Patent Description:
Passive Inter-Modulation (PIM) is an important concern for cellular operators as more downlink channels are being transmitted from the cellular radio sites. As used herein, PIM refers to interference generated by two or more carrier frequencies being exposed to non-linear mixing. The resulting signal will contain additional, unwanted frequencies or intermodulation products. As the "Passive" portion of the name implies, this non-linear mixing does not involve active devices and is frequently caused by the metallic materials and workmanship of the interconnects and other passive components in the system. Thus, one example of PIM sources includes imperfect metal connections. To add to the challenge, the newly added radio channels belong to a rising number of radio bands which increases the odds of having PIM that desensitizes the uplink receivers.

A growing number of cellular operators now require that the presence of PIM in the uplink channels be reported by radio equipment so that PIM mitigation measures can then be taken.

Some PIM-detection (PIM-D) techniques have been reported in the literature. For example, one approach suggests measuring the noise floor in the uplink channels during transmission time intervals (TTIs) where no uplink (UL) traffic is scheduled and in the guard bands of the uplink channels when uplink traffic is present. However, this approach can miss some PIM occurrences during the site operation since <NUM>) PIM may not be present during the uplink TTIs where no traffic is scheduled and <NUM>) PIM may not appear in the UL channel guard bands. Another approach introduces a method where the signal envelope for each of the downlink (DL) carriers is correlated with the uplink signal envelope. However, in this approach, the PIM problems involving DL carriers that are external to the radio, such as the ones that are transmitted by the same operator in another radio band with different equipment, may go unnoticed. In addition, the PIM levels may be so low with respect to the UL noise floor that the envelope correlation may not detect any anomaly.

In another approach, a non-linear model of the PIM is generated from the transmitted DL signals. The PIM model is then correlated with the uplink channels. This approach has at least the following drawbacks.

Document <CIT> may be construed to disclose a device for removing an intermodulation signal. The device for removing an intermodulation signal comprises: a first reception band filter to perform filtering on a reception band for a reception signal from an antenna; a transmission band filter to perform filtering on a transmission band for a transmission signal to the antenna; a second reception band filter to perform filtering on a reception band for a transmission signal to the antenna; and an intermodulation signal removal module to receive an output signal of the first reception band filter, an outer signal of the second reception band filter, and a coupling signal for an output of the transmission band filter. The intermodulation signal removal module includes: an upward intermodulation signal removal block to use a coupling signal for the transmission band filter output as a first reference signal to remove an upward intermodulation signal from an output signal of the first reception band filter; and a downward intermodulation signal removal block to use an output signal of the second reception band filter as a second reference signal to generate an antiphase signal for a downward intermodulation signal.

Some embodiments advantageously provide a method and system for distortion detection with multiple antennas.

According to the disclosure, there are provided a method, a computer-readable medium, and an apparatus according to the independent claims. Further developments are set forth in the dependent claims.

There may be two time durations where <NUM>) the UL power due to wireless device (WD) traffic, interference and noise is not expected to vary, and <NUM>) a DL covariance matrix is expected to vary. The DL covariance matrix change could be due to a change in power (e.g., physical resource block (PRB) loading in 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE)), or a change in the precoder. In LTE, these two time durations could correspond to two symbols in the same transmission time interval (TTI). The DL variation could be due to the absence/presence of cell specific reference signals (CRS) in certain symbols, or the difference between the control symbols and the data symbols. The change in the UL covariance matrix is determined. The spatial structure of the matrix that represents the change in UL corresponds to the spatial structure of the PIM signal. In other words, the decomposition of this matrix will result in vectors, where each vector corresponds to the channel between the PIM source(s) and the base station antenna ports.

Some advantages of some embodiments may include one or more of the following:.

According to one aspect, a method in a network node for determining passive intermodulation, PIM, characteristics at the network node according to claim <NUM> is provided.

According to this aspect, in some embodiments, the method further includes decomposing, at least in part, the difference matrix to generate eigenvectors and eigenvalues, the eigenvectors representing a PIM subspace, each eigenvalue corresponding to a change in PIM in a direction indicated by a corresponding eigenvector. In some embodiments, the difference matrix has submatrices and the decomposing is of at least a portion of the difference matrix. In some embodiments, the portion of the difference matrix to be decomposed is determined by a comparison of elements of the difference matrix to at least one threshold. In some embodiments, the method includes averaging a plurality of difference covariance matrices. In some embodiments, of the difference matrices are weighted, at least one of the weights being based at least in part on diagonal elements of the difference covariance matrix. In some embodiments, a measurement of a signal of the signals is prescreened to determine whether the measurement is used to determine the difference covariance matrix. In some embodiments, the prescreening is based on whether a sum of diagonal elements of the difference matrix exceeds a first threshold. In some embodiments, the prescreening is based on whether a difference between a sum of diagonal elements of the first covariance matrix and a sum of diagonal elements of the second covariance matrix exceeds a second threshold. In some embodiments, the prescreening is based on whether a sum of diagonal elements of the first and second covariance matrices does not exceed a third threshold.

According to another aspect, an apparatus configured to determine passive intermodulation, PIM, characteristics at the network node according to claim <NUM> is provided.

According to this aspect, in some embodiments, the processing circuitry <NUM> is further configured to decompose, at least in part, the difference matrix to generate eigenvectors and eigenvalues, the eigenvectors representing a PIM subspace, each eigenvalue corresponding to a change in PIM in a direction indicated by a corresponding eigenvector. In some embodiments, the difference matrix has submatrices and decomposing is of at least a portion of the difference matrix. In some embodiments, the portion of the difference matrix to be decomposed is determined by a comparison of elements of the difference matrix to at least one threshold. the processing circuitry is further configured to average a plurality of difference matrices. averages of the difference matrices are weighted, at least one of the weights being based at least in part on diagonal elements of the difference covariance matrix. a measurement of a signal of the signals is prescreened to determine whether the measurement is used to determine the difference matrix. the prescreening is based on whether a sum of diagonal elements of the difference matrix exceeds a first threshold. the prescreening is based on whether a difference between a sum of diagonal elements of the first covariance matrix and a sum of diagonal elements of the second covariance matrix exceeds a second threshold. In some embodiments, the prescreening is based on whether a sum of diagonal elements of the first and second covariance matrices does not exceed a third threshold.

Before describing in detail exemplary embodiments, it is noted that the embodiments reside primarily in combinations of apparatus components and processing steps related to distortion detection with multiple antennas. 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.

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.

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

It can be any kind of a radio network node which may comprise any of base station, radio base station, base transceiver station, base station controller, network controller, RNC, evolved Node B (eNB), Node B, gNB, Multi-cell/multicast Coordination Entity (MCE), relay node, access point, radio access point, Remote Radio Unit (RRU) Remote Radio Head (RRH).

Note that although terminology from one particular wireless system, such as, for example, 3GPP LTE and/or New Radio (NR) (also known as "<NUM>"), may be used in this disclosure, this should not be seen as limiting the scope of the disclosure to only the aforementioned system.

A method in a network node and an apparatus for determining passive intermodulation (PIM) characteristics at the network node are provided. According to one aspect, a method may include capturing signals from each of at least one antenna port at a first time and a second time. The method includes determining a first covariance matrix based on signals captured at the first time. The method also includes determining a second covariance matrix based on signals captured at the second time. The method further includes determining a difference matrix, the difference matrix being based on a difference between the first and second covariance matrices, the difference matrix corresponding to changes in PIM between the first time and the second time. As used herein, the term "time," e.g., first time and second time, can refer to an instantaneous point in time or a time interval.

Referring now to the drawing figures, in which like elements are referred to by like reference numerals, there is shown in <FIG> a schematic diagram of a communication system <NUM>, according to an embodiment, such as a 3GPP-type cellular network that may support standards such as LTE and/or NR (<NUM>), which comprises an access network <NUM>, such as a radio access network, and a core network <NUM>. The access network <NUM> comprises a plurality of network nodes 16a, 16b, 16c (referred to collectively as network nodes <NUM>), 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 <NUM>). Each network node 16a, 16b, 16c is connectable to the core network <NUM> over a wired or wireless connection <NUM>. A first wireless device (WD) 22a located in coverage area 18a is configured to wirelessly connect to, or be paged by, the corresponding network node 16c. A second WD 22b in coverage area 18b is wirelessly connectable to the corresponding network node 16a. While a plurality of WDs 22a, 22b (collectively referred to as wireless devices <NUM>) are illustrated in this example, the disclosed embodiments are equally applicable to a situation where a sole WD is in the coverage area or where a sole WD is connecting to the corresponding network node <NUM>. Note that although only two WDs <NUM> and three network nodes <NUM> are shown for convenience, the communication system may include many more WDs <NUM> and network nodes <NUM>.

A network node <NUM> is configured to include a PIM unit <NUM> which is configured to determine a difference matrix, the difference matrix being based on a difference between first and second covariance matrices, the difference matrix corresponding to changes in PIM between the first time and the second time.

The communication system <NUM> includes a network node <NUM> provided in a communication system <NUM> and including hardware <NUM> enabling it to communicate with the WD <NUM>. The hardware <NUM> may include a radio interface <NUM> for setting up and maintaining at least a wireless connection <NUM> with a WD <NUM> located in a coverage area <NUM> served by the network node <NUM>.

Thus, the network node <NUM> further has software <NUM> stored internally in, for example, memory <NUM>, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the network node <NUM> via an external connection. The processing circuitry <NUM> 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 <NUM>. Processor <NUM> corresponds to one or more processors <NUM> for performing network node <NUM> functions described herein. The memory <NUM> is configured to store data, programmatic software code and/or other information described herein. In some embodiments, the software <NUM> may include instructions that, when executed by the processor <NUM> and/or processing circuitry <NUM>, causes the processor <NUM> and/or processing circuitry <NUM> to perform the processes described herein with respect to network node <NUM>. For example, processing circuitry <NUM> of the network node <NUM> may include PIM unit <NUM> configured to process a difference matrix corresponding to PIM changes over time.

The client application <NUM> may be operable to provide a service to a human or non-human user via the WD <NUM>.

The processing circuitry <NUM> 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 WD <NUM>. The processor <NUM> corresponds to one or more processors <NUM> for performing WD <NUM> functions described herein. The WD <NUM> includes memory <NUM> that is configured to store data, programmatic software code and/or other information described herein. In some embodiments, the software <NUM> and/or the client application <NUM> may include instructions that, when executed by the processor <NUM> and/or processing circuitry <NUM>, causes the processor <NUM> and/or processing circuitry <NUM> to perform the processes described herein with respect to WD <NUM>.

In some embodiments, the inner workings of the network node <NUM> and WD <NUM> may be as shown in <FIG> and independently, the surrounding network topology may be that of <FIG>.

More precisely, the teachings of some of these embodiments may improve the data rate, latency, and/or power consumption and thereby provide benefits such as reduced user waiting time, relaxed restriction on file size, better responsiveness, extended battery lifetime, etc. In some embodiments, a measurement procedure may be provided for the purpose of monitoring data rate, latency and other factors on which the one or more embodiments improve.

Although <FIG> and <FIG> show various "units" such as PIM unit <NUM> 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.

<FIG> is a flowchart of an exemplary process in a network node <NUM> for determining PIM characteristics at the network node <NUM>. One or more blocks described herein may be performed by one or more elements of network node <NUM> such as by one or more of processing circuitry <NUM> (including the PIM unit <NUM>), processor <NUM>, and/or radio interface <NUM>. Network node <NUM> such as via processing circuitry <NUM> and/or processor <NUM> and/or radio interface <NUM> is configured to capture signals from each of at least one antenna port at a first time and a second time (Block S100). The process also includes determining a first covariance matrix based on signals captured at the first time and also includes determining a second covariance matrix based on signals captured at the second time (Block S102). The process further includes determining a difference matrix, the difference matrix being based on a difference between the first and second covariance matrices, the difference matrix corresponding to changes in PIM between the first time and the second time (Block S104).

<FIG> is a flowchart of an alternative exemplary process that may be performed by the processing circuitry <NUM>, and more particularly with the aid of the PIM unit <NUM>, according to some embodiments of the present disclosure. The process includes capturing signals from each of at least one antenna port at a first time and a second time, an antenna port being one of a physical antenna port and a logical antenna port (Block S106). The process includes determining a first covariance matrix based on signals captured at the first time (Block S108). The process also includes determining a second covariance matrix based on signals captured at the second time, the first and second covariance matrices comprising correlation terms, each correlation term being based at least in part on an expected value of a product of signals received from two antenna ports (Block S110). The process further includes determining a difference matrix, the difference matrix being based on a difference between the first and second covariance matrices, the difference matrix corresponding to changes in PIM between the first time and the second time (Block S112). The process also includes decomposing at least part of the difference matrix to generate eigenvectors and eigenvalues, the eigenvectors representing a PIM subspace, each eigenvalue corresponding to a change in PIM in a direction indicated by a corresponding eigenvector (Block S114).

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 distortion detection with multiple antennas.

In some embodiments, with reference to <FIG>, the following steps may be performed by, for example, processing circuitry <NUM>, including PIM unit <NUM> in some embodiments, and/or by other processing circuitry separate from the network node <NUM>.

<FIG> shows an embodiment where the two time periods are chosen from a set of time periods that is greater than <NUM>. The measured data (Block S126) (DL and/or UL) can be used to choose the two time periods, by ensuring that the DL (or UL) power variation exceeds a certain threshold between the two symbols. The predetermined trigger (Block S <NUM>) may still be used to ensure that the set of time periods captured is not expected to have a variation in UL power due to desired WD <NUM> traffic and interference. Optionally, a downlink metric such as covariance or power may be calculated (Block S <NUM>), which serves as a basis for choosing the first and the second intervals (Block S <NUM>). Then, UL covariance matrices are obtained from the captured data (Block S <NUM>). To do this, there may be a waiting period between the first and the second time intervals (Block S <NUM>). The difference between the UL covariance matrices is calculated (Block S138) and processed (Block S140). Note that the trigger for data capture (Block S <NUM>) may be predetermined and may be based on physical layer characteristics. Note also that if DL capture is available prior to uplink captures, then it could also be used as input to UL data capture (to only capture first and second symbols). The result of the step of choosing first and second time intervals (Block S132) may be input to step S136, in the event it is desirable to calculate the UL covariance for all time periods.

<FIG> shows an example embodiment where the processing by the processing circuitry <NUM> is performed for subsets of the antenna ports (where each subset is an antenna group). Note that some or all of this processing and the processing described below may be performed by the PIM unit <NUM> of processor <NUM>. In other words, in some embodiments, the processor <NUM> may be configured, such as by software, firmware, etc., to in all or part, perform the functions herein ascribed to the PIM unit <NUM>. The new function could be input to any of the vertically stacked blocks. It may reduce the processing of all the following blocks where data/processing is split into subsets. A function that identifies antenna groups (Block S <NUM>) may be based on the difference matrix discussed above or based on information from some other PIM related function that is running, such as PIM detection, PIM mitigation, etc. In Step S144, the UL covariance based on captured data is calculated for each antenna group. To do this, there may be a waiting period between first and the second time intervals (Block S <NUM>). The difference between the UL covariance matrices is calculated for each antenna group (Block S148) and processed for each antenna group (Block S150). The processing of each antenna group (Block S <NUM>) may include matrix decomposition to determine the spatial properties of PIM sources for each antenna group. The processing may include identifying which antenna ports are impacted by the PIM for each antenna group. These ports may be ordered from most impacted to least impacted. The processing may include identifying and/or refining the antenna groups.

Note that the capture of data from which the covariance matrices are obtained may be captured near an antenna. The remaining steps of the methods described herein may be performed away from the antenna and away from the network node as desired or needed. For example, the difference covariance matrix calculation and decomposition can be remote from the antennas. As another example, the decomposition could be moved to another location away from the antennas. In this example, the difference covariance matrices can be sent from near the antennas to the remote location.

Thus, appropriate time periods are chosen such that the only variation in power across the <NUM> UL periods is due to a change in PIM power - which is due to a change in the amount of power hitting the PIM source. The change in UL covariance matrix between the time periods is determined, and the properties of this 'difference' matrix are used to identify the spatial properties of the PIM source(s).

According to one aspect, a method in a network node <NUM> for determining passive intermodulation, PIM, characteristics at the network node <NUM> is provided. The method includes capturing signals from each of at least one antenna port at a first time and a second time. The method also includes determining a first covariance matrix based on signals captured at the first time. Further, the method includes determining a second covariance matrix based on signals captured at the second time. Yet further, the method includes determining a difference matrix, the difference matrix being based on a difference between the first and second covariance matrices, the difference matrix corresponding to changes in PIM between the first time and the second time.

According to another aspect, an apparatus is configured to determine passive intermodulation, PIM, characteristics at the network node <NUM>. The apparatus includes processing circuitry <NUM> configured to capture signals from each of at least one antenna port at a first time and a second time. The processing circuitry <NUM> is further configured to determine a first covariance matrix based on signals captured at the first time. The processing circuitry <NUM> is configured to determine a second covariance matrix based on signals captured at the second time. The processing circuitry <NUM> is further configured to determine a difference matrix, the difference matrix being based on a difference between the first and second covariance matrices, the difference matrix corresponding to changes in PIM between the first time and the second time.

According to yet another aspect, a method in a network node <NUM> for determining passive intermodulation, PIM, characteristics at the network node <NUM> is provided. The method includes capturing signals from each of at least one antenna port at a first time and a second time, an antenna port being one of a physical antenna port and a logical antenna port. The method also includes determining a first covariance matrix based on signals captured at the first time. The method also includes determining a second covariance matrix based on signals captured at the second time, the first and second covariance matrices comprising correlation terms, each correlation term being based at least in part on an expected value of a product of signals received from two antenna ports. The method further includes determining a difference matrix, the difference matrix being based on a difference between the first and second covariance matrices, the difference matrix corresponding to changes in PIM between the first time and the second time. The method further includes decomposing at least part of the difference matrix to generate eigenvectors and eigenvalues, the eigenvectors representing a PIM subspace, each eigenvalue corresponding to a change in PIM in a direction indicated by a corresponding eigenvector.

Claim 1:
A method for determining passive intermodulation, PIM, characteristics at a network node (<NUM>), the method comprising:
capturing (S100, S106, S116, S126) signals from each of a plurality of antenna ports at a first time period and a second time period, wherein between the first and second time periods, (i) a downlink, DL, covariance matrix is to change and (ii) a first and a second uplink, UL, covariance matrix are expected not to change with respect to one another for the components of UL transmit covariance that are due to wireless device, WD, UL traffic, WD interference and noise;
determining (S102, S108, S118, S134, S144) the first UL covariance matrix based on signals captured at the first time period;
determining (S102, S110, S120, S136, S146) the second UL covariance matrix based on signals captured at the second time period; and
determining (S104, S112, S122, S138, S148) a difference matrix, the difference matrix being based on a difference between the first and second UL covariance matrices, the difference matrix corresponding to changes in PIM between the first time period and the second time period.