WO2025215397A1

WO2025215397A1 - Energy efficient operation of digital predistortion (dpd) sleep using a sliding window

Info

Publication number: WO2025215397A1
Application number: PCT/IB2024/053474
Authority: WO
Inventors: Shiguang Guo; Kris BAILEY
Original assignee: Telefonaktiebolaget LM Ericsson AB
Current assignee: Telefonaktiebolaget LM Ericsson AB
Priority date: 2024-04-09
Filing date: 2024-04-09
Publication date: 2025-10-16
Anticipated expiration: 2026-10-09

Abstract

A method, network node and user equipment (UE) for energy efficient operation of digital predistortion (DPD) sleep using a sliding window are disclosed. According to one aspect, a method in a network node or UE includes performing a sequence of power measurements of power at an input of a power amplifier (PA). The method includes determining a predicted power variation based at least in part on the power measurements. The method also includes determining whether to change an operational state of a digital predistorter (DPD), based at least in part on the predicted power.

Description

ENERGY EFFICIENT OPERATION OF DIGITAL PREDISTORTION (DPD) SLEEP USING A SLIDING WINDOW

TECHNICAL FIELD

The present disclosure relates to wireless communications, and in particular, to energy efficient operation of digital predistortion (DPD) sleep using a sliding window.

BACKGROUND

The Third Generation Partnership Project (3 GPP) 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 3GPP is also developing standards for Sixth Generation (6G) wireless communication networks.

Active Antenna System (AAS) is one of the key technologies adopted by Fourth Generation (4G) Long Term Evolution (LTE) and Fifth Generation (5G) New Radio (NR) to enhance the wireless network performance and capacity by using full dimension Multiple Input Multiple Output (MIMO), which is denoted as FD-MIMO, or massive MIMO. A typical AAS system consists of a two-dimensional antenna element array with M rows, N columns, and K polarizations (K=2 in case of cross-polarization), as shown in FIG. 1.

In AAS radio, certain baseband functionalities, such as beamforming in downlink and pre-equalizer in uplink are implemented inside the radio. This is to support high number of antenna branches with reasonable front haul cost (transport network between baseband and radio). As a result, a vast amount of baseband is available to radio.

AAS radio, also called Massive MIMO radio, will employ many independent RF path, each of which will have its own PA (power amplifier). Each PA will need linearization algorithm, such as DPD (digital pre-distortion) implemented on application specific integrated circuitry (ASIC). So, the more antenna branches the radio has, the more DPD will be used in massive MIMO radio.

Massive MIMO radio

Massive MIMO radio, also called Active Antenna System (AAS) radio, is one of various technologies adopted by Fourth Generation (4G) Long Term Evolution (LTE) and Fifth Generation (5G) New Radio (NR) to enhance the wireless network performance and capacity by using full dimension Multiple Input Multiple Output (MIMO), which is denoted as FD-MIMO, or massive MIMO. A typical AAS system consists of a two- dimensional antenna element array with M rows, N columns, and K polarizations (K=2 in case of cross-polarization), as shown in FIG. 1.

In AAS radio, certain baseband functionalities, such as beamforming in the downlink (DL) and pre- equalization in the uplink (UL) are implemented inside the radio. This is to support a high number of antenna branches with reasonable front haul cost (transport network between baseband and radio). As a result, a vast amount of baseband is available to radio.

AAS radio will employ many independent radio frequency (RF) paths, each of which will have its own PA (power amplifier). Each PA will employ a linearization algorithm, such as DPD (digital pre-distortion) implemented on an ASIC. So, the more antenna branches the radio has, the more DPD will be used in massive MIMO radio.

A power amplifier per RF branch in radio is typically non-linear. Digital predistortion (DPD) is used to mitigate this non-linearity in PA. It applies pre-distortion at the input of PA so that the output of the PA is linearized. As shown in FIG. 2, DPD operation is applied before the PA to pre-distort x[n], which is the output of the baseband. The signals x[n], y[n], z[n] are the input of the DPD, the input of the PA and the output of the PA, respectively. Assume that the transfer function of the PA is g(.) and the transfer function of the DPD is f(.), the design of the DPD should be, f(.) = Constant * inverse(g(.)) such that z[n] ⁼ g(y[n]) ⁼ Constant * g(f(x[n])) = Constant*x[n] i.e., the output of PA is linear to x[n] after the PA.

As shown in FIG. 3, the DPD takes the input x[n] from baseband (BB), and applies a pre-compensation coefficient calculated based on the DPD error (i.e., internal error vector magnitude (EVM)), which is calculated by: e[n]=x[n]-z[n]

As shown in FIG. 3, the DPD error e[n] will be converted to a non-linear finite impulse response (FIR) filter in the functional block labeled “Algor”. The filter will perform pre-distortion on the input x[n].

The DPD is typically implemented as a non-linear adaptive filter with tap coefficients taken from a lookup table (LUT) that is addressed based on sample amplitude. A feedback based closed loop control is employed to update the DPD LUT coefficient values to track the changes in PA non-linearity over time, as the signal characteristics and PA temperature change. A simple proportional integrator (PI) based controller is shown in FIG. 3. Different control parameters may lead to different controller outcomes. FIG. 4 shows that the controlled output will be stable after it converges.

High energy consumption in AAS radio

Due to the high number of RF branches and the high number of DPD hardware (HW) resources needed to support linearization of a wide instantaneous bandwidth (IBW), dual-band PA, the total energy consumption devoted just to the DPD’s continuous adaptation calculations needed to perform real-time update of DPD LUT contents is significant. If the capacity is high, this increased calculation cost is justifiable. However, in low-capacity scenario, such as non-busy hour, the higher cost would not be justified.

An energy saving scheme is an important area in both network and mobile sides. This is important for cost efficiency from an operator’s viewpoint and from an environmental point of view.

Traditional energy efficiency schemes used in radio focus on different levels of HW sleep to save energy. This includes sleep in time (symbol based power saving, where the PA bias is briefly turned off when signal amplitude is zero) and spatial domains (massive MIMO sleep). In massive MIMO sleep, certain RF branches may be turned off in order to turn off the radio ASIC along with the RF path that includes the PA. Determination of when to sleep will rely on traffic level prediction in layer 2 and/or layer 3.

However, the traditional energy efficiency schemes will impact end-to-end radio performance or limit overall traffic throughput capability. The traffic prediction is typically performed at Layer 2 and layer 3. Both layer 2 and layer 3 are implemented in a DU (digital unit) or cloud radio access network (RAN). Significant network latency and delay will make prediction obsolete and bring performance risk to the network.

In addition to delay impact, turning off and on the complete HW component such as half of the RF chain in massive MIMO sleep takes time. This would not be feasible if the traffic level variation is high.

As a result, end-to-end performance will likely be impacted in order to save energy. This is sometimes not acceptable to support delay sensitive traffic or mission critical traffic, which typically requires a high performance network to achieve an intended quality of service (QoS). Traditionally, digital predistortion (DPD) processes DL data samples in the time domain and runs its control loop adaptation algorithm continually to ensure good correction performance, such as lower EVM and improved adjacent channel leakage ratio (ACLR). More DPD in massive MIMO radio will result in a significant amount of energy consumption due to the intensive signal processing calculations needed for DPD operations. This will increase the operation cost of a service provider.

Traditional DPD explores simpler algorithms to reduce energy consumption. This, however, fails to achieve good performance in selected scenarios.

SUMMARY

Some embodiments advantageously provide methods, network nodes and user equipments (UEs) for energy efficient operation of digital predistortion (DPD) sleep using a sliding window.

Running DPD at all times may not be necessary if the traffic variation is small (such as a low capacity scenario at night), traffic level is low (such as at non-busy daylight hours) and PA temperature is low due to lower ambient temperature. In these conditions, a PA exhibits a relatively linear behavior and the DPD update may not be needed. Small degradation of DPD performance may be tolerated and a work round may be used to reduce the degradation. So, it is possible to turn off DPD updates or reduce DPD update frequency in order to save energy.

According to one aspect, a method in a network node configured for wireless communication is provided. The method includes performing a sequence of power measurements of power at an input of a power amplifier, PA. The method also includes determining a predicted power variation based at least in part on the power measurements. The method also includes determining whether to change an operational state of a digital predistorter, DPD, based at least in part on the predicted power variation.

According to this aspect, in some embodiments, determining whether to change the operational state of the DPD is based at least in part on a temperature variation. In some embodiments, determining whether to change the operational state of the DPD is based at least in time on a traffic load. In some embodiments, the sequence of power measurements are performed during a sliding window of time. In some embodiments, the change in operational state of the DPD includes a change in a rate of updating the DPD. In some embodiments, the change in operational state of the DPD includes disablement of the DPD. In some embodiments, the change in operational state of the DPD is based at least in part on a change in power backoff of the power amplifier. In some embodiments, determining whether to change in operational state of the DPD is based at least in part on a change in power input at the DPD. In some embodiments, determining whether to change in operational state of the DPD includes re-enablement of the DPD after an expiry of a timer. In some embodiments, determining whether to change in operational state of the DPD includes re-enablement of the DPD based at least in part on a reduction in an amount of change of power at the input of the DPD. In some embodiments, the network node is one of a radio base station and a user equipment, UE.

According to another aspect, a network node is configured to perform a sequence of power measurements of power at an input of a power amplifier, PA, determine a predicted power variation based at least in part on the power measurements, and determine whether to change an operational state of a digital predistorter, DPD, based at least in part on the predicted power variation.

BRIEF DESCRIPTION OF THE DRAWINGS

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:

FIG. 1 is a diagram of a two-dimensional antenna element array;

FIG. 2 illustrates PA linearization using DPD;

FIG. 3 is a block diagram of DPD;

FIG. 4 is a graph of response for closed loop control;

FIG. 5 shows power prediction using a sliding window;

FIG. 6 shows a sliding window to update a sample list;

FIG. 7 is an example AAS architecture;

FIG. 8 is a massive MIMO radio software architecture;

FIG. 9 is a schematic diagram of an example network architecture illustrating a communication system according to principles disclosed herein;

FIG. 10 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;

FIG. 11 is a block diagram of a virtualization environment according to some embodiments of the present disclosure;

FIG. 12 is a flowchart of an example process in a network node for energy efficient operation of digital predistortion (DPD) sleep using a sliding window according to some embodiments of the present disclosure;

FIG. 13 is a diagram showing a scheduling decision made by DU/vDU multiple slots ahead of radio processing according to some embodiments of the present disclosure;

FIG. 14 is a diagram showing power obtained by averaging over multiple samples according to some embodiments of the present disclosure;

FIG. 15 is a diagram showing a power variation prediction according to some embodiments of the present disclosure;

FIG. 16 is a diagram showing a fall back in the event of a fast power change according to some embodiments of the present disclosure; and

FIG. 17 is a diagram showing potential power variation symbol by symbol according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

Before describing in detail exemplary embodiments, it is noted that the embodiments reside primarily in combinations of apparatus components and processing steps related to energy efficient operation of digital predistortion (DPD) sleep using a sliding window. 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.

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.

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.

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.

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.

The term “network node” used herein may 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.

In some embodiments, the non-limiting terms wireless device (WD) or a user equipment (UE) are used interchangeably. The UE herein may 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.

Also, in some embodiments the generic term “radio network node” is used. It may 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-cell/multicast Coordination Entity (MCE), relay node, access point, radio access point, Remote Radio Unit (RRU) Remote Radio Head (RRH).

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.

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, may be distributed among several physical devices.

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.

Some embodiments are directed to energy efficient operation of digital predistortion (DPD) sleep using a sliding window.

Returning to the drawing figures, in which like elements are referred to by like reference numerals, there is shown in FIG. 5, a diagram of a power measurement at a current time t4 together with most recent power measurements at times tl, t2 and t3 before power amplification is used to predict the potential power at later time tn. Some embodiments include predicting power at tn using the most recent power measurements:

P_tn=(P_tl+P_t2+P_t3+P_t4)/4, where P_tl, P_t2, P_t3, P_t4 are the power at tl, t2, t3, t4, respectively. These may be the most recent time samples. Here, 4 most recent samples are used as one example. It may be another number. If P_tn is close to P_t4, i.e.: abs(P_tn-P_t4) < delta, it means that power variation from t4 to tn should be small enough so that the DPD update won’t be necessary. DPD update may be reduced or turned off.

At the next time sample, t4, P_tn will be updated with a real measurement at tn and the prediction will continue with updated measurement points. As shown in FIG. 6, a sliding window is used to use the latest set of samples.

The power and power variation prediction may decide when to reduce or turn off DPD update. This is referred to herein as a reduced DPD operation state. A fall-back mechanism using temperature measurement and/or power back off may be used to turn on DPD from the reduced DPD operation state. This may ensure that DPD performance is achieved throughout a time interval.

Once the DPD update is reduced or suspended, there may be a small increase in EVM.

If the traffic level is low, then the needed radio resources (time and frequency) will be less, i.e., more bandwidth is available. The small degradation of EVM due to less frequent DPD updates may be compensated by available radio resources (used bandwidth) using more conservative link adaptation, such as a lower modulation and coding scheme (MCS).

In some embodiments, DPD operation is reduced to save energy in certain situations. Some embodiments do not impact user planes, i.e., time, frequency, and spatial domains. In some embodiments, the radio resource utilization is not impacted, and end-to- end performance is maximized. This may ensure no end-to-end performance is impacted.

Advanced Antenna System (AAS) integrates antenna, radio, and part of the baseband processing like beamforming into one box. AAS is also called AIR, i.e., antenna integrated radio. As shown in FIG. 7, AAS, or AIR, is also called ORAN compliant radio unit (O-RU). ORAN will be explained in the subsequent section. Some embodiments may be implemented in a massive MIMO radio software architecture, such as shown in FIG. 8.

FIG. 9 is a schematic diagram of a communication system 10, according to an embodiment, such as a 3 GPP-type cellular network that may support standards such as ETE 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.

Also, it is contemplated that a UE 22 may 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 may 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 may be in communication with an eNB for LTE/E-UTRAN and a gNB for NR/NG-RAN.

A network node 16 (eNB or gNB) is configured to include an NN DPD controller 24 which is configured to determining whether to change an operational state of a digital predistorter, DPD, based at least in part on the predicted power. A user equipment 22 is configured to include a UE DPD controller 26 which is configured to determining whether to change an operational state of a digital predistorter, DPD, based at least in part on the predicted power.

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. 10.

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 to radiate and receive signal(s) carrying electromagnetic waves. The radio interface 30 also includes a NN DPD 34 operable under the control of the NN DPD controller 24. The radio interface 30 also includes an NN PA 35 configured to amplify signals received from the NN DPD 34.

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).

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 an NN DPD controller 24 which is configured to determining whether to change an operational state of a digital predistorter, DPD, based at least in part on the predicted power.

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 to radiate and receive signal(s) carrying electromagnetic waves. The radio interface also includes a UE DPD 48 operable under the control of the UE DPD controller 26. The radio interface 46 also includes a UE PA 49 configured to amplify signals received from the UE DPD 48.

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).

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.

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. For example, the processing circuitry 50 of the user equipment 22 may include UE DPD controller 26 which is configured to determine whether to change an operational state of a digital predistorter, DPD, based at least in part on the predicted power.

In some embodiments, the inner workings of the network node 16 and UE 22 may be as shown in FIG. 10 and independently, the surrounding network topology may be that of FIG. 9.

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. Although FIGS. 9 and 10 show various “units” such as NN DPD controller 24 and UE DPD controller 26 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.

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.

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, (one or more of which may be generally referred to as UEs 22) to the core network 14 over one or more wireless connections.

FIG. 11 is a block diagram illustrating a virtualization environment 60 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 may 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 60 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 69 includes components defined by the O-RAN Alliance, such as an O-Cloud environment orchestrated by a Service Management and Orchestration Framework via an 0-2 interface.

Applications 62 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment 60 to implement some of the features, functions, and/or benefits of some of the embodiments disclosed herein.

Hardware 64 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 66 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs 68a and 68b (one or more of which may be generally referred to as VMs 68), and/or perform any of the functions, features and/or benefits described in relation with some embodiments described herein. The virtualization layer 66 may present a virtual operating platform that appears like networking hardware to the VMs 68

The VMs 68 comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer 66. Different embodiments of the instance of a virtual appliance 62 may be implemented on one or more of VMs 68, 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 may be located in data centers, and customer premise equipment.

In the context of NFV, a VM 68 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 68, and that part of hardware 64 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 68 on top of the hardware 64 and corresponds to the application 62.

Hardware 64 may be implemented in a standalone network node with generic or specific components. Hardware 64 may implement some functions via virtualization. Alternatively, hardware 64 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 70, which, among others, oversees lifecycle management of applications 62. In some embodiments, hardware 64 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 may be provided with the use of a control system 72 which may alternatively be used for communication between hardware nodes and radio units.

FIG. 12 is a flowchart of an example process in a network node 16 or a UE 22 for energy efficient operation of digital predistortion (DPD) sleep using a sliding window. 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 NN DPD controller 24), processor 38, and/or radio interface 30. Similarly, one or more blocks described herein may be performed by one or more elements of UE 22 such as by one or more of processing circuitry 50 (including the UE DPD controller 26), processor 52, and/or radio interface 46. The network node 16 and/or the UE 22 may be configured to perform a sequence of power measurements of power at an input of a power amplifier, PA 35, 49 (Block S10). The process includes determining a predicted power variation based at least in part on the power measurements (Block S12). The process also includes determining whether to change an operational state of a digital predistorter, DPD 34, 48, based at least in part on the predicted power variation (Block S 14).

In some embodiments, determining whether to change the operational state of the DPD 34, 48 is based at least in part on a temperature variation. In some embodiments, determining whether to change the operational state of the DPD 34, 48 is based at least in time on a traffic load. In some embodiments, the sequence of power measurements are performed during a sliding window of time. In some embodiments, the change in operational state of the DPD 34, 48 includes a change in a rate of updating the DPD 34, 48. In some embodiments, the change in operational state of the DPD 34, 48 includes disablement of the DPD 34, 48. In some embodiments, the change in operational state of the DPD 34, 48 is based at least in part on a change in power backoff of the power amplifier 35, 49. In some embodiments, determining whether to change in operational state of the DPD 34, 48 is based at least in part on a change in power input at the DPD 34, 48. In some embodiments, determining whether to change in operational state of the DPD 34, 48 includes re-enablement of the DPD 34, 48 after an expiry of a timer. In some embodiments, determining whether to change in operational state of the DPD 34, 48 includes re-enablement of the DPD 34, 48 based at least in part on a reduction in an amount of change of power at the input of the DPD 34, 48. In some embodiments, the radio is in one of a radio base station (e.g. network node 16) and a user equipment, UE 22.

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 energy efficient operation of digital predistortion (DPD) sleep using a sliding window.

Massive MIMO radio architecture

Advanced Antenna System (AAS) integrates antenna, radio, and part of the baseband processing like beamforming into one box. AAS is also called AIR, i.e., antenna integrated radio. As shown in FIG. 8, AAS, or AIR, is also called an ORAN compliant radio unit (O-RU).

Baseband function beamforming may be performed in AAS on different channels/signals, such as physical downlink shared channel (PDSCH), channel state information reference signal (CSI-RS), demodulation reference signal (DM-RS), etc.

A typical massive MIMO radio architecture may be employed to implement some embodiments described herein. Such a massive MIMO radio architecture may have the following features:

• Baseband operation in massive MIMO radio to perform beamforming, IFFT/FFT, pre-equalizer, etc.;

• One radio connects to one or multiple DU for multiple carriers; • All carriers will be combined to each RF branch at a multicarrier block MCB of a digital front end (DFE);

• Multiple RF branches will be available (such as 64 or 32). Each RF branch will have its own PA 35, 49;

• All BB data will be mapped to all RF branches for beamforming purposes;

• BB LI is split between DU and Radio;

FIG. 13 is a diagram of a scheduling decision made by DU/vDU multiple slots ahead of radio processing according to some embodiments of the present disclosure.

• EMCA (e.g. many core architecture) on massive MIMO radio (available for all future radios in low, mid, and high band) process BB LI lower algorithms such as beamforming, AC, pre-equalizer etc.;

• It has the knowledges of scheduling details for all carriers, all UEs, and all RF branches:

• DU only sees selected carriers for scheduling details;

• DFE only seems time domain for composite signal from multiple carriers;

• It is assumed that additional buffering (extra Memory) is introduced so that addition data are saved for training and prediction in machine learning (ML):

• Today, EMCA does not buffer anything; and/or

• It is assumed that C2 and Cl supporting all needed signaling between UPC, LI lower, and Radio/DFE.

Digital power measurement before PA in radio

Averaged power may be estimated within the radio DFE by averaging over multiple samples, as shown in FIG. 14. It may be a fraction of orthogonal frequency division multiplexed (OFDM) symbols. It may be paired with corresponding frequency domain data in baseband per OFDM symbol.

In static traffic conditions, the waveform of the PA 35, 49 input is expected to fluctuating very little. Once DPD correction converges to its final state, the DPD error is expected to be small. In dynamic traffic conditions, the waveform at the PA input may have rapid rise or fall in power level. In this case, DPD error and RF output operating band unwanted emissions (OBUE) & EVM may degrade briefly while the DPD 34, 48 responds to converge the DPD correction to a new level. The DPD 34, 48 must maintain correction performance sufficiently to meet all RF performance requirements at all times under worst-case expected transient conditions.

PA temperature measurement

Excessive PA temperature changes, even under low or static traffic conditions, may result in a high DPD error. This may require an immediate DPD adaptation update to maintain sufficient DPD correction performance.

Power variation prediction using sliding window

Power variation may be predicted by taking the two close power measurement samples as shown in FIG. 15. Historical power may be obtained by averaging a few samples in the parting using a sliding window. power_variation = ( latest_power - sum_of_historic_power ) / number_power_samples

Protection model

Turn on immediately

Power backoff is needed when DPD 34, 48 enters reduced operation mode. This is to reduce the potential impact on ACLR. See FIG. 16.

When DPD reduced mode is entered, an indication may be sent to baseband so that baseband will take corresponding action such as using a conservative link adaption scheme to compensate for the potential EVM degradation.

In order to secure DPD performance, a few protection mechanisms may be put in place.

Predefined power variation occasions

As shown in FIG. 17, a large power variation typically occurs between control (PDCCH) and traffic (PDSCH) symbols. It may also happen when a number of users changes. Due to a resource allocation strategy, traffic power variation within the slot may typically be very small.

Reduced DPD operation timeout

DPD 34, 48 may be turned back on after a certain period regardless of power variation estimation. This is to eliminate the accumulated residual error in power prediction.

PA Temperature

Real time PA temperature and other power estimation (in baseband) or power measurement (in the radio) may trigger DPD 34, 48 back to normal immediately as a fallback mechanism to ensure a good DPD performance. Power backoff

Power backoff may be used when DPD reduced operation state is triggered.

Restart immediately

If fast power is detected anytime during DPD reduced state, then immediate restart may be performed.

State machine

DPD 34, 48 will operate in a normal and reduced state. In a reduced state, the actuator will be turned off or reduced. Fall-back events may be used to turn on DPD 34, 48 immediately. The following information relates to simulation of the embodiments disclosed herein.

Test 1: power saving with DPD OFF

Carrier config: 2xLTE20MHz 155MHz IBW 40dBm on all 32 br.

Two branches (brO and br8) are selected for measurement. Worst OBUE and EVM is selected from the worst case of two carrier for the two branches.

Brief summary:

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 may 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.

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, may 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.

These computer program instructions may also be stored in a computer readable memory or storage medium that may 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.

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. 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).

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 may 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.

Abbreviations that may be used in the preceding description include: Abbreviation Explanation

AAS advance antenna system

ACLR adjacent carrier leakage ratio

ASIC application specific IC

BB baseband

DFE digital front end

DPD Digital pre-distortion

DU digital unit

EE energy efficiency

EVM error vector magnitude

OFDM orthogonal frequency division multiplexing

ORAN open RAN

PA power amplifier

QoS quality of service

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 without departing from the scope of the following claims.

Claims

What is claimed is:

1. A method in a network node (16) configured for wireless communication, the method comprising: performing (S10) a sequence of power measurements of power at an input of a power amplifier, PA (35, 49); determining (S 12) a predicted power variation based at least in part on the power measurements; and determining (S14) whether to change an operational state of a digital predistorter, DPD, (34, 48), based at least in part on the predicted power variation.

2. The method of Claim 1, wherein determining whether to change the operational state of the DPD (34, 48) is based at least in part on a temperature variation.

3. The method of any of Claims 1 and 2, wherein determining whether to change the operational state of the DPD (34, 48) is based at least in time on a traffic load.

4. The method of any of Claims 1-3, wherein the sequence of power measurements are performed during a sliding window of time.

5. The method of any of Claims 1-4, wherein the change in operational state of the DPD (34, 48) includes a change in a rate of updating the DPD (34, 48).

6. The method of any of Claims 1-5, wherein the change in operational state of the DPD (34, 48) includes disablement of the DPD (34, 48).

7. The method of any of Claims 1-6, wherein the change in operational state of the DPD (34, 48) is based at least in part on a change in power backoff of the power amplifier (35, 49).

8. The method of any of Claims 1-7, wherein determining whether to change in operational state of the DPD (34, 48) is based at least in part on a change in power input at the DPD (34, 48).

9. The method of any of Claims 1-8, wherein determining whether to change in operational state of the DPD (34, 48) includes re-enablement of the DPD (34, 48) after an expiry of a timer.

10. The method of any of Claims 1-9, wherein determining whether to change in operational state of the DPD (34, 48) includes re-enablement of the DPD (34, 48) based at least in part on a reduction in an amount of change of power at the input of the DPD (34, 48).

11. The method of any of Claims 1-10, wherein the network node (16) is one of a radio base station and a user equipment, UE (22).

12. A network node (16), the network node (16) configured to: perform a sequence of power measurements of power at an input of a power amplifier, PA (35, 49); determine a predicted power variation based at least in part on the power measurements; and determine whether to change an operational state of a digital predistorter, DPD (34, 48), based at least in part on the predicted power variation.

13. The network node (16) of Claim 12, wherein determining whether to change the operational state of the DPD (34, 48) is based at least in part on a temperature variation.

14. The network node (16) of any of Claims 12 and 13, wherein determining whether to change the operational state of the DPD (34, 48) is based at least in time on a traffic load.

15. The network node (16) of any of Claims 12-14, wherein the sequence of power measurements are performed during a sliding window of time.

16. The network node (16) of any of Claims 12-15, wherein the change in operational state of the DPD (34, 48) includes a change in a rate of updating the DPD (34, 48).

17. The network node (16) of any of Claims 12-16, wherein the change in operational state of the DPD (34, 48) includes disablement of the DPD (34, 48).

18. The network node (16) of any of Claims 12-17, wherein the change in operational state of the DPD (34, 48) is based at least in part on a change in power backoff of the power amplifier (35, 49).

19. The network node (16) of any of Claims 12-18, wherein determining whether to change in operational state of the DPD (34, 48) is based at least in part on a change in power input at the DPD (34, 48).

20. The network node (16) of any of Claims 12-19, wherein determining whether to change in operational state of the DPD (34, 48) includes re-enablement of the DPD (34, 48) after an expiry of a timer.

21. The network node (16) of any of Claims 12-20, wherein determining whether to change in operational state of the DPD (34, 48) includes re-enablement of the DPD (34, 48) based at least in part on a reduction in an amount of change of power at the input of the DPD (34, 48).

22. The network node (16) of any of Claims 12-21, wherein the network node (16) is one of a radio base station and a user equipment, UE (22).