A distributed and adaptive scheduling scheme for power-overbooked multi-carrier radios

Abstract

A method, system and apparatus are disclosed. In an example embodiment, a network node is configured to determine a resource constraint pattern for distributed management of shared resource across multiple carriers. The network node is configured to calculate at least one metric based on the resource constraint pattern. The network node is configured to schedule a transmission in at least one slot based on the at least one metric.

Description

[0001] A DISTRIBUTED AND ADAPTIVE SCHEDULING SCHEME FOR POWER-

[0002] OVERBOOKED MULTI-CARRIER RADIOS

[0003] TECHNICAL FIELD

[0004] The present disclosure relates to wireless communications, and in particular, to managing power and resource utilization.

[0005] BACKGROUND

[0006] The Third Generation Partnership Project (3GPP) has developed and is developing standards for Fourth Generation (4G) (also referred to as Long Term Evolution (LTE)) and Fifth Generation (5G) (also referred to as New Radio (NR)) wireless communication systems. Such systems provide, among other features, broadband communication between network nodes, such as base stations, and user equipment (UE), as well as communication between network nodes and between UEs. The 3 GPP is also developing standards for Sixth Generation (6G) wireless communication networks.

[0007] Mobile networks are constantly evolving to support various use-cases and more users that would impose an ever-growing traffic demand. To address the increasing data rate, different technologies, such as carrier aggregation, massive Multiple Input Multiple Output (MIMO), and beamforming, are introduced to the new generations of mobile networks. Using such technologies to increase the number of antennas and to scale the bandwidth, however, can proportionately increase the power consumption. Also, dimensioning total power consumption can also contribute to a larger size and weight of the radio products, as more power dissipation would require more extensive cooling. Hence, it may be important to have an energy efficient Radio Access Network (RAN) solution.

[0008] Power pooling is a new concept that is proposed to efficiently share the total power capability of a multi-band radio across different sector-carriers. The idea is to reduce the total power capability of the radio, compared to the sum of the advertised power of all sector-carriers sharing the radio, thus reducing the size and weight of the radio. Under the assumption that different sector carriers have relatively uncorrelated peak resource utilization events, it is possible to maintain almost the same Key Performance Indicators (KPIs), such as coverage and throughput for each sector carrier. For example, consider a dual band radio with a total power capability of 40 W, supporting two carriers of 20 MHz bandwidth. With 25% power overbooking, each carrier is configured with a total power of 25 Watt, thus the total configured power exceeds the radio nominal power (i.e., 50 > 40). Overbooking the power helps elevate the Power Spectral Density (PSD) (from the PSD of 1 Watt / MHz to 1.25 Watt / MHz in this example), which would provide the same coverage as if the radio had a higher power capability. The two sector carriers, however, may not allocate the whole bandwidth at a high PSD level at the same time.

[0009] The radio may overheat if the total power usage constantly exceeds the nominal power capability. Moreover, the transmitted signal may experience an excessively higher Error Vector Mean (EVM) during a period of a power overshoot event while the total power used by the carriers exceeds the radio power capability.

[0010] Thus, certain measures should be taken, e.g., at the radio and / or baseband, to avoid radio overheating in the presence of power overbooking, while maintaining the same KPIs as if a radio with higher power capability were implemented. There are different approaches to address the impacts of power overbooking. Particularly, some of the existing solutions implement certain adaptations only at the radio, while other methods rely on joint design and coordination of the radio and baseband.

[0011] FIG. 1 shows an overview of the network node deployment architecture, illustrating the main components, namely radio unit (RU), and the digital unit (DU). The digital unit includes the radio processing controller (RPC), and the baseband units (BBUs). The RPC handles higher layer functionalities for one or multiple BBUs and can be collocated with the BBU(s) or located at a remote central unit in a cloud-based implementation. A scheduler in a BBU will handle scheduling of resources of one component carrier. It’s worth noting that the schedulers of different component carriers (CCs) could be implemented by the same BBU (referred to as local carriers), or by BBUs at different DUs.

[0012] The most straightforward schemes are those which are transparent to the baseband and scheduler, and just rely on the radio to avoid overheating. In practice, the radio continuously measures the consumed power and would apply a power backoff if it finds the total power is exceeding a specific threshold over a certain time interval. In case of a power backoff, the radio may then follow a slow-recovery procedure to gradually increase the power in a step-by-step manner after recovering from an overheating event. Such a method, however, may result in a prolonged power backoff, and therefore a degraded coverage over the busy hours. That is, under a high loading condition, both carriers may strive to allocate the whole bandwidth which would result in a prolonged power overshoot event. This may eventually cause the radio to backoff the power, which would impact the coverage.

[0013] Another extreme approach is to have a tight coordination between the radio and the baseband, and among the schedulers of different carriers. In this way it would be possible to avoid any power overshoot events by making joint scheduling decisions across different sector carriers. Such schemes firstly need to extend the existing interfaces (such as the fronthaul interface between baseband and radio, or the E5 tunnel among the schedulers) to pass new signaling information. Hence, they may not be applicable to legacy radio products. Moreover, the overhead of signaling, and the complexity of making joint scheduling decisions across different sector carriers could be prohibitively large.

[0014] SUMMARY

[0015] Some embodiments advantageously provide methods, systems, and apparatuses for managing power and resource utilization.

[0016] Described herein are solutions that enable distributed implementation of the scheduler for different sector carriers, while maintaining a minimum coordination between the sector carriers, or between the baseband and the radio.

[0017] Advantages of some embodiments include not requiring any additional signaling across schedulers of different sector carriers, or between BBU and the radio. This is in contrast with some of the existing approaches, which require signaling and coordination across sector carriers at the TTI-level.

[0018] Some embodiments enable distributed implementation of the scheduler for different sector carriers, while ensuring certain constraints on the total power in the presence of power overbooking at a low complexity. By protecting certain slots against power overshooting, cell-defining reference signals can be robustly transmitted. The EVM-aware scheduler described in some embodiments helps reduce the risk of EVM, and saves energy at the same time, by applying user-specific backoffs for users with a good channel condition, while the users at the cell edge may still get covered with an elevated PSD.

[0019] According to one aspect of the present disclosure, a network node is provided. Network node is configured to determine a resource constraint pattern for distributed management of shared resource across multiple carriers. Network node is configured to calculate at least one metric based on the resource constraint pattern. Network node is configured to schedule a transmission in at least one slot based on the at least one metric. According to one or more embodiments of this aspect, the resource constraint pattern includes at least one resource-specific estimate of a parameter.

[0020] According to one or more embodiments of this aspect, the parameter includes at least one of error vector magnitude, EVM, phase noise, or distortion.

[0021] According to one or more embodiments of this aspect, the resource constraint pattern indicates that, in the at least one slot, power overbooking is one of: restricted; unrestricted; or permitted below a threshold and restricted above the threshold.

[0022] According to one or more embodiments of this aspect, the threshold is based on maintaining a maximum error vector magnitude, EVM, within a predetermined range.

[0023] According to one or more embodiments of this aspect, network node is further configured to apply a power backoff based on at least one of channel quality information, CQI, and error vector magnitude, EVM.

[0024] According to one or more embodiments of this aspect, network node is further configured to limit total allocated resources in the at least one slot based on a power constraint.

[0025] According to one or more embodiments of this aspect, network node is further configured to schedule the transmission based on a risk of error vector magnitude, EVM, in the at least one slot.

[0026] According to one or more embodiments of this aspect, network node is further configured to characterize, with an error vector magnitude, EVM, level, at least one of a component carrier, CC, and sub-bands of a same carrier.

[0027] According to one or more embodiments of this aspect, network node is further configured to use the EVM level to perform the scheduling of the transmission.

[0028] According to one or more embodiments of this aspect, the EVM, level is configured for use in a radio resource configuration, RRC, for cell selection.

[0029] According to one or more embodiments of this aspect, network node is further configured to adjust a link adaptation based on the at least one metric on a per-user basis.

[0030] According to another aspect of the present disclosure, a method implemented by a network node is provided. The method includes determining a resource constraint pattern for distributed management of shared resource across multiple carriers. The method includes calculating at least one metric based on the resource constraint pattern. The method includes scheduling a transmission in at least one slot based on the at least one metric. According to one or more embodiments of this aspect, the resource constraint pattern incudes at least one resource-specific estimate of a parameter.

[0031] According to one or more embodiments of this aspect, the parameter includes at least one of error vector magnitude, EVM, phase noise, or distortion.

[0032] According to one or more embodiments of this aspect, the resource constraint pattern indicates that, in the at least one slot, power overbooking is one of: restricted; unrestricted; or permitted below a threshold and restricted above the threshold.

[0033] According to one or more embodiments of this aspect, the threshold is based on maintaining a maximum error vector magnitude, EVM, within a predetermined range.

[0034] According to one or more embodiments of this aspect, network node is further configured to apply a power backoff based on at least one of channel quality information, CQI, and error vector magnitude, EVM.

[0035] According to one or more embodiments of this aspect, the method further includes limiting total allocated resources in the at least one slot based on a power constraint.

[0036] According to one or more embodiments of this aspect, the method further includes scheduling the transmission based on a risk of error vector magnitude, EVM, in the at least one slot.

[0037] According to one or more embodiments of this aspect, the method further includes characterizing, with an error vector magnitude, EVM, level, at least one of a component carrier, CC, and sub-bands of a same carrier.

[0038] According to one or more embodiments of this aspect, the method further includes using the EVM level to perform the scheduling of the transmission.

[0039] According to one or more embodiments of this aspect, the EVM, level is configured for use in a radio resource configuration, RRC, for cell selection.

[0040] According to one or more embodiments of this aspect, the method further includes adjusting a link adaptation based on the at least one metric on a per-user basis.

[0041] BRIEF DESCRIPTION OF THE DRAWINGS

[0042] A more complete understanding of the present embodiments, and the attendant advantages and features thereof, will be more readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings wherein:

[0043] FIG. 1 is an network node deployment architecture; FIG. 2 is a schematic diagram of an example network architecture illustrating a communication system according to principles disclosed herein;

[0044] FIG. 3 is a block diagram of a network node in communication with a user equipment over a wireless connection according to some embodiments of the present disclosure;

[0045] FIG. 4 is a block diagram illustrating a virtualization environment according to some embodiments of the present disclosure;

[0046] FIG. 5 is a flowchart of an example process in a network node according to some embodiments of the present disclosure;

[0047] FIG. 6 is an example of a resource constraint pattern according to some embodiments of the present disclosure;

[0048] FIG. 7 is a flowchart of another example process in a network node;

[0049] FIG. 8 is a graph of variation of the EVM versus the total radio output power according to some embodiments of the present disclosure;

[0050] FIG. 9 is a flowchart of an example process to apply EVM-aware adaptations by a scheduler according to some embodiments of the present disclosure; and

[0051] FIG. 10 is a graph of an example smooth backoff function according to some embodiments of the present disclosure.

[0052] DETAILED DESCRIPTION

[0053] Before describing in detail exemplary embodiments, it is noted that the embodiments reside primarily in combinations of apparatus components and processing steps related to managing power and resource utilization. Accordingly, components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.

[0054] As used herein, relational terms, such as “first” and “second,” “top” and “bottom,” and the like, may be used solely to distinguish one entity or element from another entity or element without necessarily requiring or implying any physical or logical relationship or order between such entities or elements. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the concepts described herein. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and / or “including” when used herein, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0055] In embodiments described herein, the joining term, “in communication with” and the like, may be used to indicate electrical or data communication, which may be accomplished by physical contact, induction, electromagnetic radiation, radio signaling, infrared signaling or optical signaling, for example. One having ordinary skill in the art will appreciate that multiple components may interoperate and modifications and variations are possible of achieving the electrical and data communication.

[0056] In some embodiments described herein, the term “coupled,” “connected,” and the like, may be used herein to indicate a connection, although not necessarily directly, and may include wired and / or wireless connections.

[0057] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the concepts described herein. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and / or “including” when used herein, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0058] The term “network node” used herein can be any kind of network node comprised in a radio network which may further comprise any of base station (BS), radio base station, base transceiver station (BTS), base station controller (BSC), radio network controller (RNC), g Node B (gNB), evolved Node B (eNB or eNodeB), Node B, multistandard radio (MSR) radio node such as MSR BS, multi-cell / multicast coordination entity (MCE), relay node, donor node controlling relay, radio access point (AP), transmission points, transmission nodes, Remote Radio Unit (RRU) Remote Radio Head (RRH), a core network node (e.g., mobile management entity (MME), self-organizing network (SON) node, a coordinating node, positioning node, MDT node, etc.), an external node (e.g., 3rd party node, a node external to the current network), nodes in distributed antenna system (DAS), a spectrum access system (SAS) node, an element management system (EMS), etc. The network node may also comprise test equipment. The term “radio node” used herein may be used to also denote a user equipment (UE) such as a wireless device (WD) or a radio network node.

[0059] In some embodiments, the non-limiting terms wireless device (WD) or a user equipment (UE) are used interchangeably. The UE herein can be any type of wireless device capable of communicating with a network node or another UE over radio signals, such as a wireless device (WD). The UE may also be a radio communication device, target device, device to device (D2D) UE, machine type UE or UE capable of machine to machine communication (M2M), low-cost and / or low-complexity UE, a sensor equipped with UE, Tablet, mobile terminals, smart phone, laptop embedded equipped (LEE), laptop mounted equipment (LME), USB dongles, Customer Premises Equipment (CPE), an Internet of Things (loT) device, or a Narrowband loT (NB-IOT) device etc.

[0060] Also, in some embodiments the generic term “radio network node” is used. It can be any kind of a radio network node which may comprise any of base station, radio base station, base transceiver station, base station controller, network controller, RNC, evolved Node B (eNB), Node B, gNB, Multi-ccll / multicast Coordination Entity (MCE), relay node, access point, radio access point, Remote Radio Unit (RRU) Remote Radio Head (RRH).

[0061] Note that although terminology from one particular wireless system, such as, for example, 3GPP LTE and / or New Radio (NR), may be used in this disclosure, this should not be seen as limiting the scope of the disclosure to only the aforementioned system. Other wireless systems, including without limitation Wide Band Code Division Multiple Access (WCDMA), Worldwide Interoperability for Microwave Access (WiMax), Ultra Mobile Broadband (UMB) and Global System for Mobile Communications (GSM), may also benefit from exploiting the ideas covered within this disclosure.

[0062] Note further, that functions described herein as being performed by a user equipment or a network node may be distributed over a plurality of user equipments and / or network nodes. In other words, it is contemplated that the functions of the network node and user equipment described herein are not limited to performance by a single physical device and, in fact, can be distributed among several physical devices.

[0063] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms used herein should be interpreted as having a meaning that is consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0064] Some embodiments are directed to managing power and resource utilization.

[0065] Referring to the drawing figures, in which like elements are referred to by like reference numerals, there is shown in FIG. 2 a schematic diagram of a communication system 10, according to an embodiment, such as a 3GPP-type cellular network that may support standards such as LTE and / or NR (5G), which comprises an access network 12, such as a radio access network, and a core network 14. The access network 12 comprises a plurality of network nodes 16a, 16b, 16c (referred to collectively as network nodes 16), such as NBs, eNBs, gNBs or other types of wireless access points, each defining a corresponding coverage area 18a, 18b, 18c (referred to collectively as coverage areas 18). Each network node 16a, 16b, 16c is connectable to the core network 14 over a wired or wireless connection 20. A first user equipment (UE) 22a located in coverage area 18a is configured to wirelessly connect to, or be paged by, the corresponding network node 16a. A second UE 22b in coverage area 18b is wirelessly connectable to the corresponding network node 16b. While a plurality of UEs 22a, 22b (collectively referred to as user equipments 22) are illustrated in this example, the disclosed embodiments are equally applicable to a situation where a sole UE is in the coverage area or where a sole UE is connecting to the corresponding network node 16. Note that although only two UEs 22 and three network nodes 16 are shown for convenience, the communication system may include many more UEs 22 and network nodes 16.

[0066] Also, it is contemplated that a UE 22 can be in simultaneous communication and / or configured to separately communicate with more than one network node 16 and more than one type of network node 16. For example, a UE 22 can have dual connectivity with a network node 16 that supports LTE and the same or a different network node 16 that supports NR. As an example, UE 22 can be in communication with an eNB for LTE / E-UTRAN and a gNB for NR / NG-RAN.

[0067] A network node 16 (eNB or gNB) is configured to include a power management unit 24 which is configured to perform one or more network node 16 functions described herein, including functions related to managing power and resource utilization.

[0068] Example implementations, in accordance with an embodiment, of the UE 22 and network node 16 discussed in the preceding paragraphs will now be described with reference to FIG. 2. The communication system 10 includes a network node 16 provided in a communication system 10 and including hardware 28 enabling it to communicate with the UE 22. The hardware 28 may include a radio interface 30 for setting up and maintaining at least a wireless connection 32 with a UE 22 located in a coverage area 18 served by the network node 16. The radio interface 30 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and / or one or more RF transceivers. The radio interface 30 includes an array of antennas 34 to radiate and receive signal(s) carrying electromagnetic waves.

[0069] In the embodiment shown, the hardware 28 of the network node 16 further includes processing circuitry 36. The processing circuitry 36 may include a processor 38 and a memory 40. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 36 may comprise integrated circuitry for processing and / or control, e.g., one or more processors and / or processor cores and / or FPGAs (Field Programmable Gate Array) and / or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 38 may be configured to access (e.g., write to and / or read from) the memory 40, which may comprise any kind of volatile and / or nonvolatile memory, e.g., cache and / or buffer memory and / or RAM (Random Access Memory) and / or ROM (Read-Only Memory) and / or optical memory and / or EPROM (Erasable Programmable Read-Only Memory).

[0070] Thus, the network node 16 further has software 42 stored internally in, for example, memory 40, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the network node 16 via an external connection. The software 42 may be executable by the processing circuitry 36. The processing circuitry 36 may be configured to control any of the methods and / or processes described herein and / or to cause such methods, and / or processes to be performed, e.g., by network node 16. Processor 38 corresponds to one or more processors 38 for performing network node 16 functions described herein. The memory 40 is configured to store data, programmatic software code and / or other information described herein. In some embodiments, the software 42 may include instructions that, when executed by the processor 38 and / or processing circuitry 36, causes the processor 38 and / or processing circuitry 36 to perform the processes described herein with respect to network node 16. For example, processing circuitry 36 of the network node 16 may include power management unit 24, which is configured to perform one or more network node 16 functions described herein, including functions related to managing power and resource utilization. The communication system 10 further includes the UE 22 already referred to. The UE 22 may have hardware 44 that may include a radio interface 46 configured to set up and maintain a wireless connection 32 with a network node 16 serving a coverage area 18 in which the UE 22 is currently located. The radio interface 46 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and / or one or more RF transceivers. The radio interface 46 includes an array of antennas 48 to radiate and receive signal(s) carrying electromagnetic waves.

[0071] The hardware 44 of the UE 22 further includes processing circuitry 50. The processing circuitry 50 may include a processor 52 and memory 54. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 50 may comprise integrated circuitry for processing and / or control, e.g., one or more processors and / or processor cores and / or FPGAs (Field Programmable Gate Array) and / or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 52 may be configured to access (e.g., write to and / or read from) memory 54, which may comprise any kind of volatile and / or nonvolatile memory, e.g., cache and / or buffer memory and / or RAM (Random Access Memory) and / or ROM (Read-Only Memory) and / or optical memory and / or EPROM (Erasable Programmable Read-Only Memory).

[0072] Thus, the UE 22 may further comprise software 56, which is stored in, for example, memory 54 at the UE 22, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the UE 22. The software 56 may be executable by the processing circuitry 50. The software 56 may include a client application 58. The client application 58 may be operable to provide a service to a human or non-human user via the UE 22.

[0073] The processing circuitry 50 may be configured to control any of the methods and / or processes described herein and / or to cause such methods, and / or processes to be performed, e.g., by UE 22. The processor 52 corresponds to one or more processors 52 for performing UE 22 functions described herein. The UE 22 includes memory 54 that is configured to store data, programmatic software code and / or other information described herein. In some embodiments, the software 56 and / or the client application 58 may include instructions that, when executed by the processor 52 and / or processing circuitry 50, causes the processor 52 and / or processing circuitry 50 to perform the processes described herein with respect to UE 22. In some embodiments, the inner workings of the network node 16 and UE 22 may be as shown in FIG. 3 and independently, the surrounding network topology may be that of FIG. 2.

[0074] The wireless connection 32 between the UE 22 and the network node 16 is in accordance with the teachings of the embodiments described throughout this disclosure. More precisely, the teachings of some of these embodiments may improve the data rate, latency, and / or power consumption and thereby provide benefits such as reduced user waiting time, relaxed restriction on file size, better responsiveness, extended battery lifetime, etc. In some embodiments, a measurement procedure may be provided for the purpose of monitoring data rate, latency and other factors on which the one or more embodiments improve.

[0075] Although FIGS. 2 and 3 show various “units” such as power management unit 24, as being within a respective processor, it is contemplated that these units may be implemented such that a portion of the unit is stored in a corresponding memory within the processing circuitry. In other words, the units may be implemented in hardware or in a combination of hardware and software within the processing circuitry.

[0076] For example, in some embodiments, the telecommunication system 10 includes one or more Open-RAN (ORAN) network nodes 16. An ORAN network node 16 is a node in the telecommunication system 10 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 system 10, including one or more network nodes 16 in the access network 12 and / or core network nodes 14.

[0077] Examples of an ORAN network node 16 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 O- RAN Alliance or comparable technologies. The network nodes 16 facilitate direct or indirect connection of user equipment (UE), such as by connecting UEs 22a, 22b, 22c, and QQ112d (one or more of which may be generally referred to as UEs 22) to the core network 14 over one or more wireless connections.

[0078] FIG. 4 is a block diagram illustrating a virtualization environment 94 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 94 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 94 includes components defined by the 0-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an 0-2 interface.

[0079] Applications 96 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment 94 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.

[0080] Hardware 98 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 100 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs 102a and 102b (one or more of which may be generally referred to as VMs 102), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer 100 may present a virtual operating platform that appears like networking hardware to the VMs QQ508.

[0081] The VMs 102 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer 100. Different embodiments of the instance of a virtual appliance 96 may be implemented on one or more of VMs 102, 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.

[0082] In the context of NFV, a VM 102 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 102, and that part of hardware 98 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 102 on top of the hardware 98 and corresponds to the application 96.

[0083] Hardware 98 may be implemented in a standalone network node with generic or specific components. Hardware 98 may implement some functions via virtualization. Alternatively, hardware 98 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 104, which, among others, oversees lifecycle management of applications 96. In some embodiments, hardware 98 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 106 which may alternatively be used for communication between hardware nodes and radio units.

[0084] FIG. 5 is a flowchart of an example process in a network node 16. One or more blocks described herein may be performed by one or more elements of network node 16 such as by one or more of processing circuitry 36 (including the power management unit 24), processor 38, and / or radio interface 30. Network node 16 is configured to determine a resource constraint pattern for distributed management of shared resource across multiple carriers (Block S200). Network node 16 is configured to calculate at least one metric based on the resource constraint pattern (Block S202). Network node 16 is configured to schedule a transmission in at least one slot based on the at least one metric (Block S204).

[0085] In some embodiments, the resource constraint pattern comprises at least one resource-specific estimate of a parameter.

[0086] In some embodiments, the parameter comprises at least one of error vector magnitude, EVM, phase noise, or distortion.

[0087] In some embodiments, the resource constraint pattern indicates that, in the at least one slot, power overbooking is one of: restricted; unrestricted; or permitted below a threshold and restricted above the threshold.

[0088] In some embodiments, the threshold is based on maintaining a maximum error vector magnitude, EVM, within a predetermined range.

[0089] In some embodiments, network node 16 is further configured to apply a power backoff based on at least one of channel quality information, CQI, and error vector magnitude, EVM.

[0090] In some embodiments, network node 16 is further configured to limit total allocated resources in the at least one slot based on a power constraint.

[0091] In some embodiments, network node 16 is further configured to schedule the transmission based on a risk of error vector magnitude, EVM, in the at least one slot.

[0092] In some embodiments, network node 16 is further configured to characterize, with an error vector magnitude, EVM, level, at least one of a component carrier, CC, and subbands of a same carrier.

[0093] In some embodiments, network node 16 is further configured to use the EVM level to perform the scheduling of the transmission.

[0094] In some embodiments, the EVM, level is configured for use in a radio resource configuration, RRC, for cell selection.

[0095] In some embodiments, network node 16 is further configured to adjust a link adaptation based on the at least one metric on a per-user basis.

[0096] Having described the general process flow of arrangements of the disclosure and having provided examples of hardware and software arrangements for implementing the processes and functions of the disclosure, the sections below provide details and examples of arrangements for managing power and resource utilization. One or more network node functions described below may be performed by one or more of processing circuitry 50, processor 52, power management unit 24, etc.

[0097] Some embodiments relate to implementing power and resource utilization constraints based on a pre-configured pattern for different Sector carriers. The preconfigured pattern may provide the scheduler of each CC with a resource-specific estimate of a parameter (such as EVM, phase noise, distortion, etc.) across spatial / temporal / frequency domain resources.

[0098] • A temporal power constraint pattern can be pre-configured for each CC (see FIG. 6), where: o In certain time slots more restrictive conditions are applied so that the transmitted signals over such slots would be protected against a power overshooting. Such protected slots would be useful for robust transmission of reference signals (such as synchronization signal block (SSB), channel state information reference signals (CSI-RS), tracking reference signal (TRS), etc.), so that the coverage is not compromised in the presence of power overbooking. o There can be certain slots in a pattern where all CC can book the maximum configured power, but the transmitted signals over those slots would be exposed to a higher level of EVM. Such time slots would be favorable for transmission of signals with a lower MCS index towards the users at the cell-edge where a higher PSD is desirable while a higher EVM is experienced. o Another type of slots in the pattern are partially protected, where overbooking is allowed to a certain extent, thus the maximum EVM is maintained in a specific range.

[0099] • The pre-configured pattern provides the scheduler with an estimate of the worst-case potential EVM. The scheduler of each CC then may individually implement different adaptations based on the knowledge of the potential EVM. o The scheduler can adjust the link adaptation on a per-user basis. For example, it can apply a power backoff depending on the reported CQI and the potential EVM for given resources. By backing off the power, and possibly using a lower MCS, the scheduler may reduce the risk of EVM especially for the users with a good CQI. o The scheduler can limit the total allocated resources to meet the power constraint in each slot. o The scheduler can also choose selected users to be scheduled on each resource depending on the risk of EVM. For example, users at the cell-edge may prefer to get scheduled with a higher PSD at an unprotected time slot where there is a more risk of EVM, while the users near the cell center may benefit to be scheduled in a protected / partially protected time slot.

[0100] • Each CC, or even different sub-bands of the same carrier, can be characterized with a different level of EVM. Accordingly, each CC can be tailored to serve certain group of users (e.g., cell-edge vs. cell-center). This information then can be used by the scheduler (for user selection and resource assignment), or by the RRC algorithm for cell selection.

[0101] In some embodiments, the scheduler of each sector carrier is provided with a preconfigured pattern regarding power or resource utilization constraints, so that each scheduler would be able to make decentralized decisions, while optimizing the resource allocation decisions based the knowledge of resource specific parameters such as EVM.

[0102] The pattern described herein can be defined by the baseband (in case of local carriers where the CCs are managed by the same baseband unit), or by the RPC which is jointly handling multiple BBUs. The pattern then can be semi-statically updated based on long-term traffic conditions or other system parameters.

[0103] In some embodiments, each sector carrier of a multi-band radio is configured with a temporal power constraint pattern. The pattern is defined at the time of the sector carrier configuration, and then can get semi-statically updated / re-configured, e.g., via network node 16. Based on the knowledge of the power constraint in each slot, the scheduler attains an estimate of the worst-case potential EVM. The scheduler, e.g., via network node 16, of each CC then may individually implement different adaptations based on the knowledge of the potential EVM. The flowchart in FIG. 7 shows an overview of example steps to implement solutions described herein. An example process performed, e.g., via the network node 16, includes getting the temporal pattern for the CC, generated based on the radio power capability, and system configurations (RS signals, periodicity, etc.) (Block SI 10). The worst-case potential EVM is calculated for the current time slot based on the power constraint pattern and the radio specifications (Block SI 12). Certain scheduling adaptations are implemented based on the worst-case potential EVM for the current time slot (Block SI 14). Each of these steps is further discussed in the following.

[0104] • Generating a power constraint pattern

[0105] As described above, a power constraint pattern may comprise different types of slots each targeting a different level of power overbooking. Particularly, in the protected slots a restrictive condition may be applied so that the total power may never exceed the radio power capability, thus the transmitted signals over such slots would be protected against a power overshooting and excessive EVM. Such protected slots are devised to ensure robust transmission of reference signals (such as SSB, CSI-RS, TRS, etc.).

[0106] Let {T1;T2, ... , TRdenote the periodicity of different reference signals that are to be protected. The minimum periodicity of a pattern is given by To= LCM^, T2, ... , TR). that is the least common multiple of the periodicity of the protected reference signals. Then a time slot t G {0,1, ... , To} in each period of the pattern is set as “protected” if a reference signal is transmitted over that TTI. FIG. 6 shows one period of a pattern where To= 40 TTIs.

[0107] Let Pndenote the nominal power of the radio, and Pc(in dB) denote a fair share of power assigned to Carrier c. Let A denote the maximum potential overbooking (in dB) in an unprotected slot, so that the total allocated power of each carrier may reach Pc+ A (dB) in an unprotected slot. There may be yet another type of slots in the pattern which are so- called partially protected, where overbooking is allowed up to 8 < A. That is, in a partially protected slot, each carrier may exceed its fair share of power by 8 dB.

[0108] As an example, consider a deterministic periodic pattern, wherein in each period a certain portion a < 1 of the remaining slots, after labeling the protected slots, are set as partially protected, and 1 — a portion of slots are marked as unprotected. Given these ratios, it is possible to label the slots in one period as unprotected and partially protected according to a weighted rround-robinmechanism. Another method is to use a Pseudo random sequence to label the slots based on the given ratios. FIG. 6 shows a deterministic periodic pattern where a = 1 (i.e., comprising just protected and partially protected slots), while the partial overbooking parameter is chosen to be 8 = 0.6A as an example.

[0109] Given a method to generate a pattern, a pattern may be characterized by certain parameters including the periodicity and time-offset of the protected reference signals, the ratio of the partially protected slots, a, the partial and maximum power overbooking amounts, 8, and A. Then at each time slot, it can be determined the power constraint for each carrier based on the described power constraint pattern.

[0110] A pre-configured pattern can be also semi-statically updated, e.g., via network node 16. For example, it can be programmed to be changing based on the long-term estimates of the traffic load at different times of the day (busy hour versus low traffic hours, etc.). Specifically, certain parameters of the pattern can be adaptively adjusted based on the ongoing long-term estimates of the traffic condition. For example, a larger (smaller, respectively) partial overbooking 8 might be desired for low-traffic (busy) hours. • Finding a resource-specific estimate of the potential EVM

[0111] The radio, e.g., via network node 16, implements certain CFR mechanisms to maintain the EVM below a nominal threshold while the total power remains within the radio power capability. Allocating power beyond the radio nominal power, however, may result in an excessive EVM that is scaled with deviation from the rated nominal power. FIG. 8 shows a commonly adopted model wherein the EVM is exponentially scaled when deviating from the radio nominal power. In this example, the nominal EVM when allocating the full nominal power of the radio is 3%, while the EVM is measured at 7% when overbooking power by 0.75 dB. For this radio with given specifications, the exponential model of FIG. 8, which depicts Variation of the EVM versus the total radio output power, provides an approximation of the potential EVM for every output power.

[0112] By implementing a power constraint pattern, as exemplified in FIG. 6, the scheduler of each sector carrier can figure out the maximum potential power overbooking in each slot, which readily translates to a worst-case potential EVM using the EVM curve of FIG. 8 (known based on the radio specifications). By using a power constraint pattern the worst-case potential EVM can be different depending on the time slot index.

[0113] Based on the radio design / specification and the CFR algorithm implementation, the radio can operate in a way that different CC (or even sub-carriers of the same CC) experience a different level of EVM. This feature could be used, e.g., to manage inter- band / carrier interference. Alternatively, this may capture heterogeneity of the radio across different CCs. Such characteristics of the radio along with the knowledge of the power constraint pattern may provide the scheduler with a resource-specific estimate of the potential EVM, which then can be used to implement various adaptations.

[0114] • EVM-aware scheduling adaptations

[0115] The scheduler, e.g., via network node 16, of each CC may individually implement different adaptations based on the worst-case potential EVM in each time slot. In the first step, the scheduler may fetch certain subset(s) of users that are preferred to be scheduled on each resource depending on the risk of EVM (see FIG. 9, which depicts a process to apply EVM-aware adaptations by a scheduler). Particularly, the users might be pre-filtered and organized into certain sub-lists, where users are identified, e.g., as cell-edge, cellcenter, etc., depending on their reported CQI. The scheduler then can fetch the filtered list(s) of users and prioritize them for getting scheduled in the current slot. For example, users at the cell-edge may be prioritized to get scheduled with a higher PSD at an unprotected time slot where there is a greater risk of EVM, while the users near the cell center may benefit to be scheduled in a (partially) protected time slot.

[0116] With reference to FIG. 9, the example process (performed, e.g., via the network node 16) includes fetching a filtered list of users that are preferred to be scheduled in the current slot (Block SI 16). If the power constraint is not met (Block SI 18), the allocation for the current slot is finalized (Block S120). If the power constraint is met, the next scheduling entity from the list is fetched (Block S122). If the request is served (Block S124), Step S122 is repeated. If the request is not served, the next RBG is allocated (Block S126), a user-specific back-off is applied, and LA is updated (Block S128). If there is more RBG to allocate (Block SI 30), the process proceeds to step S124, else it proceeds to step S120.

[0117] In some embodiments, the scheduler, e.g., via network node 16, may keep allocating resources to schedulable entities from other priority lists, or from a generic list, if the higher priority users do not claim all the resources in a given time slot. Filtering the users and prioritizing them, however, is an optional sub-routine, and might be skipped by the scheduler depending on the implementation.

[0118] The scheduler, e.g., via network node 16, keeps allocating the resources to the users till the total allocated power meets the power constraint of the current time slot. In this way, the scheduler may limit the allocated resources to meet the power constraint in each slot.

[0119] After allocating each RBG, the scheduler, e.g., via network node 16, adjusts the link adaptation based on the knowledge of EVM on a per-user basis. Particularly, the impact on link performance due to EVM (which is treated as a noise floor) depends on the selected MCS. Intuitively, for a low MCS with QPSK modulation a higher EVM could be acceptable, whereas a high MCS may result in excessive BLER in the presence of higher EVM. To achieve a target BLER, the MCS should be selected by taking the expected achievable SINR into account. In legacy LA schemes and in the absence of EVM, this is achieved by making a rough estimate of the link SINR based on the reported CQI of the user, i.e., cqiBasedSinr. The estimated SINR is further corrected by applying an outer-loop adjustment offset:

[0120] SINROLLA= cqiBasedSinr — ollaOffset

[0121] The effective SINR of the link, however, is upper bounded in the presence of EVM by where SINRHis called EVM-limited SINR. In the presence of EVM, there is introduced a back-off to correct the estimate of SINR. Such backoff would then help reduce the total allocated power of the radio, which in turn degrades the EVM as well. So, by applying a backoff for the users with a good CQI (i.e., with SINR0LLAgreater than a lower threshold SINR0LLA> SINRL). it is possible to improve the EVM-limited SINR, and thus the achievable SINR for all users. We select SINRLto be the threshold up to which the LA would choose a QPSK modulation (e.g., SINRL= 2.011 dB).

[0122] To calculate a backoff, we employ a smooth backoff function, parametrized by SINRLand a target SINR, SI NRLargeL(EV M) that is a function of EVM. The backoff function maps the estimated SINR0LLAfor each user to a backoff in dB, where the backoff for users with SINR0LLA< SINRLis set to zero, while a nominal backoff, Backoffnominai, is applied for a user with SINR0LLA= SINRtarget. An example of a backoff function with SINRtarget= SINRH+ Backof fnominai is:

[0123] An example of a smooth backoff function is depicted in FIG. 10 for Backof fnominai= 2 dB , and SINRtarget= 13 dB. The estimated SINR is then adjusted according to the power backoff:

[0124] SINR = SINROLLA— Backoff

[0125] By backing off the power, the LA would use a lower MCS that matches the estimated SINR, thus alleviating the risk of EVM.

[0126] The scheduler, e.g., via network node 16, may finalize the allocation after all RBGs are allocated, or after the total allocated power reaches the maximum threshold for the current time slot. At this stage, there might be a chance to further optimize the power or resource allocation. For example, the scheduler may revert some power backoffs if all the RBGs are allocated and there still exists some power headroom. Alternatively, the scheduler may keep the allocation as is and just sends the scheduling decision to the lower layer for transmission.

[0127] Other Example Embodiments

[0128] As discussed above, each CC, or even different sub-bands of the same carrier can be characterized with a different level of EVM following a certain pattern. Particularly, some advanced radios can be programmed to implement a colored (i.e., multi-level) EVM 1 across different carriers / sub-bands, e.g., via network node 16. This can be learned through signaling of radio specifications to the DU. Alternatively, the DU can program the radio to apply a colored EVM pattern across different sub-bands / carriers. Accordingly, each CC would be tailored to serve certain group of users (e.g., cell-edge vs. cell-center). This information can be used by the scheduler for user selection and resource assignment. Alternatively, the RRC algorithm may consider this information for cell selection and / or for carrier activation.

[0129] Particularly, the users can be pre-filtered and organized into different categories, such as cell-edge, cell-center, etc., based on their RSRP, or CQI measurements. Then users with a good channel condition would get a higher priority to get assigned to the CCs with lower EVM. On the other hand, the cell edge users would get higher priority to get assigned to the CCs with a higher EVM. This may help to enhance the bandwidth efficiency and cell throughput in the network.

[0130] In an O-RAN architecture, different functional blocks of network node, such as RPC, BBU, RU, etc., could be supplied by different vendors. In such an implementation, different components should communicate over an open interface. Some embodiments may introduce certain signaling between different functional blocks which would be communicated over an open interface in an ORAN architecture. Particularly, in the first step, the RPC would receive certain radio characteristics and capabilities (such as EVM characteristics, nominal power, etc.) which are used to characterize a temporal / frequency specific constraint pattern. The defined pattern, possibly along with some other radio characteristics, then are indicated by RPC to BBUs to enable various adaptations. In another embodiment described herein, the RPC or BBU may communicate the defined pattern to the radio as well which could enable certain adaptations for advanced RUs (such as implementing a customized subband specific EVM pattern).

[0131] As will be appreciated by one of skill in the art, the concepts described herein may be embodied as a method, data processing system, computer program product and / or computer storage media storing an executable computer program. Accordingly, the concepts described herein may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects all generally referred to herein as a “circuit” or “module.” Any process, step, action and / or functionality described herein may be performed by, and / or associated to, a corresponding module, which may be implemented in software and / or firmware and / or hardware. Furthermore, the disclosure may take the form of a computer program product on a tangible computer usable storage medium having computer program code embodied in the medium that can be executed by a computer. Any suitable tangible computer readable medium may be utilized including hard disks, CD-ROMs, electronic storage devices, optical storage devices, or magnetic storage devices.

[0132] Some embodiments are described herein with reference to flowchart illustrations and / or block diagrams of methods, systems and computer program products. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer (to thereby create a special purpose computer), special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0133] These computer program instructions may also be stored in a computer readable memory or storage medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instruction means which implement the function / act specified in the flowchart and / or block diagram block or blocks.

[0134] The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0135] It is to be understood that the functions / acts noted in the blocks may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality / acts involved. Although some of the diagrams include arrows on communication paths to show a primary direction of communication, it is to be understood that communication may occur in the opposite direction to the depicted arrows. Computer program code for carrying out operations of the concepts described herein may be written in an object oriented programming language such as Python, Java® or C++. However, the computer program code for carrying out operations of the disclosure may also be written in conventional procedural programming languages, such as the "C" programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer. In the latter scenario, the remote computer may be connected to the user's computer through a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0136] Many different embodiments have been disclosed herein, in connection with the above description and the drawings. It will be understood that it would be unduly repetitious and obfuscating to literally describe and illustrate every combination and subcombination of these embodiments. Accordingly, all embodiments can be combined in any way and / or combination, and the present specification, including the drawings, shall be construed to constitute a complete written description of all combinations and subcombinations of the embodiments described herein, and of the manner and process of making and using them, and shall support claims to any such combination or subcombination.

[0137] Abbreviations that may be used in the preceding description include:

[0138] Abbreviation Explanation

[0139] CA Carrier Aggregation

[0140] CFR Crest Factor Reduction

[0141] CQI Channel Quality Index

[0142] CSLRS Channel State Information Reference Signal

[0143] EVM Error Vector Mean

[0144] KPI Key Performance Indicator

[0145] LA Link Adaptation

[0146] MCS Modulation Coding Scheme

[0147] MIMO Multiple Input Multiple Output

[0148] OLLA Outer Loop Link Adaptation

[0149] PSD Power Spectral Density

[0150] RAN Radio Access Network RBG Resource Block Group

[0151] RPC Radio Plane Control

[0152] SC Sector Carrier

[0153] SINR Signal Interference-Noise Ratio

[0154] SSB Synchronization Signal Block

[0155] TRS Tracking Reference Signal

[0156] TTI Time Transmission Interval

[0157] It will be appreciated by persons skilled in the art that the embodiments described herein are not limited to what has been particularly shown and described herein above. In addition, unless mention was made above to the contrary, it should be noted that all of the accompanying drawings are not to scale. A variety of modifications and variations are possible in light of the above teachings.

Claims

What is claimed is:

1. A method implemented in a network node (16), the method comprising: determining (S200) a resource constraint pattern for distributed management of shared resource across multiple carriers; calculating (S202) at least one metric based on the resource constraint pattern; and scheduling (S204) a transmission in at least one slot based on the at least one metric.

2. The method of Claim 1, wherein the resource constraint pattern comprises at least one resource-specific estimate of a parameter.

3. The method of Claim 2, wherein the parameter comprises at least one of error vector magnitude, EVM, phase noise, or distortion.

4. The method of any one of Claims 1-3, wherein the resource constraint pattern indicates that, in the at least one slot, power overbooking is one of: restricted; unrestricted; or permitted below a threshold and restricted above the threshold.

5. The method of Claim 4, wherein the threshold is based on maintaining a maximum error vector magnitude, EVM, within a predetermined range.

6. The method of any one of Claims 1-5, further comprising applying a power backoff based on at least one of channel quality information, CQI, and error vector magnitude, EVM.

7. The method of any one of Claims 1-6, further comprising limiting total allocated resources in the at least one slot based on a power constraint.

8. The method of any one of Claims 1-6, further comprising scheduling the transmission based on a risk of error vector magnitude, EVM, in the at least one slot.

9. The method of any one of Claims 1-8, further comprising characterizing, with an error vector magnitude, EVM, level, at least one of a component carrier, CC, and sub-bands of a same carrier.

10. The method of Claim 9, further comprising using the EVM level to perform the scheduling of the transmission.

11. The method of Claim 9, wherein the EVM, level is configured for use in a radio resource configuration, RRC, for cell selection.

12. The method of any one of Claims 1-11, further comprising adjusting a link adaptation based on the at least one metric on a per-user basis.

13. A network node (16) comprising processing circuitry (36) configured to: determine a resource constraint pattern for distributed management of shared resource across multiple carriers; calculate at least one metric based on the resource constraint pattern; and schedule a transmission in at least one slot based on the at least one metric.

14. The network node (16) of Claim 13, wherein the resource constraint pattern comprises at least one resource-specific estimate of a parameter.

15. The network node (16) of Claim 14, wherein the parameter comprises at least one of error vector magnitude, EVM, phase noise, or distortion.

16. The network node (16) of any one of Claims 13-15, wherein the resource constraint pattern indicates that, in the at least one slot, power overbooking is one of: restricted; unrestricted; or permitted below a threshold and restricted above the threshold.

17. The network node (16) of Claim 16, wherein the threshold is based on maintaining a maximum error vector magnitude, EVM, within a predetermined range.

18. The network node (16) of any one of Claims 13-17, wherein the processing circuitry (36) is further configured to apply a power backoff based on at least one of channel quality information, CQI, and error vector magnitude, EVM.

19. The network node (16) of any one of Claims 13-18, wherein the processing circuitry (36) is further configured to limit total allocated resources in the at least one slot based on a power constraint.

20. The network node (16) of any one of Claims 13-18, wherein the processing circuitry (36) is further configured to schedule the transmission based on a risk of error vector magnitude, EVM, in the at least one slot.

21. The network node (16) of any one of Claims 13-20, wherein the processing circuitry (36) is further configured to characterize, with an error vector magnitude, EVM, level, at least one of a component carrier, CC, and sub-bands of a same carrier.

22. The network node (16) of Claim 21, wherein the processing circuitry (36) is further configured to use the EVM level to perform the scheduling of the transmission.

23. The network node (16) of Claim 21, wherein the EVM, level is configured for use in a radio resource configuration, RRC, for cell selection.

24. The network node (16) of any one of Claims 13-23, wherein the processing circuitry (36) is further configured to adjust a link adaptation based on the at least one metric on a per-user basis.

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