Self-interference estimation with synchronized repetitive injections

Abstract

A method and network node for self-interference estimation with synchronized repetitive injections are disclosed. According to one aspect, a method in a network node includes repetitively injecting into at least one transmitter of the radio a plurality of injection signals and downlink traffic on at least one downlink carrier frequency, the plurality of injection signals being synchronized so that injections signals have a same relative start time for each repetition of the plurality of injection signals. The method includes sequentially capturing in the receiver, multiple instances of an uplink signal in an uplink frequency range, the uplink signal including the plurality of injection signals and uplink traffic. The method also includes estimating self-interference in the sequentially captured multiple instances of the uplink signal.

Description

[0001] SELF-INTERFERENCE ESTIMATION WITH SYNCHRONIZED REPETITIVE INJECTIONS

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to wireless communications, and in particular, to self-interference estimation with synchronized repetitive injections.

[0004] BACKGROUND

[0005] 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 3GPP is also developing standards for Sixth Generation (6G) wireless communication networks.

[0006] A communications system with a transmitter and a receiver has the potential to suffer from self-interference due to some non-linear behavior of active or passive components. Self-interference is caused by aggressors (on the transmitter side) that impact a victim receiver. There are many configurations that may be considered within this communications system. The ‘transmitter side’ may correspond to some subset of the total available downlink spectrum, and also to some subset of the total available antenna branches on one or more radios. In this context, a communications system may be multiple co-located radios.

[0007] Some examples of self-interference include:

[0008] Intermodulation caused in the transmitter (such as in a power amplifier) leaking into a receiver, or having insufficient isolation from some nearby receiver;

[0009] Passive intermodulation (PIM) caused beyond the transmitter, then picked up by a receiver in the same radio, or another nearby radio.

[0010] Some aggressor configurations are shown in FIG. 1 where the star represents a PIM source. In this example, there are two aggressors, which may correspond to downlink carriers at two separate frequencies. Each example in FIG. 1 shows a certain downlink configuration with a PIM source (depicted by arrows from different antenna branches). The aggressor configuration may span multiple antennas, and multiple radios. FIG. 1 does not show the concept of using a subset of the available downlink spectrum. FIG. 1 shows two arrows pointing towards the PIM source, which represent 2 downlink (DL) carriers. However, it is possible for selfinterference to be caused by only 1 DL carrier, or more than 2 DL carriers.

[0011] The examples in FIG. 1 depict scenarios when the source of self-interference is a PIM source (i.e., the star). There are other examples such as transmitter leakage.

[0012] FIG. 2 shows a single victim receiver for each of the diagrams from FIG. 1. The arrow points from the PIM source (where PIM interference is generated) to the victim receiver. Only a single victim is shown but there could be more than one victim receiver with multiple antennas - any of the receivers connected to these antennas may be considered.

[0013] A victim receiver may also be considered after some antenna combining (such as interference rejection combining or maximal ratio combining). In FIG. 3, the victim receiver may be considered as a receiver of the signal coming exiting the combiner in FIG. 3.

[0014] Some detection, classification and modelling methods for self-interference require an estimate of the self-interference signal. The self-interference signal is in a victim receiver which may also contain other signals such as noise, other interference, and the desired traffic that the receiver is serving. These other signals make the estimate of the self-interference noisy. Some methods require some modelling of the PIM source, such as a nonlinear polynomial model.

[0015] Most methods require using the noisy estimate of the self-interference with a nonlinear model of the PIM source in order to determine parameters of the nonlinear model. Noisy estimates of self-interference result in poorer estimates of the nonlinear model parameters.

[0016] SUMMARY

[0017] Some embodiments advantageously provide methods and network nodes for self-interference estimation with synchronized repetitive injections.

[0018] Some embodiments relate to aggressor signals mixing in some non-linear manner (due to PIM or an active component) and causing self-interference in a victim receiver. Some embodiments include methods to more accurately estimate the selfinterference signal caused by the aggressor signals in the presence of other noise and interference.

[0019] Some embodiments involve multiple data injections in a specific aggressor configuration. All injections for a particular aggressor signal may be nearly the same to cause the self-interference to be nearly equal for each of the multiple injections. The aggressor configurations may relate to 1) what subset of frequencies are used by the data injections from the available downlink spectrum and 2) the antenna branches used by the aggressors. As an example, consider 3 different frequency division duplex (FDD) carriers being used on a site. The configuration for a specific aggressor signal may be the lower 50% of the spectrum of carrier #1, sent on antenna branches A&B, and 100% of aggressors 2 and 3 only on antenna branch C. Many permutations of aggressor configurations may be considered.

[0020] During each injection, the self-interference signal may be captured in a victim receiver. The multiple captures of the self-interference may be processed in a manner to isolate the self-interference signal from the other signals in the uplink. These other signals are typically different for each of the captures. The estimate of this selfinterference signal will be less noisy than a single capture.

[0021] Processing the multiple captures may be as simple as linearly combining the multiple captures. There may be some anomaly detection methods used to remove captures that were significantly different from the majority of captures. Some embodiments include anomaly detection methods related to time series that are available to identify captures that are anomalies, which may either be dropped, or given a lower weighting. Some embodiments include unsupervised methods to process these multiple captures to come up with a single estimate (i.e., k-means).

[0022] In each repetition, the self-interference may be expected to be nearly the same, whereas the other signals (that were not caused by the aggressor signals with repeated injections) will be different in each capture - and average out in the combining.

[0023] Some embodiments include methods for achieving a less noisy estimate of PIM (or active IM) which may be used for detection of the self-interference in the presence of other interference, noise and uplink transmissions. The PIM detection may be specific to a specific aggressor configuration.

[0024] Some embodiments include repeatedly injecting the same signal(s) for a specific aggressor configuration. For each injection, the self-interference in a victim receiver may be captured and processed to provide an estimate of the interference signal caused by the specific aggressor configuration. The self-interference may be caused by non-linear behavior, causing the selfinterference to be generated at frequencies that potentially fall within the configured uplink spectrum. In some embodiments, the estimate of the interference signal is made in the presence of an radio frequency (RF) environment that is beyond the control of the victim receiver (i.e., noise, and time-variant data uplink traffic and other interference).

[0025] Some embodiments provide a higher quality estimate of the self-interference signal for non-linear self-interference channels. Typically, noise, other interference and uplink traffic would result in a noisier estimate of this self-interference signal. A higher quality signal estimate will benefit the application that is using the estimate of the self-interference signal.

[0026] The higher quality estimate achievable by methods disclosed herein does not require knowledge of the injection signals in the aggressors.

[0027] Some embodiments may be used for determining the impact of a particular aggressor configuration without requiring all other downlink transmissions to be stopped.

[0028] According to one aspect, a method in a network node including at least one radio that includes at least one transmitter and at least one receiver is provided. The method includes repetitively injecting into at least one transmitter of the radio a plurality of injection signals and downlink traffic on at least one downlink carrier frequency, the plurality of injection signals being synchronized so that injections signals have a same relative start time for each repetition of the plurality of injection signals. The method includes sequentially capturing in the receiver, multiple instances of an uplink signal in an uplink frequency range, the uplink signal including the plurality of injection signals and uplink traffic. The method also includes estimating self-interference in the sequentially captured multiple instances of the uplink signal.

[0029] According to this aspect, in some embodiments, repetitively injecting includes transmitting the plurality of injection signals on a subset of antennas of the radio. In some embodiments, repetitively injecting the plurality of injection signals includes injecting a first set of injection signals on a first set of antennas of the radio and injecting a second set of injection signals on a second set of antennas of the radio. In some embodiments, estimating the self-interference includes determining a weighted combination of the captured multiple instances of the uplink signal. In some embodiments, estimating the self-interference includes removing anomalous captures of the captured multiple instances of the uplink signal when performing the estimation. In some embodiments, each injection signal of the plurality of injections signals include different data. In some embodiments, the at least one downlink carrier frequency is selected to generate self-interference in a selected uplink frequency range. In some embodiments, a first set of injection signals are injected at a first set of downlink carrier frequencies and a second set of injection signals are injected at a second set of downlink carrier frequencies. In some embodiments, estimating the selfinterference includes differentiating between injection signals and traffic signals. In some embodiments, sequentially capturing multiple instances of an uplink signal includes synchronizing the captures relative to a start time for each repetition of the plurality of injection signals. In some embodiments, the plurality of injections signals include repeating signals also used for other purposes in the network node, including at least one of a cell specific reference signal, CRS, a tracking reference signal and a sounding reference signal. In some embodiments, estimating the self-interference includes selecting and combining captures of the multiple instances of the uplink signal based at least in part on a cross-correlation of captured multiple instances of the uplink signal. In some embodiments, estimating the self-interference includes combining only phases of the captured multiple instances of the uplink signal.

[0030] According to another aspect, a network node including at least one radio that includes at least one transmitter and at least one receiver is provided. The network node is configured to repetitively inject into at least one transmitter of the radio a plurality of injection signals and downlink traffic on at least one downlink carrier frequency, the plurality of injection signals being synchronized so that injections signals have a same relative start time for each repetition of the plurality of injection signals. The network node is also configured to sequentially capture in the receiver, multiple instances of an uplink signal in an uplink frequency range, the uplink signal including the plurality of injection signals and uplink traffic. The network node is also configured to estimate self-interference in the sequentially captured multiple instances of the uplink signal.

[0031] According to this aspect, in some embodiment, repetitively injecting includes transmitting the plurality of injection signals on a subset of antennas of the radio. In some embodiments, repetitively injecting the plurality of injection signals includes injecting a first set of injection signals on a first set of antennas of the radio and injecting a second set of injection signals on a second set of antennas of the radio. In some embodiments, estimating the self-interference includes determining a weighted combination of the captured multiple instances of the uplink signal. In some embodiments, estimating the self-interference includes disregarding anomalous captures of the captured multiple instances of the uplink signal when performing the estimation. In some embodiments, each injection signal of the plurality of injections signals include different data. In some embodiments, the at least one downlink carrier frequency is selected to generate self-interference in a selected uplink frequency range. In some embodiments, a first set of injection signals are injected at a first set of downlink carrier frequencies and a second set of injection signals are injected at a second set of downlink carrier frequencies. In some embodiments, estimating the selfinterference includes differentiating between injection signals and traffic signals. In some embodiments, sequentially capturing multiple instances of an uplink signal includes synchronizing the captures relative to a start time for each repetition of the plurality of injection signals. In some embodiments, the plurality of injections signals include repeating signals also used for other purposes in the network node, including at least one of a cell specific reference signal, CRS, a tracking reference signal and a sounding reference signal. In some embodiments, estimating the self-interference includes selecting and combining captures of the multiple instances of the uplink signal based at least in part on a cross-correlation of captured multiple instances of the uplink signal. In some embodiments, estimating the self-interference includes combining only phases of the captured multiple instances of the uplink signal.

[0032] BRIEF DESCRIPTION OF THE DRAWINGS

[0033] 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:

[0034] FIG. 1 is an example of a PIM source of self-interference;

[0035] FIG. 2 is another example of a PIM source self-interference;

[0036] FIG. 3 is an example of a victim receiver after antenna combining;

[0037] FIG. 4 is a schematic diagram of an example network architecture illustrating a communication system according to principles disclosed herein;

[0038] FIG. 5 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;

[0039] FIG. 6 is a block diagram illustrating a virtualization environment 94 in which functions implemented by some embodiments may be virtualized;

[0040] FIG. 7 is a flowchart of an example process in a network node for selfinterference estimation with synchronized repetitive injections according to principles disclosed herein;

[0041] FIG. 8 is a case with only one radio and two antennas;

[0042] FIG. 9 is an example spectrum diagram with two downlink carriers and a wideband PIM signal;

[0043] FIG. 10 is an example spectrum diagram where a subset of the downlink carriers is repeated multiple times;

[0044] FIG. 11 shows example spectrum diagrams where subsets of downlink carriers are repeated on different antennas;

[0045] FIG. 12 is an example of self-interference involving two radios;

[0046] FIG. 13 shows example spectrum diagrams where each radio has one carrier;

[0047] FIG. 14 is a flowchart of another example process in a network node for selfinterference estimation with synchronized repetitive injections according to principles disclosed herein.

[0048] DETAILED DESCRIPTION

[0049] Before describing in detail example embodiments, it is noted that the embodiments reside primarily in combinations of apparatus components and processing steps related to self-interference estimation with synchronized repetitive injections. 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.

[0050] 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.

[0051] 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.

[0052] 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.

[0053] 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.

[0054] 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, multi- standard 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), selforganizing 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.

[0055] 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.

[0056] 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).

[0057] 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.

[0058] 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.

[0059] Some embodiments are directed to self-interference estimation with synchronized repetitive injections.

[0060] Returning to the drawing figures, in which like elements are referred to by like reference numerals, there is shown in FIG. 4 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.

[0061] 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.

[0062] A network node 16 (eNB or gNB) is configured to include an self-interference (SI) test unit 24 which is configured to inject injection signals into a transmitter and sequentially capture multiple instances of the uplink signal. Some or all of the functionality of SI test unit 24 may be implemented in a radio of the network node.

[0063] 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. 5.

[0064] 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 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 30 may be formed as or may include, for example, one or more RF transmitters 36, one or more RF receivers 38, and / or one or more RF transceivers. The radio 30 includes an array of antennas 34 to radiate and receive signal(s) carrying electromagnetic waves. As used herein, the term “radio” may include one or more radios 30 and / or one or more transmitters 36 and / or one or more receivers 38 and antennas 34 or subgroup of antennas 34. A network node 16 may include multiple radios. Self-interference may affect one or more of these radios.

[0065] In the embodiment shown, the hardware 28 of the network node 16 further includes processing circuitry 40. The processing circuitry 40 may include a processor 42 and a memory 44. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 40 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 42 may be configured to access (e.g., write to and / or read from) the memory 44, 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).

[0066] Thus, the network node 16 further has software 46 stored internally in, for example, memory 44, 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 46 may be executable by the processing circuitry 40. The processing circuitry 40 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 42 corresponds to one or more processors 42 for performing network node 16 functions described herein. The memory 44 is configured to store data, programmatic software code and / or other information described herein. In some embodiments, the software 46 may include instructions that, when executed by the processor 42 and / or processing circuitry 40, causes the processor 42 and / or processing circuitry 40 to perform the processes described herein with respect to network node 16. For example, processing circuitry 40 of the network node 16 may include an SI test unit 24 which is configured to inject injection signals into a transmitter and sequentially capture multiple instances of the uplink signal. Some or all of the functionality of SI test unit 24 may be implemented in the radio 30 of the network node 16.

[0067] The communication system 10 further includes the UE 22 already referred to. The UE 22 may have hardware 48 that may include a radio 50 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 50 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 50 includes an array of antennas 52 to radiate and receive signal(s) carrying electromagnetic waves.

[0068] The hardware 48 of the UE 22 further includes processing circuitry 54. The processing circuitry 54 may include a processor 56 and memory 58. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 54 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 56 may be configured to access (e.g., write to and / or read from) memory 58, 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).

[0069] Thus, the UE 22 may further comprise software 60, which is stored in, for example, memory 58 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 60 may be executable by the processing circuitry 54. The software 60 may include a client application 62. The client application 62 may be operable to provide a service to a human or non-human user via the UE 22.

[0070] The processing circuitry 54 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 56 corresponds to one or more processors 56 for performing UE 22 functions described herein. The UE 22 includes memory 58 that is configured to store data, programmatic software code and / or other information described herein. In some embodiments, the software 60 and / or the client application 62 may include instructions that, when executed by the processor 56 and / or processing circuitry 54, causes the processor 56 and / or processing circuitry 54 to perform the processes described herein with respect to UE 22.

[0071] In some embodiments, the inner workings of the network node 16 and UE 22 may be as shown in FIG. 5 and independently, the surrounding network topology may be that of FIG. 4.

[0072] 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.

[0073] Although FIGS. 4 and 5 show various “units” such as the SI test 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.

[0074] In some embodiments, the communication system 10 includes one or more Open-RAN (ORAN) network nodes 16. An ORAN network node 16 is a node in the communication 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 communication 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 0-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.

[0075] FIG. 6 is a block diagram illustrating a virtualization environment 64 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 64 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 64 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.

[0076] Applications 66 (which may alternatively be called software instances, virtual appliances, network functions, virtual nodes, virtual network functions, etc.) are run in the virtualization environment 64 to implement some of the features, functions, and / or benefits of some of the embodiments disclosed herein.

[0077] Hardware 68 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 70 (also referred to as hypervisors or virtual machine monitors (VMMs)), provide VMs 72a and 72b (one or more of which may be generally referred to as VMs 72), and / or perform any of the functions, features and / or benefits described in relation with some embodiments described herein. The virtualization layer 68may present a virtual operating platform that appears like networking hardware to the VMs 72.

[0078] The VMs 72 may comprise virtual processing, virtual memory, virtual networking or interface and virtual storage, and may be run by a corresponding virtualization layer 70. Different embodiments of the instance of a virtual appliance 66 may be implemented on one or more of VMs 72, 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.

[0079] In the context of NFV, a VM 72 may be a software implementation of a physical machine that runs programs as if they were executing on a physical, nonvirtualized machine. Each of the VMs 72, and that part of hardware 68 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 72 on top of the hardware 68 and corresponds to the application 66.

[0080] Hardware 68 may be implemented in a standalone network node with generic or specific components. Hardware 68 may implement some functions via virtualization. Alternatively, hardware 68 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 74, which, among others, oversees lifecycle management of applications 66. 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 may be provided with the use of a control system 76 which may alternatively be used for communication between hardware nodes and radio units.

[0081] FIG. 7 is a flowchart of an example process in a network node 16 for selfinterference estimation with synchronized repetitive injections. 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 40 (including the SI test unit 24), processor 42, and / or radio 30. Network node 16 such as via processing circuitry 40 and / or processor 42 and / or radio 30 is configured to repetitively inject into at least one transmitter 36 of the radio 30 a plurality of injection signals and downlink traffic on at least one downlink carrier frequency, the plurality of injection signals being synchronized so that injections signals have a same relative start time for each repetition of the plurality of injection signals (Block S10). The method includes sequentially capturing in a receiver 38 of the radio 30, multiple instances of an uplink signal in an uplink frequency range, the uplink signal including the plurality of injection signals and uplink traffic (Block S12). The method also includes estimating self-interference in the sequentially captured multiple instances of the uplink signal (Block s 14).

[0082] According to this aspect, in some embodiments, repetitively injecting includes transmitting the plurality of injection signals on a subset of antennas 34 of the radio 30. In some embodiments, repetitively injecting the plurality of injection signals includes injecting a first set of injection signals on a first set of antennas 34 of the radio 30 and injecting a second set of injection signals on a second set of antennas 34 of the radio 30. In some embodiments, estimating the self-interference includes determining a weighted combination of the captured multiple instances of the uplink signal. In some embodiments, estimating the self-interference includes removing anomalous captures of the captured multiple instances of the uplink signal when performing the estimation. In some embodiments, each injection signal of the plurality of injections signals include different data. In some embodiments, the at least one downlink carrier frequency is selected to generate self-interference in a selected uplink frequency range. In some embodiments, a first set of injection signals are injected at a first set of downlink carrier frequencies and a second set of injection signals are injected at a second set of downlink carrier frequencies. In some embodiments, estimating the self-interference includes differentiating between injection signals and traffic signals. In some embodiments, sequentially capturing multiple instances of an uplink signal includes synchronizing the captures relative to a start time for each repetition of the plurality of injection signals. In some embodiments, the plurality of injections signals include repeating signals also used for other purposes in the network node 16, including at least one of a cell specific reference signal, CRS, a tracking reference signal and a sounding reference signal. In some embodiments, estimating the self-interference includes selecting and combining captures of the multiple instances of the uplink signal based at least in part on a crosscorrelation of captured multiple instances of the uplink signal. In some embodiments, estimating the self-interference includes combining only phases of the captured multiple instances of the uplink signal.

[0083] 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 self-interference estimation with synchronized repetitive injections.

[0084] FIG. 8 shows a case with only one radio such as radio 30 two antennas 34. The DL traffic is sent into the radio and radiated from both antennas 34. This DL traffic is intended to reach some UEs 22. Some of the power of the DL traffic hits the PIM source, represented by the star. An interference signal is generated and then is picked- up by both antennas 34. The UEs 22 are also sending uplink (UL) traffic which is also picked-up by both antennas 34. The self-interference experienced by the radio 30 is a non-linear function of the aggressor signals. A spectrum diagram is shown in FIG. 9. In this diagram there are two DL carriers at different frequencies. The diagram shows the spectrum of the DL carriers that come from both antennas 34. The diagram also shows a representation of the wideband PIM signal that is generated and picked-up at both antennas 34. The diagram shows the actual frequency range used for the UL (indicated with dashed lines), which is where a UE’s UL signals will be located in the frequency domain.

[0085] In some embodiments, the signals that are represented by f_DLl and f_DL2 are repeated several times, synchronously, such that the PIM signal represented by f_PIM also repeats. Any UL signals or other interference around f_UL is not expected to repeat.

[0086] In some embodiments, a subset of the DL carriers is repeated multiple times. The repeated data in the two carriers is synchronized with each other, but the actual data does not need to be the same in the two carriers (although it may be the same). Only the portion of PIM that is caused by the repetitive part of the DL signals is shown in FIG. 10. I.e., FIG. 10 does not show the total PIM signal that would result from the entire frequency range of the DL carriers. FIG. 10 shows a subset of frequency ranges that are repeated multiple times with no constraint on the remainer of the spectrum. The resultant PIM is due only to the repetitive parts of the DL signals.

[0087] Another example is shown in FIG. 11, where a subset of f_DLl is repeated on one antenna, and a subset of f_DL2 is repeated on a different antenna. In some embodiments, a subset of frequency ranges that are repeated multiple times with no constraint on the remainer of the spectrum. The resultant PIM is due only to the repetitive parts of the DL signals.

[0088] Many variations are possible with respect to radios, subsets of frequency ranges and antennas 34. The repetitive signals should be synchronized (i.e., their relative start times are the same for each repetition). The repetitive signals should also be selected to result in a PIM spectrum that overlaps the frequency range at which the receiver 38 is operating. The example shows only two subsets with repetitive signals, however there may be just one, or more than two (the same comment for number of carriers).

[0089] In the case of FIG. 11, the spectrum may be the same as above where each radio transmits two carriers. However, FIG. 12 shows the case where each of the radios operates one carrier, but at different frequencies. In FIG. 12, an input to radio 1, i.e., a radio 30, includes normal downlink traffic at both antennas 34 and a repetitive injection of a subset of frequency ranges and antennas 34. Similarly, an input to radio 2, i.e. another radio 30, includes normal downlink traffic at both antennas 34 and a repetitive injection of a subset of frequency ranges and antennas 34. An output signal from the radio 1 may contain normal traffic from both antennas 34 and self-interference. The self-interference is present in the output signal only if it has some frequency content in the frequency range used by the receivers of radio 1.

[0090] FIG. 13 shows a spectrum corresponding to FIG. 12 where each radio operates one carrier. In FIG. 13, the repetitive signals are on a subset of the frequency range on a subset of the antennas 34.

[0091] The UL signal may be captured during each DL repetition. These captures should be synchronized with the injection start time so that the relative time offset between the injection- start time and capture-start time is the same for all captures.

[0092] The multiple captures may be combined to form an estimate of the selfinterference due to the synthesized injection signal. Some of the captures may be dropped (not considered) if they are deemed less useful. One attribute that would make a capture less useful is if there were some strong UL traffic or some other UL interference during that particular capture.

[0093] FIG. 14 is a flowchart of another example process in a network node 16 configured for self-interference estimation with synchronized repetitive injections. In a first step, a specific aggressor configuration is selected (Block S16). An aggressor configuration may include, for example, a specific downlink spectrum, certain antenna branches and correlation between antenna branches. An injection signal may be synthesized to conform to the selected aggressor configuration (Block S 18). The synthesized injection signal may then be injected (Block S20). The signal in the victim receiver 38 is captured to include the self-interference signal from the injection (Block S22). The steps of Blocks S20 and S22 may be repeated a number N of times. Then multiple captures are processed to produce an estimate of the self-interference due to the synthesized injections signal (Block S24).

[0094] Some example variations may include one or more of the following:

[0095] In some embodiments, the injections need only occur on a subset of the aggressor carrier(s) (i.e., the aggressor configuration); a subset of the antenna branches; a subset of the available downlink spectrum; and / or a subset of radios 30 on site

[0096] Instead of performing signal injections, the repeating signals may be ones that otherwise occur in a wireless system, such as cell-specific reference signals in long term evolution (LTE). As noted above, some captures may be filtered out, if they are deemed to be anomalous. Captures may occur on a subset of the victim receivers 38, a subset of the antenna branches of antennas 34, bandwidth and time. The captures may be combined by addition or by a weighted sum of captures. The weights may be based on criteria such as cross-correlation values between capture sequences. Phase only combining based on correlations may be performed. The phase values, distribution of phase values, or some statistics of the phase values may also be reported along with the higher quality estimate of the self-interference.

[0097] Thus, some embodiments provide a low noise estimate of self-interference in one or more victim receivers 38.

[0098] Cloud Implementation

[0099] A module may exist in the cloud that requests that the injections be implemented for specific aggressor carriers, and that captures be performed on specific victim receivers 38. The requests must also include the information to ensure the captures are done at the time when self-interference from the specific aggressors is present in the victim receiver 38.

[0100] The data captures may be transferred to the cloud for combining. Alternatively, the combining may be done in a distributed manner, and the higher quality estimate of the self-interference signal may be sent to the cloud where other applications that require the self-interference signal may be located.

[0101] ORAN implementation

[0102] In an ORAN network, as described above, there may be a higher level entity that coordinates the self-interference estimation processes through different DUs and / or RUs.

[0103] A request may be made to a DU or RU with aggressors that injections occur on specific aggressor carriers simultaneously. In some embodiments, this may be without regard to the data in the injection. In some embodiments, the DU or RU may need to know the injection times. In some embodiments, a DU or RU may be informed when captures should be done.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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).

[0109] 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.

[0110] 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) including at least one radio (30) that includes at least one transmitter (36) and at least one receiver (38), the method comprising: repetitively injecting (S10) into at least one transmitter (36) of the radio (30) a plurality of injection signals and downlink traffic on at least one downlink carrier frequency, the plurality of injection signals being synchronized so that injections signals have a same relative start time for each repetition of the plurality of injection signals; sequentially capturing (S 12) in the receiver (38), multiple instances of an uplink signal in an uplink frequency range, the uplink signal including the plurality of injection signals and uplink traffic; and estimating (S14) self-interference in the sequentially captured multiple instances of the uplink signal.

2. The method of Claim 1, wherein the radio (30) includes antennas (34) and repetitively injecting includes transmitting the plurality of injection signals on a subset of the antennas (34) of the radio (30).

3. The method of any of Claims 1 and 2, wherein the radio (30) includes antennas (34) and repetitively injecting the plurality of injection signals includes injecting a first set of injection signals on a first set of the antennas (34) of the radio (30) and injecting a second set of injection signals on a second set of the antennas (34) of the radio (30).

4. The method of any of Claims 1-3, wherein estimating the selfinterference includes determining a weighted combination of the captured multiple instances of the uplink signal.

5. The method of any of Claims 1-4, wherein estimating the selfinterference includes removing anomalous captures of the captured multiple instances of the uplink signal when performing the estimation.

6. The method of any of Claims 1-5, wherein each injection signal of the plurality of injections signals include different data.

7. The method of any of Claims 1-6, wherein the at least one downlink carrier frequency is selected to generate self-interference in a selected uplink frequency range.

8. The method of any of Claims 1-7, wherein a first set of injection signals are injected at a first set of downlink carrier frequencies and a second set of injection signals are injected at a second set of downlink carrier frequencies.

9. The method of any of Claims 1-8, wherein estimating the selfinterference includes differentiating between injection signals and traffic signals.

10. The method of any of Claims 1-9, wherein sequentially capturing multiple instances of an uplink signal includes synchronizing the captures relative to a start time for each repetition of the plurality of injection signals.

11. The method of any of Claims 1-10, wherein the plurality of injections signals include repeating signals also used for other purposes in the network node (16), including at least one of a cell specific reference signal, CRS, a tracking reference signal and a sounding reference signal.

12. The method of any of Claims 1-11, wherein estimating the selfinterference includes selecting and combining captures of the multiple instances of the uplink signal based at least in part on a cross-correlation of captured multiple instances of the uplink signal.

13. The method of any of Claims 1-12, wherein estimating the selfinterference includes combining only phases of the captured multiple instances of the uplink signal.

14. A network node (16) including at least one radio (30) that includes atleast one transmitter (36) and at least one receiver (38), the network node (16) configured to: repetitively inject into at least one transmitter (36) of the radio (30) a plurality of injection signals and downlink traffic on at least one downlink carrier frequency, the plurality of injection signals being synchronized so that injections signals have a same relative start time for each repetition of the plurality of injection signals; sequentially capture in the receiver (38), multiple instances of an uplink signal in an uplink frequency range, the uplink signal including the plurality of injection signals and uplink traffic; and estimate self-interference in the sequentially captured multiple instances of the uplink signal.

15. The network node (16) of Claim 14, wherein the radio (30) includes antennas (34) and repetitively injecting includes transmitting the plurality of injection signals on a subset of antennas (34) of the radio (30).

16. The network node (16) of any of Claims 14 and 15, wherein the radio (30) includes antennas (34) and repetitively injecting the plurality of injection signals includes injecting a first set of injection signals on a first set of the antennas (34) of the radio (30) and injecting a second set of injection signals on a second set of the antennas (34) of the radio (30).

17. The network node (16) of any of Claims 14-16, wherein estimating the self-interference includes determining a weighted combination of the captured multiple instances of the uplink signal.

18. The network node (16) of any of Claims 14-17, wherein estimating the self-interference includes disregarding anomalous captures of the captured multiple instances of the uplink signal when performing the estimation.

19. The network node (16) of any of Claims 14-18, wherein each injection signal of the plurality of injections signals include different data.

20. The network node (16) of any of Claims 14-19, wherein the at least onedownlink carrier frequency is selected to generate self-interference in a selected uplink frequency range.

21. The network node (16) of any of Claims 14-20, wherein a first set of injection signals are injected at a first set of downlink carrier frequencies and a second set of injection signals are injected at a second set of downlink carrier frequencies.

22. The network node (16) of any of Claims 14-21, wherein estimating the self-interference includes differentiating between injection signals and traffic signals.

23. The network node (16) of any of Claims 14-22, wherein sequentially capturing multiple instances of an uplink signal includes synchronizing the captures relative to a start time for each repetition of the plurality of injection signals.

24. The network node (16) of any of Claims 14-23, wherein the plurality of injections signals include repeating signals also used for other purposes in the network node (16), including at least one of a cell specific reference signal, CRS, a tracking reference signal and a sounding reference signal.

25. The network node (16) of any of Claims 14-24, wherein estimating the self-interference includes selecting and combining captures of the multiple instances of the uplink signal based at least in part on a cross-correlation of captured multiple instances of the uplink signal.

26. The network node (16) of any of Claims 14-25, wherein estimating the self-interference includes combining only phases of the captured multiple instances of the uplink signal.

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