Interference Mitigation with Multi-Band Digital Predistortion

Abstract

Embodiments of the present disclosure relate to interference mitigation with multi-band digital predistortion. A method includes: determining a plurality of digital predistortion engines, determining signals for the predistortion engines, determining terms for a matrix and filtering the matrix, based on the filtered matrix, determining a correlation matrix, obtaining a predistorted signal from the digital predistortion engines, where the predistorted signal is predistorted based on the determined correlation matrix, and combining the predistorted signals into a combined predistorted signal.

Description

Technical Field

[0001] The following exemplary embodiments relate to wireless communication and operation on multiple frequency bands. Background Art

[0002] An access node may support a wireless network connection to a terminal device. A part of the access node is a power amplifier, and the power amplifier may introduce nonlinearities, which may cause an undesired broadening of the spectrum used. Therefore, it is desirable to be able to predict the type of nonlinearities that may be introduced so that measures can be taken to mitigate or prevent the occurrence of nonlinearities. Summary of the Invention

[0003] The scope of protection sought by the various embodiments of the present invention is defined by the independent claims. The exemplary embodiments and features (if any) described in this specification that do not fall within the scope of the independent claims will be construed as examples useful for understanding the various embodiments of the present invention.

[0004] According to another aspect, there is provided an apparatus including components: for determining a plurality of digital predistortion engines, determining a signal for the predistortion engines, determining terms for a matrix and filtering the matrix, based on the filtered matrix, determining a correlation matrix, obtaining a predistorted signal from the digital predistortion engines, wherein the predistorted signal is predistorted based on the determined correlation matrix, and combining the predistorted signals into a combined predistorted signal.

[0005] According to another aspect, there is provided an apparatus including at least one processor and at least one memory including computer program code, wherein the at least one memory and the computer program code are configured to, together with the at least one processor, cause the apparatus to: determine a plurality of digital predistortion engines, determine a signal for the predistortion engines, determine terms for a matrix and filtering the matrix, based on the filtered matrix, determine a correlation matrix, obtaining a predistorted signal from the digital predistortion engines, wherein the predistorted signal is predistorted based on the determined correlation matrix, and combining the predistorted signals into a combined predistorted signal.

[0006] According to another aspect, there is provided a method including: determining a plurality of digital predistortion engines, determining a signal for the predistortion engines, determining terms for a matrix and filtering the matrix, based on the filtered matrix, determining a correlation matrix, obtaining a predistorted signal from the digital predistortion engines, wherein the predistorted signal is predistorted based on the determined correlation matrix, and combining the predistorted signals into a combined predistorted signal.

[0007] According to another aspect, there is provided a computer program product which is readable by a computer and, when executed by the computer, is configured to cause the computer to perform a computer process including: determining a plurality of digital predistortion engines, determining a signal for the predistortion engines, determining terms for a matrix and filtering the matrix, based on the filtered matrix, determining a correlation matrix, obtaining a predistorted signal from the digital predistortion engines, wherein the predistorted signal is predistorted based on the determined correlation matrix, and combining the predistorted signals into a combined predistorted signal.

[0008] According to another aspect, there is provided a computer program product including a computer-readable medium carrying computer program code therein including code for performing the following operations: determining a plurality of digital predistortion engines, determining a signal for the predistortion engines, determining terms for a matrix and filtering the matrix, based on the filtered matrix, determining a correlation matrix, obtaining a predistorted signal from the digital predistortion engines, wherein the predistorted signal is predistorted based on the determined correlation matrix, and combining the predistorted signals into a combined predistorted signal.

[0009] According to another aspect, there is provided a computer program product including instructions for causing an apparatus to at least perform the following operations: determining a plurality of digital predistortion engines, determining a signal for the predistortion engines, determining terms for a matrix and filtering the matrix, based on the filtered matrix, determining a correlation matrix, obtaining a predistorted signal from the digital predistortion engines, wherein the predistorted signal is predistorted based on the determined correlation matrix, and combining the predistorted signals into a combined predistorted signal.

[0010] According to another aspect, there is provided a computer program including instructions for causing an apparatus to at least perform the following operations: determining a plurality of digital predistortion engines, determining a signal for the predistortion engines, determining terms for a matrix and filtering the matrix, based on the filtered matrix, determining a correlation matrix, obtaining a predistorted signal from the digital predistortion engines, wherein the predistorted signal is predistorted based on the determined correlation matrix, and combining the predistorted signals into a combined predistorted signal.

[0011] According to another aspect, there is provided a computer-readable medium including program instructions for causing an apparatus to at least perform the following operations: determining a plurality of digital predistortion engines, determining a signal for the predistortion engines, determining terms for a matrix and filtering the matrix, based on the filtered matrix, determining a correlation matrix, obtaining a predistorted signal from the digital predistortion engines, wherein the predistorted signal is predistorted based on the determined correlation matrix, and combining the predistorted signals into a combined predistorted signal.

[0012] According to another aspect, there is provided a non-transitory computer-readable medium including program instructions for causing a device to perform at least the following operations: determining a plurality of digital predistortion engines, determining signals for the predistortion engines, determining terms for a matrix and filtering the matrix, based on the filtered matrix, determining a correlation matrix, obtaining predistorted signals from the digital predistortion engines, wherein the predistorted signals are predistorted based on the determined correlation matrix, and combining the predistorted signals into a combined predistorted signal.

[0013] According to another aspect, there is provided a system including a transmitter, a power amplifier, and a device, the device including at least one processor and at least one memory including computer program code, wherein the system is caused to: determine a plurality of digital predistortion engines, determine signals for the predistortion engines, determine terms for a matrix and filter the matrix, based on the filtered matrix, determine a correlation matrix, obtain predistorted signals from the digital predistortion engines, wherein the predistorted signals are predistorted based on the determined correlation matrix, and combine the predistorted signals into a combined predistorted signal.

[0014] According to another aspect, there is provided a system including components for: determining a plurality of digital predistortion engines, determining signals for the predistortion engines, determining terms for a matrix and filtering the matrix, based on the filtered matrix, determining a correlation matrix, obtaining predistorted signals from the digital predistortion engines, wherein the predistorted signals are predistorted based on the determined correlation matrix, and combining the predistorted signals into a combined predistorted signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Hereinafter, the present invention will be described in more detail in conjunction with embodiments and the drawings, where

[0016] Figure 1 illustrates an exemplary embodiment of a radio access network.

[0017] Figure 2 illustrates an exemplary embodiment of mitigating non-linearity.

[0018] Figure 3 illustrates a flowchart according to an exemplary embodiment.

[0019] Figure 4 、 Figure 5 and Figure 6 illustrates simulation results according to an exemplary embodiment.

[0020] Figure 7 illustrates an exemplary embodiment of a device. DETAILED DESCRIPTION

[0021] The following embodiments are exemplary. Although the present specification may refer to "one", "a", or "some" embodiments at several places in the text, this does not necessarily mean that each reference is to the same (multiple) embodiment, nor does it necessarily mean that a particular feature applies only to a single embodiment. Individual features of different embodiments may also be combined to provide other embodiments.

[0022] As used in this application, the term "circuitry" refers to all of the following: (a) an implementation of pure hardware circuitry, such as an implementation only in analog and / or digital circuitry, and (b) a combination of circuitry and software (and / or firmware), such as, if applicable: (i) a combination of (multiple) processors or (ii) a portion of software / (multiple) processors (including (multiple) digital signal processors), software, and memory, which work together to enable the device to perform various functions, and (c) circuitry that requires software or firmware to operate, such as (multiple) microprocessors or a portion of (multiple) microprocessors, even if the software or firmware is not physically present. This definition of "circuitry" applies to all uses of the term in this application. As a further example, as used in this application, the term "circuitry" will also cover an implementation of only one processor (or multiple processors) or a portion of a processor and its (or their) accompanying software and / or firmware. By way of example and where applicable to a particular element, the term "circuitry" will also cover a baseband integrated circuit or an application processor integrated circuit for a mobile phone, or a similar integrated circuit in a server, a cellular network device, or other network device. The above embodiments of circuitry may also be considered embodiments of means for providing embodiments of the methods or processes described in this document.

[0023] The techniques and methods described herein can be implemented by various means. For example, these techniques can be implemented in hardware (one or more devices), firmware (one or more devices), software (one or more modules), or a combination thereof. For a hardware implementation, the (multiple) devices of an embodiment can be implemented in one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), graphics processing units (GPUs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof. For firmware or software, the implementation can be performed by modules of at least one chipset (e.g., programs, functions, etc.) that perform the functions described herein. The software code can be stored in a memory unit and executed by a processor. The memory unit can be implemented within or outside the processor. In the latter case, it can be communicatively coupled to the processor via any suitable means. Additionally, as will be appreciated by those skilled in the art, the components of the systems described herein can be rearranged and / or supplemented by additional components to support the implementation of the various aspects described thereof, and they are not limited to the exact configurations set forth in the given figures.

[0024] The embodiments described herein can be implemented in a communication system, such as in at least one of the following: Global System for Mobile Communications (GSM) or any other second generation cellular communication system, Universal Mobile Telecommunications System (UMTS, 3G) based on Wideband Code Division Multiple Access (W-CDMA), High Speed Packet Access (HSPA), Long Term Evolution (LTE), Advanced LTE, systems based on the IEEE 802.11 standard, systems based on the IEEE 802.15 standard, and / or fifth generation (5G) mobile or cellular communication systems. However, the embodiments are not limited to the systems given as examples, but those skilled in the art can apply the solution to other communication systems that provide the necessary attributes.

[0025] Figure 1 An example of a simplified system architecture is depicted, which shows some elements and functional entities, all of which are logical units and whose implementation may be different from that shown. Figure 1 The connections shown in are logical connections; the actual physical connections may vary. It will be apparent to those skilled in the art that the system may also include other functions and structures in addition to the Figure 1 functions and structures shown in. Figure 1 The example of shows a part of an exemplary radio access network.

[0026] Figure 1FIG. 0 shows terminal devices 100 and 102, which are configured to be in a wireless connection with an access node (such as an (e / g)NodeB) 104 that provides a cell on one or more communication channels in the cell. The access node 104 may also be referred to as a node. The physical link from the terminal device to the (e / g)NodeB is referred to as the uplink or reverse link, and the physical link from the (e / g)NodeB to the terminal device is referred to as the downlink or forward link. It should be understood that the (e / g)NodeB or its functionality may be implemented by any entity such as a node, host, server, or access point suitable for this purpose. Note that although one cell is discussed in this exemplary embodiment for simplicity of explanation, in some exemplary embodiments, an access node may provide multiple cells.

[0027] The communication system may include more than one (e / g)NodeB, in which case the (e / g)NodeB may also be configured to communicate with each other via a wired or wireless link designed for this purpose. These links may be used for signaling purposes. The (e / g)NodeB is a computing device that is configured to control the radio resources of the communication system to which it is coupled. The (e / g)NodeB may also be referred to as a base station, access point, or any other type of interface device, including a relay station capable of operating in a wireless environment. The (e / g)NodeB includes or is coupled to a transceiver. The transceiver of the (e / g)NodeB provides a connection to an antenna unit that establishes a two-way radio link to the user equipment. The antenna unit may include multiple antennas or antenna elements. The (e / g)NodeB is also connected to a core network 110 (CN or Next Generation Core NGC). Depending on the system, the corresponding party on the CN side may be a Serving Gateway (S-GW, routing and forwarding user data packets), a Packet Data Network Gateway (P-GW) for providing connectivity between the terminal device (UE) and an external packet data network, or a Mobility Management Entity (MME), etc.

[0028] The terminal device (which may also be referred to as a UE, user equipment, user terminal, user device, etc.) illustrates a type of device to which resources on the air interface are allocated and assigned, and thus any feature described herein with respect to the terminal device may be implemented using a corresponding device, such as a relay node. Examples of such relay nodes are Layer 3 relays (self-backhaul relays) towards the base station. Another example of such a relay node is a Layer 2 relay. Such a relay node may include a terminal device part and a Distributed Unit (DU) part. For example, a CU (Centralized Unit) may coordinate DU operations via an F1AP interface.

[0029] A terminal device may refer to a portable computing device, which includes a wireless mobile communication device that operates with or without a subscriber identity module (SIM) or an embedded SIM, eSIM, including but not limited to the following types of devices: workstations (mobile phones), smartphones, personal digital assistants (PDAs), mobile phones, devices using a wireless modem (such as alarm or measurement devices, etc.), laptop computers and / or touchscreen computers, tablet computers, gaming consoles, laptop computers, and multimedia devices. It should be understood that the terminal device may also be a dedicated or nearly dedicated uplink-only device, an example of which is a camera or video camera that loads images or video clips onto the network. The terminal device may also be a device capable of operating in an Internet of Things (IoT) network, which is a scenario in which objects are provided with the ability to transmit data over a network without the need for human-to-human or human-to-machine interaction. The terminal device may also utilize the cloud. In some applications, the terminal device may include small portable devices with a radio part (such as watches, headphones, or glasses), and the computing is performed in the cloud. The terminal device (or a layer 3 relay node in some embodiments) is configured to perform one or more user equipment functions.

[0030] The various technologies described herein may also be applied to cyber-physical systems (CPSs) (systems that coordinate computational elements for controlling physical entities). CPSs may enable the implementation and utilization of large-scale interconnected ICT devices (sensors, actuators, processor microcontrollers, etc.) embedded in physical objects at different locations. A mobile cyber-physical system, in which the physical systems discussed therein have inherent mobility, is a subcategory of cyber-physical systems. Examples of mobile physical systems include mobile robots and electronic devices transported by humans or animals.

[0031] In addition, although the device has been depicted as a single entity, different units, processors, and / or memory units may be implemented (not all shown Figure 1 herein).

[0032] 5G supports the use of multiple-input multiple-output (MIMO) antennas, far more base stations or nodes than LTE (the so-called small cell concept), including macro sites that operate in cooperation with smaller base stations and employ various radio technologies depending on service requirements, use cases, and / or available spectrum. 5G mobile communications supports a wide range of use cases and related applications, including video streaming, augmented reality, different ways of data sharing, and various forms of machine type applications, such as (massive) machine type communication (mMTC), including vehicle safety, different sensors, and real-time control. 5G is expected to have multiple radio interfaces, namely below 6 GHz, cmWave, and mmWave, and can also be integrated with existing traditional radio access technologies such as LTE. At least in the early stages, the integration with LTE can be implemented as a system where macro coverage is provided by LTE and 5G radio interface access comes from small cells by aggregating to LTE. In other words, 5G is planned to support both inter-RAT operability (such as LTE-5G) and inter-RI operability (inter-radio interface operability, such as below 6 GHz–cmWave, below 6 GHz–cmWave–mmWave). One of the concepts considered in 5G networks is network slicing, where multiple independent and dedicated virtual subnets (network instances) can be created within the same infrastructure to run services with different requirements for latency, reliability, throughput, and mobility.

[0033] The current architecture in LTE networks is fully distributed in the radio and fully centralized in the core network. Low-latency applications and services in 5G may require bringing content closer to the radio, which may lead to local breakout and multi-access edge computing (MEC). 5G enables analysis and knowledge generation to occur at the data source. This approach requires leveraging resources that may not be continuously connected to the network, such as laptops, smartphones, tablets, and sensors. MEC provides a distributed computing environment for application and service hosting. It also has the ability to store and process content closer to cellular users to speed up response times. Edge computing encompasses a wide range of technologies, such as wireless sensor networks, mobile data collection, mobile signature analysis, cooperative distributed peer-to-peer ad hoc networks, and processing that can also be classified as local cloud / fog computing and grid / grid computing, dew computing, mobile edge computing, small cloud computing (cloudlet), distributed data storage and retrieval, self-healing autonomous networks, remote cloud services, augmented and virtual reality, data caching, Internet of Things (massive connectivity and / or latency-critical), mission-critical communications (autonomous vehicles, traffic safety, real-time analytics, time-critical control, healthcare applications).

[0034] The communication system is also capable of communicating with other networks, such as the public switched telephone network or the Internet 112, and / or of utilizing the services provided by them. The communication network may also be capable of supporting the use of cloud services, for example, at least a part of the core network operations may be performed as cloud services (which is depicted by the "cloud" 114 in Figure 1 ). The communication system may also include a central control entity, etc., to provide facilities for the networks of different operators to cooperate, for example, in spectrum sharing.

[0035] The edge cloud can be brought into the radio access network (RAN) by leveraging network function virtualization (NFV) and software defined network (SDN). The use of the edge cloud may mean that the access node operations are performed at least partly in a server, host, or node that is operationally coupled to a remote radio head or a base station including a radio part. The node operations may also be distributed among multiple servers, nodes, or hosts. The application of the cloud RAN architecture enables the RAN real-time functions to be performed on the RAN side (in the distributed unit DU 104) and the non-real-time functions to be performed in a centralized manner (in the centralized unit CU 108).

[0036] It should also be understood that the distribution of the labor force between the core network operations and the base station operations may be different from that of LTE, or even non-existent. Some other technologies that can be used, such as big data and all-IP, may change the way the network is built and managed. The 5G (or new radio, NR) network is designed to support multiple hierarchies, where the MEC server can be placed between the core and the base station or node B (gNB). It should be understood that MEC can also be applied to 4G networks.

[0037] 5G can also utilize satellite communication to enhance or supplement the coverage of 5G services - for example, by providing backhaul. Possible use cases include providing service continuity for machine-to-machine (M2M) or Internet of Things (IoT) devices or passengers in vehicles, and / or ensuring service availability for critical communications and / or future railway / maritime / aviation communications. Satellite communication can utilize geostationary Earth orbit (GEO) satellite systems or low Earth orbit (LEO) satellite systems, such as megaconstellations (systems in which hundreds (nanosatellites) are deployed). Each satellite 106 in a megaconstellation can cover several satellite-enabled network entities that create a ground cell. The ground cell can be created by a ground relay node 104 or by a gNB located on the ground or in a satellite, or a part of the gNB (e.g., DU) can be on the satellite and a part of the gNB (e.g., CU) can be on the ground. Additionally or alternatively, a high-altitude platform station (HAPS) system can be utilized. A HAPS can be understood as a radio station located at a fixed point relative to the Earth and on an object at an altitude of 20 - 50 km. For example, broadband access can be provided via HAPS using a light solar aircraft and an airship operating continuously for several months at an altitude of 20 - 25 km.

[0038] It should be noted that the depicted system is an example of a part of a radio access system and the system can include multiple (e / g)NodeBs, terminal devices can access multiple radio cells and the system can also include other devices, such as physical layer relay nodes or other network elements, etc. At least one of the (e / g)NodeBs can be a home (e / g)nodeB. Additionally, in the geographical area of a radio communication system, multiple different types of radio cells and multiple radio cells can be provided. The radio cells can be macrocells (or umbrella cells), which are large cells, typically having a diameter of up to several tens of kilometers, or they can be smaller cells, such as microcells, femtocells or picocells. Figure 1 The (e / g)NodeBs can provide any type of these cells. A cellular radio system can be implemented as a multi-layer network including multiple types of cells. In some exemplary embodiments, in a multi-layer network, one access node provides one or more cells of one type, so multiple (e / g) nodes are required to provide such a network structure.

[0039] To meet the need for improving the deployment and performance of communication systems, the concept of "plug-and-play" (e / g)NodeBs has been introduced. A network capable of using "plug-and-play" (e / g)NodeBs can include, in addition to home (e / g)NodeBs (H(e / g)nodeB), a home node B gateway, or HNB-GW ( Figure 1(not shown in the figure). A Home Node B Gateway (HNB-GW) that can be installed within an operator's network can aggregate traffic from a large number of HNBs back to the core network.

[0040] In a wireless network, operating on multiple frequency bands is beneficial because it achieves flexibility that cannot be achieved when operating on a single frequency band. However, if the frequency bands are close to each other, the possibility of intermodulation interference increases. Intermodulation can be understood as amplitude modulation of a signal containing two or more different frequencies, frequency components, and it may be caused by non-linearity in the system. In an access node, the source of non-linearity may be the power amplifier PA, due to limitations of its electronic components, or it may also be caused by the algorithms used. Intermodulation between frequency components can form additional components not only at frequencies that are integer multiples of any of the frequency components but also at the sum and difference frequencies of the original frequencies and at the sums and differences of multiples of these frequencies. If intermodulation interference occurs, it may not be possible to filter it out. This may be due to the limited roll-off response of the filters used. For example, in digital filtering, the hardware or software implementation may include a limited number of multipliers, forcing each filter to use a limited number of taps. For example, some designs allocate 32, 64, 96 filter taps to each digital filter. Due to the limited number of filter taps, the filter roll-off may occur slowly in a frequency, resulting in interference to signals in adjacent frequency bands.

[0041] To mitigate the non-linearity caused by the PA, digital pre-distortion DPD can be utilized. DPD can enable the PA to operate at or near its saturation point. DPD can utilize algorithms such as direct learning algorithm DLA, indirect learning algorithm ILA, or fixed-point-based algorithms. For example, in ILA, the output signal is used as the input to a post-distortion device to extract the parameters of the pre-distortion device. On the other hand, DLA can be based on an identified PA model, and the inverse PA model is the DPD function to be calculated (i.e., determined). DLA can model the PA as a memory polynomial with odd terms, for example, only odd terms, and then the inverse function of the memory polynomial can be calculated through a recursive algorithm.

[0042] Figure 2An exemplary embodiment of how DPD with direct learning can be used with a power amplifier to mitigate nonlinearity is illustrated. A signal is first input to a digital predistorter 210 that then performs a DPD function, and then the predistorted signal is converted by a digital-to-analog converter DAC 220 into an analog signal, which is then amplified by a power amplifier 230. The amplified analog signal is transmitted by a transmitter 240. Moreover, the output amplified analog signal is used as an input to a feedback loop 250. In the feedback loop 250, the amplified analog signal is input to an analog-to-digital converter 260 to obtain a digital signal. The obtained digital signal is then input to an identification unit 270, which filters and normalizes the signal. The identification unit can also receive as input the predistorted signal output by the digital predistorter 210. The identification unit 270 can then determine the characteristics of the PA 230 based on the input signal by, for example, extraction. These characteristics can then be used by a function unit 280 to determine a DPD function, which can be used as an output from the feedback loop 250, which is then provided as an input to the digital predistorter 210. Note that the digital predistorter 210 also receives the non-predistorted signal as input and therefore uses the feedback predistorted signal and the non-predistorted signal to generate a new predistorted signal.

[0043] An example of modeling a nonlinear component such as PA 230 is the generalized memory polynomial GMP model. Other models that can be used to model nonlinear electronic components are, for example, the radially pruned Volterra model and the simplified radially pruned Volterra model. In the GMP model, the linear and multiple nonlinear parts can be expressed in terms of the input signal x(n). The input signal can be offset by q (i.e., x(nq)) to represent the memory of the nonlinear device. Therefore, the nonlinear output of the component y(n) can be expressed in terms of linear and nonlinear terms. These terms can also be understood as characteristics of the component.

[0044] The DPD engine can be understood as a component, which can be a logic component that performs pre-distortion of the input signal in order to mitigate the nonlinearity introduced by the PA when amplifying the signal. Therefore, due to the feedback loop, the DPD engine can dynamically generate the inverse of the PA characteristic. In some exemplary embodiments, the DPD engine is implemented as a combination of a linear filter and N-1 high-order linear filters, but the implementation can vary. In this exemplary embodiment, the input to the linear filter can be the input signal. Each high-order filter can take as input a certain power of the input amplitude, and each filter can also have a different number of taps. Filtering can be used to pre-distort the input signal and mitigate PA distortion so that the baseband equivalent of the output of the PA is close to the same as the input signal.

[0045] When multiple frequency bands are used, each carrier or each frequency band may have a DPD engine, or there may be a combination of an engine dedicated to one carrier and an engine dedicated to one frequency band. Thus, for example, if three frequency bands are used, there may accordingly be three DPD engines, one for each frequency band. However, if the frequency bands (i.e., radio frequency RF bands) are close to each other causing intermodulation IM interference between them, multiple DPD engines may not be able to mitigate such interference. Thus, it is desirable to further enhance the DPD implementation such that self-interference can be mitigated, thereby allowing multi-band operation even if the frequency bands are close to each other.

[0046] Figure 3 A flowchart according to an exemplary embodiment is illustrated, in which multiple DPD engines can be used even if there are multiple frequency bands close to each other. In other words, self-interference mitigation for multi-band DPD (SIMM DPD) is illustrated in this exemplary embodiment. First, in S1, it is determined how many DPD engines are needed. One DPD engine can be allocated for each carrier, or one DPD engine can be allocated for each frequency band, or a combination of both. Next, in S2, the frequency of the numerically controlled oscillator, NCO, is obtained such that there is an NCO corresponding to the DPD engine. For example, there is one NCO for each DPD engine. The NCO frequency can be, for example, the center of the carrier set. The NCO can be understood as a digital signal generator that creates a synchronized, discrete-time, discrete-value representation of a waveform. The NCO can be used in combination with a DAC. Some benefits of the NCO can include agility, accuracy, stability, and reliability.

[0047] Next, in S3, a filter is selected for the DPD engine. For example, each DPD engine may have a filter. In this exemplary embodiment, the filter is a finite impulse response FIR filter, but other filters can be used in some other exemplary embodiments. FIR is a filter with a finite-duration impulse response. In some other exemplary embodiments, one FIR filter can be used for multiple or even all DPD engines. If a real FIR filter is used, i.e., an FIR filter without complex coefficients, then the center of the DPD engine can be set to 0 Hz. If a complex FIR filter is used, i.e., an FIR filter with complex coefficients, then the FIR filter can be specifically designed for its corresponding DPD engine. The center of the complex filter may coincide with the corresponding DPD engine. Then in S4, a signal is determined for the DPD engine. For example, an offset term of 0 Hz can be determined for the real FIR filter and represented as txb1, x1b, x2b, and x3b. Alternatively, if a complex FIR filter is used, then no offset of the signal is required, and these terms can be represented as tx, x1, x2, x3. In S5, terms are then selected for the matrix, thereby also selecting the storage depth and the non-linearity order.

[0048] In S6, a basis function filter is performed on the matrix to generate a filtered matrix. The basis function filter can be understood as filtering the non-linear terms in the time domain. It should be noted that the selected configuration can be used regardless of whether the terms are shifted to 0 Hz or the center. It should also be noted that if a complex FIR is used, the signal is not shifted. Then in S7, the filtered correlation matrix is determined. In this exemplary embodiment, the filtered matrix is an autocorrelation matrix and a cross-correlation matrix. Based on the matrix, coefficients can be obtained according to the DPD algorithm used. Then in S8, the pre-distorted digital signal is generated by the DPD engine. Each DPD engine can generate a pre-distorted digital signal. If a real FIR filter is used, then if the signal is shifted to 0 Hz, the pre-distorted signal is centered at 0 Hz. Then in S9, the pre-distorted signal is shifted back to the carrier or the band center. Alternatively, if a complex FIR filter is used, no shifting back is required because the signal was not shifted to 0 Hz previously. Then in S10, the pre-distorted signals from the DPD engines are combined into a total pre-distorted signal. For example, this can be described as: total pre-distorted signal = pre-distorted signal 1 + pre-distorted signal 2 + pre-distorted signal 3. Then the total pre-distorted signal can be used as part of the feedback loop of the engine to allow determination of which DPD interferes with which DPD.

[0049] Figure 4 Illustrated is such as Figure 3 the simulation results of an exemplary embodiment such as the exemplary embodiment illustrated in

[0050] The sampling rate of the DPD engine in this exemplary embodiment is 491.52 MSPS. A higher sampling rate can also be used if a particular multi-band configuration is wider to meet the Nyquist criterion. The signal in this exemplary embodiment can be represented as tx = x1 + x2 + x3, where tx is the un-pre-distorted signal complex, which includes Figure 1All three signals. x1 is the first carrier located at -45 MHz, i.e., Band 1, x2 is the second carrier located at 15 MHz, i.e., Band 2, and x3 is the third carrier located at +45 MHz, i.e., Band 3. Accordingly,

[0051] x1b is the first carrier offset to 0 Hz. The associated NCO1 offset is +45 MHz, x2b is the second carrier offset to 0 Hz. The associated NCO2 offset is -15 MHz, and x3b is the third carrier offset to 0 Hz. The associated NCO3 offset is -45 MHz. Fb1 is the feedback of the first carrier offset to 0 Hz. The associated NCO1 offset of +45 MHz is used with filtering to extract it. txb1 is the complex tx offset with NCO1 in x1b, which is +45 MHz. It should be noted that the components x1b, txb1, and Fb1 associated with the first DPD engine are offset to 0 Hz with NCO1.

[0052] The equations associated with the first DPD engine are discussed below. It should be noted that the equations associated with the second DPD and the third DPD may be the same or similar. Figure 4 The results illustrated in are obtained from the 3 DPD engines used in the exemplary embodiment. Thus, the matrix YMat is obtained:

[0053] YMat = [x1b x1b*|x1b| 2 x1b*|x2b| 2 x1b*|x3b| 2 txb1*|txb1| 2 x1b*|x1b| 4 x1b*|x2b| 4 x1b*|x3b| 4 txb1*|txb1| 4

[0054] The vertical columns of the matrix YMat are time-based offsets such as n, n + 1, n + 2, etc. Thus, YMat is an n x 9 matrix. However, it should be noted that the terms described above may not be fixed, but the terms can be selected based on the complexity of the DPD model and the complexity of the PA and carrier configuration. It should be noted that for simplicity, the memory terms are excluded from the discussion. Examples of some additional terms that can be used in some exemplary embodiments are:

[0055] x1b*(|x1b| 2 +|x2b| 2 +|x3b| 2 ) k ,

[0056] x1b*(|x1b|​2 +|x2b| 2 ) k ,

[0057] x1b*(|x1b| 2 +|x3b| 2 ) k ,

[0058] x1b*(|x2b| 2 +|x3b| 2 ) k

[0059] x1b*|x1b| 2*k1* |x2b| 2*k2 *|x3b| 2*k3

[0060] x1b*|x1b| 2*k1 *|x2b| 2*k2

[0061] x1b*|x1b| 2*k1 *|x3b| 2*k3

[0062] x1b*|x2b| 2*k2 *|x3b| 2*k3

[0063] The matrix is derived without basis function filtering, so basis function filtering is applied next. Basis function filtering can be performed in the time domain or the frequency domain. An example of basis function filtering applied to third-order nonlinearity is:

[0064] f(x1b*|x1b| 2 )

[0065] YMatf = [f(x1b) f(x1b*|x1b| 2 )f(x1b*|x2b| 2 )f(x1b*|x3b| 2 )f(txb1*|txb1| 2 )f(x1b*|x1b| 4 )f(x1b*|x2b| 4 )...f(x1b*|x3b| 4 )f(txb1*|txb1| 4 )]

[0066] Note that the non - linear terms in YMatf are filtered, so they do not exhibit frequency components outside the filter f. This is beneficial for SIM MDPD where adjacent carrier IMs may interfere with each other. Therefore, the auto - correlation and cross - correlation functions generated for DPD engines 2 and 3 may limit the frequency content within the filter response bandwidth. This allows adjacent DPD engines to obtain an accurate estimate of the interfering IM. Due to basis function filtering, the least - squares solution can obtain the frequency content applicable to a certain DPD engine. Although adjacent DPD engines overlap in the frequency domain, their own IMs can be identified through multiple iterations.

[0067] If the auto - correlation and cross - correlation functions are not filtered, the non - linear basis functions will exhibit unrestricted frequency components. Therefore, when such IMs interfere between adjacent DPD engines, it will result in invalid IM estimates. This solution may not be able to correctly mitigate the self - interference component because the least - squares solution used by the DPD engine may not have the correct frequency exposure for the interfering IM. The following are examples of the auto - correlation and cross - correlation functions.

[0068] Auto - correlation function after basis function filtering: Auto1=(YMatf H )(YMatf)

[0069] Cross - correlation function after basis function filtering: Cross1=(YMatf H )(f(Fb1))

[0070] DLA coefficient: wn1 = Auto1 -1 *(Cross1).

[0071] Once the identification is completed, the predistortion waveform can be generated in the baseband at 0Hz. The predistortion waveform Pred1b(n) can then be shifted to the correct frequency conjugate to NCO1. The following equations illustrate how to generate the predistortion waveform for the first DPD engine corresponding to carrier 1. The predistortion waveforms for other carriers can be generated in a similar manner.

[0072] Pred1b(n)=x1b(n)+filter(TotalError(n))

[0073] TotalError(n)=ymat n *wn1

[0074] ymat nis the row vector of the matrix YMat corresponding to time n. TotalError is filtered before it is added to the desired signal x1b. Note that Pred1b is at the baseband 0Hz in this example. Pred1b(n) is then shifted back to its original frequency of -45MHz before being added to other predistorted signals.

[0075] Figure 5 The figure shows when Figure 4 the simulation results when using a 65-tap digital filter in the exemplary embodiment of. Each carrier can be centered in the middle of the filter. For example, the filter can be a real FIR or complex FIR filter. If a real FIR filter is used, the carrier is shifted to 0Hz. If a complex filter is used, the shift may not be required. The IM within the filter is corrected, and the correction can be controlled by widening or narrowing the filter without exceeding the number of dedicated filter taps.

[0076] Figure 6 The figure shows the simulation results when a real FIR filter is applied to an undistorted, clean signal in band 2. Since the filter is real and symmetric around 0Hz, the carrier is shifted to place the center of carrier 2 or band 2 close to 0Hz, which is the center of the filter. As shown, the filter cannot completely suppress carrier 3. Therefore, Figure 4 any inter-carrier IM 410 shown in does not experience any attenuation. This can be corrected by applying Figure 3 the exemplary embodiment shown in.

[0077] The advantages of the above exemplary embodiments include the ability to linearize the PA in multi-carrier and multi-band scenarios. The above SIM MDPD can be used in conjunction with any carrier separation. Therefore, in some exemplary embodiments, the above SIMMDPD concept can be used to split continuous carriers such as NR-100 into multiple bands.

[0078] Figure 7 The figure shows an example embodiment of a device that can be an access node or included in an access node. The device can be, for example, a circuit system or chipset suitable for an access node to implement the described embodiments. Device 700 can be an electronic device including one or more electronic circuit systems. Device 700 can include communication control circuit system 710 such as at least one processor, and at least one memory 720 including computer program code (software) 722, where at least one memory and computer program code (software) 722 are configured to, together with at least one processor, cause device 700 to perform any of the example embodiments of the above access node.

[0079] The memory 720 can be implemented using any suitable data storage technology, such as semiconductor-based memory devices, flash memory, magnetic memory devices and systems, optical memory devices and systems, fixed memory, and removable memory. The memory can include a configuration database for storing configuration data. For example, the configuration database can store the current list of neighboring cells, and in some example embodiments, the frame structure used in the detected neighboring cells.

[0080] The apparatus 700 may further include a communication interface 730, which includes hardware and / or software for implementing communication connectivity according to one or more communication protocols. The communication interface 730 can provide radio communication capabilities for the apparatus to communicate in a cellular communication system. For example, the communication interface can provide a radio interface to a terminal device. The apparatus 700 may further include another interface towards a core network and / or an access node of a cellular communication system, such as a network coordinator device. The apparatus 700 may also include a scheduler 740 configured to allocate resources.

[0081] The processor 710 interprets computer program instructions and processes data. The processor 710 may include one or more programmable processors. The processor 710 may include programmable hardware with embedded firmware, and alternatively or additionally, may include one or more application-specific integrated circuits (ASICs).

[0082] The processor 710 is coupled to the memory 720. The processor is configured to read data from the memory 720 and write data to the memory 720. The memory 720 may include one or more memory units. The memory units can be volatile or non-volatile. It should be noted that in some example embodiments, there may be one or more non-volatile memory units and one or more volatile memory units, or alternatively, one or more non-volatile memory units, or alternatively, one or more volatile memory units. Volatile memory can be, for example, RAM, DRAM, or SDRAM. Non-volatile memory can be, for example, ROM, PROM, EEPROM, flash memory, optical storage, or magnetic storage. Generally, the memory can be referred to as a non-transitory computer-readable medium. The memory 720 stores computer-readable instructions executed by the processor 710. For example, the non-volatile memory stores the computer-readable instructions and the processor 710 uses the volatile memory for temporarily storing data and / or instructions to execute the instructions.

[0083] The computer-readable instructions may have been pre-stored in the memory 720, or alternatively or additionally, they may be received by the apparatus via an electromagnetic carrier signal and / or may be copied from a physical entity such as a computer program product. The execution of the computer-readable instructions causes the apparatus 700 to perform the above-described functionality.

[0084] In the context of this document, a "memory" or "computer-readable medium" can be any non-transitory medium or can contain, store, communicate, propagate, or transport instructions for use by or in connection with an instruction execution system, apparatus, or device, such as a computer.

[0085] Note that apparatus 700 may also include Figure 7 various components not shown in the figure. The various components can be hardware components and / or software components.

[0086] Although the present invention has been described above with reference to examples according to the accompanying drawings, it is obvious that the present invention is not limited thereto, but can be modified in various ways within the scope of the appended claims. Therefore, all words and expressions should be interpreted broadly and they are intended to illustrate the embodiments rather than limit the embodiments. It is obvious to those skilled in the art that the inventive concept can be implemented in various ways as technology progresses. In addition, it is clear to those skilled in the art that the described embodiments can, but do not have to, be combined with other embodiments in various ways.

Claims

1. A device for communication, comprising at least one processor and at least one memory, the at least one memory including computer program code, wherein the at least one memory and the computer program code are configured to, together with the at least one processor, cause the device to: Determine a plurality of digital predistortion engines; Determine signals for the plurality of digital predistortion engines, wherein the signals are received at a plurality of carrier frequencies or over a plurality of frequency bands, and the number of digital predistortion engines included in the plurality of digital predistortion engines is determined based on the plurality of carrier frequencies or based on the plurality of frequency bands; Determine terms for a matrix and perform basis function filtering on the matrix, wherein the terms are determined based on the signals and on the frequencies of the signals, and the matrix is established based on a combination of the terms; Based on the filtered matrix, determine a correlation matrix; Obtain a predistorted signal from the digital predistortion engines, wherein the predistorted signal is predistorted based on the determined correlation matrix; And Combine the predistorted signals into a combined predistorted signal.

2. The device according to claim 1, wherein the determined terms are memoryless terms.

3. The device according to claim 1, wherein the combined predistorted signal is input to a power amplifier.

4. The device according to claim 1, wherein at least one of the plurality of digital predistortion engines includes a filter that is a real finite impulse response filter.

5. The device according to claim 4, wherein the at least one predistortion engine is caused to perform an offset of a signal included in the determined signals to obtain an offset signal.

6. The device according to claim 5, wherein, before the offset signal is combined into the combined predistorted signal, the at least one predistortion engine performs an offset of the offset signal back to its original frequency.

7. The device according to claim 1, wherein at least one of the plurality of digital predistortion engines includes a filter for performing the basis function filtering on the matrix, and the filter is a complex finite impulse response filter.

8. The device according to claim 1, wherein the correlation matrix includes an autocorrelation matrix and a cross-correlation matrix.

9. The device according to claim 1, wherein the basis function filtering includes non-linear filtering terms.

10. The device according to claim 1, wherein the terms are determined based on at least one of the following: the complexity of the digital predistortion engines, the complexity of the power amplifier, and / or the complexity of the carrier configuration.

11. The device according to any one of claims 1 to 10, wherein the device is included in an access node.

12. A communication method, comprising: Determine a plurality of digital predistortion engines; Determine a signal for the plurality of digital predistortion engines, where the signal is received at a plurality of carrier frequencies or over a plurality of frequency bands, and the number of digital predistortion engines included in the plurality of digital predistortion engines is determined based on the plurality of carrier frequencies or based on the plurality of frequency bands; Determine terms for a matrix and perform basis function filtering on the matrix, where the terms are determined based on the signal and based on the frequency of the signal, and the matrix is established based on a combination of the terms; Determine a correlation matrix based on the filtered matrix; Obtain a predistorted signal from the digital predistortion engines, where the predistorted signal is predistorted based on the determined correlation matrix; And Combine the predistorted signals into a combined predistorted signal.

13. A computer-readable medium for communication, comprising program instructions for causing a device to perform at least the following operations: Determine a plurality of digital predistortion engines; Determine a signal for the plurality of digital predistortion engines, where the signal is received at a plurality of carrier frequencies or over a plurality of frequency bands, and the number of digital predistortion engines included in the plurality of digital predistortion engines is determined based on the plurality of carrier frequencies or based on the plurality of frequency bands; Determine terms for a matrix and perform basis function filtering on the matrix, where the terms are determined based on the signal and based on the frequency of the signal, and the matrix is established based on a combination of the terms; Determine a correlation matrix based on the filtered matrix; Obtain a predistorted signal from the digital predistortion engines, where the predistorted signal is predistorted based on the determined correlation matrix; And Combine the predistorted signals into a combined predistorted signal.

14. A device for communication, comprising components for: Determine a plurality of digital predistortion engines; Determine a signal for the plurality of digital predistortion engines, where the signal is received at a plurality of carrier frequencies or over a plurality of frequency bands, and the number of digital predistortion engines included in the plurality of digital predistortion engines is determined based on the plurality of carrier frequencies or based on the plurality of frequency bands; Determine terms for a matrix and perform basis function filtering on the matrix, where the terms are determined based on the signal and based on the frequency of the signal, and the matrix is established based on a combination of the terms; Determine a correlation matrix based on the filtered matrix; Obtain a predistorted signal from the digital predistortion engines, where the predistorted signal is predistorted based on the determined correlation matrix; And Combine the predistorted signals into a combined predistorted signal.

15. A communication system, comprising a transmitter, a power amplifier, and a device, the device comprising at least one processor and at least one memory, the at least one memory comprising computer program code, where the system is caused to: Determine a plurality of digital predistortion engines; Determine a signal for the plurality of digital predistortion engines, wherein the signal is received at a plurality of carrier frequencies or over a plurality of frequency bands, and the number of digital predistortion engines included in the plurality of digital predistortion engines is determined based on the plurality of carrier frequencies or based on the plurality of frequency bands; Determine terms for a matrix and perform basis function filtering on the matrix, wherein the terms are determined based on the signal and on the frequency of the signal, and the matrix is established based on a combination of the terms; Determine a correlation matrix based on the filtered matrix; Obtain a predistorted signal from the digital predistortion engines, wherein the predistorted signal is predistorted based on the determined correlation matrix; And Combine the predistorted signals into a combined predistorted signal.

16. A system for communication, comprising components for: Determine a plurality of digital predistortion engines; Determine a signal for the plurality of digital predistortion engines, wherein the signal is received at a plurality of carrier frequencies or over a plurality of frequency bands, and the number of digital predistortion engines included in the plurality of digital predistortion engines is determined based on the plurality of carrier frequencies or based on the plurality of frequency bands; Determine terms for a matrix and perform basis function filtering on the matrix, wherein the terms are determined based on the signal and on the frequency of the signal, and the matrix is established based on a combination of the terms; Determine a correlation matrix based on the filtered matrix; Obtain a predistorted signal from the digital predistortion engines, wherein the predistorted signal is predistorted based on the determined correlation matrix; And Combine the predistorted signals into a combined predistorted signal.

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