Detecting and mitigating radio frequency anomalies

Abstract

Methods, systems, and devices for wireless communications are described. A system may include a set of gateways configured to receive respective gateway signals. The system may include a spectrum analysis system configured to generate respective subsets of spectrum data based on the respective gateway signals. The system may include an anomaly detector configured to generate anomaly data in accordance with respective received radio frequency power information. The system may include a channel assignment manager configured to assign, for each of a set of satellite beams, respective sets of channels to frequencies within a respective beam bandwidth of each of the satellite beams in accordance with the anomaly data. The system may include one or more modems configured to communicate one or more messages between the set of gateways and a set of user terminals via the satellite beams.

Description

DETECTING AND MITIGATING RADIO FREQUENCY ANOMALIESCROSS REFERENCE

[0001] The present Application for Patent claims priority to U.S. Provisional Patent Application No. 63 / 645,387 by Martins de Moraes et al., entitled “SYSTEMS AND METHODS FOR DETECTING AND MITIGATING RF ANOMALIES,” filed May 10, 2024, which is assigned to the assignee hereof, and which is expressly incorporated by reference in its entirety herein.BACKGROUND

[0002] The following relates generally to communications, including detecting and mitigating radio frequency anomalies.

[0003] Wired and wireless communications systems are widely deployed to provide various types of communication content such as voice, video, packet data, messaging, broadcast, and so on. Some communications systems may be used in the context of secure communications, such as tactical communications. In addition, some communication systems may experience interference from various sources including hostile jamming intended to disrupt communication signaling. Such communications systems may be subject to various constraints and challenges.SUMMARY

[0004] The described techniques relate to improved methods, systems, devices, and apparatuses that support detecting and mitigating radio frequency anomalies. For example, the described techniques provide for a system for wireless communications. The system may include a set of gateways. Each gateway of the set of gateways may support a respective subset of satellite beams and may be configured to receive respective gateway signals. Each respective gateway signal may correspond to a respective portion of an RF band. The system may include a spectrum analysis system coupled with the set of gateways. The spectrum analysis system may be or may include a set of spectrum processors that analyze a spectrum of a received signal and provide received RF power information regarding received signal power across the spectrum. In some cases, the spectrum analysis system may perform one or more reduction procedures. The spectrum analysis system may be configured to generate respective subsets of spectrum data based on the respective gateway signals. Each respective subset of spectrum data may indicate respective received RF power informationcorresponding to the respective portion of the RF band. The system may include one or more satellite modem termination systems (SMTSs) in communication with the set of gateways. The one or more SMTSs may allocate, for each of the satellite beams, respective subsets of resources of respective sets of channels for communication between the set of gateways and a set of user terminals via the satellite beams.

[0005] The system may include an anomaly detector in communication with the spectrum analysis system. The anomaly detector may be configured to generate anomaly data in accordance with the respective received RF power information. The anomaly data may be associated with a set of spectrum data including the respective subsets of spectrum data. The anomaly detector may generate the anomaly data based on applying one or more anomaly detection models on the set of spectrum data. The system may include a channel assignment manager in communication with the anomaly detector and the one or more SMTSs. The channel assignment manager may be configured to assign, for each of the satellite beams, the respective sets of channels to frequencies within a respective beam bandwidth of each of the satellite beams. The channel assignment manager may assign each respective set of channels to a subset of frequencies in accordance with the anomaly data. The system may include one or more modems in communication with the set of gateways. The one or more modems may be configured to communicate one or more messages between the set of gateways and the set of user terminals via the satellite beams using the respective subsets of resources of the respective sets of channels.

[0006] Further, the described techniques provide for a method by a system for wireless communications. The method may include receiving, by a plurality of gateways, respective gateway signals, each gateway of the plurality of gateways supporting a respective subset of a plurality of satellite beams. Each respective gateway signal corresponds to a respective portion of a radio frequency band. Further, the method may include generating, by a spectrum analysis system coupled with the plurality of gateways, respective subsets of spectrum data based at least in part on the respective gateway signals. Each respective subset of spectrum data indicates respective received radio frequency power information corresponding to the respective portion of the radio frequency band. The method may include allocating, by one or more satellite modem termination systems in communication with the plurality of gateways, for each of the plurality of satellite beams, respective subsets of resources of respective sets of channels for communication between the plurality of gateways and a plurality of user terminals via the plurality of satellite beams. The method may include generating, by ananomaly detector in communication with the spectrum analysis system and configured to generate, in accordance with the respective received radio frequency power information, anomaly data associated with a set of spectrum data comprising the respective subsets of spectrum data based at least in part on applying one or more anomaly detection models on the set of spectrum data. The method may include assigning, by a channel assignment manager in communication with the anomaly detector and the one or more satellite modem termination systems, for each of the plurality of satellite beams, the respective sets of channels to frequencies within a respective beam bandwidth of each of the plurality of satellite beams in accordance with the anomaly data. Further, the method may include communicating, by one or more modems in communication with the plurality of gateways, one or more messages between the plurality of gateways and the plurality of user terminals via the plurality of satellite beams using the respective subsets of resources of the respective sets of channels.BRIEF DESCRIPTION OF THE DRAWINGS

[0007] FIG. 1 shows an example of a satellite communication system that supports detecting and mitigating radio frequency (RF) anomalies in accordance with examples described herein.

[0008] FIG. 2 shows an example of a system that supports detecting and mitigating RF anomalies in accordance with aspects of the present disclosure.

[0009] FIG. 3 shows an example of a spectrum data diagram that supports detecting and mitigating RF anomalies in accordance with aspects of the present disclosure.

[0010] FIG. 4 shows an example of a channel assignment diagram that supports detecting and mitigating RF anomalies in accordance with aspects of the present disclosure.

[0011] FIG. 5 shows a diagram of a system including a device that supports detecting and mitigating RF anomalies in accordance with aspects of the present disclosure.

[0012] FIG. 6 shows a flowchart illustrating methods that support detecting and mitigating RF anomalies in accordance with aspects of the present disclosure.DETAILED DESCRIPTION

[0013] In some satellite communication systems, one or more devices may experience interference such as radio frequency (RF) jamming. For example, wireless communications systems used for secure communications, such as for tactical communications between military entities, may be subject to interference or attempts to jam the communicationchannels. Such communications may be expected to provide a high level of robustness to external tampering, a high level of reliability, and so on. In some instances, especially in military applications, a hostile jammer may transmit a strong signal in order to degrade communications. In some cases, devices within a wireless communications system may be subject to one or more attacks (e.g., denial of service attacks) based on intentional or malicious interference with RF signals by broadcasting a high-power signal on a same set of frequencies as a target signal (e.g., blocking or disrupting the target’s ability to communicate). Such interference may be referred to as RF anomalies. RF anomalies may include interference resulting from jamming, (e.g., interference attacks), communication by one or more other entities (e.g., unlicensed users), other sources of RF signal power (e.g., RF leakage or backscattering), or any combination thereof.

[0014] As described herein, a system may support detecting and mitigating RF anomalies (e.g., preventing negative effects of detected interference). The system may include one or more entities (e.g., components) to support anomaly detection and channel assignment in accordance with detected anomaly data (e.g., in accordance with environmental factors or metrics, such as interference levels associated with one or more frequencies). For example, the system may include a set of gateways. Each gateway of the set of gateways may support a respective subset of satellite beams and may be configured to receive respective gateway signals. Each respective gateway signal may correspond to a respective portion of an RF band, and may correspond to one or more satellite beams. In some cases, the system may include a spectrum analysis system coupled with the set of gateways. In some examples, the spectrum analysis system may be or may include a set of spectrum processors (e.g., spectrum analyzers) that analyze a spectrum of a received signal and provide received RF power information. The spectrum processors may perform one or more reduction procedures such as decimation or down sampling. The spectrum analysis system may be configured to generate respective subsets of spectrum data (e.g., quantized data) based on the respective gateway signals (e.g., by applying decimation). Each respective subset of spectrum data may indicate respective received RF power information corresponding to the respective portion of the RF band. Further, the system may include one or more satellite modem termination systems (SMTSs) in communication with the set of gateways. The one or more SMTSs may allocate, for each of the satellite beams, respective subsets of resources of respective sets of channels for communication between the set of gateways and a set of user terminals via the satellite beams.

[0015] In some implementations, the system may include an anomaly detector in communication with the spectrum analysis system. The anomaly detector may be configured to generate anomaly data in accordance with the respective received RF power information. The anomaly data may be associated with a set of spectrum data including the respective subsets of spectrum data. In some cases, the anomaly detector may generate the anomaly data based on applying one or more anomaly detection models on the set of spectrum data. Additionally, or alternatively, the system may include a channel assignment manager in communication with the anomaly detector and the one or more SMTSs. The channel assignment manager may be configured to assign, for each of the satellite beams, the respective sets of channels to frequencies within a respective beam bandwidth of each of the satellite beams. The channel assignment manager may assign each respective set of channels to a subset of frequencies in accordance with the anomaly data. The system may include one or more modems in communication with the set of gateways. The one or more modems may be configured to communicate one or more messages between the set of gateways and the set of user terminals via the satellite beams using the respective subsets of resources of the respective sets of channels (e.g., in accordance with the channel assignment and the anomaly data as described herein). Accordingly, techniques described herein may support a system that assigns (e.g., allocates) channels to frequencies according to anomaly data recorded at the system, which may allow the system to support wireless communications (e.g., despite interference from attacks or otherwise).

[0016] Aspects of the disclosure are initially described in the context of satellite communication systems. Aspects of the disclosure are then described in the context of systems and a spectrum data diagram. Aspects of the disclosure are further illustrated by and described with reference to apparatus diagrams, system diagrams, block diagrams, and flowcharts that relate to detecting and mitigating RF anomalies.

[0017] FIG. 1 shows an example of a satellite communication system 100 that supports detecting and mitigating RF anomalies in accordance with examples described herein. The satellite communication system 100 includes a device 105 and a device 110 that may be capable of wireless communication via one or more wireless communication links (e.g., satellite beams, tactical data links), via a satellite 115, or a combination thereof. For example, on a forward link the device 110 may transmit signaling 145 (e.g., forward uplink) to the satellite 115. In some cases, the satellite 115 may transmit (e.g., relay) signaling 150 (e.g., forward downlink) to the device 105. In some examples, signaling 150 may be a relayedversion of signaling 145. In some implementations, the satellite 115 may perform up- conversion (e.g., converting signaling to a higher frequency band), down-conversion (e.g., converting signaling to a lower frequency band), or both, to generate the signaling 150 based on the signaling 145. For example, an uplink satellite beam servicing the device 110 may have a first frequency range and a downlink satellite beam servicing the device 105 may have a second frequency range. The satellite 115 may up-convert the signaling 145 (if the second frequency range is higher than the first frequency range) or may down-convert the signaling 145 (if the second frequency range is lower than the first frequency range) to generate the signaling 150. The satellite 115 may perform similar operations to up-convert or downconvert signaling 120 to generate signaling 125 on the return link. The satellite communication system 100 may include a single satellite 115 that may support the satellite beams for user terminals, or may include multiple satellites 115, in some cases. The satellite(s) 115 may be in any appropriate orbits such as geostationary earth orbit (GEO), medium earth orbit (MEO), or low earth orbit (LEO), or combinations thereof.

[0018] In some implementations, the satellite communication system 100 may support communication from the device 110 to the device 105 and vice versa (e.g., via the satellite 115). For example, the device 110 may transmit signaling 145 (e.g., forward uplink) to the satellite 115, and the satellite 115 may transmit (e.g., relay) signaling 150 (e.g., forward downlink) to the device 105. Device 105 and device 110 may include electronic and wireless communication devices such as a handheld device carried by a user, a satellite, or may be located in a vehicle such as an aircraft, a tank, a ship, or other type of vehicle. Wireless communication links as described herein may support secure communication between device 105 and device 110 and may include anti -jamming capabilities. Anti -jamming may refer to reducing or cancelling the impact of an interference or jamming signal. A jamming signal may be any signal that interferes with the reception of a desired signal.

[0019] For example, a device 130 may transmit one or more jamming signals 135 to disrupt communications for one or more devices (e.g., device 105 and device 110). A device 130 may be a handheld device carried by a user, may be located in a vehicle such as aircraft, tank, ship or other type of vehicle, a satellite, or may be a stationary device such as a radio antenna. The one or more jamming signals 135 may be relatively strong signals that are transmitted to intentionally interfere with successful communications between device 105 and device 110. In other examples, the one or more jamming signals 135 may include one or more interference signals transmitted without intent to jam communications of the device 105 andthe device 110 (e.g., a relatively strong communication signal used by other devices, or some other source of RF noise). In some cases, the device 130 may transmit the one or more jamming signals 135 (e.g., a jamming signal 135-a, a jamming signal 135-b, and a jamming signal 135-c), which may disrupt or interfere with communications at device 105, device 110, satellite 115, or any combination thereof. In some examples, a same jamming signal may interfere with communications at device 105, device 110, and satellite 115 (e.g., jamming signal 135-a, jamming signal 135-b, and jamming signal 135-c may be a same jamming signal emitted from the device 130).

[0020] In some implementations, device 105 may be or may include one or more user terminals and device 110 may be or may include one or more gateways. The device 110 (e.g., the one or more gateways) may communicate with a network device 140, and the network device 140 may support communication between the device 110 and the device 105 via the satellite 115. The device 110 may include a spectrum processor in communication with the network device 140. The network device 140 may include an anomaly detector 230 and a channel assignment manager 240. In some cases, device 110 may communicate with an SMTS controller in communication with one or more SMTS servers. For example, the device 110 may receive one or more channel assignments (e.g., allocations), as allocated by the one or more SMTS servers, from the SMTS controller. The channel assignment manager 240 may be in communication with the SMTS controller.

[0021] The device 105 may include communication equipment (e.g., one or more modems) that provides communication services for one or more onboard devices via the one or more modems. The communication equipment may have Concurrent Multi-Net (CMN) or Concurrent Contention Receive (CCR) capability, which are examples of tactical data link capabilities. The communication equipment may support one or more examples of CMN or CCR such as CMN-4 or CCR-4. The onboard devices may be mobile or other devices within the device 105 and may use a wired or a wireless connection (a wireless connection may be, for example, of a wireless local area network (WLAN) technology such as IEEE 802.11 (WiFi), or other wireless communication technology). The onboard device may be related to mobility of the device 105 or to a mission of the device 105, for example.

[0022] The communication equipment may also include circuits and / or one or more processors for processing (e.g., performing frequency conversion, modulating / demodulating, multiplexing / demultiplexing, filtering, forwarding, and so on) RF communication signals (e.g., signals over wireless communication links). Such circuits and / or processors may beincluded in an antenna communication assembly, which may be mounted internally or externally to a body or fuselage of the vehicle or aircraft represented by device 105. Additionally, or alternatively, the transceiver may include circuits and / or processors for performing various RF signal operations (e.g., receiving, performing frequency conversion, modulating, demodulating, multiplexing, demultiplexing, and so on).

[0023] Techniques described herein may support detecting interference of a satellite system and performing one or more mitigation or remediation methods described herein (e.g., rather than performing manual or time intensive processes). In some implementations, systems and methods described herein may provide one or more users (e.g., analysts, operators) with data for performing investigations. Some implementations may support generating alerts for RF anomalies. Additionally, or alternatively, implementations described herein may provide capability for automating the one or more mitigation or remediation methods described herein. In some cases, these techniques may support curating an RF threat intelligence dataset and detection capability set which other entities may subscribe to through one or more digital platforms (e.g., a computer, server, or other device used by one or more users). In some implementations, the techniques described herein may decrease the time to defend against interference, to protect a network, and to support a customer’s connectivity.

[0024] Some wireless communications systems may support a first detection model that can be used to detect anomalies (e.g., environmental metrics, interference, or the like). In some cases, the first detection model may provide data for multiple consumers (e.g., for different applications). From the perspective of a monitoring device, the first detection model may continuously run on multiple beams. In some cases, the first detection model may output data (e.g., anomaly data) to an application (e.g., one or more third party applications). The application may be integrated with a digital platform for one or more use cases. For example, the application may alert end users of one or more characteristics associated with RF interference (e.g., alerting end users to RF interference). Additionally, or alternatively, the application may provide a historical look-back on one or more interference patterns (e.g., a history of spectrum information indicating interference patterns).

[0025] In some cases, one or more architectures described herein may support such an application. For example, techniques described herein may support creating a specific serverless code execution service that sends messages to a digital platform or service. In some cases, the serverless code execution service may be executed on a cloud platform (e.g., Amazon Web Services (AWS), Google Cloud Platform (GCP)). For example, the serverlesscode execution service may be implemented as a Lambda function on AWS. Additionally, or alternatively, the techniques described herein may allow the digital platform or service to listen to a relevant message bus stream (e.g., message bus stream output by the serverless code execution service). The digital platform or service may then relay information associated with the stream to one or more appropriate users via one or more messages. In some cases, techniques described herein may provide, for the digital platform or service, an ability to query an events table for past detections (e.g., a history of interference or anomaly information) or an ability to query another table that contains information associated with interference patterns (e.g., spectrum information that indicates interference patterns).

[0026] Some implementations described herein may separate an engine that coordinates pulling raw data and pushing the results from one or more detection models (e.g., a model ‘A’ and a model ‘B’). However, a detection model may use a relatively large amount of data (e.g., 10 minutes of recorded full RF spectrum) for detecting anomaly data. Accordingly, it may be less advantageous to separate the detection model into a separate system or machine. Thus, in some implementations, a network device may support an abstraction inside a same program to allow a “local” model to run and may also allow potential future external models (e.g., a model ‘C’ and a model ‘D’). In some cases, a network device (or one or more other devices described herein) may perform one or more procedures based on the one or more detection models (e.g., in coordination with an engine). For example, the network device may identify one or more frequencies that are experiencing interference (e.g., on a per-beam basis).Accordingly, the network device may identify one or more times (e.g., durations) during which there is no interference (or interference below a threshold). In some cases, the network device may determine which frequencies are available for use at a particular time (or duration) for a particular beam. Additionally, or alternatively, the network device may identify whether one or more particular frequencies are routinely being interfered with (e.g., whether interference associated with a particular frequency exceeds a threshold interference level for a threshold duration or for a threshold quantity of measurements).

[0027] Some wireless communications systems may be vulnerable to RF jamming, which may include an attack (e.g., a denial of service attack) based on intentional or malicious interference with RF signals. For example, an attacking device (e.g., the device 130) may broadcast a high-power signal on one or more frequencies that overlap with a target signal transmitted by the device 105, received by the device 110, or both. The high-power signal may block or disrupt the ability of a target device (e.g., the device 105, the device 110) tocommunicate. The device 130 may perform jamming according to one or more jammer device techniques. For example, constant jammers may transmit a continuous high-power noise sweeping from one channel to another (e.g., following a fixed strategy and repeating this process over time). Deceptive jammers may send illegitimate packets through one or more wireless channels to keep the wireless channels busy. Random jammers may operate randomly and may not follow a specific strategy (e.g., when jumping from one channel to another). Reactive jammers may continuously monitor a state of one or more frequency channels and may attempt to target channels that are used for communication (e.g., based on monitoring the state). Techniques described herein may mitigate the effects of these jammer device techniques.

[0028] One or more devices described herein (e.g., the device 110, the network device 140) may support various algorithms and techniques to detect RF interference using a spectrum analyzer (e.g., an anomaly detector, a spectrum analysis system). Examples of such algorithms and techniques may include frequency hopping (e.g., rapidly switching between frequencies), manual tuning (e.g., setting thresholds for selected metrics based on empirical observations), fuzzy logic, artificial intelligence (Al), machine learning (ML), game theory, channel surfing, mapping jammed region, and timing channels.

[0029] The one or more devices may support peak detection or threshold-based techniques for mitigating interference or jamming (e.g., using a spectrum analyzer). For example, the one or more devices may identify and flag peaks or spikes in a frequency spectrum that exceed a predefined threshold. These peaks may indicate a presence of interfering signals or transmissions. The one or more devices may set a predefined threshold for one or more signal features (e.g., signal power or frequency). In some cases, the one or more devices may be configured with the predefined threshold. Accordingly, the one or more devices may trigger an alert when a value (e.g., associated with a frequency within the analyzed spectrum) satisfies the predefined threshold. Peak detection or threshold-based techniques may have one or more limitations (e.g., frequent false positives, unadaptable). Additionally, or alternatively, the one or more devices may support adaptive thresholding. For example, instead of using a fixed threshold, the one or more devices may use an adaptive thresholding algorithm that dynamically adjusts a threshold based on a measured noise floor (or one or more other parameters). Adaptive thresholding may help the one or more devices to distinguish interference from legitimate signals in varying environments.

[0030] In some implementations, the one or more devices may support a spectral mask algorithm for detecting interference. For example, the one or more devices may use a predefined spectral mask (or reference spectrum) as a template for expected signal characteristics within a measured spectrum). Deviations or violations of the spectral mask may be flagged as potential interference. In some cases, the one or more devices may support a frequency hopping spread spectrum (FHSS) technique. For example, one or more devices may support one or more algorithms specifically designed to detect one or more frequency hopping signals (which may be commonly used in spread-spectrum systems). In accordance with these algorithms, the one or more devices may seek (e.g., monitor for) patterns or signatures of frequency hopping in the spectrum. In some examples, the one or more devices may rapidly switch channel frequencies (e.g., to avoid interference from frequency hopping). However, such techniques may have one or more limitations (e.g., requiring significant control and wider bandwidth, and a chosen hop sequence may be detected by a jamming device).

[0031] In some implementations, the one or more devices may support a correlation and matched filtering technique for mitigating interference. Such a technique may involve correlating a received signal with a known reference signal or using matched filters to detect a presence of specific signal patterns or modulation types. In some cases, the one or more devices may support a spectrogram (e.g., waterfall) analysis technique. For example, the one or more devices may use a spectrogram which displays a frequency content of a signal over time. The device may analyze the spectrogram using one or more image processing and pattern recognition algorithms to identify interference patterns or signatures. In some examples, the one or more devices may support a timing channels technique, which may include purposely introducing a time delay into a transmitted signal. However, such delays may increase synchronization issues.

[0032] In some implementations, the one or more devices may support a signal classification technique for mitigating interference. For example, the one or more devices may implement one or more machine learning algorithms (e.g., support vector machines (SVMs) or neural networks). The one or more machine learning algorithms may be trained to classify and identify different types of signals (including interference) based on one or more spectral characteristics. Additionally, or alternatively, the one or more devices may support one or more hybrid approaches for mitigating interference. For example, in many practicalscenarios, a combination of multiple algorithms and techniques described herein may be employed to improve accuracy and reliability of interference detection.

[0033] The satellite communication system 100 may be or may support a system for detecting and mitigating RF anomalies. The system may be formed of the device 105, the device 110, the satellite 115, one or more user devices, one or more servers, or any combination thereof. For example, the system may include a set of gateways. Each gateway of the set of gateways may support a respective subset of satellite beams and may be configured to receive respective gateway signals. Each respective gateway signal may correspond to a respective portion of an RF band. In some cases, the system may include a spectrum analysis system coupled with the set of gateways. In some examples, the spectrum analysis system may be or may include a set of spectrum processors (e.g., spectrum analyzers) that analyze a spectrum of a received signal and provide received RF power information. The set of spectrum processors may perform one or more reduction procedures such as decimation or down sampling. Decimation may include converting an RF signal power across a relatively broad spectrum (e.g., multiple gigahertz of one or more RF bands) into quantized data according to a particular granularity across the spectrum. For example, the spectrum analysis system may generate a particular quantity of bits to represent an RF signal power for each frequency of a set of frequencies within the spectrum. The spectrum analysis system may be configured to generate respective subsets of spectrum data (e.g., quantized data) based on the respective gateway signals (e.g., by performing decimation). Each respective subset of spectrum data may indicate respective received RF power information corresponding to the respective portion of the RF band. Further, the system may include one or more SMTSs in communication with the set of gateways. The one or more SMTSs may allocate, for each of the satellite beams, respective subsets of resources of respective sets of channels for communication between the set of gateways and a set of user terminals via the satellite beams.

[0034] In some implementations, the system may include the anomaly detector 230 in communication with the spectrum analysis system. The anomaly detector 230 may be configured to generate anomaly data in accordance with the respective received RF power information. The anomaly data may be associated with a set of spectrum data including the respective subsets of spectrum data. In some cases, the anomaly detector 230 may generate the anomaly data based on applying one or more anomaly detection models on the set of spectrum data. Additionally, or alternatively, the system may include a channel assignmentmanager 240 in communication with the anomaly detector 230 and the one or more SMTSs. The channel assignment manager 240 may be configured to assign, for each of the satellite beams, the respective sets of channels to frequencies within a respective beam bandwidth of each of the satellite beams. The channel assignment manager 240 may assign each respective set of channels to a subset of frequencies in accordance with the anomaly data. The system may include one or more modems in communication with the set of gateways. The one or more modems may be configured to communicate one or more messages between the set of gateways and the set of user terminals via the satellite beams using the respective subsets of resources of the respective sets of channels (e.g., in accordance with the channel assignment and the anomaly data as described herein). Accordingly, techniques described herein may support a system that assigns (e.g., allocates) channels to frequencies according to anomaly data recorded at the system, which may allow the system to support wireless communications (e.g., despite interference from attacks or otherwise).

[0035] FIG. 2 shows an example of a system 200 that supports detecting and mitigating RF anomalies in accordance with aspects of the present disclosure. The system 200 may implement or be implemented by one or more aspects described with reference to FIG. 1. For example, the device 105, the device 110, and the satellite 115 may include one or more components of the system 200 and may perform one or more functions using the one or more components. The system 200 may include one or more gateways 205 that provide a means for communication between a network device and one or more user terminals 220 (e.g., within the system 200) served by one or more satellites 115-a. The one or more user terminals 220 may be served via one or more satellite beams 224.

[0036] The system 200 may include one or more modems 215 in communication with a spectrum analysis system 210. For example, each of the one or more gateways 205 may include one or more modems 215, which may decode data from gateway signals 265, and encode data for transmission to the one or more user terminals 220 via the one or more satellites 115-a. The one or more modems 215 may be coupled with respective antenna systems of the one or more gateways 205. The spectrum analysis system 210 may include one or more spectrum processors 225 (e.g., spectrum analyzers) that may support processing spectrum information (e.g., digital information representative of a spectrum for communication) according to one or more schemes (e.g., down sampling, decimation, or the like). For example, the one or more spectrum processors 225 (e.g., at least one spectrum processor at each gateway) may down sample the spectrum information for more practicalprocessing by one or more other components of the system 200. In some cases, the spectrum analysis system 210 may store the spectrum information (e.g., spectrum data 212) in one or more data storage units 227 of the system via a forwarding unit (e.g., a decimator forwarder). The spectrum analysis system 210 may be coupled with the one or more modems 215, or to the respective antenna systems of the one or more gateways 205 (e.g., via one or more couplers or splitters).

[0037] The system may include a data storage manager 226 to manage the one or more data storage units 227. For example, the data storage manager 226 may be configured to store anomaly data associated with the spectrum information for a threshold duration. The anomaly data may include one or more interference patterns associated with the spectrum information (e.g., set of spectrum data). In some implementations, a media management service may pull spectrum data (e.g., structured spectrum data) associated with a particular beam and time duration (e.g., as specified by a user) for viewing by a user.

[0038] The system 200 may include an anomaly detector 230 capable of detecting anomalies (e.g., interference, environmental metrics associated with spectrum data) based on the spectrum data 212 from the spectrum analysis system 210. The system 200 may include a channel assignment manager 240 capable of assigning one or more channels to frequencies based on anomaly data output from the anomaly detector 230. Additionally, or alternatively, the system 200 may include an SMTS controller 250 in communication with one or more SMTSs 260 (e.g., SMTS servers), the spectrum analysis system 210, the one or more gateways 205, the channel assignment manager 240, or any combination thereof. The one or more SMTSs 260 may allocate resources (e.g., time and frequency resources) for communication between the one or more gateways 205 and the one or more user terminals 220.

[0039] Each gateway of the one or more gateways 205 may support a respective subset of satellite beams and may be configured to receive respective gateway signals 265. Each respective gateway signal 265 may correspond to a respective portion of an RF band. The spectrum analysis system 210 may be or may include the one or more spectrum processors 225 (e.g., spectrum analyzers). The one or more spectrum processors may receive a respective gateway signal 265 via a gateway antenna (e.g., via an RF coupling to the RF signal from an antenna of a respective gateway of the one or more gateways 205). In some cases, the one or more spectrum processors 225 may perform one or more procedures to reduce spectrum data (e.g., decimation, down sampling). The spectrum analysis system 210 may be configured togenerate respective subsets of spectrum data based on the respective gateway signals. Each respective subset of spectrum data may indicate respective received RF power information corresponding to the respective portion of the RF band.

[0040] In some implementations, a forward uplink and a return uplink may operate in a same frequency range (e.g., 30 GHz-40 GHz). Additionally, or alternatively, a return downlink and a forward downlink may operate in a non-overlapping frequency range (e.g., 20 GHz-30 GHz). The system 200 (e.g., satellite system) may use any suitable bandwidth for each beam (e.g., 500 MHz, 1 GHz, 2 GHz, 3.5 GHz, and so on). Accordingly, in one example, a gateway receive beam (e.g., corresponding to a return downlink signal) may include multiple service beams each spanning a first frequency range (e.g., 1 GHz each). Thus, the return downlink signal may include a total frequency range spanning each of the multiple service beams (e.g., 4 GHz of spectrum representing 4 service beams). In some cases, the total frequency range may be translated (e.g., up-converted or down-converted) from one or more uplink beam frequency ranges (e.g., by satellite 115-a). The spectrum analysis system 210 may attribute power observed at one or more frequencies (e.g., 25 GHz) to other frequencies (e.g., 35 GHz), for example, because interference present on a return uplink signal is translated (e.g., by satellite 115-a) to a return downlink signal (e.g., assuming that interference is more likely to be present in one or more uplink beams instead of one or more downlink beams at the gateways). Thus, the spectrum data output by spectrum analysis system 210 may be frequency translated based on the up-conversion or down-conversion performed at the satellite 115-a (e.g., the spectrum analysis system 210 may translate the signal power in the received frequency range of the return downlink signals to the frequency range of the return uplink signals). In some cases, the satellite 115-a, or multiple satellites, may have different frequency translation, and thus the spectrum analysis system 210 may perform the frequency translation taking into account individual up-conversion or downconversion between return uplink signals and return downlink signals. For example, a gateway 205 may receive a return downlink signal having a bandwidth of 2 GHz that represents four return uplink signals, each having 0.5 GHz bandwidth and downconverted by respective downconversion frequency offsets. The spectrum analysis system 210 may attribute signal power in the return downlink signal to the respective frequency ranges of the four return uplink signals by applying the inverse of the respective downconversion frequency offsets.

[0041] In some implementations, spectrum data may be aggregated from multiple spectrum processors 225 (e.g., by the spectrum analysis system 210). Each spectrum processor 225 of the multiple spectrum processors 225 may detect a different frequency range (e.g., because the gateways may support different subsets of service beams). In accordance with these different detected frequency ranges, the spectrum analysis system 210 may determine which regions of the detected frequency spectrum (e.g., the aggregated frequency spectrum) correspond to one or more beams. In some examples, the spectrum analysis system 210 may perform a frequency translation (if applicable). Then, the spectrum analysis system 210 may combine the different frequency ranges, which may overlap, partially overlap, or may be disparate (e.g., based on an averaging scheme or another function for combining frequency range information).

[0042] The one or more SMTSs 260 may allocate, for each of the satellite beams, respective subsets of resources of respective sets of channels for communication between the set of gateways and a set of user terminals via the satellite beams. In some implementations, the SMTS controller 250 may control (e.g., manage) the one or more SMTSs 260 according to one or more configurations. For example, the SMTS controller 250 may facilitate communication between the spectrum analysis system 210, the channel assignment manager 240, and the one or more SMTSs 260. Additionally, or alternatively, the one or more SMTSs 260 may communicate directly with the spectrum analysis system 210 and the channel assignment manager 240.

[0043] The SMTS controller 250 may include an SMTS agent 252 (including a validator), a controller 254, a web server 256, and an alert component 258. The SMTS agent 252 may handle communications with the one or more SMTSs 260. For example, the SMTS agent 252 may receive one or more status indications from the SMTSs 260 (e.g., resource and availability indications). Further, the SMTS agent 252 may transmit one or more new return carrier group (RCG) commands to the one or more SMTSs 260 based on information generated by one or more components as described herein. For example, the SMTS agent 252 may retrieve one or more SMTS commands (e.g., status indications) and one or more committed RCG configurations from the one or more data storage units. As described herein, the term “RCG configuration” (e.g., return carrier group configuration) may refer to a configuration of parameters (e.g., position of channels within a beam bandwidth) associated with all legitimate carriers that may be obtained from the one or more SMTSs 260.

[0044] The controller 254 may store (e.g., write) a last RCG configuration in the one or more data storage units, and may similarly load (e.g., read) the last RCG configuration from the one or more data storage units. Additionally, or alternatively, the web server 256 may receive one or more RCG configurations (e.g., signed RCG configurations) from a load balancer entity. The load balancer entity may receive the one or more RCG configurations from a topic (e.g., the one or more RCG configurations may be pushed to message bus stream from the channel assignment manager 240). In some cases, the web server 256 may receive one or more commands (e.g., curl commands, fetch status commands, enable or disable commands) from one or more users (e.g., the one or more user terminals 220) via the load balancer entity. In some examples, the alert component 258 may output one or more alerts to one or more users (e.g., the one or more user terminals 220) via one or more alerting services. The one or more alerts may be based on the one or more SMTS status commands, the one or more committed RCG configurations, one or more indications from the controller 254, or any combination thereof. The one or more alerts may include indications of spectrum status information, resource information, SMTS availability information, or any combination thereof.

[0045] In some implementations, the anomaly detector 230 may be configured to generate anomaly data in accordance with the respective received RF power information. The anomaly data may be associated with a set of spectrum data including the respective subsets of spectrum data. In some cases, the anomaly detector 230 may generate the anomaly data based on applying one or more anomaly detection models on the set of spectrum data. As described herein, the term “anomaly data” (e.g., anomaly detection data) may refer to one or more classifications (e.g., based on indications or measurements of spectrum data) of anomalous behavior corresponding to one or more particular frequencies. The term “anomaly detector” may refer to a system that identifies unexpected signals (e.g., signals having interference above a configured threshold) within one or more monitored frequencies. In some cases, the set of spectrum data may be represented according to one or more visualization schemes, as illustrated and described with reference to FIG. 3. In any case, the anomaly detector 230 may be configured to generate the anomaly data based on the set of spectrum data (e.g., whether or not the set of spectrum data is in a particular format).

[0046] In some implementations, the anomaly detector 230 may operate according to a timing trigger 232 (e.g., a cron trigger operating according to a periodicity). Accordingly, the anomaly detector 230 may perform one or more anomaly detection operations according to aconfigured period. At 234 (e.g., in response to an indication from the timing trigger 232), the anomaly detector 230 may fetch (e.g., retrieve, obtain) the set of spectrum data (e.g., including the respective subsets of spectrum data) from the one or more data storage units (e.g., as stored by the spectrum analysis system 210). In some cases, the anomaly detector 230 may fetch one or more committed RCG configurations. At 236, the anomaly detector 230 may call one or more anomaly detection models to generate the anomaly data (e.g., based on the one or more committed RCG configurations). At 238, the anomaly detector 230 may write one or more results (e.g., the anomaly data) to the one or more data storage units of the system. In some examples, the anomaly detector 230 may use one or more queues during the anomaly detection process. For example, the anomaly detector 230 may store the set of spectrum data in a data queue to prepare for calling the one or more anomaly detection models on the spectrum data. Additionally, or alternatively, the anomaly detector 230 may store the anomaly data in a results queue prior to writing the one or more results to the one or more data storage units of the system.

[0047] In some cases, the one or more anomaly detection models may include a threshold model, a bit error rate (BER) aware model, a channel-aware model, or any combination thereof. A channel-aware model may be an anomaly detection model that is based on interference (e.g., anomalies) detected with respect to one or more channels. For example, in accordance with the channel-aware model, the anomaly detector 230 may determine an interference level (e.g., an anomaly level) associated with each channel of a set of channels (e.g., channels previously assigned by channel assignment manager 240), and may determine which channels correspond to an interference level higher than other channels (or a power level exceeding an expected power level or a threshold power level). Accordingly, the anomaly detector 230 may output (to the channel assignment manager 240) an indication of anomalies associated with each channel. In some cases, the anomaly detector 230 may be configured to determine a minimum power value and a maximum power value based on the respective received RF power information associated with each respective subset of spectrum data. The minimum power value and the maximum power value may correspond to each respective subset of spectrum data. The anomaly detector 230 may generate the anomaly data associated with the set of spectrum data based on a difference between the minimum power value and the maximum power value satisfying a threshold. For example, the anomaly detector 230 may determine that a particular frequency is associated with an anomaly if a difference between the minimum power value and the maximum power value associated withthe frequency exceeds the threshold. In some cases, the anomaly detector 230 may determine that one or more frequencies are associated with anomalies if a power over time is relatively constant for the one or more frequencies (since actual signals may be observed to start and stop over a duration and may have a larger minimum-to-maximum differential). Additionally, or alternatively, the anomaly detector 230 may be configured to generate the anomaly data associated with the set of spectrum data based on the minimum power value satisfying a second threshold, the maximum power value satisfying a third threshold, or both.

[0048] In some implementations, the anomaly detector 230 may be configured to generate correlation data based on the respective received RF power information associated with each respective subset of spectrum data. The correlation data may indicate a respective correlation value between each pair of frequencies within the RF band. For example, the correlation data may be represented along an x-y plane (e.g., or another data storage or representation technique for mapping at least two parameters), where each pair of frequencies within the RF band is shown as a value at an (x, y) coordinate of the x-y plane (e.g., for visualization purposes). In some cases, the anomaly detector 230 may generate the anomaly data such that the anomaly data indicates that a set of frequencies of the RF band include one or more anomalies based on the set of frequencies being correlated in accordance with the correlation data. For example, the set of frequencies may be correlated if one or more parameters (e.g., power) associated with each of the set of frequencies are similar (e.g., indicating a common power source). Additionally, or alternatively, a high negative correlation between a set of frequencies may indicate that signals may have a same source (e.g., jamming device), but the source is switching between the set of frequencies (e.g., frequency hopping due to maximum power constraints). In some examples, the anomaly detector 230 may be configured to output the correlation data to a user interface for displaying an indication of the respective correlation values between each pair frequencies of the RF band.

[0049] The channel assignment manager 240 may be configured to assign, for each of the satellite beams, the respective sets of channels to frequencies within a respective beam bandwidth of each of the satellite beams. The channel assignment manager 240 may assign each respective set of channels to a subset of frequencies in accordance with the anomaly data (e.g., output from the anomaly detector 230).

[0050] In some implementations, the channel assignment manager 240 may operate according to a timing trigger 242 (e.g., a cron trigger). The timing trigger 242 may operate in accordance with the timing trigger 232 (e.g., according to a periodicity). In some cases, thetiming trigger 242 and the timing trigger 232 may be a same timing trigger. In any case, the channel assignment manager 240 may perform one or more channel assignment operations according to a configured period (e.g., as with the anomaly detector 230). At 244 (e.g., in response to an indication from the timing trigger 242), the channel assignment manager 240 may fetch (e.g., retrieve, obtain) the set of anomaly data (and the set of spectrum data) from the one or more data storage units (e.g., as stored by the anomaly detector 230). At 246, the channel assignment manager 240 may assign the respective sets of channels to frequencies within the respective beam bandwidth of each of the satellite beams (e.g., RCG channel assignment). At 248, the channel assignment manager 240 may write one or more results (e.g., channel assignment information, RCG configuration) to the one or more data storage units of the system. In some cases, the channel assignment manager 240 may push the one or more results to a topic (e.g., a message bus stream) and may push recommend SMTS commands for RCG changes (e.g., in accordance with the one or more results) to one or more user data management services (e.g., via an alerting service). In some examples, the channel assignment manager 240 may use one or more queues during the channel assignment process. For example, the channel assignment manager 240 may store the anomaly data in a data queue to prepare for the channel assignment process. Additionally, or alternatively, the channel assignment manager 240 may store the one or more results (e.g., channel assignment information) in a results queue prior to writing the one or more results to the one or more data storage units of the system.

[0051] In some cases, the channel assignment manager 240 may be configured to modify a channel size and channel placement for each of the respective sets of channels based on a usable communication bandwidth that is in accordance with the anomaly data. For example, the channel assignment manager 240 may determine the usable communication bandwidth based on the anomaly data (e.g., the usable communication bandwidth may include a set of frequencies that have interference below a threshold interference level). In accordance with the determined usable communication bandwidth, the channel assignment manager 240 may modify (e.g., increase or decrease) a channel size and channel placement for each of the respective sets of channels. In some examples, the channel assignment manager 240 may be configured to perform channel assignment in accordance with the anomaly data. For example, the channel assignment manager 240 may assign the respective sets of channels to a set of frequencies that excludes frequencies associated with anomalies that satisfy a threshold anomaly strength (e.g., associated with interference above a threshold interference level).

[0052] In some implementations, the channel assignment manager 240 may be configured to determine one or more environmental metrics or one or more channel metrics associated with one or more frequencies within the respective beam bandwidths of each of the set of satellite beams. The one or more environmental metrics may include an interference level. The one or more channel metrics may include a modulation and coding scheme (MCS), a BER, or both. The channel assignment manager 240 may assign the respective sets of channels to a set of frequencies that excludes the one or more frequencies based on the one or more environmental metrics or the one or more channel metrics satisfying one or more threshold values. The one or more threshold values may include a threshold interference level (e.g., in accordance with a threshold model for anomaly detection), a threshold BER (e.g., in accordance with a channel aware or BER-aware model for anomaly detection), or both. Additionally, or alternatively, the channel assignment manager 240 may be configured to assign the respective sets of channels to a set of frequencies that includes the one or more frequencies based on a performance level associated with the one or more environmental metrics satisfying a threshold performance value (e.g., if the one or more frequencies have an interference level that may not inhibit communication). In some cases, the channel assignment manager 240 may perform channel assignment based on a total available bandwidth (which may be based on an output of the anomaly detector 230). For example, if a total available bandwidth (a bandwidth without anomalies, or with anomalies below a threshold anomaly strength) is greater than a threshold bandwidth, the channel assignment manager 240 may apply one or more assignment algorithms that are non-BER aware. If the total available bandwidth is less than a threshold, the channel assignment manager 240 may apply a BER aware model or another assignment algorithm that assigns one or more channels to frequencies associated with anomalies.

[0053] In some implementations, the channel assignment manager 240 may be configured to assign a first set of channels to a first set of frequencies during a first duration in accordance with the anomaly data. In some cases, the channel assignment manager 240 may assign the first set of channels to a second set of frequencies during a second duration if the anomaly data indicates interference (e.g., above a threshold interference level) in one or more of the first set of frequencies for the first duration (e.g., for a threshold duration within the first duration).

[0054] Additionally, or alternatively, the channel assignment manager 240 may be configured to perform a periodic channel assignment procedure in accordance with a periodicspectrum polling of the spectrum analysis system and in accordance with the anomaly data. For example, the channel assignment manager 240 may assign a first set of channels to a first set of frequencies at a first instance in accordance with the anomaly data. Further, the channel assignment manager 240 may assign the first set of channels to a second set of frequencies at a second instance in accordance with the anomaly data and in accordance with the periodic channel assignment procedure (e.g., if the anomaly data indicates that the first set of frequencies exceeds a threshold interference level after a period).

[0055] In some implementations, the channel assignment manager 240 may be configured to assign a first set of channels to a first set of frequencies according to a randomized channel placement scheme. The randomized channel placement scheme may be based on one or more constraints configured at the channel assignment manager. The one or more constraints may include a configured set of frequencies, a threshold interference level, a target channel size, a target quantity of channels, or other parameters described herein. For example, the channel assignment manager 240 may assign the first set of channels to the first set of frequencies using a random scheme (e.g., using a random number generator) while also following a target set of constraints for channel assignment (e.g., placement) as described herein.

[0056] In some cases, the channel assignment manager 240 may be configured to assign a first set of channels to a first set of frequencies according to a probabilistic channel placement scheme (e.g., a probabilistic channel assignment scheme). The probabilistic channel placement scheme may be based on anomaly data generated by the anomaly detector 230 for one or more prior time periods. For example, the anomaly detector 230 may generate a quantity of anomaly data for a set of frequencies over a threshold duration (e.g., a threshold quantity of minutes, hours, or the like). The channel assignment manager 240 may use the anomaly data previously generated to assign the first set of channels to the first set of frequencies (e.g., using a predictive or probabilistic scheme for anomaly data and channel assignment).

[0057] In some implementations, data processed by the anomaly detector 230 (e.g., anomaly data output from the anomaly detection models) may include indications of which frequencies include no or relatively low interference (e.g., “good” frequencies) and which frequencies include relatively high interference (e.g., “bad” frequencies). The channel assignment manager 240 may apply one or more algorithms (e.g., placement algorithms) to determine how channels may be assigned to frequencies within an RF band (e.g., decide where to place channels) according one or more parameters or constraints specified by theone or more SMTSs 260 (e.g., SMTS rules and restrictions). For example, one or more parameters (e.g., requirements) of the one or more algorithms may come from the one or more SMTSs 260 since the one or more SMTSs 260 perform channel placement (e.g., resource allocation for channels). Accordingly, the one or more SMTSs 260 may determine one or more available sizes of channels that may be placed. In some cases, the one or more SMTSs may transmit channel information (e.g., quantity of channels or requested sizes for each channel) to the channel assignment manager 240. The channel assignment manager 240, in communication with the one or more SMTSs 260, may perform one or more algorithms of a set of various (e.g., different) algorithms to assign channels in an RF spectrum.

[0058] In some implementations, the channel assignment manager 240 may support one or more channel assignment algorithms which may be referred to as “greedy”. The term “greedy” may refer to a behavior of an algorithm that is concerned with a current step. For example, the channel assignment manager 240 may attempt to perform a best channel assignment configuration at each step (e.g., without regard to a total result of channel placement). In some cases, greedy channel assignment algorithms may have an impact (e.g., one or more drawbacks) for channel assignment. For example, such algorithms may use a fixed list of channels to be placed. There may be no optimization to improve bandwidth usage or fill remaining frequency gaps.

[0059] In some implementations, the channel assignment manager 240 may support a first channel assignment algorithm, which may be referred to as a “binary” algorithm. In accordance with the first channel assignment algorithm, the channel assignment manager 240 may interpret the anomaly data (e.g., generated by the anomaly detector 230) to be a binary set. For example, the channel assignment manager 240 may place (e.g., assign) channels on frequencies where there is no interference (or relatively low interference). If a possible placement (e.g., assignment) would result in a channel overlapping with interference, the channel assignment manager 240 may reject the possible placement. However, in some cases, interference may be widespread within an RF spectrum. For example, there may be very few frequencies with little or no interference (e.g., “safe” frequencies) which may be used. In such cases, the first channel assignment algorithm may completely remove a relatively large portion of channels, which may make a beam unusable. In any case, the system described herein may be able to handle some interference.

[0060] Accordingly, the channel assignment manager 240 may be configured to assign channels to one or more frequencies that include interference up to a threshold interferencelevel. For example, the channel assignment manager 240 may support a second channel assignment algorithm, which may be referred to as a “BER aware” algorithm. When managing signals with noise and interference, the system 200 may include one or more components (e.g., the channel assignment manager 240, the anomaly detector 230) that may calculate an effect of the noise and interference on a channel or a set of frequencies by estimating a BER. The one or more components may calculate the BER based on a quantity of errors associated with a particular frequency with respect to a quantity of information transmitted. In some cases, the BER rate may be associated with a signal to interference-plus- noise ratio (SINR) (e.g., a relationship between a total power of a signal and a total noise and interference power that overlaps the signal). Thus, instead of completely avoiding interference, the channel assignment manager 240 may calculate whether the interference would disrupt transmission on one or more particular frequencies. In some cases, if a BER associated with one or more frequencies is calculated to satisfy a BER threshold (e.g., if the BER is within acceptable limits), the channel assignment manager 240 may assign one or more channels to the one or more frequencies. Thus, the system 200 may support a more robust algorithm that resists variation in types of attacks (e.g., different types of interference or jamming). Further, the system 200 may handle beams with relatively large signal traffic. In some cases, the system 200 may support maintaining increased bandwidth usage (e.g., with a slight degradation with increased burst errors).

[0061] The one or more modems 215 may be configured to communicate one or more messages between the set of gateways and the set of user terminals via the satellite beams using the respective subsets of resources of the respective sets of channels (e.g., in accordance with the channel assignment and the anomaly data as described herein). Accordingly, techniques described herein may support a system that assigns (e.g., allocates) channels to frequencies according to anomaly data recorded at the system, which may allow the system to support wireless communications (e.g., despite interference from attacks or otherwise).

[0062] FIG. 3 shows an example of a spectrum data diagram 300 that supports detecting and mitigating RF anomalies in accordance with aspects of the present disclosure. The spectrum data diagram 300 may include a horizontal axis representing frequency and a vertical axis representing power. Accordingly, the spectrum data diagram 300 may illustrate a power level for each of a set of frequencies within an RF spectrum. The spectrum data diagram 300 may be an example of a visualization of data that may be processed by the anomaly detector 230, the channel assignment manager 240, or both, as described herein withreference to FIGs. 1 and 2. The spectrum data diagram 300 may illustrate a set of power measurements for the RF spectrum (or a portion thereof), including a power measurement 305 (e.g., a maximum power measurement, an upper-bound power measurement), a power measurement 310 (e.g., an average power measurement, a median power measurement, or a “last” power measurement), and a power measurement 315 (e.g., a minimum power measurement, a lower-bound power measurement). Each power measurement of the set of power measurements may be determined (e.g., calculated) over a duration (e.g., as specified by one or more configurations, one or more users, or both). For example, the power measurement 305 may be a maximum power measurement measured over the duration and the power measurement 315 may be a minimum power measurement measured over the duration. The spectrum data diagram 300 may illustrate a down-converted range of the RF spectrum (or a portion thereof) (e.g., shown as around 1 GHz, but may be related to a different frequency range for channel assignment).

[0063] The spectrum data diagram 300 may illustrate a threshold power level 320. The threshold power level 320 may be configured according to previously recorded data (e.g., interference previously observed), one or more predictive models, interference currently observed, or any combination thereof. In some cases, the channel assignment manager 240 (or the anomaly detector 230) may modify the threshold power level 320 based on a quantity of channels to be assigned, a target channel size, and an amount of interference over the RF spectrum. For example, the channel assignment manager 240 may select the threshold power level 320 such that the quantity of channels may be assigned according to the target channel size. In some cases, the channel assignment manager 240 may select one or more threshold power levels. For example, the one or more threshold power levels may include the threshold power level 320 and a respective threshold (e.g., maximum) power level for the power measurement 305, for the power measurement 310, for the power measurement 315, or any combination thereof (which may be represented by the threshold power level 320 or another power level, in different contexts).

[0064] The channel assignment manager 240 (or the anomaly detector 230, or both) may assign one or more channels to frequencies within the RF spectrum in accordance with a comparison between the set of power measurements and the one or more threshold power levels (e.g., as applied and described with reference to FIG. 4). For example, at 325, the channel assignment manager 240 may determine that the power measurement 305 is higher than the threshold power level 320. Further, at 330, the channel assignment manager 240 maydetermine that the power measurement 315 is lower than the threshold power level 320. In some cases, the channel assignment manager 240 may refrain from assigning channels to a set of frequencies 370 based on the power measurement 305 exceeding the threshold power level 320. Additionally, or alternatively, the channel assignment manager 240 may be configured to assign channels to frequencies at 325 based on the power measurement 315 failing to exceed the threshold power level 320. For example, the channel assignment manager 240 may assign channels to frequencies at 325 despite the power measurement 305 exceeding the threshold power level 320 (e.g., if the RF spectrum has a relatively large amount of interference such that few channels may be placed under acceptable interference levels).

[0065] In some implementations, the channel assignment manager 240 may avoid (e.g., refrain from) assigning channels to a set of one or more frequencies if interference is relatively high for a quantity of power measurements. For example, at 335, the channel assignment manager 240 may determine that the power measurement 305 is higher than the threshold power level 320. At 340, the channel assignment manager 240 may determine that the power measurement 310 is higher than the threshold power level 320. Similarly, at 345, the channel assignment manager 240 may determine that the power measurement 315 is higher than the threshold power level 320. In accordance with the power measurement 305, the power measurement 310, and the power measurement 315 exceeding the threshold power level 320, the channel assignment manager 240 may refrain from assigning channels to a set of frequencies 375.

[0066] Based on the comparison between the set of power measurements and the one or more threshold power levels, the channel assignment manager 240 may assign one or more channels to a remaining set of frequencies. In one example, the channel assignment manager 240 may assign a first set of channels to a set of frequencies 350 and a second set of channels to a set of frequencies 355 (e.g., since the set of frequencies 350 and the set of frequencies 355 are below the threshold power level 320). Additionally, or alternatively, the channel assignment manager 240 may assign a third set of channels to a set of frequencies 360 and may assign a fourth set of channels to a set of frequencies 365 (e.g., since the set of frequencies 360 and the set of frequencies 365 are at or below the threshold power level 320, despite potentially having some interference). In some cases, the channel assignment manager 240 may send an indication (e.g., to the one or more SMTSs 260) that the third set of channels and the fourth set of channels are associated with at least some interference. One or more entities (e.g., one or more users, the one or more SMTSs 260) may use the indicationwhen placing channels. For example, the one or more entities may determine to place channels associated with high-impact information where there is lower interference, and may place channels associated with lower-impact information where there is higher interference.

[0067] In some implementations, a system described herein may support one or more visual representation methods (e.g., dashboards) to present information shown in the spectrum data diagram 300. For example, the system may support a waterfall diagram showing a relationship between frequency, time, and power over a duration (e.g., time period). One or more entities (e.g., the anomaly detector 230) may identify power levels at each frequency to determine whether there are anomalies (e.g., abnormalities) at a particular frequency. In some cases, the system may support a maximum power diagram that shows a relationship between a mean (e.g., average) power and time. For example, the maximum power diagram may show a mean power across a set of frequencies over time (e.g., illustrating changes in power levels over time). Additionally, or alternatively, the system may support a third diagram type (e.g., a “min-max-lasf ’ diagram) that illustrates a relationship between frequency and power. The third diagram type may illustrate a minimum power level, a maximum power level, and a “last” power level (e.g., a most-recently measured power level) over a duration (e.g., a selected time period) for each frequency within an RF spectrum. One or more entities may identify interference trends using the third diagram type. The spectrum data diagram 300 may be an example of the third diagram type.

[0068] In some implementations, the anomaly detector 230 (or the channel assignment manager 240, or both) may use various metrics to evaluate whether a signal (e.g., associated with a frequency) is anomalous. For example, the anomaly detector 230 may calculate a mean squared error according to formula 1,where n is a quantity of samples, ytis a particular observed power level, and ytis a predicted (e.g., expected) power level. In some cases, the anomaly detector 230 may use an unsupervised metric (e.g., no labeled data) such as K-Means clustering. K-Means clustering may be used for clustering similar data points. For example, the anomaly detector 230 may group data points into k clusters based on similarities between data points. The anomaly detector 230 may iteratively calculate a distance between each data point and a centroid (e.g., center) of a cluster and may assign data points to a cluster with a closest centroid. Then, theanomaly detector 230 may update a mean of the data points in each cluster and may repeat the process until centroids stabilize.

[0069] In some implementations, the anomaly detector 230 may support a density -based spatial clustering of applications with noise (DBSCAN) algorithm. The DBSCAN algorithm may identify data points that are close together and may assign them to a same cluster. The DBSCAN algorithm may operate without a pre-specified quantity of clusters, and may identify clusters of varying shapes and sizes. In some cases, the anomaly detector 230 may support one or more statistical methods for anomaly detection, such as using Z-scores. For example, a z-score method may be used to identify outliers (e.g., anomalies) in datasets by analyzing a distribution of spectrum data. The anomaly detector 230 may calculate a distance between a data point and a mean of the data points in a set of data points (e.g., measured in standard deviations) and may flag any data points that satisfy a threshold distance (e.g., 0.75 standard deviations) from the mean.

[0070] In some implementations, the anomaly detector 230 may support feature extraction using one or more pre-trained convolutional neural networks (CNNs). For example, the anomaly detector 230 may use pre-trained CNN models (ResNet-50, VGG-16) to extract features from spectrogram images and correlation plots. An output of the one or more pre-trained CNNs may be a set of feature vectors corresponding to each image. The set of feature vectors may encode visual information for viewing spectrum data. In an unsupervised context, the anomaly detector 230 may expect normal data points (e.g., non- anomalous data points) to have feature representations that cluster together. In contrast, anomalous data points may have feature representations that significantly differ from the expected normal data points. In some cases, the anomaly detector 230 may remove a final classification layer (e.g., from the one or more pre-trained CNN models) and may simply retrieve an output after an average pooling layer. The anomaly detector 230 may use the output of the average pooling layer to determine anomalies in accordance with techniques described herein.

[0071] In some implementations, the anomaly detector 230 may perform anomaly detection according to one or more detection models. The anomaly detector 230 may support a min-max detection model. For example, the anomaly detector 230 may calculate a minimum power over time (e.g., the power measurement 315) and a maximum power over time (e.g., the power measurement 305). In response to jamming from an external device (e.g., constant jamming), the anomaly detector 230 may detect the jamming based on aminimum power level over time. For example, constant jamming may cause an increase in the power measurement 315 over time, a similar value as the power measurement 305, or both. Legitimate signals (e.g., signals based on time division multiple access (TDMA) generally fluctuate between on and off, which may result in the power measurement 315 being at a (relatively low) noise level for a particular frequency. Further, terminals may have particular settings in legitimate TDMAs, such that a transmit power may be known to the anomaly detector 230. Accordingly, the anomaly detector 230 may determine a jamming signal based on the power measurement 305 (e.g., the maximum power over time). For example, if the power measurement 305 is above a threshold, the anomaly detector 230 may detect a jamming signal that may disrupt normal service.

[0072] In some cases, the anomaly detector 230 may determine whether to calculate correlations associated with the RF spectrum (e.g., calculating which frequencies have a same or similar power). For example, constant power interferences may not be detectable based on correlations between frequencies (due to weak correlations), since there may be no variation in power over time. In such cases, the anomaly detector 230 may determine to apply a different anomaly detection method. For varying-power interferences, the anomaly detector 230 may detect interference based on calculating correlations between frequencies. The anomaly detector 230 may detect interference based on the correlation data (e.g., even small variations may be detected, both with positive and negative correlations). In some examples, high positive correlations (close to 1) may indicate that a source of the interference is likely the same and that power in these frequencies was transmitted at a same time. High negative correlations (close to -1) may indicate that corresponding signals may have a same source, but the source may be switching between these frequencies (e.g., due to maximum power constraints). In some cases, the anomaly detector 230 may rely on correlation calculation for anomaly detection even when a data sampling rate is much lower than a Nyquist rate. For example, the anomaly detector 230 may observe interference that occurs at a same time based on multiple samples (despite the sampling rate being lower than the Nyquist rate). In some examples, some legitimate TDMAs may be detected in correlation calculations. In some implementations, locations of each legitimate carrier of a set (e.g., an RCG configuration) may be obtained from the one or more SMTSs 260 (e.g., by the anomaly detector 230). Additionally, or alternatively, the anomaly detector 230 may use a method to match carriers and to remove the legitimate carriers from the anomaly detection phase.

[0073] FIG. 4 shows a channel assignment diagram 400 that supports detecting and mitigating RF anomalies in accordance with aspects of the present disclosure. The channel assignment diagram 400 includes an RF spectrum 405 (or a portion thereof) as described herein. The channel assignment diagram 400 may illustrate aspects that implement or are implemented by aspects described with reference to FIGs. 1-3. For example, a channel assignment manager 240 may perform a channel assignment procedure to assign each channel of a set of channels 420 to a respective set of frequencies (e.g., a respective frequency band).

[0074] The channel assignment manager 240 may determine that a first set of frequency ranges 410 are usable for communication based on one or more outputs from an anomaly detector 230 as described herein. For example, the first set of frequency ranges 410 may not include anomalies, or may include interference that is at or below an interference threshold. The channel assignment manager 240 may assign a set of channels 420 within the RF spectrum 405, which may, for example, be a beam bandwidth of a satellite beam. For example, the channel assignment manager 240 may assign a first channel 412-a to a first frequency range 410-a, a second channel 412-b to a second frequency range 410-b, a third channel 412-c to a third frequency range 410-c, a fourth channel 412-d to a fourth frequency range 410-d, a fifth channel 412-e to a fifth frequency range 410-e, and a sixth channel 412-f to a sixth frequency range 410-f. Similarly, the channel assignment manager 240 may determine that a second set of frequency ranges 415 are not to be used for communication. For example, the second set of frequency ranges 415 may include anomalies, or may include interference that is above an interference threshold. Accordingly, the channel assignment manager 240 may refrain from assigning channels to frequency range 415-a, frequency range 415-b, frequency range 415-c, and frequency range 415-d.

[0075] FIG. 5 shows a diagram of a communications network 500 including a network device 505 that supports detecting and mitigating RF anomalies in accordance with aspects of the present disclosure. Communications network 500 depicts a system for detecting anomalies and assigning channels to frequencies in accordance with the detected anomalies. Communications network 500 may include a network device 505 and a detector array 510. In some implementations, the detector array 510 may include one or more detectors 515. The network device may be an example of at least portions of one or more devices described herein with reference to FIG. 1 (e.g., a device 105, a device 110, a satellite 115). The network device 505 may include a channel assignment manager 520, at least one memory 530 (including code 535), at least one processor 540, a spectrum analysis system 545, and ananomaly detector 550. In some cases, the network device 505 may include the detector array 510. For example, the one or more detectors 515 may be part of or may be in communication with the spectrum analysis system 545 via connections 556 (e.g., wired or wireless connections). The one or more detectors 515 may be examples of spectrum processors (e.g., spectrum analyzers capable of decimation, down sampling, or otherwise modifying detected spectrum information for processing at the network device 505). In some cases, each gateway of a set of gateways (e.g., gateways associated with the device 105 or the device 110, gateways 205) may have a detector 515 that is coupled with an RF feed of the gateway. For example, a respective detector 515 may receive a respective RF feed (e.g., one or more RF signals) for communication at each gateway.

[0076] At least a portion of communications network 500 may be located within a ground system of communications network 500 (e.g., a ground system associated with the device 110 as described with reference to FIG. 1). A portion of communications network 500 that is not in the ground system may be located within a space segment of communications network 500 (e.g., in a satellite system). For example, detector array 510, channel assignment manager 520, spectrum analysis system 545, processor 540, and memory 530 may be included in a space segment of communications network 500. In another example, detector array 510 and spectrum analysis system 545 may be included in a space segment of communications network 500, while channel assignment manager 520, processor 540, and memory 530, may be included in the ground segment of communications network 500. In yet another example, channel assignment manager 520, spectrum analysis system 545, processor 540, memory 530, and a first detector array 510 may be included within the ground segment and a second detector array 510 (e.g., including one or more of detectors 515) may be included within the space segment. In some cases, the detector array 510 may be an example of the spectrum processors 225 of FIG. 2, and may include one or more detectors 515.

[0077] Bus 525 may represent an interface over which signals may be exchanged between components of network device 505 and a location (e.g., a central location) that may be used to distribute the signals to the processing components of communications network 500 (e.g., channel assignment manager 520, anomaly detector 550, spectrum analysis system 545). Bus 525 may include one or more wired interfaces. Additionally, or alternatively, bus 525 may be a wireless interface that is used to wirelessly communicate signaling between the processing components — e.g., in accordance with a communication protocol. The spectrum analysissystem 545 may be coupled with the one or more detectors 515 via one or more wired or wireless interfaces.

[0078] The memory 530 may include volatile memory (e.g., RAM) and / or non-volatile memory (e.g., ROM). Other types of memory may also be possible. The memory 530 may store code 535 that is computer-readable and computer-executable. The code may include instructions that, when executed by the processor 540, cause the communications network 500 to perform various functions described herein. The code 535 may be stored in a non- transitory computer-readable medium such as system memory or another type of memory. In some cases, the code 535 may not be directly executable by the processor 540 but may cause a computer (e.g., when compiled and executed) to perform functions described herein. In some cases, the memory 530 may contain, among other things, a BIOS which may control basic hardware or software operation such as the interaction with peripheral components or devices.

[0079] Processor 540 may include an intelligent hardware device (e.g., a general-purpose processor, a DSP, a CPU, a microcontroller, an ASIC, a field programmable gate array (FPGA), a PLD, a graphics processing unit (GPU), a discrete gate or transistor logic component, a discrete hardware component, or any combination thereof). The processor 540 may be configured to execute computer-readable instructions stored in a memory (e.g., memory 530) to cause the network device 505 to perform various functions (e.g., functions or tasks supporting detecting and mitigating RF anomalies). For example, the communications network 500 or a component of the communications network 500 may include a processor 540 and memory 530 coupled with the processor 540 that are configured to perform various functions described herein.

[0080] Spectrum analysis system 545 may be configured to process (e.g., demodulate, decode) signaling information received from the one or more detectors 515. In some cases, the one or more detectors 515 may generate the signaling information based on signaling received by one or more antenna elements associated with the network device 505 or gateways (e.g., gateways associated with the device 110, gateways 205) coupled with the network device 505. The spectrum analysis system 545, the one or more detectors 515, or both may generate spectrum information 552 for processing by the network device 505. For example, the spectrum information 552 may include information representative of the signaling information received by the one or more detectors 515, but may be modified (e.g., down sampled, decimated, adjusted to a lower frequency spectrum) for processing bycomponents of the network device 505. For example, the spectrum analysis system 545 may adjust a frequency spectrum based on a frequency translation performed by a satellite (e.g., the satellite 115) between uplink and downlink signals, as described above. In some examples, the satellite may include a separate detector that can detect spectrum information (including interference or anomaly information). The satellite may transmit the spectrum information (along with translation information related to translation of the spectrum information at the satellite) to the network device 505. In accordance with the spectrum information and the translation information, the spectrum analysis system 545 may adjust the frequency spectrum (e.g., the spectrum information) for processing by one or more other components of the network device 505.

[0081] Anomaly detector 550 may be configured to process the spectrum information 552 received from spectrum analysis system 545. Anomaly detector 550 may generate anomaly data 554 based on the spectrum information 552 according to one or more models as described herein with reference to FIG. 2. Anomaly detector 550 may also be configured to transfer the anomaly data 554 to one or more components of the network device 505 (e.g., to the channel assignment manager 520). In some cases, the anomaly detector 550 may transfer the anomaly data 554 to the one or more components of the network device 505 according to a periodicity (e.g., configured at the network device 505). In accordance with the periodicity, one or more components of the network device 505 may perform operations (e.g., anomaly detection, channel assignment) to support communication at the network device 505 while mitigating effects of interference.

[0082] Channel assignment manager 520 may be configured to manage channel assignments for communication at the network device 505, at one or more gateways associated with the network device 505, at one or more satellites, at one or more user terminals, or any combination thereof. In some cases, the channel assignment manager 520 may assign a set of one or more frequencies to each channel of a set of channels. For example, the channel assignment manager 520 may assign a first set of frequencies to a first channel. Similarly, the channel assignment manager 520 may assign a second set of frequencies to a second channel. The first channel and the second channel may be contiguous or non-contiguous in the frequency band. Accordingly, communication on the first channel may use the first set of frequencies and communication on the second channel may use the second set of frequencies (e.g., including communication between the one or more gateways, satellites, and terminals).

[0083] In some implementations, the communications network 500 may support a system that includes the network device 505. The system may include a set of gateways (e.g., supported by the one or more detectors 515, the spectrum analysis system 545, one or more modems, or any combination thereof). Each gateway of the set of gateways may support a respective subset of satellite beams and may be configured to receive respective gateway signals. Each respective gateway signal may correspond to a respective portion of an RF band. In some cases, the system may include the spectrum analysis system 545, which may be coupled with the set of gateways. In some examples, the spectrum analysis system 545 may be or may include a set of spectrum processors (e.g., spectrum analyzers, the one or more detectors 515). In some cases, the one or more detectors 515 may detect an RF band (e.g., an input spectrum) of the gateway signals (e.g., return downlink signals). In such cases, the set of spectrum processors may downconvert the input spectrum (e.g., a relatively high frequency band) to an output spectrum (e.g., a relatively low frequency band). In some other cases, the one or more detectors 515 may detect (e.g., receive) a down-converted spectrum (e.g., an intermediate frequency (IF) spectrum). For example, one or more components of a gateway antenna may translate an RF band to an IF band such that the one or more detectors 515 receives the IF band (e.g., IF spectrum). Additionally, or alternatively, the spectrum analysis system 545 may perform one or more procedures to reduce (e.g., decimate, down sample) spectrum data such that a threshold (e.g., limited) quantity of samples may be communicated for each portion of frequencies (e.g., for each portion of spectrum) that corresponds to at least a portion of a channel (e.g., a minimum channel size). The spectrum analysis system 545 may be configured to generate respective subsets of spectrum data based on the respective gateway signals. Each respective subset of spectrum data may indicate respective received RF power information corresponding to the respective portion of the RF band. In some cases, the system may include one or more SMTSs in communication with the set of gateways. The one or more SMTSs may allocate, for each of the satellite beams, respective subsets of resources of respective sets of channels for communication between the set of gateways and a set of user terminals via the satellite beams.

[0084] In some implementations, the system may include the anomaly detector 550 in communication with the spectrum analysis system 545. The anomaly detector 550 may be configured to generate anomaly data in accordance with the respective received RF power information. The anomaly data may be associated with a set of spectrum data including the respective subsets of spectrum data. In some cases, the anomaly detector 550 may generatethe anomaly data based on applying one or more anomaly detection models on the set of spectrum data. The system may include the channel assignment manager 520 in communication with the anomaly detector 550 and the one or more SMTSs. The channel assignment manager 520 may be configured to assign, for each of the satellite beams, the respective sets of channels to frequencies within a respective beam bandwidth of each of the satellite beams. The channel assignment manager 520 may assign each respective set of channels to a subset of frequencies in accordance with the anomaly data. The system may include one or more modems in communication with the set of gateways. The one or more modems may be configured to communicate one or more messages between the set of gateways and the set of user terminals via the satellite beams using the respective subsets of resources of the respective sets of channels (e.g., in accordance with the channel assignment and the anomaly data as described herein).

[0085] In some examples, channel assignment manager 520, spectrum analysis system 545, anomaly detector 550, one or more other components described herein, or various combinations or components thereof, may be implemented in hardware (e.g., in communications management circuitry). The hardware may include at least one processor, a DSP, an ASIC, a one FPGA or other PLD, a discrete gate or transistor logic, discrete hardware components, or any combination thereof configured as or otherwise supporting a means for performing the functions described in the present disclosure. In some examples, at least one processor and at least one memory coupled with the at least one processor may be configured to perform one or more of the functions described herein (e.g., by executing, by the at least one processor, instructions stored in the at least one memory).

[0086] Additionally, or alternatively, channel assignment manager 520, spectrum analysis system 545, anomaly detector 550, one or more other components described herein, or various combinations or components thereof, may be implemented in code 535 (e.g., as communications management software or firmware), executed by at least one processor 540. If implemented in code 535 executed by at least one processor 540, the functions of channel assignment manager 520, spectrum analysis system 545, anomaly detector 550, or various combinations or components thereof may be performed by a general-purpose processor, a DSP, a CPU, an ASIC, an FPGA, a GPU, or any combination of these or other programmable logic devices (e.g., configured as or otherwise supporting a means for performing the functions described in the present disclosure).

[0087] FIG. 6 shows a flowchart illustrating a method 600 that supports detecting and mitigating RF anomalies in accordance with aspects of the present disclosure. The operations of the method 600 may be implemented by a satellite communications system or its components as described herein. For example, the operations of the method 600 may be performed by a satellite communications system as described with reference to FIGs. 1 through 5. In some examples, a satellite communications system may execute a set of instructions to control the functional elements of the satellite communications system to perform the described functions. Additionally, or alternatively, the satellite communications system may perform aspects of the described functions using special-purpose hardware.

[0088] At 605, the method may include receiving, by a plurality of gateways, respective gateway signals, each gateway of the plurality of gateways supporting a respective subset of a plurality of satellite beams, wherein each respective gateway signal corresponds to a respective portion of an RF band. The operations of 605 may be performed in accordance with examples as disclosed herein.

[0089] At 610, the method may include generating, by a spectrum analysis system coupled with the plurality of gateways, respective subsets of spectrum data based at least in part on the respective gateway signals, wherein each respective subset of spectrum data indicates respective received RF power information corresponding to the respective portion of the RF band. The operations of 610 may be performed in accordance with examples as disclosed herein.

[0090] At 615, the method may include allocating, by one or more satellite modem termination systems in communication with the plurality of gateways, for each of the plurality of satellite beams, respective subsets of resources of respective sets of channels for communication between the plurality of gateways and a plurality of user terminals via the plurality of satellite beams. The operations of 615 may be performed in accordance with examples as disclosed herein.

[0091] At 620, the method may include generating, by an anomaly detector in communication with the spectrum analysis system and configured to generate, in accordance with the respective received RF power information, anomaly data associated with a set of spectrum data comprising the respective subsets of spectrum data based at least in part on applying one or more anomaly detection models on the set of spectrum data. The operations of 620 may be performed in accordance with examples as disclosed herein.

[0092] At 625, the method may include assigning, by a channel assignment manager in communication with the anomaly detector and the one or more satellite modem termination systems, for each of the plurality of satellite beams, the respective sets of channels to frequencies within a respective beam bandwidth of each of the plurality of satellite beams in accordance with the anomaly data. The operations of 625 may be performed in accordance with examples as disclosed herein.

[0093] At 630, the method may include communicating, by one or more modems in communication with the plurality of gateways, one or more messages between the plurality of gateways and the plurality of user terminals via the plurality of satellite beams using the respective subsets of resources of the respective sets of channels. The operations of 630 may be performed in accordance with examples as disclosed herein.

[0094] In some examples, an apparatus as described herein may perform a method or methods, such as the method 600. The apparatus may include features, circuitry, logic, means, or instructions (e.g., a non-transitory computer-readable medium storing instructions executable by a processor), or any combination thereof for performing the following aspects of the present disclosure:

[0095] It should be noted that these methods describe examples of implementations, and that the operations and the steps may be rearranged or otherwise modified such that other implementations are possible. In some examples, aspects from two or more of the methods may be combined. For example, aspects of each of the methods may include steps or aspects of the other methods, or other steps or techniques described herein.

[0096] Information and signals described herein may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0097] The various illustrative blocks and modules described in connection with the disclosure herein may be implemented or performed with a general purpose processor, a DSP, an ASIC, an FPGA, a GPU, or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, orstate machine. A processor may also be implemented as a combination of computing devices (e.g., a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration).

[0098] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored on or transmitted over as one or more instructions or code on a computer readable medium. Other examples and implementations are within the scope of the disclosure and appended claims. For example, due to the nature of software, functions described herein can be implemented using software executed by a processor, hardware, firmware, hardwiring, or combinations of any of these. Features implementing functions may also be physically located at various positions, including being distributed such that portions of functions are implemented at different physical locations.

[0099] Computer readable media includes both non transitory computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A non-transitory storage medium may be any available medium that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, non-transitory computer readable media may include RAM, ROM, electrically erasable programmable read-only memory (EEPROM), flash memory, compact disk read-only memory (CDROM) or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to carry or store desired program code means in the form of instructions or data structures and that can be accessed by a general purpose or special purpose computer, or a general purpose or special purpose processor. Also, any connection is properly termed a computer readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk and disc, as used herein, include CD, laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above are also included within the scope of computer readable media.

[0100] As used herein, including in the claims, “or” as used in a list of items (e.g., a list of items prefaced by a phrase such as “at least one of’ or “one or more of’) indicates an inclusive list such that, for example, a list of at least one of A, B, or C means A or B or C or AB or AC or BC or ABC (i.e., A and B and C). Also, as used herein, the phrase “based on” shall not be construed as a reference to a closed set of conditions. For example, an exemplary step that is described as “based on condition A” may be based on both a condition A and a condition B without departing from the scope of the present disclosure. In other words, as used herein, the phrase “based on” shall be construed in the same manner as the phrase “based at least in part on.”

[0101] In the appended figures, similar components or features may have the same reference label. Further, various components of the same type may be distinguished by following the reference label by a dash and a second label that distinguishes among the similar components. If just the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label, or other subsequent reference label.

[0102] The description set forth herein, in connection with the appended drawings, describes example configurations and does not represent all the examples that may be implemented or that are within the scope of the claims. The term “exemplary” used herein means “serving as an example, instance, or illustration,” and not “preferred” or “advantageous over other examples.” The detailed description includes specific details for the purpose of providing an understanding of the described techniques. These techniques, however, may be practiced without these specific details. In some instances, well known structures and devices are shown in block diagram form in order to avoid obscuring the concepts of the described examples.

[0103] The description herein is provided to enable a person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the scope of the disclosure. Thus, the disclosure is not limited to the examples and designs described herein but is to be accorded the broadest scope consistent with the principles and novel features disclosed herein.

Claims

CLAIMSWhat is claimed is:

1. A system, comprising: a plurality of gateways (215), each gateway of the plurality of gateways (215) supporting a respective subset of a plurality of satellite beams (224), wherein the plurality of gateways (215) are configured to receive respective gateway signals (265), each respective gateway signal (265) corresponding to a respective portion of a radio frequency band; a spectrum analysis system (210) coupled with the plurality of gateways, the spectrum analysis system (210) configured to generate respective subsets of spectrum data based at least in part on the respective gateway signals (265), wherein each respective subset of spectrum data indicates respective received radio frequency power information corresponding to the respective portion of the radio frequency band; one or more satellite modem termination systems (260) in communication with the plurality of gateways (215), wherein the one or more satellite modem termination systems (260) allocate, for each of the plurality of satellite beams (224), respective subsets of resources of respective sets of channels (420) for communication between the plurality of gateways and a plurality of user terminals (220) via the plurality of satellite beams (224); an anomaly detector (230) in communication with the spectrum analysis system (210) and configured to generate, in accordance with the respective received radio frequency power information, anomaly data (554) associated with a set of spectrum data (212) comprising the respective subsets of spectrum data based at least in part on applying one or more anomaly detection models on the set of spectrum data (212); a channel assignment manager (240) in communication with the anomaly detector (230) and the one or more satellite modem termination systems (260) and configured to assign, for each of the plurality of satellite beams, the respective sets of channels (420) to frequencies (410) within a respective beam bandwidth (405) of each of the plurality of satellite beams (224) in accordance with the anomaly data (554); and one or more modems (215) in communication with the plurality of gateways (215) and configured to communicate one or more messages between the plurality of gateways (215) and the plurality of user terminals (220) via the plurality ofsatellite beams (224) using the respective subsets of resources of the respective sets of channels.

2. The system of claim 1, wherein the channel assignment manager (240) is further configured to: modify a channel size and channel placement for each of the respective sets of channels (420) based at least in part on a usable communication bandwidth that is in accordance with the anomaly data (554).

3. The system of any one of claims 1 or 2, wherein the one or more anomaly detection models comprise a threshold model, a bit error rate aware model, a channel-aware model, or any combination thereof.

4. The system of any one of claims 1 through 3, wherein, to assign the respective sets of channels (420) to frequencies (410), the channel assignment manager (240) is further configured to: assign, in accordance with the anomaly data (554), the respective sets of channels (420) to a set of frequencies (410) that excludes frequencies associated with anomalies (415) that satisfy a threshold anomaly strength.

5. The system of any one of claims 1 through 4, wherein the channel assignment manager (240) is further configured to: determine one or more environmental metrics associated with one or more frequencies (415) within the respective beam bandwidths of each of the plurality of satellite beams, the one or more environmental metrics comprising an interference level, a bit error rate, or both; and assign the respective sets of channels (420) to a set of frequencies (410) that excludes the one or more frequencies (415) based at least in part on the one or more environmental metrics satisfying one or more threshold values, the one or more threshold values comprising a threshold interference level, a threshold bit error rate, or both.

6. The system of any one of claims 1 through 4, wherein the channel assignment manager (240) is further configured to: determine one or more environmental metrics associated with one or more frequencies (415) within the respective beam bandwidths of each of the pluralityof satellite beams, the one or more environmental metrics comprising an interference level, a bit error rate, or both; and assign the respective sets of channels (420) to a set of frequencies (410) that includes the one or more frequencies (415) based at least in part on a performance level associated with the one or more environmental metrics satisfying a threshold performance value.

7. The system of any one of claims 1 through 6, wherein the channel assignment manager (240) is further configured to: assign a first set of channels (420) to a first set of frequencies (410) during a first duration in accordance with the anomaly data (554); and assign the first set of channels (420) to a second set of frequencies (410) during a second duration in accordance with the anomaly data (554) indicating interference in the first set of frequencies (410) for the first duration.

8. The system of any one of claims 1 through 7, wherein the channel assignment manager (240) is further configured to: perform a periodic channel assignment procedure in accordance with a periodic spectrum polling of the spectrum analysis system (210) and in accordance with the anomaly data (554).

9. The system of claim 8, wherein, to perform the periodic channel assignment procedure, the channel assignment manager (240) is further configured to: assign a first set of channels (420) to a first set of frequencies (410) at a first instance in accordance with the anomaly data (554); and assign the first set of channels (420) to a second set of frequencies (410) at a second instance in accordance with the anomaly data (554) and in accordance with the periodic channel assignment procedure.

10. The system of any one of claims 1 through 6, wherein the channel assignment manager (240) is further configured to: assign a first set of channels (420) to a first set of frequencies (410) according to a randomized channel placement scheme that is based at least in part on one or more constraints configured at the channel assignment manager (240).

11. The system of any one of claims 1 through 6, wherein the channel assignment manager (240) is further configured to: assign a first set of channels (420) to a first set of frequencies (410) according to a probabilistic channel placement scheme that is based at least in part on anomaly data (554) generated by the anomaly detector (230) for one or more prior time periods.

12. The system of any one of claims 1 through 11, wherein the anomaly detector (230) is further configured to: determine, based at least in part on the respective received radio frequency power information associated with the set of spectrum data (212), a minimum power value and a maximum power value corresponding to each respective subset of spectrum data; and generate the anomaly data (554) associated with the set of spectrum data (212) based at least in part on a difference between the minimum power value and the maximum power value satisfying a threshold.

13. The system of claim 12, wherein the anomaly detector (230) is further configured to: generate the anomaly data (554) associated with the set of spectrum data (212) based at least in part on the minimum power value satisfying a second threshold, the maximum power value satisfying a third threshold, or both.

14. The system of any one of claims 1 through 13, wherein the anomaly detector (230) is further configured to: generate correlation data based at least in part on the respective received radio frequency power information associated with of the set of spectrum data (212), wherein the correlation data indicates a respective correlation value between each pair of frequencies within the radio frequency band; and generate the anomaly data (554) indicating that a plurality of frequencies (415) of the radio frequency band include one or more anomalies based at least in part on the plurality of frequencies (415) being correlated in accordance with the correlation data.

15. The system of claim 14, wherein the anomaly detector (230) is further configured to: output the correlation data to a user interface for displaying an indication of the respective correlation values between each pair frequencies of the radio frequency band.

16. The system of any one of claims 1 through 15, further comprising: a data storage manager 226 configured to store the anomaly data (554) associated with the set of spectrum data for a threshold duration, wherein the anomaly data (554) comprises one or more interference patterns associated with the set of spectrum data.

17. A method, comprising: receiving, by a plurality of gateways (215), respective gateway signals, each gateway of the plurality of gateways (215) supporting a respective subset of a plurality of satellite beams (224), wherein each respective gateway signal (265) corresponds to a respective portion of a radio frequency band; generating, by a spectrum analysis system (210) coupled with the plurality of gateways (215), respective subsets of spectrum data based at least in part on the respective gateway signals (265), wherein each respective subset of spectrum data indicates respective received radio frequency power information corresponding to the respective portion of the radio frequency band; allocating, by one or more satellite modem termination systems (260) in communication with the plurality of gateways (215), for each of the plurality of satellite beams (224), respective subsets of resources of respective sets of channels (420) for communication between the plurality of gateways (215) and a plurality of user terminals (220) via the plurality of satellite beams (224); generating, by an anomaly detector (230) in communication with the spectrum analysis system (210) and configured to generate, in accordance with the respective received radio frequency power information, anomaly data (554) associated with a set of spectrum data (212) comprising the respective subsets of spectrum data based at least in part on applying one or more anomaly detection models on the set of spectrum data (212);assigning, by a channel assignment manager (240) in communication with the anomaly detector (230) and the one or more satellite modem termination systems (260), for each of the plurality of satellite beams (224), the respective sets of channels (420) to frequencies within a respective beam bandwidth (405) of each of the plurality of satellite beams (224) in accordance with the anomaly data (554); and communicating, by one or more modems (215) in communication with the plurality of gateways, one or more messages between the plurality of gateways (215) and the plurality of user terminals (220) via the plurality of satellite beams (224) using the respective subsets of resources of the respective sets of channels (420).

18. The method of claim 17, further comprising: modifying, by the channel assignment manager (240), a channel size and channel placement for each of the respective sets of channels (420) based at least in part on a usable communication bandwidth that is in accordance with the anomaly data (554).

19. The method of any one of claims 17 or 18, wherein the one or more anomaly detection models comprise a threshold model, a bit error rate aware model, a channel-aware model, or any combination thereof.

20. The method of any one of claims 17 through 19, wherein assigning the respective sets of channels to frequencies comprises: assigning, by the channel assignment manager (240), in accordance with the anomaly data (554), the respective sets of channels (420) to a set of frequencies (410) that excludes frequencies associated with anomalies (415) that satisfy a threshold anomaly strength.

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