System and method for RAN power and environmental orchestration

A power and environmental orchestration (P&EO) system uses network utilization condition information to implement scenarios that partially or fully reduce power requirements for radio access network (RAN) elements. A network device obtains power orchestration scenarios for a RAN and evaluates utilization data of multiple components of the RAN against the power orchestration scenarios. The network device determines that the utilization data meets a threshold for one of the power orchestration scenarios and applies the one of the power orchestration scenarios to reconfigure the RAN for reduced power consumption.

BACKGROUND

Development and design of radio access networks (RANs) present certain challenges from a network-side perspective, including increased power consumption of RAN components. Typically, wireless cell sites, hubs, or other sites are completely turned on and consuming full power or they are completely down and consuming none.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

In current radio access networks (RANs), there is no way to gracefully reduce power consumption during times of lower load. Various proposed solutions generally entail a complete shutdown of some elements, but there is no coordinated way of orchestrating the various components involved. Under normal operating conditions under a standard power grid, optimizing power consumption by RAN resources can reduce overall energy consumption in a wireless network. When emergency backup power is being used (e.g., in the event of a power failure), it would be beneficial to provide optimized power consumption of RAN resources to ensure that wireless access remains available to users.

According to implementations described herein, a Power and Environmental Orchestration (P&EO) system may use various RAN and network utilization condition information, from power control and measurement elements, to implement scenarios that partially or fully reduce power and cooling based on controlled systems.

The P&EO system may be designed to work with a network function virtualization (NFV) environment and can run on a Virtualized Controller Platform (VCP). The P&EO system can ingest power usage information from various devices in the site such as RU's (Radio Units), blades running in the VCP itself, transport equipment, power and cooling equipment, etc. The P&EO system may also ingest utilization information from virtualized Base Band Units (vBBU), as well as other equipment.

Further, P&EO system may have functional control over RAN elements such that adjustments to their configurations can be actively implemented to reduce power loads based on certain power orchestration scenarios. For example, as the user load meets certain usage scenario thresholds, the scenario may be enacted to reduce the Effective Isotropic Radiated Power (EIRP) of a transmit antenna power, which in turn results in reduced power consumption. Some units can be completely turned off. The cooling can then be reduced to match the resulting reduction in generated heat.

FIG. 1illustrates an exemplary environment100in which an embodiment of the P&EO system may be implemented. As illustrated, environment100includes an access network105, one or more edge networks130, a core network150, and one or more data networks160. Access network105may include wireless stations110-1through110-X (referred to collectively as wireless stations110and generally as wireless station110). Environment100further includes a P&EO controller170, a Self-Organizing Network (SON) function175, a P&EO prediction system180, and one or more UE devices190.

The number, the type, and the arrangement of network devices and the number of UE devices190illustrated inFIG. 1are exemplary. A network device, a network element, or a network function (referred to herein simply as a network device) may be implemented according to one or multiple network architectures, such as a client device, a server device, a peer device, a proxy device, a cloud device, a virtualized function, and/or another type of network architecture (e.g., Software Defined Networking (SDN), virtual, logical, network slicing, etc.). Additionally, a network device may be implemented according to various computing architectures, such as centralized, distributed, cloud (e.g., elastic, public, private, etc.), edge, fog, and/or another type of computing architecture.

Environment100includes communication links120between the networks, between the network devices, and between UE devices190and the network devices. Environment100may be implemented to include wired, optical, and/or wireless communication links120among the network devices and the networks illustrated. A connection via a communication link120may be direct or indirect. For example, an indirect connection may involve an intermediary device and/or an intermediary network not illustrated inFIG. 1. A direct connection may not involve an intermediary device and/or an intermediary network. The number and the arrangement of communication links illustrated in environment100are exemplary.

Access network105may include one or multiple networks of one or multiple types and technologies. For example, access network105may include a Fifth Generation (5G) radio access network (RAN), Fourth Generation (4G) RAN, and/or another type of future generation RAN. By way of further example, access network105may be implemented to include a 5G New Radio (5G NR) RAN, an Evolved UMTS Terrestrial Radio Access Network (E-UTRAN) of a Long Term Evolution (LTE) network, an LTE-Advanced (LTE-A) network, and/or an LTE-A Pro network, and/or another type of RAN (e.g., a legacy RAN). Access network105may further include other types of wireless networks, such as a WiFi network, a Worldwide Interoperability for Microwave Access (WiMAX) network, a local area network (LAN), or another type of network that may provide an on-ramp to wireless stations110and/or core network150.

Depending on the implementation, access network105may include one or multiple types of wireless stations110. For example, wireless station110may include a next generation Node B (gNB) for a 5G NR RAN, an evolved Node B (eNB), an evolved Long Term Evolution (eLTE) eNB, a radio network controller (RNC), a remote radio head (RRH), a baseband unit (BBU), a small cell node (e.g., a picocell device, a femtocell device, a microcell device, a home eNB, a repeater, etc.), or another type of wireless node. According to various embodiments, access network105may be implemented according to various wireless technologies (e.g., radio access technology (RAT), etc.), wireless standards, wireless frequencies/bands, and so forth. According to an implementation, wireless stations110may include a gNB with multiple distributed components, such as a central unit (CU), a distributed unit (DU), a remote unit (RU or a remote radio unit (RRU)), or another type of distributed arrangement. As further discussed below, wireless stations110(as part of access network105) may be part of a Self-Organizing Network (SON) that may be reconfigured by another component in networks105,130, and/or150.

Each wireless station110typically uses multiple carrier frequencies in a single instance. For example, a single wireless station110may provide coverage over an area referred to as a cell. A cell typically uses multiple carrier frequencies to meet capacity demands and provide guaranteed service quality within each cell. It is not cost effective to deploy all carrier frequencies on every cell that a wireless carrier manages in a particular area. A cell may be divided into one or more sectors, with each sector providing different areas of coverage that may overlap. A particular sector may also transmit and/or receive signals on one or more predefined carrier frequencies. The combination of a sector and a particular carrier frequency may be referred to herein as a “sector carrier.”

Edge network130includes a platform that provides application services at the edge of a network, such as services for the P&EO system described herein. For example, edge network130may be implemented as a Multi-access Edge Compute (MEC) platform. Edge network130may include network devices located to provide geographic proximity to various groups of wireless stations110. In some embodiments, components of edge network130may be co-located with wireless stations110in RAN105. In other embodiments, wireless stations110may connect to edge network130via wired (e.g., optical) backhaul links120.

Edge network130may be implemented using one or multiple technologies including, for example, network function virtualization (NFV), software defined networking (SDN), cloud computing, or another type of network technology. Depending on the implementation, edge network130may include, for example, virtualized network functions (VNFs), multi-access (MA) applications/services, and/or servers. Edge network130may also include other network devices that support its operation, such as, for example, a network function virtualization orchestrator (NFVO), a virtualized infrastructure manager (VIM), an operations support system (OSS), a local domain name server (DNS), a virtual network function manager (VNFM), and/or other types of network devices and/or network resources (e.g., storage devices, communication links, etc.).

Core network150may include one or multiple networks of one or multiple network types and technologies. For example, core network150may be implemented to include a next generation core (NGC) network for a 5G network, an Evolved Packet Core (EPC) of an LTE network, an LTE-A network, an LTE-A Pro network, and/or a legacy core network. Depending on the implementation, core network150may include various network components and devices155, such as for example, a user plane function (UPF), an access and mobility management function (AMF), a session management function (SMF), a unified data management (UDM) device or function, an authentication server function (AUSF), a network slice selection function (NSSF), network data analytics function (NWDAF), and so forth. For purposes of illustration and description, network devices155may include various types of network devices that may be resident in core network150.

Core network150may manage communication sessions for UE devices190. For example, core network130may establish an Internet Protocol (IP) connection between UE device190and a particular data network160. Furthermore, core network150may enable UE device190to communicate with an application server or another type of network device165located in a particular data network160using a communication method that does not require the establishment of an IP connection between UE device190and data network160, such as, for example, Data over Non-Access Stratum (DoNAS).

Data network160may include one or multiple networks. For example, data network160may be implemented to include a service or an application-layer network, the Internet, an Internet Protocol Multimedia Subsystem (IMS) network, a Rich Communication Service (RCS) network, a cloud network, a packet-switched network, or other type of network that hosts a user device application or service. Depending on the implementation, data network160may include various network devices that provide various applications, services, or other type of user device assets (e.g., servers (e.g., web, application, cloud, etc.), mass storage devices, data center devices), and/or other types of network services pertaining to various network-related functions.

P&EO controller170may include one or more network devices configured to implement the P&EO system. According to an implementation, P&EO controller170may monitor RAN utilization data and implement power orchestration scenarios during periods of low use to reduce/optimize power consumption by RAN components, while maintaining required levels of service. According to an implementation, P&EO controller170may be included at a network edge, such as within access network105or edge network130. According to another implementation, P&EO controller170may select an edge resource, from the multiple edge networks130and or wireless stations110, to provide requested power optimization services and may instruct the edge devices to perform container provisioning and service provisioning for the P&EO system. P&EO controller170is described further in connection with, for example,FIGS. 3-5.

As further shown, core network150may include a SON function175. Depending on the embodiment, SON function175may be implemented as one or more network devices and/or software (e.g., a program). SON function175may include logic for modifying operating parameters of access network105, including those of wireless stations110. As further explained below, P&EO controller170may notify SON function175when thresholds (e.g., one or more indicators of RAN utilization levels) for a power orchestration scenario have been met. SON function175may determine an optimal solution for a reduced power use configuration (e.g. EIRP, up or down tilt, or other applicable parameters) for the given scenario. According to an implementation, SON function175may enact the reduced power use configuration by issuing commands to wireless stations110and/or other components in access network105. In another implementation, SON function175may direct P&EO controller170to implement some or all of the configuration changes to enact the reduced power use configuration.

P&EO prediction system180may generate power orchestration scenarios350that can be used by P&EO controller170to detect and initiate reduced power use configurations for devices in access network105. According to an implementation, P&EO prediction system180may ingest historical network data and apply machine learning to predict conditions when wireless stations110or other network elements can implement reduced power use configurations.

UE devices190may each include a mobile device, such as wireless or cellular telephone device (e.g., a conventional cell phone with data processing capabilities), a smart phone, a personal digital assistant (PDA) that can include a radiotelephone, etc. In another implementation, UE device190may include any type of mobile or fixed computer device or system, such as a personal computer (PC), a laptop, a tablet computer, a notebook, a netbook, a wearable computer (e.g., a wrist watch, eyeglasses, etc.), a game playing device, a music playing device, etc. In other implementations, UE devices190may be implemented as a machine-type communications (MTC) device, an Internet of Things (IoT) device, a machine-to-machine (M2M) device, etc., that includes communication functionality, such as a home appliance device, a home monitoring device, a camera, etc. UE devices190may connect to wireless stations110in a wireless manner.

FIG. 2Aillustrates exemplary logical components of wireless stations110ofFIG. 1according to one implementation. Consistent withFIG. 1, wireless stations110is included in access network105. Although access network105may include other wireless stations110, they are not shown inFIG. 2A. Each of wireless station includes a central unit (CU)202, distributed units (DUs)204-1through204-M, and, for each DU204, one or more Radio Units (RUs)206-1through206-N. RU206may also be referred to as a remote radio head (RRH). For simplicity, other RUs are not shown inFIG. 2A.

CUs202may control DUs204over a front haul interface. CUs202may manage, for example, sharing access network105, conveying user data, mobility, sessions, etc. For each CU202, there may be multiple DUs204that the CU202controls.

CU202may process upper layers402of the communication protocol stack for wireless stations110. CUs202may not necessarily be physically located near DUs204, and may be implemented as cloud computing elements, through network function virtualization (NFV) capabilities of the cloud. In one implementation, CU202communicates with components of core network150through S1/NG interfaces and with other CUs202through X2/XN interfaces.

DUs204may be controlled by CU202. For each DU204in access network150, there is only one CU202. However, each DU204may send signals to multiple RUs206for transmission. DUs204may handle UE device mobility, from DU to DU, from a wireless station110to another wireless station110, from a cell to another cell, from a beam to another beam, etc. DUs204communicate with a CU202through an F1 interface, and may process lower layers of a communication protocol stack for wireless station110.

FIG. 2Billustrates exemplary logical components of the RUs206ofFIG. 2Aaccording to one implementation. As shown, RU206-1may include radio circuit (RC)212-1and antenna elements214-1. RU206-2may include radio circuit212-2and antenna elements214-2. Depending on the implementation, RU206-1and RU206-2may include additional, fewer, different, or differently arranged components than those illustrated inFIG. 2B.

RC212may receive signals from DU206, process them, and send them to antenna elements214for transmission. Antenna elements214may receive the signals and radiate the signals as a beam216. InFIG. 2B, antenna elements214-1are shown as forming a beam216-1that reaches coverage area218-1and, and antenna elements214-2are shown as forming beam216-2that reach coverage area218-2.

RUs206inFIG. 2Bare capable of controlling beam shape, beam strength, and beam directions to balance traffic load over different bands. For example, assume that beam216-1and beam216-2cover the same area. DU204may set a minimum transmit power level at RU206-1for which UE devices in coverage area218-1may connect to wireless station110through beam216-1. If SON function175instructs CU202and thus DU204to increase the minimum transmit power level for RU206-1, the UE devices102in coverage area218-1may no longer remain connected to wireless station110via beam216-1(assuming that the signal strengths are the same). In the scenario, the UE devices102may then connect to wireless station110via beam218-2(which may occupy another frequency band), assuming that minimum transmit power level for the corresponding RU206-2remains the same. Accordingly, by lowering or raising the minimum transmit power level at DUs204, SON function175may decrease or increase the traffic load at a particular band.

In another example, assume that beams216-1and216-2cover the same area (i.e.,218-1and218-2are the same) and that beam216-1carries more traffic than beam216-2by y % (e.g., 15%). If beams216-1and216-2differ in direction by an angle X (e.g., 1 degree) beam216-1(which may be determined by comparing the portion of beam216-1with at least 3 DB power to the portion of beam216-2with at least 3 DB power), SON function175may instruct DU204(via CU202) to tilt up beam216-2, to better cover its area.

FIG. 3is a block diagram illustrating an exemplary implementation of the P&EO system of in a portion300of network environment100. As shown inFIG. 3, network portion300may include P&EO controller170, SON function175, a power supply305, one or more air conditioning (A/C) units310, intermediate equipment315-1through315-X (referred to collectively as “intermediate equipment315”), radio equipment320-1through320-Y (referred to collectively as “radios320”), a power control bus330, a data bus340, and power orchestration scenarios350.

Power supply305may include an emergency or permanent electrical power source for equipment associated with a wireless station110or another component of access network105. For example, a permanent power supply may include a continuous alternating current (AC) power source. Alternatively, power supply305may include an emergency direct current (DC) power source, such as a generator or a battery that engages in the event of a power failure, for example.

A/C unit310may include an environmental cooling system for intermediate equipment315and/or radio equipment320in access network105. A/C unit310may also include an environmental cooling system for systems impacted by changes to loads in wireless stations110, such as backend systems in edge network130and/or core network150.

Intermediate equipment315may include components such as routers and multiplexers within access network105. Intermediate equipment315may correspond to access network equipment located between core network150and RU206, for example. Radio equipment320may include one or more radio components of wireless station110, such as RU206.

Power control bus330may include a communications channel to allow P&EO controller170to adjust power levels to devices in access network105and/or other components in network portion300.

Data bus340may include a message bus to exchange data between components in network portion300. The data may include user demand and utilization data, as well as RAN and other data. The power utilization is also collected either from the equipment itself or from clamp on power meters (not shown), which may tie into data bus340. Data bus340may support, for example, a publish-subscribe (pub-sub) model. In a data bus340, such as a Pulsar bus or Kafka bus, a producer contributes a stream of records to one or more topics. A consumer subscribes to the one or more topics, and selectively retrieves records of subscribed topics for consumption. Data bus340may feed real-time open source remote procedure calls (e.g., gRPC), Simple Network Management Protocol (SNMP), or other data to P&EO controller170.

Power orchestration scenarios350may include model for different access network105configurations that can be implemented to optimize network equipment utilization and power consumption for given customer use rates. For example, power orchestration scenarios350may identity times and/or usage thresholds where the number of active sector carriers can be reduced for certain wireless stations110while still providing required levels of service.

For example, assume the number of users served by a wireless station110with twelve sector carriers falls to a low level during an off-peak period. When at full power, assume the wireless station110consumes 15 kWh. Preferably, a power orchestration scenario350would permit the wireless station110to serve the active users during the off-peak period using only two sector carriers with significantly reduced power (e.g., 1 or 2 kWh) and a corresponding cooling adjustment. As described further herein, power orchestration scenarios350may be modeled and adapted by applying artificial intelligence and/or machine learning to historical network data, such as data collected via data bus340.

AlthoughFIG. 3illustrates one arrangement of an environment300for a P&EO system, in other implementations, environment300may contain fewer components, different components, differently-arranged components, or additional components than depicted inFIG. 3. For example, in another implementation, a network data analytics function (NWDAF) or another core network component may provide additional network utilization data. Thus, communications described above in connection withFIG. 3may use different communications interfaces to exchange data and provide power orchestration scenarios350than described above. Alternatively, or additionally, one or more components of environment300may perform one or more other tasks described as being performed by one or more other components of environment300.

FIG. 4is a block diagram illustrating an exemplary implementation of the P&EO system of in a virtualization platform400of the network environment100. As shown inFIG. 4, virtualization platform400may include a virtualized controller platform (VCP)410. Components of VCP410may be included in core network150(e.g., network devices155), an edge hub for access network105, or edge network130.

VCP410may include one or more physical computing resources, such a as processors, computer devices, etc., referred to as blades412inFIG. 4. Virtual network devices, referred to herein as network function virtualization (NFV) instances416-1through416-Q, may be implemented on blades412under direction of a hypervisor414or another type of virtual machine monitor. In other implementations, NFV instances416may be implemented using one or multiple virtualization technologies, such as a hypervisor, a host, a container, a virtual machine (VM), a network function virtualization (NFV) infrastructure, a network function virtualization orchestrator (NFVO), a virtual network function manager (VNFM), a virtualized infrastructure manager (VIM), a platform manager and/or other types of virtualization elements (e.g., virtual network function (VNF), etc.), layers, hardware resources, operating systems, software resources, engines, etc.

According to an implementation, P&EO controller170may be implemented as one of NFV instances416within VCP410. Other NFV instances416may control forwarding of packets via to/from access network105. For example, NFV instances416may be configured to support network slices configured with different characteristics to support different types of applications and/or services, such as video streaming, massive Internet-of-Things (IoT) traffic, autonomous driving, etc. NFV instances416may also apply admission controls to direct wireless stations110and/or other network devices in backhaul links120to admit, block, delay or redirect a requesting UE device190depending on slice congestion levels and other factors. Thus, the usage and power consumption of blades410may be directly or indirectly related to the number of active NFV instances416executing on410. Blades410may report power usage information to P&EO controller170via data bus340, for example.

FIG. 4illustrates exemplary components of virtualization platform400. Depending on the implementation, virtualization platform400may include additional, fewer, different, or differently arranged components than those illustrated inFIG. 4.

FIG. 5is a flow diagram illustrating exemplary processes500for optimizing power consumption in a radio access network. In one implementation, process500may be performed by P&EO controller170. In another implementation, process500may be performed by P&EO controller170in conjunction with SON function175and/or another network device in network environment100.

Process500may include obtaining power orchestration scenarios (block510). For example, power orchestration scenarios350may be provided to P&EO controller170and/or generated by P&EO controller170. The power orchestration scenarios may include triggering thresholds and network configurations to optimize power consumption for access network105, particularly during periods of low utilization.

Process500may further include ingesting utilization data (block520), evaluating the utilization data against the power orchestration scenarios (block530), and determining if a power orchestration scenario is met (block540). For example, P&EO controller170may receive utilization and power use information from devices (e.g., intermediate equipment315, radio equipment320, etc.) in access network105via data bus340. P&EO controller170may identify thresholds from power orchestration scenarios350and determine if one or more thresholds are met in the collected utilization and power use information.

If a power orchestration scenario is not met (block540—No), process500may return to process block520to continue to ingest utilization data. If a power orchestration scenario is met (block540—Yes), process500may include interfacing with a SON function to check for an alternate solution (block550) and determining if an alternate SON solution is available (block560). For example, P&EO controller170may optionally interface with SON function175to confirm or change optimal reduced-power settings for access network105. In one implementation, SON function175may verify that a particular power orchestration scenario350identified by P&EO controller170is suitable for implementation. In another implementation, SON function175may provide an alternative reduced-power configuration for access network105or override a power orchestration scenario to maintain full power.

If an alternate SON solution is available (block560—Yes), process500may additionally include applying a power control template from the SON recommendation (block570). For example, SON function175may provide control information to P&EO controller170as to what the optimal reduced power settings are for access network105. Alternatively, SON function175may determine that other network factors may preclude implementation of reduced power settings.

If an alternate SON solution is not available (block560—No), process500additionally include applying the power orchestration scenario (block580). For example, P&EO controller170may determine that appropriate low-utilization thresholds are met for one or more wireless stations110in access network105and that SON function175has not supplied additional input (if applicable). P&EO controller170may then implement an appropriate power orchestration scenario350to optimize use of radio resources in wireless station110and reduce power consumption in access network105. For example, a number of sector carriers for a wireless station110may be powered down while the power level of the remaining sector carriers may be increased and antenna down tilt increased to control interference to other sites. Alternatively, P&EO controller170may determine that utilization levels needs to increase above a threshold for one or more wireless stations110and that SON function175has not supplied additional input (if applicable). Accordingly, P&EO controller170may implement an appropriate power orchestration scenario350to increase use of radio resources in wireless station110to higher or full capacity.

FIG. 6. is a diagram illustrating P&EO prediction system180for generating/updating power consumption models, according to an implementation described herein. System180may include one or more modeling functions610and a prediction engine620. System180may be implemented, for example, in one or more network devices155of core network150. In other implementations, system180may be implemented in one or more of edge networks130or in a distributed environment.

Modeling function610may receive utilization data602, environmental conditions604, and power measurements606from network sources. Utilization parameters602, for example, may be collected by one or more Operations, Administration, and Maintenance (OAM) systems in network environment100(e.g., in access network105and/or core network150) and stored in a database where modeling function610may access these data elements to estimate/predict low utilization periods for possible power level savings based on various parameters, such as those listed in connection withFIG. 7, as well as others that can be considered. For each wireless station110, modeling function610may create a predictive utilization model, such as prediction weight table612, that predicts the power savings vs. network performance cost trade off.

FIG. 7provides a diagram illustrating a portion of a prediction weight table612for a power orchestration scenario. Referring toFIG. 7, prediction weight table612may include one or more parameter identifier fields705, one or more threshold fields710, one or more weight factor fields715, and a variety of entries750associated with each of fields705-715. In table700, each set of rows may correspond to a separate threshold input parameter. In one implementation, thresholds may apply to the resource usage and performance of each respective wireless station110. That is, each wireless station110(or another network element) may have a table700that is fed into the prediction engine620.

Parameter identifier field705may include one or more measurable indicators of a wireless station110that may have an impact on network power consumption. Parameter identifier field705may include one or two or more features in combination, that may be indicative of particular network conditions where power consumption can be reduced. Features may include, for example, a utilization percentage, a number of connected users (e.g., a number of radio resource control (RRC) connections), a physical resource block (PRB) utilization level, a transition time interval (TTI) utilization, a throughput level (e.g., burst user throughput), Channel Quality Indicator (CQI) Received Signal Strength Indication (RSSI) value, Timing Advance (TA) distance, mobility, etc. Each data element in parameter identifier field705maps to a particular threshold in threshold field710, which is mapped to power savings weighting factor in weight factor field715.

Threshold field710may include one or more thresholds for features in corresponding parameter identifier fields705. Threshold field710may include a numerical value, a percentage value, or another type of value that may indicate, for example, that a wireless station may be experiencing low utilization.

Weight factor field715may include a weight factor for elements in corresponding parameter identifier fields705. The weight factor may be indicative of the potential power savings associated with corresponding element. The weight values in weight factor field715may have an initial estimate but can be changed over time as various conditions or results vary depending on the specific user patterns or other unique factors for a specific wireless station110. Further, the feedback from SON function175may alter thresholds dynamically as well. This approach can be used to refine scenarios over time as actual realized power savings vs. network performance results. Utilization in some scenarios may be cyclical (i.e., time of day, commuter vs. work-at-home traffic, etc.). Thus required power levels can be predictable.

AlthoughFIG. 7shows exemplary information that may be provided in prediction model612for a wireless station110, in other implementations, prediction model612may contain less, different, differently-arranged, or additional information than depicted inFIG. 7. For example, fields in prediction model612may be broken down by sector carrier and include time of day and other external data. Also, prediction model612may be replaced with a flat file structure with strings of features and settings in place of designated fields.

Returning toFIG. 6, prediction engine620may receive prediction models612and may create power orchestration scenarios350based on the prediction models612. For example, prediction engine620may determine combinations of wireless stations110that can support predicted conditions with lower-than-normal power for given periods. Prediction engine620may identify, for example, different combinations of sector carriers at different wireless stations that can be used to provide a low-power consumption scenario for periods of low RAN utilization. According to an implementation, prediction engine620may apply artificial intelligence to provide initial estimates based on training data and provide updates as historical data is added to the data set. Power orchestration scenarios350may be provided to P&EO controller170for implementation, as described above in connection withFIG. 3, for example.

FIG. 8is a flow diagram illustrating an exemplary process800for generating a power orchestration scenario the P&EO system. In one implementation, process800may be performed by prediction system180. In another implementation, process800may be performed by P&EO prediction system180in conjunction with one or more other network devices in network environment100, such as P&EO controller170and/or SON function175.

Process800may include ingesting network utilization data (block810), and estimating possible power level savings (block820). For example, modeling function610of P&EO prediction system180may receive RAN utilization data and other data from network elements. In one implementation, various network utilization data may be collected via OAM systems that feed a local database accessible by modeling function610. In one aspect, modeling function610may normalize the data, remove outliers, etc. Using different artificial intelligence and machine learning processes, for example, modeling function610may access the stored data elements to estimate and/or predict possible power level savings based on the various parameters. According to an implementation, modeling function610may generate a prediction weight table612for each wireless station110.

Process800may further include generating a power orchestration scenario (block830), and providing the power orchestration scenario to a controller (block840). For example, prediction engine620may receive prediction models612from modeling function610and may create power orchestration scenarios350based on the prediction models612. Prediction engine620may forward the power orchestration scenarios350to P&EO controller170for implementation. Additionally, as new network utilization data is provided, modeling function610may provide updated prediction models612, which in turn may be used by prediction engine620to updated power orchestration scenarios350.

FIG. 9is a block diagram illustrating exemplary components of a device that may correspond to one of the devices ofFIGS. 1-8. Each of wireless station110, network devices155, P&EO controller170, SON function175, P&EO prediction system180, end device190, and VCP410may be implemented as a combination of hardware and software on one or more of devices900. As shown inFIG. 9, device900may include a bus910, a processor920, a memory930with software935, an input device940, an output device950, and a communication interface960.

Communication channel910may include a path that permits communication among the components of device900. Processor920may include a processor, a microprocessor, or processing logic that may interpret and execute instructions. Memory930may include any type of dynamic storage device that may store information and instructions, for execution by processor920, and/or any type of non-volatile storage device that may store information for use by processor920.

Software935includes an application or a program that provides a function and/or a process. Software935is also intended to include firmware, middleware, microcode, hardware description language (HDL), and/or other form of instruction. By way of example, when device900is an P&EO controller170, software935may include power orchestration scenarios350, as described herein.

Input device940may include a mechanism that permits a user to input information to device900, such as a keyboard, a keypad, a button, a switch, touch screen, etc. Output device950may include a mechanism that outputs information to the user, such as a display, a speaker, one or more light emitting diodes (LEDs), etc.

Communication interface960may include a transceiver that enables device900to communicate with other devices and/or systems via wireless communications, wired communications, or a combination of wireless and wired communications. For example, communication interface960may include mechanisms for communicating with another device or system via a network. Communication interface960may include an antenna assembly for transmission and/or reception of RF signals. For example, communication interface960may include one or more antennas to transmit and/or receive RF signals over the air. In one implementation, for example, communication interface960may communicate with a network and/or devices connected to a network. Alternatively or additionally, communication interface960may be a logical component that includes input and output ports, input and output systems, and/or other input and output components that facilitate the transmission of data to other devices.

Device900may perform certain operations in response to processor920executing software instructions (e.g., software935) contained in a computer-readable medium, such as memory930. A computer-readable medium may be defined as a non-transitory memory device. A non-transitory memory device may include memory space within a single physical memory device or spread across multiple physical memory devices. The software instructions may be read into memory930from another computer-readable medium or from another device. The software instructions contained in memory930may cause processor920to perform processes described herein. Alternatively, hardwired circuitry may be used in place of or in combination with software instructions to implement processes described herein. Thus, implementations described herein are not limited to any specific combination of hardware circuitry and software.

Device900may include fewer components, additional components, different components, and/or differently arranged components than those illustrated inFIG. 9. As an example, in some implementations, a display may not be included in device900. As another example, device900may include one or more switch fabrics instead of, or in addition to, bus910. Additionally, or alternatively, one or more components of device900may perform one or more tasks described as being performed by one or more other components of device900.

Systems and methods described herein provide a power and environmental orchestration (P&EO) system that uses network utilization condition information to implement scenarios that partially or fully reduce power requirements for radio access network (RAN) elements. A network device obtains power orchestration scenarios for a RAN and evaluates utilization data of multiple components of the RAN against the power orchestration scenarios. The network device determines that the utilization data meets a threshold for one of the power orchestration scenarios and applies the one of the power orchestration scenarios to reconfigure the RAN for reduced power consumption.

The P&EO system described herein provides the ability to measure, predict, and control power consumption based on user demand for predicted performance, which can reduce the cost of power use and also plant costs. The P&EO system may also allow networks to adapt to known power constraints, such as scheduled outages, brownouts, etc. In a power failure scenario, the P&EO system described herein also may apply reduced performance criteria to maximize battery and generator capacity until a service restoration. Additionally, the P&EO system may allow certain types of traffic, such as IoT with low bandwidth, to be moved to a lower power band (such as 700 MHz) if demand is low, since the power needed for higher bands (such as millimeter-wave bands) can be reserved for higher bandwidth applications.

Additionally, embodiments described herein may be implemented as a non-transitory computer-readable storage medium that stores data and/or information, such as instructions, program code, a data structure, a program module, an application, a script, or other known or conventional form suitable for use in a computing environment. The program code, instructions, application, etc., is readable and executable by a processor (e.g., processor920) of a device. A non-transitory storage medium includes one or more of the storage mediums described in relation to memory930.

No element, act, or instruction set forth in this description should be construed as critical or essential to the embodiments described herein unless explicitly indicated as such. All structural and functional equivalents to the elements of the various aspects set forth in this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims.