, able to provide RAN Compute (Baseband functions) closer to the physical Radios and composed by a Cloud RAN Transport Network and a Cloud RAN Execution Environment.Cloud RAN Transport

[0005] It is commonly recognized that the existing broadband access residential networks are not fit to support the stringent requirements posed by the RAN, from latency, throughput and QoS perspective.

[0006] At current state of art, in order to preserve the best RAN performances, the latency between RUs and RAN Compute (Baseband) functions should be limited to within lOOus while exceptions might be allowed with feature trade-offs on the RAN functionality.

[0007] Packet Fronthaul has been designed to transport the RAN services over the existing fiber infrastructure. In such a case, the only operator concern is the physical latency imposed by the geographical distances, namely the speed of light over optical fibers (200,000 km / s equivalent to 5us / km latency). For this reason, in the next description the Transport latency for Cloud RAN Transport is referred to as the fiber distance among the RAN network functions.Cloud RAN Execution Environment

[0008] The distributed Cloud RAN computing platforms (typically COTS (commercial off the shelf)) need to be placed in shelters, central offices, or data centers close to the Radios, due to the RAN latency constraints and the restricted operational temperatures, security, power supply, and dimensions of their platforms. Some Tier 1 operators are used with the operational advantages of the pooling of RAN resources (as previously used in C-RAN) and may want to concentrate more RAN functions in a Cloud aggregation site within a certain area from the Radio Units. In the 5G Cloud RAN and RAN Compute, two functions are typically described with different constraints:• Distributed Units (DU) managing real-time processes with the Radio Units, requiring very low latency.• Centralized Unit managing quasi or non-real-time processes between the Distributed Unit and the Packet Core, with relaxed latency constraints almost equivalent to traditional backhauling.

[0009] At current state-of-art, latency between RU’s (Radio Units) and DU’s (Distributed Units) should stay below lOOus in order to provide the best network performances, while latency extensions are under evaluation. Figure 1 illustrates the transition from D-RAN to Cloud RAN, including the preference for latency below lOOus.

[0010] The max latency constraints between RU’s and their relevant DU functions in the Cloud Execution environment can be enforced using settings known as affinity parameters (i.e., Kubernetes affinity).

[0011] The setup of affinity constraints in the Cloud Execution environment, depending on the position of multiple physical nodes, can be complex and prone to error since it involves the coordination between the RAN organization, owning the RAN network and relevant RAN skills, and the IT (information technology) organization owning the Cloud Execution environment and relevant Cloud skills.SUMMARY

[0012] One embodiment under the present disclosure comprises a method for meeting Cloud RAN service run-time requirements. The method comprises selecting one or more cloud clusters compatible with one or more RUs, the selecting based at least in part on latency and / or one or more settings; instantiating one or more virtual functions, referred to as RAPDs, in the one or more cloud clusters, each of the one or more RAPDs receiving one or more affinity labels; and enabling RAPD latency monitoring to validate the one or more affinity labels.

[0013] Another embodiment of a method under the present disclosure is a method for run-time instantiation of new DU binding. The method comprises deploying one or more DUs to manage one or more RUs; filtering one or more cloud clusters reporting one or more affinity labels; identifying any available cloud clusters; and if there are one or more available cloud clusters, then selecting a target cloud cluster from the one or more available cloud clusters; and instantiating a new DU in the target cloud cluster. If there are no available cloud clusters, then the next step is raising exception handling.

[0014] Another embodiment under the present disclosure comprises a system for meeting Cloud RAN service run-time requirements. The system comprises one or more RUs; and one or more cloud clusters configured to provide one or more microservices to the one or more RUs, each of the microservices being given one or more affinity labels to support redundancy and / or differentiation of services at the one or more RUs, wherein the one or more affinity labels is based at least in part on a proximity area around the one or more RUs, the proximity area defined by a communication latency.

[0015] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an indication of the scope of the claimed subject matter.BRIEF DESCRIPTION OF THE DRAWINGS

[0016] For a more complete understanding of the present disclosure, reference is now made to the following descriptions taken in conjunction with the accompanying drawings, in which:

[0017] Fig. 1 illustrates the transition from D-RAN to Cloud RAN;

[0018] Fig. 2 illustrates Cloud RAN allocation based on latency requirements;

[0019] Fig. 3 illustrates a system embodiment under the present disclosure;

[0020] Fig. 4 illustrates a system embodiment under the present disclosure;

[0021] Fig. 5 illustrates a system embodiment under the present disclosure;

[0022] Fig. 6 illustrates a flow-chart of a method embodiment under the present disclosure;

[0023] Fig. 7 illustrates a flow-chart of a method embodiment under the present disclosure;

[0024] Fig. 8 illustrates possible YAML pseudo code for RAPD definition under the present disclosure;

[0025] Fig. 9 illustrates possible YAML pseudo code for DU instantiation under the present disclosure;

[0026] Fig. 10 shows a schematic of a communication system embodiment under the present disclosure;

[0027] Fig. 11 shows a schematic of a user equipment embodiment under the present disclosure;

[0028] Fig. 12 shows a schematic of a network node embodiment under the present disclosure; and

[0029] Fig. 13 shows a schematic of a virtualization environment embodiment under the present disclosure.DETAILED DESCRIPTION

[0030] Before describing various embodiments of the present disclosure in detail, it is to be understood that this disclosure is not limited to the parameters of the particularlyexemplified systems, methods, apparatus, products, processes, and / or kits, which may, of course, vary. Thus, while certain embodiments of the present disclosure will be described in detail, with reference to specific configurations, parameters, components, elements, etc., the descriptions are illustrative and are not to be construed as limiting the scope of the claimed embodiments. In addition, the terminology used herein is for the purpose of describing the embodiments and is not necessarily intended to limit the scope of the claimed embodiments.

[0031] Some of the embodiments contemplated herein will now be described more fully with reference to the accompanying drawings. Embodiments are provided by way of example to convey the scope of the subject matter to those skilled in the art.

[0032] As discussed above, there currently exist certain challenges. For example:• The Cloud infrastructure aspects are managed by IT (information technology) department that wish to consider transport as a fixed infrastructure to deal with and not to manage directly.• The RAN infrastructure is managed by Radio department that is traditionally dealing with RF (radio frequency) coverage and mobile backhaul over MW (microwave) and / or over Fiber (optical), therefore with limited knowledge of the Data Center and Transport requirements.

[0033] Such a process is limiting the Cloud RAN potentiality as it would result in too restrictive rules, and it is also prone to errors and misalignment since it implies a communication between two different departments with different expertise and datasets (IT and RAN). In case of changes in the RAN infrastructure, the Radio department should then verify the capability of the underlying DC infrastructure to verify the actual latency and throughput provided between e.g., Kubernetes pods and the IT department.

[0034] Figure 2 illustrates Cloud RAN allocation based on latency requirements. This process is too complex for DC operators (without RAN and Transport competences) and it is not able to fulfill continuous demand for new RAN services, leading to the risk of dis-optimized Cloud infrastructures not able to track the flexibility of the RAN networks without overdimensioning the hardware and the transport infrastructure. As a result, at current times of sustainability and zero-carbon footprint, the approach to over-dimension Transport does not appear to be acceptable anymore.

[0035] Certain aspects of the disclosure and their embodiments may provide solutions to these or other challenges. The present disclosure includes embodiments of a fast, sustainable, and automatic method to meet Cloud RAN service run-time requirements with the usage of Cloud Affinity methods. For example, in some embodiments, for each installed RU (Radio Unit, which may be local or remote (RRU)), the Telecom operator can instantiate a special set of virtual functions, referred as “Radio Affinity POD (RAPD)”, correlated with the RU in all the Cloud clusters / servers that have compatible Cloud and Transport characteristics to host the RU relevant DU and or DU / CU services. The special RAPD images can contain the identification of the RU, microservices to expose the RU identity and affinity labels and, optionally, microservices to continuously monitor the communication status between the RU and the Cloud server to validate the expected latency assumptions. In certain embodiments, the RAPD can also provide additional telemetry and observability services to control the transport communication network towards the RU.

[0036] Embodiments under the present disclosure can include a new RU POD image, representing one or more physical RUs (local or remote) and instantiated in a multitude of Cloud servers within a RAN proximity area from the one or more RU’s. The RU PODs can be correlated with the RU with a unique identifier within the Cloud Server, an RU affinity label (RAE) and an RU anti-affinity label (RAAL). The proximity area is defined as the set of Cloud servers that have communication links with the RU and communication latency below a certain threshold. In one embodiment the RAPD can also support periodic measurement of the latency towards the RUs to validate and monitor the communication latency from the Cloud to the RU. Affinity and anti-affinity labels are updated in case temporarily the values become worse or better. The RU affinity and anti-affinity labels can be used to assist the instantiation of RAN processes (distributed Unit, DU) on the same server of the RU POD or the opposite (avoiding it). In another embodiment, the affinity and anti-affinity labels can be used to provide cluster diversity to increase the resiliency of the Cloud RAN coverage using the RU anti-affinity label.

[0037] While some of the described embodiments make reference to “affinity” or “anti-affinity,” the teachings disclosed herein are applicable in a variety of deployment scenarios outside of the Kubernetes context where affinity is commonly referenced. The embodiments described herein can be applicable to a variety of scenarios where nodes and / or cloud-based functions may be assigned to e.g., RUs based on features like, e.g.: latency, distance, or otherfactors. Certain embodiments could use terminology like kinship to an RU, bias for an RU, latency radius to a RU, assignment to an RU, RU tasks, distance to an RU, or other terminology while still keeping consistent with the teachings disclosed herein.

[0038] Figure 3 illustrates one possible system embodiment 500 under the present disclosure. Embodiments can solve the challenge of tight latency constraints imposed by the NG- LLS (next generation lower-layer split) fronthaul interfaces valid for proprietary and Open RAN solutions. In this embodiment, RU 550 can be associated with distributed Units (DU) 510, 530, and 560. RAPDs 520, 540, 570 can be implemented at each of the DUs 510, 530, 560. DUs and / or DU / CUs can be located in one or more cloud clusters 590. RAPD services can be deployed within a certain radius rl from the physical RU 550, constrained by the maximum allowed latency (possibly lOOus). Centralized Unit (CU) 580 can be located outside the radius rl at e.g., r2. RAPDs 520, 540, 570 can provide RAPD services, such as providing a binding to the RU 550 and additional parameters such as an affinity label and an anti-affinity label. RAPD services can include optionally monitoring the communication from their hosting node towards the RU to check service availability and latency (including Transport and Cloud domain sections). Embodiments can comprise the RAPD 520, 540, 570 installations in the compatible Cloud RAN clusters from latency and sustainability perspective, with the translation of Physical and Transport measurements into Cloud related language. Orchestrator 595 (e.g., a Data Center (DC) Orchestrator) may manage the RU 550 and any associated nodes 585, including RAPDs 520, 540, 570 and DUs 510, 530, 560. Responsive to Cloud RAN requirements, orchestrator 595 can allocate or dis-allocate their related DU and CU services by referring to the RAPD affinity and anti-affinity labels.

[0039] Additional embodiments can improve and relate to sustainability requirements. For example, the RAPD services can provide details about their energy efficiency that can be abstracted into PUE (power usage effectiveness) parameters from Cloud perspective. For example, in Figure 4 sustainable energy can be used at various locations with a network. In Figure 4, RU 750 can be associated with DUs 710, 730, 760, which can have implemented RAPDs 720, 740, 770. CU 780 can also be associated with RU 750. Each DU 710, 730, 760 and CU 780 can be powered by sustainable energy, such as nuclear, solar or other.

[0040] Certain embodiments may provide one or more of the following technical advantages.

[0041] One advantage of certain embodiments is to provide higher flexibility and automation in the deployment of Cloud RAN services. This can be due to the mapping of the physical RU nodes within the Cloud RAN execution infrastructure with well-known language and methods widely available in most of the commercial operating systems.

[0042] Another advantage of certain embodiment is the bottom-up that significantly reduces the learning curve for Cloud RAN operations within the existing Cloud infrastructures. The NG-LLS latency constraints can be calculated during RU installation and imposed on Cloud RAN by instantiating a group of attached RAPD services. RU latency constraints, network and cloud performances can be monitored automatically by the RAPD services without Cloud RAN orchestration intervention. At run-time, an orchestrator (e.g., DC Orchestrator) can allocate DU services based on the RAPD POD affinity labels that are well known parameters for Cloud operators, instead of complicated RAN specific rules.

[0043] A further advantage is that Cloud RAN sustainability and energy efficiency can be improved thanks to the increased automation (error- free) in the allocation of DU and CU based on existing and well-established ICT good practices for power efficiency.

[0044] Another advantage is that, unlike other methods proposed in the literature, certain embodiments can make use of functionalities already available in the cloud RAN architecture components without impacts on the orchestrator or in the RU.

[0045] Furthermore, certain proposed embodiments can add resiliency to the Cloud RAN deployment since in case of host failure the DU can be easily migrated in another site where a RAPD is present.

[0046] Certain embodiments can automate the deployment of Cloud RAN processes for the management of RU. Certain proposed methods can be based on the deployment of POD images representing the physical RUs in the Cloud servers that satisfies its Fronthaul and Backhaul latency constraints.

[0047] Figure 5 illustrates one possible system embodiment 800 under the present disclosure. Figure 5 shows an example of RAPD deployment and service instantiation. Three RUs are shown, RU 1 , RU2, RU3. Three Kubernetes clusters A, B, C are shown implemented to provide e.g., redundancy services. Each cluster A, B, C can comprise one or more servers 810. RAPD microservices 820 are assigned an RU affinity label (RAE) that refers to the physical RU1, RU2, RU3 so that they can mark the sites and the servers able to support its relevant distributed unitprocesses (DU). Additionally, and optionally, RAPD microservices 820 can be assigned with an RU anti-affinity label (RAAL) to support redundancy and differentiation of services. RAPD microservices 820 can be optionally equipped with probe capability to supervision the communication between the Cloud site and the physical RU1, RU2, RU3 in order to confirm its compliance to its NG-LLS latency constraints.

[0048] Certain embodiments can include methods for one or more of two phases:• RU binding: Physical RU installation and RAPD binding;• DU deployment: DU allocation based on RAD or RAAL affinity.

[0049] When a new RU is activated, the neighbor Cloud sites supposed to satisfy latency criteria are selected for RAPD. The RAPD services processes are instantiated with the same affinity label pointing to the physical RU.

[0050] In certain additional embodiments, each RAPD service can start validation and monitoring of the actual latency towards the RU and possibly disable / enable reporting of its affinity label. In case this addition is present step two (planning) could be simplified since RAPD will autonomously detect the valid latency condition of the server.

[0051] Figure 6 illustrates one possible method embodiment 1000 of RU and RAPD binding. Step 1010, is selecting one or more cloud clusters / servers compatible with one or more RUs, based at least in part on latency and / or one or more settings. Step 1020 is instantiating one or more virtual functions, referred to as RAPDs in the one or more cloud clusters, each of the one or more RAPDs receiving one or more affinity labels. RAPD services can provide e.g., DU services; CU services; other CNF (cloud native functions). Step 1030 is enabling RAPD latency monitoring to validate RU affinity label. Method 1000 can comprise a variety of additional or alternative steps or other variations. For example, in some cases, an additional step before 1010 can be selecting or installing one or more RUs. In some variations, step 1020 can be in response to RU installation, or to RU migration to Cloud RAN.

[0052] Whenever a new DU (distributed unit) process needs to be instantiated to control the physical RU, an orchestrator may check for all the Cloud sites reporting their target RAPD binding (RAL or RAAL) to the RU.

[0053] Figure 7 illustrates another possible method embodiment 1200 of run-time instantiation of new DU binding. Step 1210 is the orchestrator deploying DU to manage RU. Step 1220 is filtering clusters / servers reporting an RU affinity label (RAL). Step 1230 is determining ifthere’s an available cluster / server. If yes, then at 1240, a target cluster / server is selected among relevant affinity servers. Step 1250 is then instantiating the DU and then returning to step 1210. If there’s not an available cluster / server, then at 1260, exception handling is raised and the process returns to 1210.

[0054] Embodiments under the present disclosure can comprise Cloud and Cloud RAN deployment. Embodiments can leverage on Cloud specific functionality (affinity, antiaffinity) available in most of the commercially available deployments to abstract and enforce RAN deployment constraints. The RAPD images can be deployed as part of e.g., DC Orchestration and can be bound to their attached physical RU using existing labels already used by most Cloud Operating systems. It should be noted that the affinity label has a local scope within each Cluster therefore it can be advantageously reused in multiple clusters to support Cloud service resiliency.

[0055] Pod Affinity and Anti-Affinity can enable the creation of rules that control where to place the pods relative to other pods. A user must label the nodes and use label selectors in pod specifications. Pod Affinity / Anti- Affinity can allow a pod to specify an affinity (or antiaffinity) towards a set of pods.

[0056] Figure 8 illustrates an example embodiment of how Affinity and AntiAffinity rules work based on RAPD labels. Figure 8 shows YAML pseudo code for RAPD definition. With an affinity rule, the scheduler can place the DU-RRU-x pod on the same node as RAPD-RRU-x pod if the label on the new DU-RRU-x pod matches the label on the RAPD-RRU- x pod. It follows a pseudo-code of deployment file for the RAPD in bind with the physical RRU- 1. It allows the RAPD to be deployed with replica 2 on a Cloud server in anti-affinity with its replica. The assigned label is “RAPD-RRU-1.”

[0057] It then follows, a pseudo-code of deployment file for the DU-POD to bind with the RAPD for physical RRU-1. Figure 9 shows YAML pseudo code for DU instantiation. It allows the DU-RRU-1 POD to be deployed with replica 2 on a Cloud server in anti-affinity with its replica and in Affinity with the RAPD with label “rapd-rru-1”.

[0058] Other embodiments of the present disclosure can encompass 0-RAN Implementation. It should be noted that references to baseband unit functions, virtual functions, or other functions may carry different terms in different network types. For example, in Cloud RAN BBU functions become CU and DU functions. The embodiments disclosed herein can beimplemented in a variety of network types and are not meant to be limited to one network type or one network function.

[0059] Figure 10 shows an example of a communication system 3100 in accordance with some embodiments.

[0060] In the example, the communication system 3100 includes a telecommunication network 3102 that includes an access network 3104, such as a radio access network (RAN), and a core network 3106, which includes one or more core network nodes 3108. The access network 3104 includes one or more access network nodes, such as network nodes 3110a and 3110b (one or more of which may be generally referred to as network nodes 3110), or any other similar 3rd Generation Partnership Project (3GPP) access nodes or non-3GPP access points. Moreover, as will be appreciated by those of skill in the art, a network node is not necessarily limited to an implementation in which a radio portion and a baseband portion are supplied and integrated by a single vendor. Thus, it will be understood that network nodes include disaggregated implementations or portions thereof. For example, in some embodiments, the telecommunication network 3102 includes one or more Open-RAN (ORAN) network nodes. An ORAN network node is a node in the telecommunication network 3102 that supports an ORAN specification (e.g., a specification published by the O-RAN Alliance, or any similar organization) and may operate alone or together with other nodes to implement one or more functionalities of any node in the telecommunication network 3102, including one or more network nodes 3110 and / or core network nodes 3108.

[0061] Examples of an ORAN network node include an open radio unit (O-RU), an open distributed unit (O-DU), an open central unit (O-CU), including an O-CU control plane (O-CU-CP) or an O-CU user plane (O-CU-UP), a RAN intelligent controller (near-real time or non-real time) hosting software or software plug-ins, such as a near-real time control application (e.g., xApp) or a non-real time control application (e.g., rApp), or any combination thereof (the adjective “open” designating support of an ORAN specification). The network node may support a specification by, for example, supporting an interface defined by the ORAN specification, such as an Al, Fl, Wl, El, E2, X2, Xn interface, an open fronthaul user plane interface, or an open fronthaul management plane interface. Moreover, an ORAN access node may be a logical node in a physical node. Furthermore, an ORAN network node may be implemented in a virtualization environment (described further below) in which one or more network functions are virtualized.For example, the virtualization environment may include an O-Cloud computing platform orchestrated by a Service Management and Orchestration Framework via an 0-2 interface defined by the 0-RAN Alliance or comparable technologies. The network nodes 3110 facilitate direct or indirect connection of user equipment (UE), such as by connecting UEs 3112a, 3112b, 3112c, and 3112d (one or more of which may be generally referred to as UEs 3112) to the core network 3106 over one or more wireless connections.

[0062] Example wireless communications over a wireless connection include transmitting and / or receiving wireless signals using electromagnetic waves, radio waves, infrared waves, and / or other types of signals suitable for conveying information without the use of wires, cables, or other material conductors. Moreover, in different embodiments, the communication system 3100 may include any number of wired or wireless networks, network nodes, UEs, and / or any other components or systems that may facilitate or participate in the communication of data and / or signals whether via wired or wireless connections. The communication system 3100 may include and / or interface with any type of communication, telecommunication, data, cellular, radio network, and / or other similar type of system.

[0063] The UEs 3112 may be any of a wide variety of communication devices, including wireless devices arranged, configured, and / or operable to communicate wirelessly with the network nodes 3110 and other communication devices. Similarly, the network nodes 3110 are arranged, capable, configured, and / or operable to communicate directly or indirectly with the UEs 3112 and / or with other network nodes or equipment in the telecommunication network 3102 to enable and / or provide network access, such as wireless network access, and / or to perform other functions, such as administration in the telecommunication network 3102.

[0064] In the depicted example, the core network 3106 connects the network nodes 3110 to one or more host computing systems, such as host 3116. These connections may be direct or indirect via one or more intermediary networks or devices. In other examples, network nodes may be directly coupled to hosts. The core network 3106 includes one more core network nodes (e.g., core network node 3108) that are structured with hardware and software components. Features of these components may be substantially similar to those described with respect to the UEs, network nodes, and / or hosts, such that the descriptions thereof are generally applicable to the corresponding components of the core network node 3108. Example core network nodes include functions of one or more of a Mobile Switching Center (MSC), Mobility Management Entity(MME), Home Subscriber Server (HSS), Access and Mobility Management Function (AMF), Session Management Function (SMF), Authentication Server Function (AUSF), Subscription Identifier De-concealing Function (SIDF), Unified Data Management (UDM), Security Edge Protection Proxy (SEPP), Network Exposure Function (NEF), and / or a User Plane Function (UPF).

[0065] The host 3116 may be under the ownership or control of a service provider other than an operator or provider of the access network 3104 and / or the telecommunication network 3102. The host 3116 may host a variety of applications to provide one or more service. Examples of such applications include live and pre-recorded audio / video content, data collection services such as retrieving and compiling data on various ambient conditions detected by a plurality of UEs, analytics functionality, social media, functions for controlling or otherwise interacting with remote devices, functions for an alarm and surveillance center, or any other such function performed by a server.

[0066] As a whole, the communication system 3100 of Figure 10 enables connectivity between the UEs, network nodes, and hosts. In that sense, the communication system may be configured to operate according to predefined rules or procedures, such as specific standards that include, but are not limited to: Global System for Mobile Communications (GSM); Universal Mobile Telecommunications System (UMTS); Long Term Evolution (LTE), and / or other suitable 2G, 3G, 4G, 5G standards, or any applicable future generation standard (e.g., 6G); wireless local area network (WLAN) standards, such as the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standards (WiFi); and / or any other appropriate wireless communication standard, such as the Worldwide Interoperability for Microwave Access (WiMax), Bluetooth, Z- Wave, Near Field Communication (NFC) ZigBee, LiFi, and / or any low-power wide-area network (LPWAN) standards such as LoRa and Sigfox.

[0067] In some examples, the telecommunication network 3102 is a cellular network that implements 3GPP standardized features. Accordingly, the telecommunications network 3102 may support network slicing to provide different logical networks to different devices that are connected to the telecommunication network 3102. For example, the telecommunications network 3102 may provide Ultra Reliable Low Latency Communication (URLLC) services to some UEs, while providing Enhanced Mobile Broadband (eMBB) services to other UEs, and / or Massive Machine Type Communication (mMTC)ZMassive Internet of Things (loT) services to yet further UEs.

[0068] In some examples, the UEs 3112 are configured to transmit and / or receive information without direct human interaction. For instance, a UE may be designed to transmit information to the access network 3104 on a predetermined schedule, when triggered by an internal or external event, or in response to requests from the access network 3104. Additionally, a UE may be configured for operating in single- or multi-RAT or multi-standard mode. For example, a UE may operate with any one or combination of Wi-Fi, NR (New Radio) and LIE, i.e., being configured for multi-radio dual connectivity (MR-DC), such as E-UTRA (Evolved-Universal Terrestrial Radio Access) New Radio - Dual Connectivity (EN-DC).

[0069] In the example, the hub 3114 communicates with the access network 3104 to facilitate indirect communication between one or more UEs (e.g., UE 3112c and / or 3112d) and network nodes (e.g., network node 3110b). In some examples, the hub 3114 may be a controller, router, content source and analytics, or any of the other communication devices described herein regarding UEs. For example, the hub 3114 may be a broadband router enabling access to the core network 3106 for the UEs. As another example, the hub 3114 may be a controller that sends commands or instructions to one or more actuators in the UEs. Commands or instructions may be received from the UEs, network nodes 3110, or by executable code, script, process, or other instructions in the hub 3114. As another example, the hub 3114 may be a data collector that acts as temporary storage for UE data and, in some embodiments, may perform analysis or other processing of the data. As another example, the hub 3114 may be a content source. For example, for a UE that is a VR (Virtual Reality) device, display, loudspeaker, or other media delivery device, the hub 3114 may retrieve VR assets, video, audio, or other media or data related to sensory information via a network node, which the hub 3114 then provides to the UE either directly, after performing local processing, and / or after adding additional local content. In still another example, the hub 3114 acts as a proxy server or orchestrator for the UEs, in particular if one or more of the UEs are low energy loT devices.

[0070] The hub 3114 may have a constant / persistent or intermittent connection to the network node 3110b. The hub 3114 may also allow for a different communication scheme and / or schedule between the hub 3114 and UEs (e.g., UE 3112c and / or 3112d), and between the hub 3114 and the core network 3106. In other examples, the hub 3114 is connected to the core network 3106 and / or one or more UEs via a wired connection. Moreover, the hub 3114 may be configured to connect to an M2M (Machine to Machine) service provider over the access network3104 and / or to another UE over a direct connection. In some scenarios, UEs may establish a wireless connection with the network nodes 3110 while still connected via the hub 3114 via a wired or wireless connection. In some embodiments, the hub 3114 may be a dedicated hub - that is, a hub whose primary function is to route communications to / from the UEs from / to the network node 3110b. In other embodiments, the hub 3114 may be a non-dedicated hub - that is, a device which is capable of operating to route communications between the UEs and network node 3110b, but which is additionally capable of operating as a communication start and / or end point for certain data channels.

[0071] Figure 11 shows a UE 3200 in accordance with some embodiments. The UE 3200 presents additional details of some embodiments of the UEs 3112 of Figure 10. As used herein, a UE refers to a device capable, configured, arranged and / or operable to communicate wirelessly with network nodes and / or other UEs. Examples of a UE include, but are not limited to, a smart phone, mobile phone, cell phone, voice over IP (VoIP) phone, wireless local loop phone, desktop computer, personal digital assistant (PDA), wireless cameras, gaming console or device, music storage / playback device, wearable terminal device, wireless endpoint, mobile station, tablet, laptop, laptop-embedded equipment (LEE), laptop-mounted equipment (LME), an Augmented Reality (AR) or Virtual Reality (VR) device, wireless customer-premise equipment (CPE), vehicle, vehicle-mounted or vehicle embedded / integrated wireless device, etc. Other examples include any UE identified by the 3rd Generation Partnership Project (3 GPP), including a narrow band internet of things (NB-IoT) UE, a machine type communication (MTC) UE, and / or an enhanced MTC (eMTC) UE.

[0072] A UE may support device-to-device (D2D) communication, for example by implementing a 3 GPP standard for sidelink communication, Dedicated Short-Range Communication (DSRC), vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), or vehicle-to- everything (V2X). In other examples, a UE may not necessarily have a user in the sense of a human user who owns and / or operates the relevant device. Instead, a UE may represent a device that is intended for sale to, or operation by, a human user but which may not, or which may not initially, be associated with a specific human user (e.g., a smart sprinkler controller). Alternatively, a UE may represent a device that is not intended for sale to, or operation by, an end user but which may be associated with or operated for the benefit of a user (e.g., a smart power meter).

[0073] The UE 3200 includes processing circuitry 3202 that is operatively coupled via a bus 3204 to an input / output interface 3206, a power source 3208, a memory 3210, a communication interface 3212, and / or any other component, or any combination thereof. Certain UEs may utilize all or a subset of the components shown in Figure 12. The level of integration between the components may vary from one UE to another UE. Further, certain UEs may contain multiple instances of a component, such as multiple processors, memories, transceivers, transmitters, receivers, etc.

[0074] The processing circuitry 3202 is configured to process instructions and data and may be configured to implement any sequential state machine operative to execute instructions stored as machine-readable computer programs in the memory 3210. The processing circuitry 3202 may be implemented as one or more hardware-implemented state machines (e.g., in discrete logic, field-programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), etc.); programmable logic together with appropriate firmware; one or more stored computer programs, general-purpose processors, such as a microprocessor or digital signal processor (DSP), together with appropriate software; or any combination of the above. For example, the processing circuitry 3202 may include multiple central processing units (CPUs).

[0075] In the example, the input / output interface 3206 may be configured to provide an interface or interfaces to an input device, output device, or one or more input and / or output devices. Examples of an output device include a speaker, a sound card, a video card, a display, a monitor, a printer, an actuator, an emitter, a smartcard, another output device, or any combination thereof. An input device may allow a user to capture information into the UE 3200. Examples of an input device include a touch-sensitive or presence-sensitive display, a camera (e.g., a digital camera, a digital video camera, a web camera, etc.), a microphone, a sensor, a mouse, a trackball, a directional pad, a trackpad, a scroll wheel, a smartcard, and the like. The presencesensitive display may include a capacitive or resistive touch sensor to sense input from a user. A sensor may be, for instance, an accelerometer, a gyroscope, a tilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, a biometric sensor, etc., or any combination thereof. An output device may use the same type of interface port as an input device. For example, a Universal Serial Bus (USB) port may be used to provide an input device and an output device.

[0076] In some embodiments, the power source 3208 is structured as a battery or battery pack. Other types of power sources, such as an external power source (e.g., an electricityoutlet), photovoltaic device, or power cell, may be used. The power source 3208 may further include power circuitry for delivering power from the power source 3208 itself, and / or an external power source, to the various parts of the UE 3200 via input circuitry or an interface such as an electrical power cable. Delivering power may be, for example, for charging of the power source 3208. Power circuitry may perform any formatting, converting, or other modification to the power from the power source 3208 to make the power suitable for the respective components of the UE 3200 to which power is supplied.

[0077] The memory 3210 may be or be configured to include memory such as random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic disks, optical disks, hard disks, removable cartridges, flash drives, and so forth. In one example, the memory 3210 includes one or more application programs 3214, such as an operating system, web browser application, a widget, gadget engine, or other application, and corresponding data 3216. The memory 3210 may store, for use by the UE 3200, any of a variety of various operating systems or combinations of operating systems.

[0078] The memory 3210 may be configured to include a number of physical drive units, such as redundant array of independent disks (RAID), flash memory, USB flash drive, external hard disk drive, thumb drive, pen drive, key drive, high-density digital versatile disc (HD- DVD) optical disc drive, internal hard disk drive, Blu-Ray optical disc drive, holographic digital data storage (HDDS) optical disc drive, external mini-dual in-line memory module (DIMM), synchronous dynamic random access memory (SDRAM), external micro-DIMM SDRAM, smartcard memory such as tamper resistant module in the form of a universal integrated circuit card (UICC) including one or more subscriber identity modules (SIMs), such as a USIM and / or ISIM, other memory, or any combination thereof. The UICC may for example be an embedded UICC (eUICC), integrated UICC (iUICC) or a removable UICC commonly known as ‘SIM card.’ The memory 3210 may allow the UE 3200 to access instructions, application programs and the like, stored on transitory or non-transitory memory media, to off-load data, or to upload data. An article of manufacture, such as one utilizing a communication system may be tangibly embodied as or in the memory 3210, which may be or comprise a device-readable storage medium.

[0079] The processing circuitry 3202 may be configured to communicate with an access network or other network using the communication interface 3212. The communication interface 3212 may comprise one or more communication subsystems and may include or be communicatively coupled to an antenna 3222. The communication interface 3212 may include one or more transceivers used to communicate, such as by communicating with one or more remote transceivers of another device capable of wireless communication (e.g., another UE or a network node in an access network). Each transceiver may include a transmitter 3218 and / or a receiver 3220 appropriate to provide network communications (e.g., optical, electrical, frequency allocations, and so forth). Moreover, the transmitter 3218 and receiver 3220 may be coupled to one or more antennas (e.g., antenna 3222) and may share circuit components, software or firmware, or alternatively be implemented separately.

[0080] In the illustrated embodiment, communication functions of the communication interface 3212 may include cellular communication, Wi-Fi communication, LPWAN communication, data communication, voice communication, multimedia communication, short-range communications such as Bluetooth, near-field communication, location-based communication such as the use of the global positioning system (GPS) to determine a location, another like communication function, or any combination thereof. Communications may be implemented in according to one or more communication protocols and / or standards, such as IEEE 802.11, Code Division Multiplexing Access (CDMA), Wideband Code Division Multiple Access (WCDMA), GSM, LTE, New Radio (NR), UMTS, WiMax, Ethernet, transmission control protocol / internet protocol (TCP / IP), synchronous optical networking (SONET), Asynchronous Transfer Mode (ATM), QUIC, Hypertext Transfer Protocol (HTTP), and so forth.

[0081] Regardless of the type of sensor, a UE may provide an output of data captured by its sensors, through its communication interface 3212, via a wireless connection to a network node. Data captured by sensors of a UE can be communicated through a wireless connection to a network node via another UE. The output may be periodic (e.g., once every 15 minutes if it reports the sensed temperature), random (e.g., to even out the load from reporting from several sensors), in response to a triggering event (e.g., when moisture is detected an alert is sent), in response to a request (e.g., a user initiated request), or a continuous stream (e.g., a live video feed of a patient).

[0082] As another example, a UE comprises an actuator, a motor, or a switch, related to a communication interface configured to receive wireless input from a network node via a wireless connection. In response to the received wireless input the states of the actuator, the motor, or the switch may change. For example, the UE may comprise a motor that adjusts the control surfaces or rotors of a drone in flight according to the received input or to a robotic arm performing a medical procedure according to the received input.

[0083] A UE, when in the form of an Internet of Things (loT) device, may be a device for use in one or more application domains, these domains comprising, but not limited to, city wearable technology, extended industrial application and healthcare. Non-limiting examples of such an loT device are a device which is or which is embedded in: a connected refrigerator or freezer, a TV, a connected lighting device, an electricity meter, a robot vacuum cleaner, a voice controlled smart speaker, a home security camera, a motion detector, a thermostat, a smoke detector, a door / window sensor, a flood / moisture sensor, an electrical door lock, a connected doorbell, an air conditioning system like a heat pump, an autonomous vehicle, a surveillance system, a weather monitoring device, a vehicle parking monitoring device, an electric vehicle charging station, a smart watch, a fitness tracker, a wearable for tactile augmentation or sensory enhancement, a water sprinkler, an animal- or item-tracking device, a sensor for monitoring a plant or animal, an industrial robot, an Unmanned Aerial Vehicle (UAV), and any kind of medical device, like a heart rate monitor or a remote controlled surgical robot. A UE in the form of an loT device comprises circuitry and / or software in dependence of the intended application of the loT device in addition to other components as described in relation to the UE 3200 shown in Figure 12.

[0084] As yet another specific example, in an loT scenario, a UE may represent a machine or other device that performs monitoring and / or measurements, and transmits the results of such monitoring and / or measurements to another UE and / or a network node. The UE may in this case be an M2M device, which may in a 3 GPP context be referred to as an MTC device. As one particular example, the UE may implement the 3 GPP NB-IoT standard. In other scenarios, a UE may represent a vehicle, such as a car, a bus, a truck, a ship and an airplane, or other equipment that is capable of monitoring and / or reporting on its operational status or other functions associated with its operation.

[0085] In practice, any number of UEs may be used together with respect to a single use case. For example, a first UE might be or be integrated in a drone and provide the drone’s speed information (obtained through a speed sensor) to a second UE that is a remote controller operating the drone. When the user makes changes from the remote controller, the first UE may adjust the throttle on the drone (e.g., by controlling an actuator) to increase or decrease the drone’s speed. The first and / or the second UE can also include more than one of the functionalities described above. For example, a UE might comprise the sensor and the actuator, and handle communication of data for both the speed sensor and the actuators.

[0086] Figure 12 shows a network node 3300 in accordance with some embodiments. As used herein, network node refers to equipment capable, configured, arranged and / or operable to communicate directly or indirectly with a UE and / or with other network nodes or equipment, in a telecommunication network. Examples of network nodes include, but are not limited to, access points (APs) (e.g., radio access points), base stations (BSs) (e.g., radio base stations, Node Bs, evolved Node Bs (eNBs) and NR NodeBs (gNBs)), 0-RAN nodes or components of an 0-RAN node (e.g., 0-RU, 0-DU, O-CU).

[0087] Base stations may be categorized based on the amount of coverage they provide (or, stated differently, their transmit power level) and so, depending on the provided amount of coverage, may be referred to as femto base stations, pico base stations, micro base stations, or macro base stations. A base station may be a relay node or a relay donor node controlling a relay. A network node may also include one or more (or all) parts of a distributed radio base station such as centralized digital units, distributed units (e.g., in an O-RAN access node) and / or radio units (RUs), sometimes referred to as Remote Radio Units (RRU) and / or Remote Radio Heads (RRHs). Such remote radio units may or may not be integrated with an antenna as an antenna integrated radio. Parts of a distributed radio base station may also be referred to as nodes in a distributed antenna system (DAS).

[0088] Other examples of network nodes include multiple transmission point (multi-TRP) 5G access nodes, multi-standard radio (MSR) equipment such as MSRBSs, network controllers such as radio network controllers (RNCs) or base station controllers (BSCs), base transceiver stations (BTSs), transmission points, transmission nodes, multi-cell / multicast coordination entities (MCEs), Operation and Maintenance (O&M) nodes, Operations SupportSystem (OSS) nodes, Self-Organizing Network (SON) nodes, positioning nodes (e.g., Evolved Serving Mobile Location Centers (E-SMLCs)), and / or Minimization of Drive Tests (MDTs).

[0089] The network node 3300 includes a processing circuitry 3302, a memory 3304, a communication interface 3306, and a power source 3308. The network node 3300 may be composed of multiple physically separate components (e.g., a NodeB component and a RNC component, or a BTS component and a BSC component, etc.), which may each have their own respective components. In certain scenarios in which the network node 3300 comprises multiple separate components (e.g., BTS and BSC components), one or more of the separate components may be shared among several network nodes. For example, a single RNC may control multiple NodeBs. In such a scenario, each unique NodeB and RNC pair, may in some instances be considered a single separate network node. In some embodiments, the network node 3300 may be configured to support multiple radio access technologies (RATs). In such embodiments, some components may be duplicated (e.g., separate memory 3304 for different RATs) and some components may be reused (e.g., a same antenna 3310 may be shared by different RATs). The network node 3300 may also include multiple sets of the various illustrated components for different wireless technologies integrated into network node 3300, for example GSM, WCDMA, LTE, NR, WiFi, Zigbee, Z-wave, LoRaWAN, Radio Frequency Identification (RFID) or Bluetooth wireless technologies. These wireless technologies may be integrated into the same or different chip or set of chips and other components within network node 3300.

[0090] The processing circuitry 3302 may comprise a combination of one or more of a microprocessor, controller, microcontroller, central processing unit, digital signal processor, application-specific integrated circuit, field programmable gate array, or any other suitable computing device, resource, or combination of hardware, software and / or encoded logic operable to provide, either alone or in conjunction with other network node 3300 components, such as the memory 3304, to provide network node 3300 functionality.

[0091] In some embodiments, the processing circuitry 3302 includes a system on a chip (SOC). In some embodiments, the processing circuitry 3302 includes one or more of radio frequency (RF) transceiver circuitry 3312 and baseband processing circuitry 3314. In some embodiments, the RF transceiver circuitry 3312 and the baseband processing circuitry 3314 may be on separate chips (or sets of chips), boards, or units, such as radio units and digital units. Inalternative embodiments, part or all of RF transceiver circuitry 3312 and baseband processing circuitry 3314 may be on the same chip or set of chips, boards, or units.

[0092] The memory 3304 may comprise any form of volatile or non-volatile computer-readable memory including, without limitation, persistent storage, solid-state memory, remotely mounted memory, magnetic media, optical media, random access memory (RAM), readonly memory (ROM), mass storage media (for example, a hard disk), removable storage media (for example, a flash drive, a Compact Disk (CD) or a Digital Video Disk (DVD)), and / or any other volatile or non-volatile, non-transitory device-readable and / or computer-executable memory devices that store information, data, and / or instructions that may be used by the processing circuitry 3302. The memory 3304 may store any suitable instructions, data, or information, including a computer program, software, an application including one or more of logic, rules, code, tables, and / or other instructions capable of being executed by the processing circuitry 3302 and utilized by the network node 3300. The memory 3304 may be used to store any calculations made by the processing circuitry 3302 and / or any data received via the communication interface 3306. In some embodiments, the processing circuitry 3302 and memory 3304 is integrated.

[0093] The communication interface 3306 is used in wired or wireless communication of signaling and / or data between a network node, access network, and / or UE. As illustrated, the communication interface 3306 comprises port(s) / terminal(s) 3316 to send and receive data, for example to and from a network over a wired connection. The communication interface 3306 also includes radio front-end circuitry 3318 that may be coupled to, or in certain embodiments a part of, the antenna 3310. Radio front-end circuitry 3318 comprises filters 3320 and amplifiers 3322. The radio front-end circuitry 3318 may be connected to an antenna 3310 and processing circuitry 3302. The radio front-end circuitry may be configured to condition signals communicated between antenna 3310 and processing circuitry 3302. The radio front-end circuitry 3318 may receive digital data that is to be sent out to other network nodes or UEs via a wireless connection. The radio front-end circuitry 3318 may convert the digital data into a radio signal having the appropriate channel and bandwidth parameters using a combination of filters 3320 and / or amplifiers 3322. The radio signal may then be transmitted via the antenna 3310. Similarly, when receiving data, the antenna 3310 may collect radio signals which are then converted into digital data by the radio front-end circuitry 3318. The digital data may be passed to the processingcircuitry 3302. In other embodiments, the communication interface may comprise different components and / or different combinations of components.

[0094] In certain alternative embodiments, the network node 3300 does not include separate radio front-end circuitry 3318, instead, the processing circuitry 3302 includes radio frontend circuitry and is connected to the antenna 3310. Similarly, in some embodiments, all or some of the RF transceiver circuitry 3312 is part of the communication interface 3306. In still other embodiments, the communication interface 3306 includes one or more ports or terminals 3316, the radio front-end circuitry 3318, and the RF transceiver circuitry 3312, as part of a radio unit (not shown), and the communication interface 3306 communicates with the baseband processing circuitry 3314, which is part of a digital unit (not shown).

[0095] The antenna 3310 may include one or more antennas, or antenna arrays, configured to send and / or receive wireless signals. The antenna 3310 may be coupled to the radio front-end circuitry 3318 and may be any type of antenna capable of transmitting and receiving data and / or signals wirelessly. In certain embodiments, the antenna 3310 is separate from the network node 3300 and connectable to the network node 3300 through an interface or port.

[0096] The antenna 3310, communication interface 3306, and / or the processing circuitry 3302 may be configured to perform any receiving operations and / or certain obtaining operations described herein as being performed by the network node. Any information, data and / or signals may be received from a UE, another network node and / or any other network equipment. Similarly, the antenna 3310, the communication interface 3306, and / or the processing circuitry 3302 may be configured to perform any transmitting operations described herein as being performed by the network node. Any information, data and / or signals may be transmitted to a UE, another network node and / or any other network equipment.

[0097] The power source 3308 provides power to the various components of network node 3300 in a form suitable for the respective components (e.g., at a voltage and current level needed for each respective component). The power source 3308 may further comprise, or be coupled to, power management circuitry to supply the components of the network node 3300 with power for performing the functionality described herein. For example, the network node 3300 may be connectable to an external power source (e.g., the power grid, an electricity outlet) via an input circuitry or interface such as an electrical cable, whereby the external power source supplies power to power circuitry of the power source 3308. As a further example, the power source 3308 maycomprise a source of power in the form of a battery or battery pack which is connected to, or integrated in, power circuitry. The battery may provide backup power should the external power source fail.

[0098] Embodiments of the network node 3300 may include additional components beyond those shown in Figure 13 for providing certain aspects of the network node’s functionality, including any of the functionality described herein and / or any functionality necessary to support the subject matter described herein. For example, the network node 3300 may include user interface equipment to allow input of information into the network node 3300 and to allow output of information from the network node 3300. This may allow a user to perform diagnostic, maintenance, repair, and other administrative functions for the network node 3300. In some embodiments providing a core network node, such as core network node 3108 of Figure 10, some components, such as the radio front-end circuitry 3318 and the RF transceiver circuitry 3312 may be omitted.

[0099] Figure 13 is a block diagram illustrating a virtualization environment 3400 in which functions implemented by some embodiments may be virtualized. In the present context, virtualizing means creating virtual versions of apparatuses or devices which may include virtualizing hardware platforms, storage devices and networking resources. As used herein, virtualization can be applied to any device described herein, or components thereof, and relates to an implementation in which at least a portion of the functionality is implemented as one or more virtual components. Some or all of the functions described herein may be implemented as virtual components executed by one or more virtual machines (VMs) implemented in one or more virtual environments 3400 hosted by one or more of hardware nodes, such as a hardware computing device that operates as a network node, UE, core network node, or host. Further, in embodiments in which the virtual node does not require radio connectivity (e.g., a core network node or host), then the node may be entirely virtualized. In some embodiments, the virtualization environment 3400 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an O-2 interface. Virtualization may facilitate distributed implementations of a network node, UE, core network node, or host.[000100] Applications 3402 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in thevirtualization environment 3400 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.[000101] Hardware 3404 includes processing circuitry, memory that stores software and / or instructions executable by hardware processing circuitry, and / or other hardware devices as described herein, such as a network interface, input / output interface, and so forth. Software may be executed by the processing circuitry to instantiate one or more virtualization layers 3406 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs 3408a and 3408b (one or more of which may be generally referred to as VMs 3408), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer 3406 may present a virtual operating platform that appears like networking hardware to the VMs 3408.[000102] The VMs 3408 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer 3406. Different embodiments of the instance of a virtual appliance 3402 may be implemented on one or more of VMs 3408, and the implementations may be made in different ways. Virtualization of the hardware is in some contexts referred to as network function virtualization (NFV). NFV may be used to consolidate many network equipment types onto industry standard high volume server hardware, physical switches, and physical storage, which can be located in data centers, and customer premise equipment.[000103] In the context of NFV, a VM 3408 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, non-virtualized machine. Each of the VMs 3408, and that part of hardware 3404 that executes that VM, be it hardware dedicated to that VM and / or hardware shared by that VM with others of the VMs, forms separate virtual network elements. Still in the context of NFV, a virtual network function is responsible for handling specific network functions that run in one or more VMs 3408 on top of the hardware 3404 and corresponds to the application 3402.[000104] Hardware 3404 may be implemented in a standalone network node with generic or specific components. Hardware 3404 may implement some functions via virtualization. Alternatively, hardware 3404 may be part of a larger cluster of hardware (e.g., such as in a data center or CPE) where many hardware nodes work together and are managed via management and orchestration 3410, which, among others, oversees lifecycle management of applications 3402. Insome embodiments, hardware 3404 is coupled to one or more radio units that each include one or more transmitters and one or more receivers that may be coupled to one or more antennas. Radio units may communicate directly with other hardware nodes via one or more appropriate network interfaces and may be used in combination with the virtual components to provide a virtual node with radio capabilities, such as a radio access node or a base station. In some embodiments, some signaling can be provided with the use of a control system 3412 which may alternatively be used for communication between hardware nodes and radio units.[000105] Although the computing devices described herein (e.g., UEs, network nodes) may include the illustrated combination of hardware components, other embodiments may comprise computing devices with different combinations of components. It is to be understood that these computing devices may comprise any suitable combination of hardware and / or software needed to perform the tasks, features, functions and methods disclosed herein. Determining, calculating, obtaining or similar operations described herein may be performed by processing circuitry, which may process information by, for example, converting the obtained information into other information, comparing the obtained information or converted information to information stored in the network node, and / or performing one or more operations based on the obtained information or converted information, and as a result of said processing making a determination. Moreover, while components are depicted as single boxes located within a larger box, or nested within multiple boxes, in practice, computing devices may comprise multiple different physical components that make up a single illustrated component, and functionality may be partitioned between separate components. For example, a communication interface may be configured to include any of the components described herein, and / or the functionality of the components may be partitioned between the processing circuitry and the communication interface. In another example, non-computationally intensive functions of any of such components may be implemented in software or firmware and computationally intensive functions may be implemented in hardware.[000106] In certain embodiments, some or all of the functionality described herein may be provided by processing circuitry executing instructions stored on in memory, which in certain embodiments may be a computer program product in the form of a non-transitory computer-readable storage medium. In alternative embodiments, some or all of the functionality may be provided by the processing circuitry without executing instructions stored on a separate ordiscrete device-readable storage medium, such as in a hard-wired manner. In any of those particular embodiments, whether executing instructions stored on a non-transitory computer- readable storage medium or not, the processing circuitry can be configured to perform the described functionality. The benefits provided by such functionality are not limited to the processing circuitry alone or to other components of the computing device, but are enjoyed by the computing device as a whole, and / or by end users and a wireless network generally.[000107] The above-described embodiments are examples only. Alterations, modifications, and variations may be effected to the particular embodiments by those of skill in the art without departing from the scope of the description, which is defined solely by the appended claims.

Claims

CLAIMSWhat is claimed is:

1. A method for meeting Cloud Radio Access Network, RAN, service run-time requirements, comprising: selecting (1010) one or more cloud clusters (590) compatible with one or more Radio Units, RUs (550), the selecting based at least in part on latency and / or on one or more settings; instantiating (1020) one or more virtual functions, referred to as Radio Affinity Pods, RAPDs (520, 540), in the one or more cloud clusters, each of the one or more RAPDs receiving one or more affinity labels; and enabling (1030) RAPD latency monitoring to validate the one or more affinity labels.

2. The method of claim 1, wherein the selecting is in response to an installation of one or more RUs.

3. The method of claim 1 or 2, further comprising, prior to selecting, installing one or more RUs or selecting one or more RUs to transition to Cloud RAN.

4. The method of any of claims 1 to 3, wherein compatibility is based at least in part on communication latency between the one or more RUs and the one or more cloud clusters.

5. The method of any of claims 1 to 4, wherein the one or more RUs are newly installed.

6. The method of claim 1 or 4, wherein the one or more RUs are already installed and in service.

7. The method of any of claims 1 to 6, wherein the one or more affinity labels comprise one or more of: one or more RU affinity labels, RALs; one or more RU anti-affinity labels, RAALs.

8. The method of any of claims 1 to 7, wherein the method is performed by an Orchestrator (595).

9. The method of any of claims 1 to 8, wherein the one or more RAPDs are configured to provide one or more telemetry and / or observability services to control the transport communication network towards the one or more RUs.

10. The method of any of claims 1 to 9, wherein the one or more affinity labels is based at least in part on a proximity area around the one or more RUs, the proximity area defined by a communication latency.

11. The method of any of claims 1 to 10, wherein the latency monitoring is at least one of: periodic; aperiodic.

12. The method of any of claims 1 to 11, further comprising updating the one or more affinity labels based at least in part on the latency monitoring.

13. The method of any of claims 1 to 12, further comprising, based at least in part on the one or more affinity labels, instantiating or preventing instantiation of one or more Cloud Radio Access Network, Cloud RAN, processes.

14. The method of claim 13, wherein the one or more RAN processes comprises at least one of: a Distributed Unit, DU (560); a Centralized Unit, CU; a cloud-native network function, CNF.

15. The method of any of claims 1 to 14, further comprising, based at least in part on the one or more affinity labels, providing cluster diversity to increase the resiliency of the Cloud RAN coverage.

16. The method of any of claims 1 to 15, further comprising receiving, from the one or more RAPDs, one or more energy efficiency data.

17. The method of any of claims 1 to 16, wherein the monitoring, and / or telemetry and / or observability services and / or providing cluster diversity is directed by an Orchestrator (595).

18. The method of any of claims 1 to 17, wherein the one or more DUs utilize one or more clusters based on the sustainability of their energy sources.

19. The method of any of claims 1 to 18, wherein the one or more RUs are installed in an open RAN, O-RAN, system.

20. The method of any of claims 1 to 19, wherein the one or more clusters comprise one or more Kubernetes clusters.

21. The method of any of claims 1 to 20, wherein the method is at least one of: computer implemented; performed by a network node; performed by a RU; performed by a base station; performed by a core network.

22. A method for run-time instantiation of new distributed unit, DU (560), binding, comprising: deploying (1210) one or more DUs to manage one or more radio units, RUs (550); filtering (1220) one or more cloud clusters (590) reporting one or more affinity labels; identifying (1230) any available cloud cluster; if there are one or more available cloud clusters, then selecting (1240) a target cloud cluster from the one or more available cloud clusters; and instantiating (1250) a new DU in the target cloud cluster; and if there are no available cloud clusters, then raising (1260) exception handling.

23. The method of claim 22, wherein the one or more affinity labels comprise one or more of: one or more RU affinity labels, RALs; one or more RU anti-affinity labels, RAALs.

24. The method of claim 22 or 23, wherein the method is performed by an Orchestrator (595).

25. The method of any of claims 22 to 24, wherein the one or more DUs are configured to provide one or more telemetry and / or observability services to control the transport communication network towards the one or more RUs.

26. The method of any of claims 22 to 25, wherein the one or more affinity labels is based at least in part on a proximity area around the one or more RUs, the proximity area defined by a communication latency.

27. The method of any of claims 22 to 26, further comprising performing latency monitoring to validate the one or more affinity labels.

28. The method of claim 27, wherein the latency monitoring is at least one of: periodic; aperiodic.

29. The method of any of claims 27 to 28, further comprising updating the one or more affinity labels based at least in part on the latency monitoring.

30. The method of any of claims 22 to 29, further comprising, based at least in part on the one or more affinity labels, instantiating or preventing instantiation of one or more Radio Access Network, RAN, processes.

31. The method of any of claims 22 to 30, further comprising, based at least in part on the one or more affinity labels, providing cluster diversity to increase the resiliency of the Cloud RAN coverage.

32. The method of any of claims 25, 27, or 31 , wherein the monitoring, and / or telemetry and / or observability services and / or providing cluster diversity is directed by an Orchestrator (595).

33. The method of any of claims 22 to 32, further comprising receiving, from the one or more RAPDs, one or more energy efficiency data.

34. The method of any of claims 22 to 33, wherein the one or more DUs utilize one or more sustainable energy sources.

35. The method of any of claims 22 to 34, wherein the one or more RUs are installed in an open RAN, O-RAN, system.

36. The method of any of claims 22 to 35, wherein the one or more cloud clusters comprise one or more Kubernetes clusters.

37. The method of any of claims 22 to 36, wherein the method is at least one of: computer implemented; performed by a network node; performed by a RU; performed by a base station; performed by a core network.

38. A system (500) for meeting Cloud Radio Access Network, RAN, service run-time requirements, comprising: one or more Radio Units, RUs (550); and one or more cloud clusters (590) configured to provide one or more microservices to the one or more RUs, each of the microservices being given one or more affinity labels to support redundancy and / or differentiation of services at the one or more RUs, wherein the one or more affinity labels is based at least in part on a proximity area around the one or more RUs, the proximity area defined by a communication latency.

39. The system of claim 38, wherein, upon activation of the one or more RUs, one or more compatible cloud clusters are selected from the one or more cloud clusters based at least in part on one or more settings, and one or more Radio Affinity Pods, RAPDs (520, 540) are instantiated in the one or more compatible cloud clusters, each of the one or more RAPDs receiving the one or more affinity labels.

40. The system of claim 38, wherein, upon activation of the one or more RUs, one or more DUs are deployed in the one or more cloud clusters to manage the one or more RUs, and wherein the one or more cloud clusters are filtered based at least in part on the one or more affinity labelsand the one or more microservices and, if there are one or more available cloud clusters, then a target cloud cluster is selected for one of the one or more microservices, and if there are no available cloud clusters, then exception handling is raised.

41. The system of any of claims 38 to 40, wherein the system comprises at least one of: a network node; a RU; a base station; a core network; a Kubernetes cluster; a Cloud Radio Access Network; an Orchestrator.

42. A network node (3300) for meeting Cloud Radio Access Network, RAN, service run-time requirements, the network node comprising: processing circuitry (3302) configured to perform any of the steps of any of claims 1 to 37; power supply circuitry (3308) configured to supply power to the processing circuitry.

43. A system (800) for meeting Cloud Radio Access Network, RAN, service run-time requirements, the system comprising: processing circuitry (3302) configured to perform any of the steps of any of claims 1 to 37; power supply circuitry (3308) configured to supply power to the processing circuitry.

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