ULTRA-WIDEBAND INTERFERER DETECTION USING SPECTRAL PROCESSING

Techniques for identifying ultra-wideband interferers in a wireless communication network are disclosed. These techniques include scanning a plurality of channels relating to a wireless communication network and generating one or more spectrograms based on the scanning. The techniques further include identifying an ultra-wideband interferer for the wireless communication network, using the one or more spectrograms, including: analyzing, using the one or more spectrograms, at least one of: (i) power variations relating one or more channels, (ii) power slopes between one or more pairs of channels, (iii) a power level for one or more channels, (iv) carrier leakage, or (v) a period of pulse transmissions.

TECHNICAL FIELD

Embodiments presented in this disclosure generally relate to wireless communication. More specifically, embodiments disclosed herein relate to detecting ultra-wideband interferers in a wireless communication network.

BACKGROUND

The use of 6 GHz spectrum for wireless communication (e.g., for WiFi) gives rise to many new potentially interfering devices. This can include ultra-wideband (UWB) devices (e.g., operating in UWB channel 5). For example, many devices operate using channel 5 to locate UWB tags. If these devices are located near a wireless access point (AP), or another component of a wireless communication network, they can create significant interference and degrade network performance. The UBW interfering devices, however, are very difficult to detect using existing techniques.

DESCRIPTION OF EXAMPLE EMBODIMENTS

Overview

Embodiments include a method. The method includes scanning a plurality of channels relating to a wireless communication network. The method further includes generating one or more spectrograms based on the scanning. The method further includes identifying an ultra-wideband interferer for the wireless communication network, using the one or more spectrograms, including: analyzing, using the one or more spectrograms, at least one of: (i) power variations relating one or more channels, (ii) power slopes between one or more pairs of channels, (iii) a power level for one or more channels, (iv) carrier leakage, or (v) a period of pulse transmissions.

Embodiments further include a system, including a processor and a memory having instructions stored thereon which, when executed on the processor, performs operations. The operations include scanning a plurality of channels relating to a wireless communication network. The operations further include generating one or more spectrograms based on the scanning. The operations further include identifying an ultra-wideband interferer for the wireless communication network, using the one or more spectrograms, including: analyzing, using the one or more spectrograms, at least one of: (i) power variations relating one or more channels, (ii) power slopes between one or more pairs of channels, (iii) a power level for one or more channels, (iv) carrier leakage, or (v) a period of pulse transmissions.

Embodiments further include a non-transitory computer-readable medium having instructions stored thereon which, when executed by a processor, performs operations. The operations include scanning a plurality of channels relating to a wireless communication network. The operations further include generating one or more spectrograms based on the scanning. The operations further include identifying an ultra-wideband interferer for the wireless communication network, using the one or more spectrograms, including: analyzing, using the one or more spectrograms, at least one of: (i) power variations relating one or more channels, (ii) power slopes between one or more pairs of channels, (iii) a power level for one or more channels, (iv) carrier leakage, or (v) a period of pulse transmissions.

EXAMPLE EMBODIMENTS

In an embodiment, spectral processing can be used to identify UWB interferers for 6 GHz wireless networks. For example, a monitor radio can be used to scan across all 160 MHz 6 GHz channels, capturing spectrograms describing the wireless radio environment. These spectrograms can include multiple fast Fourier transform (FFT) outputs, over time, spaced at a certain period.

The captured spectrograms can then be used to detect UWB interferers, and the wireless network can be configured to avoid the UWB interferers and improve performance. For example, scanning can be separately done for each 160 MHz channel and the automatic gain control (AGC) gain can be different from one capture to the next.

The captured spectrograms can then be analyzed for the max or average power seen across the spectrograms for each 160 MHz channel. An UWB interferer present on channel 5, for example, will have one or more of the following key characteristics: (1) Flat power across 160 MHz channels 65, 97, 129, (2) A significant increase in power between 160 MHz channel 1 and 160 MHz channel 33, (3) A significant decrease in power between 160 MHz channel 161 and 160 MHz channel 193, (4) Low power in channel 1 and 193, (5) Detectible carrier leakage at 6489 MHz, and (6) a repetitive on period that is a multiple of 1 ms. The presence of these characteristics can indicate that an UWB signal is interfering on channel 5, and the wireless network can be configured to improve performance by avoiding the interferer. For example, a wireless local area network (WLAN) controller (WLC) can configure a WiFi network for a number of APs to avoid the UWB interferer. Channel 5 is merely one example, and one or more of the techniques discussed below can be applied to any suitable band and channel.

FIG.1illustrates a computing environment100for UWB interferer detection using spectral processing, according to one embodiment. The computing environment100includes a WLC120associated with a number of APs110A-N. For example, the WLC120can be used to control the APs110A-N. Each of the APs110A-N can be respectively associated with one or more wireless stations (STAs)102A-N. The STAs102A-N can include any suitable wireless devices, including computers, smartphones, tablets, wearable devices, Internet of Things (IOT) devices, APs, and any other suitable wireless device.

In an embodiment, the computing environment100further includes an UWB interferer130. For example, one or more the APs110A-N can support a WiFi network using the 6 GHz band. The UWB interferer130can transmit using UWB channel 5, creating interference in the 6 GHz band. As discussed further below with regard toFIGS.3-4, one or more of the APs110A-N, the WLC120, or any other suitable component of the computing environment100can detect the UWB interferer130. For example, as illustrated inFIG.2below, any of the APs110A-N, the WLC120, or both, can include an UWB detection service configured to facilitate detecting UWB interferers using spectral processing. The WLC120, or another suitable network component, can then configure the wireless communication network to avoid interference with the UWB interferer130and improve performance.

In an embodiment, the various components of the computing environment100communicate using one or more suitable communication networks, including the Internet, a wide area network, a local area network, or a cellular network, and uses any suitable wired or wireless communication technique (e.g., WiFi or cellular communication). Further, in an embodiment, the WLC120can be implemented using any suitable combination of physical compute systems, cloud compute nodes and storage locations, or any other suitable implementation. For example, the WLC120could be implemented using a respective server or cluster of servers.

FIG.2illustrates an AP and a controller for UWB interferer detection using spectral processing, according to one embodiment. An AP200includes a processor202, a memory210, and network components220. In an embodiment, the AP200corresponds with any of the APs110A-N illustrated inFIG.1. The processor202generally retrieves and executes programming instructions stored in the memory210. The processor202is representative of a single central processing unit (CPU), multiple CPUs, a single CPU having multiple processing cores, graphics processing units (GPUs) having multiple execution paths, and the like.

The network components220include the components necessary for the AP200to interface with a communication network, as discussed above in relation toFIG.1. For example, the network components220can include wired, WiFi, or cellular network interface components and associated software. Although the memory210is shown as a single entity, the memory210may include one or more memory devices having blocks of memory associated with physical addresses, such as random access memory (RAM), read only memory (ROM), flash memory, or other types of volatile and/or non-volatile memory.

The memory210generally includes program code for performing various functions related to use of the AP200. The program code is generally described as various functional “applications” or “modules” within the memory210, although alternate implementations may have different functions and/or combinations of functions. Within the memory210, the UWB detection service212facilitates detecting UWB interferers. This is discussed further, below, with regard toFIGS.3-5.

The controller250includes a processor252, a memory260, and network components270. In an embodiment, the controller250corresponds with the WLC120illustrated inFIG.1. Alternatively, the controller250corresponds with any other suitable controller in a wireless communication network (e.g., a WiFi network). The processor252generally retrieves and executes programming instructions stored in the memory260. The processor252is representative of a single CPU, multiple CPUs, a single CPU having multiple processing cores, graphics processing units (GPUs) having multiple execution paths, and the like.

The network components270include the components necessary for the controller250to interface with a communication network, as discussed above in relation toFIG.1. For example, the network components270can include wired, WiFi, or cellular network interface components and associated software. Although the memory260is shown as a single entity, the memory260may include one or more memory devices having blocks of memory associated with physical addresses, such as random access memory (RAM), read only memory (ROM), flash memory, or other types of volatile and/or non-volatile memory.

The memory260generally includes program code for performing various functions related to use of the controller250. The program code is generally described as various functional “applications” or “modules” within the memory260, although alternate implementations may have different functions and/or combinations of functions. Within the memory260, the UWB detection service262facilitates detecting UWB interferers. This is discussed further, below, with regard toFIGS.3-5. As illustrated inFIG.2, any suitable component in a wireless communication network can facilitate detecting UWB interferes, including an AP, a WLC, or any other suitable component.

While the AP200and controller250are each illustrated as a single entity, in an embodiment, the various components can be implemented using any suitable combination of physical compute systems, cloud compute nodes and storage locations, or any other suitable implementation. For example, the AP200, the controller250, or both could be implemented using a server or cluster of servers. As another example, the AP200, the controller250, or both, can be implemented using a combination of compute nodes and storage locations in a suitable cloud environment. For example, one or more of the components of the AP200, the controller250, or both, can be implemented using a public cloud, a private cloud, a hybrid cloud, or any other suitable implementation.

AlthoughFIG.2depicts the UWB detection service212as being located in the memory210and the UWB detection service262as being located in the memory260, that representation is also merely provided as an illustration for clarity. More generally, the AP200, the controller250, or both, or both, may include one or more computing platforms, such as computer servers for example, which may be co-located, or may form an interactively linked but distributed system, such as a cloud-based system, for instance. As a result, the processors202and252, and the memories210and260, may correspond to distributed processor and memory resources within the computing environment100. Thus, it is to be understood that the UWB detection services212and262may be stored at any suitable location within the distributed memory resources of the computing environment100.

FIG.3is a flowchart300illustrating an interactive third-party enabled interference classification platform, according to one embodiment. At block302, a UWB detection service (e.g., either, or both, of the UWB detection services212or262illustrated inFIG.2) scans 6 GHz channels. In an embodiment, a monitor radio scans across 160 MHz 6 GHz channels (e.g., across all channels). In an embodiment, the monitor radio is incorporated into an AP (e.g., one of the APs110A-N illustrated inFIG.1). Alternatively, or in addition, the monitor radio is a stand-alone radio device used to scan 6 GHz channels, or is incorporated into any suitable device in the wireless communication network.

FIGS.3-5illustrate use of 160 MHz channels. But this is merely one example. Alternatively, the UWB detection service can scan across channels of any suitable width (e.g., 80 MHz channels or any other suitable channel width). In an embodiment, the specific detection characteristics (e.g., discussed below with regard to block306andFIG.4) vary based on the channel width.

At block304, the UWB detection service generates spectrograms. In an embodiment, the spectrograms relate to multiple FFT outputs, over time, spaced at a specified period.FIG.5, below, illustrates one example of a spectrogram used to identify UWB interferes.

At block306, the UWB detection service identifies UWB interferers. This is discussed further, below, with regard toFIG.4. For example, the UWB detection service can identify UWB interferes using one or more key characteristics: (1) power variation (e.g., across 160 MHz channels 65, 97, 129), (2) power slope (e.g., between 160 MHz channel 1 and 160 MHz channel 33 and between 160 MHz channel 161 and 193), (4) total power (e.g., in channel 1 and 193), (5) carrier leakage (e.g., power before the signal turns on at 6489 MHz on FFT samples), and (6) timestamps for the start of on pulses and the period of on transmissions.

At block308, the UWB detection service configures a wireless network to avoid interferers (e.g., UWB interferers identified at block306). For example, the UWB detection service can report characteristics of the UWB interferer to a WLC. These characteristics can include channels, duty cycle, severity, or any other suitable characteristics. The WLC, or any other suitable network component, can modify radio operation based on the characteristics. For example, the WLC can instruct APs to stop using the identified channel, or to make using that channel less likely. This is merely an example.

Alternatively, or in addition, the UWB detection service could report the characteristics of the UWB interferer to the STAs (e.g., the STAs102A-N illustrated inFIG.1). The STAs can then modify their own operation to improve network performance by avoiding the UWB interferer.

FIG.4is a flowchart identifying UWB interferers using spectral processing, according to one embodiment. In an embodiment,FIG.4corresponds with block306illustrated inFIG.3. At block402, a UWB detection service (e.g., either, or both, of the UWB detection services212or262illustrated inFIG.2) identifies power variations. In an embodiment, the UWB detection service determines whether a spectrogram reflects flat power across designated channels (e.g., 160 MHz channels 65, 97, and 129). For example, the UWB detection service can determine whether a max-min power across channels 65, 97, and 129 is less than a threshold value. The threshold value can be defined prior to operation (e.g., by a developer), can be defined by a system administrator (e.g., using a suitable user interface), or can be defined dynamically using a suitable technique.

At block404, the UWB detection service identifies power slopes. In an embodiment, the UWB detection service determines whether there has been a sufficient increase in power between channels (e.g., between 160 MHz channels 1 and 33). Further, the UWB detection service determines whether there has been a sufficient decrease in power between other channels (e.g., between 160 MHz channels 161 and 193). For example, the UWB detection service can determine whether the median slope across 160 MHz channels 1 to 33 exceeds a minimum slope value. As another example, the UWB detection service can determine whether the median slope across channels 161 to 193 is less than a minimum negative slope value.

At block406, the UWB detection service identifies channel power. In an embodiment, the UWB detection service identifies whether power is low in specific channels (e.g., 160 MHz channels 1 and 193). For example, the UWB detection service can determine whether the median power in channels 1 and 193 is below a threshold maximum power value.

At block408, the UWB detection service identifies carrier leakage. In an embodiment, the UWB detection service identifies power in FFT samples to identify carrier leakage (e.g., at 6489 MHz). For example, the UWB detection service can determine whether the power at 6489 MHz is greater than the power at other frequencies near 6489 MHz for FFT samples where the power is lower than a specified threshold value.

At block410, the UWB detection service analyzes the period of on pulse transmissions. In an embodiment, the UWB detection service identifies a repetitive on-period (e.g., that is a multiple of 1 ms). For example, the UWB detection service can identify repetition of FFT samples where the power has a period that is at least a minimum duration and at most a maximum duration.

At block412, the UWB detection service determines whether criteria have been met. In an embodiment, the UWB detection service determines whether all of the criteria described above for block402-410are met. If all criteria are met, the UWB detection service proceeds to block414and detects a UWB interferer. If any of the criteria are not met, the UWB detection service proceeds to block416and detects that there is not a UWB interferer.

This is merely an example. Alternatively, the UWB detection service can detect a UWB when some, but not all, of the criteria described for block402-10are met. For example, one or more of the criteria can be given additional weight compared to other criteria. If a sufficient total weight of criteria is met, the UWB detection service proceeds to block414and detects a UWB interferer. If not, the UWB detection service proceeds to block416and detects that there is not a UWB interferer.

FIG.5illustrates an example spectral analysis500for an UWB interferer, according to one embodiment. In an embodiment, the spectral analysis500includes a UWB packet spectrum510and another UWB packet spectrum520. The UWB packet spectrums510and520each illustrated a received signal strength indication (RSSI) across the y-axis and a frequency (e.g., in MHz) across the x-axis. In an embodiment, the UWB packet spectrums510and520reflect an average (e.g., a median) of time-domain samples. Further, in an embodiment, the UWB packet spectrum520reflects samples next to the inter-frame space between UWB pulses. As discussed below, this can be used to identify carrier.

In an embodiment, the signal portion512indicates a signal across 500 MHz of bandwidth with a center of 6489 MHz. For example, this can be used to determine power variations for block402illustrated inFIG.4. The signal portions514indicate the up and down slopes as a 500 MHz signal at 6489 MHz is approached. For example, this can be used to determine power slopes for block404illustrated inFIG.4.

The signal portions516indicate lower power in low and high channels, respectively, accompanied with reduced levels of AGC gain (e.g., indicating that there is off-channel signal). For example, this can be used to determine channel power at block406illustrated inFIG.4. The signal portion522indicates carrier leakage at 6489 MHz. For example, this can be used to determine power in FFT samples at block408illustrated inFIG.4.