System and method for broadband spectral analysis and management

Abstract

The present technology relates to systems and methods for broadband spectral analysis and management. In an embodiment, the technology provides an apparatus comprising: a receiver configured to receive a first signal; and an analyzer configured to generate a spectral representation of the first signal. The analyzer is further configured to perform accumulation by averaging magnitudes of frequency components within a plurality of timestamps to enhance the signal-to-noise ratio and provide a stable representation of the power density of the first signal. Embodiments of the present technology improve analysis and management of wireless signals to achieve robust and efficient wireless communication by mitigating interference and optimizing frequency usage. Other embodiments are also present.

Description

Technical Field

[0001] The present technology relates to wireless communication systems and methods. Background Art

[0002] Wireless communication systems have become increasingly common in various fields, including telecommunications, data transmission, and Internet connectivity. These systems rely heavily on efficient management of the radio frequency (RF) spectrum to ensure reliable and high-speed communication. Various approaches involve the use of spectrum analyzers, which measure the frequency and amplitude of signals in the electromagnetic spectrum. Spectrum analyzers operate by capturing incoming signals and converting them into a spectrum, thereby providing a visual representation of both the spectrum and signal strength. Spectrum analyzers play an important role in optimizing network configurations by identifying the most suitable frequency bands and channels for operation, thereby reducing conflicts and minimizing interference. However, as the density of wireless devices and the demand for data throughput increase, effectively managing and optimizing the use of spectrum remains a major challenge.

[0003] Unfortunately, existing techniques are unsatisfactory for reasons explained below. New and improved methods and systems are desired. Summary of the Invention

[0004] In one aspect, the present disclosure relates to an apparatus comprising: an input configured to receive a first signal; a processor coupled to the input, the processor configured to: generate a second signal based on the first signal, the second signal comprising a first frequency component; calculate a first magnitude associated with the first frequency component at a first timestamp; calculate a second magnitude associated with the first frequency component at a second timestamp; calculate a third magnitude associated with the first frequency component by calculating an average based on at least the first magnitude and the second magnitude; and a memory coupled to the processor, the memory configured to store at least the first magnitude and the second magnitude.

[0005] On the other hand, the present disclosure relates to an apparatus comprising: a receiver configured to receive a first signal, the receiver comprising: an amplifier configured to amplify the first signal; a first filter coupled to the amplifier via a first node, the first filter configured to filter the first signal; an analog-to-digital converter (ADC) coupled to the first filter via a second node; and a control module configured to measure a first signal strength at the first node and a second signal strength at the second node; and an analyzer coupled to the receiver, the analyzer configured to: generate a second signal based on the first signal, the second signal comprising a first frequency component; calculate a first magnitude associated with the first frequency component at a first timestamp; calculate a second magnitude associated with the first frequency component at a second timestamp; and calculate a third magnitude associated with the first frequency component by calculating an average based on at least the first magnitude and the second magnitude.

[0006] On the other hand, the present disclosure relates to a device comprising: an input configured to receive a first signal; a processor coupled to the input, the processor configured to: generate a second signal based on the first signal, the second signal comprising a first frequency component; calculate a first magnitude associated with the first frequency component at a first timestamp; calculate a second magnitude associated with the first frequency component at a second timestamp; calculate a third magnitude associated with the first frequency component by calculating an average based on at least the first magnitude and the second magnitude; and generate a spectral representation of the first signal based at least on the third magnitude; a memory coupled to the processor, the memory configured to store at least the first magnitude and the second magnitude; and an output coupled to the processor, the output configured to output the spectral representation. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] A further understanding of the nature and advantages of certain embodiments may be achieved by reference to the remainder of the specification and drawings, in which like reference numerals are used to refer to like components. In some instances, a sub-label is associated with a reference numeral to identify one of multiple similar components. When a reference numeral is cited without specifying an existing sub-label, it is intended to refer to all such multiple similar components.

[0008] Figure 1 is a simplified diagram illustrating a wireless environment suitable for implementing various embodiments of the present technology.

[0009] Figure 2 is a simplified diagram illustrating a receiver in accordance with an embodiment of the present technology.

[0010] Figure 3 is a simplified diagram illustrating an analyzer in accordance with an embodiment of the present technology.

[0011] Figure 4 is a simplified diagram illustrating an analyzer in accordance with an embodiment of the present technology. DETAILED DESCRIPTION

[0012] The present technology relates to wireless communication systems and methods. In one embodiment, the present technology provides an apparatus comprising: a receiver configured to receive a first signal; and an analyzer configured to generate a spectral representation of the first signal. The analyzer is further configured to perform accumulation by averaging the magnitude of frequency components over multiple time stamps, thereby enhancing the signal-to-noise ratio and providing a stable representation of the power density of the first signal. Embodiments of the present technology improve the analysis and management of wireless signals, thereby achieving robust and efficient wireless communication by mitigating interference and optimizing frequency usage. Other embodiments also exist.

[0013] The growing adoption of wireless technology in a wide variety of applications has led to increased congestion in the radio spectrum, for example, in widely used frequency bands such as 2.4 GHz, 5 GHz, or 6 to 7 GHz. This congestion poses challenges to coexistence and performance optimization because multiple devices compete for limited resources. Therefore, the available spectrum has become a valuable resource that must be utilized efficiently. Various methods for spectrum management involve the use of wideband receivers and spectrum analyzers. For example, the term "wideband receiver" may refer to a device that can capture and process signals over a wide frequency range (e.g., from tens of MHz to several GHz). The term "spectrum analyzer" may refer to a device that measures the magnitude and frequency of an input signal within a specified frequency range. A spectrum analyzer can provide power estimates of signals across different frequency components, allowing the system to optimize the network configuration by selecting the optimal frequency band and channel for operation.

[0014] Despite these advances, many techniques for signal reception and spectrum analysis still face limitations, particularly in dynamic and congested RF environments. For example, in environments where WLAN and Bluetooth devices coexist, the high density of wireless communications can increase the rate of data packet collisions. Collisions occur when two or more devices transmit data on the same radio channel during overlapping periods, resulting in corrupted or lost packets.

[0015] To mitigate the risk of collisions, various techniques have been explored. For example, Bluetooth technology implements adaptive frequency hopping (AFH) to manage data communications among devices. The term "adaptive frequency hopping" may refer to a mechanism that dynamically selects a communication channel based on the interference level detected on each channel. However, due to the need to sequentially scan each channel and measure the received signal strength indicator (RSSI), such methods often suffer from latency and increased power consumption. In addition, excluding a channel from the AFH list due to detected interference may result in long delays before the channel can be re-evaluated and potentially re-added. These delays may result in underutilization of the available spectrum and reduced throughput. Furthermore, AFH technology often evaluates the quality of the Bluetooth channel in discrete time slots, resulting in a lack of real-time adaptability and an incomplete overview of the spectrum environment.

[0016] As explained above, improved methods and systems for wireless communications are provided. In various embodiments, the present technology provides a system that integrates a wideband receiver with a spectrum analyzer to provide efficient signal processing and management. This integration facilitates comprehensive and rapid analysis of the RF spectrum, enabling the system to immediately adapt to the dynamic conditions of the RF environment. The wideband receiver is designed to cover a wide frequency range, thereby reducing the hardware complexity and power consumption typically associated with separate receiver chains for different frequency bands. The spectrum analyzer evaluates power levels across the entire bandwidth through an on-chip implementation, providing a comprehensive analysis of the spectrum in real time. By simultaneously evaluating the entire bandwidth, the analyzer not only provides a detailed power distribution of the spectrum, but also enables faster decision making for dynamic frequency selection, thereby mitigating interference and enhancing overall communication quality.

[0017] Embodiments of this technology can be integrated into various wireless communication systems and applications. For example, this technology can be incorporated into modern telecommunications infrastructure to enhance the efficiency and reliability of 5G and future 6G networks by rapidly identifying and selecting optimal communication channels. Furthermore, this technology can be applied to consumer electronics to accelerate Bluetooth device connections and improve automatic gain control in smart devices, ensuring a robust and interference-free user experience even in environments heavily saturated with competing wireless signals.

[0018] The following description is presented to enable one of ordinary skill in the art to make and use the present invention and incorporate it into a specific application context. Various modifications and multiple uses in different applications will be apparent to those skilled in the art, and the general principles defined herein can be applied to a wide range of embodiments. Therefore, the present technology is not intended to be limited to the embodiments presented, but should be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0019] In the following detailed description, numerous specific details are set forth to provide a more thorough understanding of the present technology. However, it will be apparent to those skilled in the art that the present technology can be practiced without being limited to these specific details. In other instances, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring the present technology.

[0020] The reader is advised that all papers and documents filed with this specification and disclosed for public inspection with this specification are hereby incorporated by reference into this specification. All features disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purposes, unless expressly stated otherwise. Therefore, unless expressly stated otherwise, each disclosed feature is only one example of a general series of equivalent or similar features.

[0021] Furthermore, any element in a claim that does not explicitly recite “means” for performing a specified function or “step” for performing a specified function should not be construed as a “means” or “step” clause as specified in 35 U.S.C. Section 112, paragraph 6. Specifically, the use of “the step of” or “the act of” in a claim herein is not intended to invoke the provisions of 35 U.S.C. Section 112, paragraph 6.

[0022] When an element is referred to herein as being "connected" or "coupled" to another element, it is understood that the element may be directly connected to the other element or that intervening elements may exist between the elements. In contrast, when an element is referred to as being "directly connected" or "directly coupled" to another element, it is understood that no intervening elements exist in the "direct" connection between the elements. However, the presence of a direct connection does not preclude other connections in which intervening elements may exist.

[0023] In addition, the terms left, right, front, back, top, bottom, forward, reverse, clockwise and counterclockwise are used only for explanation purposes and are not limited to any fixed direction or orientation. Rather, they are only used to indicate the relative position and / or direction between various parts of an object and / or component.

[0024] Furthermore, for ease of description, the methods and processes described herein may be described in a particular order. However, it should be understood that unless the context dictates otherwise, intervening processes may occur before and / or after any portion of the described processes, and further various processes may be reordered, added, and / or omitted according to various embodiments.

[0025] Unless otherwise indicated, all numbers used herein to express quantities, dimensions, and the like should be understood as being modified in all instances by the term "about". In this application, unless specifically stated otherwise, the use of the singular includes the plural, and the use of the terms "and" and "or" means "and / or" unless otherwise indicated. In addition, the use of the terms "including" and "having" and other forms such as "includes", "included", "has", "have" and "had" should be considered non-exclusive. Moreover, terms such as "element" or "component" encompass both elements and components comprising one unit and elements and components comprising more than one unit, unless specifically stated otherwise.

[0026] As used herein, the phrase "at least one of" following a list of items (where the terms "and" or "or" are used to separate any of the items) modifies the entire list, rather than each member of the list (i.e., each item). The phrase "at least one of" does not require selection of at least one of each listed item; rather, the phrase allows for a meaning that includes at least one of any of the items and / or at least one of any combination of the items. For example, the phrase "at least one of A, B, and C" or "at least one of A, B, or C" each refers to only A, only B, or only C, and / or any combination of A, B, and C. In examples where selection of "at least one of each of A, B, and C" or, alternatively, "at least one of A, at least one of B, and at least one of C" is intended, it is explicitly described as such.

[0027] Figure 1 1 is a simplified diagram illustrating a wireless environment 100 suitable for implementing various embodiments of the present technology. This diagram provides an example only and should not unduly limit the scope of the claims. Those skilled in the art will recognize many variations, alternatives, and modifications.

[0028] As shown, wireless environment 100 may include multiple devices that wirelessly communicate with each other. For example, wireless environment 100 includes a router 102 that provides wireless connectivity and network access to multiple devices. Multiple devices may include, but are not limited to, smartphones 104, laptops 106, vehicles 108, cell phones 110, and / or other mobile or fixed devices that support wireless communication. In various embodiments, wireless environment 100 further includes an access point (AP) 112 that connects wireless environment 100 to the Internet or other networks. Multiple devices may generate multiple RF signals 114a, 114b, 114c, 114d, 114e to communicate with each other. Multiple RF signals may include, but are not limited to, cellular signals, Wi-Fi signals, GPS signals, Bluetooth signals, radio signals, TV signals, 5G signals, and / or the like.

[0029] Depending on the implementation, wireless communications may operate on different frequency bands (e.g., 2.4 GHz, 5 GHz, and / or the like). The RF signals 114a-e transmitted by these devices may differ in their properties (e.g., frequency, power level, modulation scheme, and / or the like). For example, the smartphone 104 may communicate at 2.4 GHz via Wi-Fi signals at low power levels (e.g., -50 dBm to 65 dBm) for data transmission. The vehicle 108 may communicate at 5.9 GHz using dedicated short-range communication (DSRC) signals, which require higher power levels (e.g., 13 dBm to 30 dBm) to ensure reliable connections over longer distances. In various implementations, devices may use various communications with different frequencies, depending on the application and spectrum availability. For example, the smartphone 104 may communicate at 2.4 GHz for a Bluetooth connection and switch to 5 GHz for Wi-Fi (where higher bandwidth is required).

[0030] The coexistence of multiple devices transmitting at different frequencies and power levels can lead to various operational challenges, such as interference or overlap. Interference can occur when unwanted signals affect the quality or performance of desired signals, resulting in signal degradation or data loss. Overlap can also occur when frequency bands used by different wireless signals partially or completely overlap, causing interference and signal degradation.

[0031] To address these challenges, spectrum analysis and management can be employed to ensure efficient wireless communication. In various examples, spectrum analysis is performed by a receiver, an analyzer, or a combination of the two. The term "receiver" may refer to a device capable of capturing and processing signals within a certain frequency or frequency range. The term "analyzer" may refer to a device that measures the magnitude and frequency of input signals within a specified frequency range, thereby providing a visual representation of spectrum usage and signal quality. For example, a wireless device (e.g., smartphone 104, laptop 106, vehicle 108, cellular phone 110) may include a receiver and / or analyzer to monitor the RF environment. The receiver can detect and identify the desired signal for communication and perform gain control to avoid signal saturation or distortion. The analyzer can measure and display signal characteristics such as frequency, power, bandwidth, etc. This allows the system to dynamically adjust operating parameters and optimize network configuration, such as AFH scan acceleration, received signal strength indicator (RSSI) calibration acceleration, automatic gain control (AGC) optimization, and / or the like.

[0032] Figure 2 2 is a simplified diagram illustrating a receiver 200 according to an embodiment of the present technology. This diagram merely provides an example, which should not unduly limit the scope of the claims. Those skilled in the art will recognize many variations, alternatives, and modifications.

[0033] Depending on the application, receiver 200 may be integrated into a chip or implemented as a standalone device to capture and process signals within a certain frequency or frequency range. For example, receiver 200 may include a wideband receiver. The term "wideband receiver" may refer to a device capable of simultaneously detecting, processing, and analyzing a wide range of frequencies. For example, a wideband receiver may cover the entire 2.4 GHz band, the 5 GHz band, the 5.9 GHz band, or the 6 to 7 GHz band and may be used for Wi-Fi, Bluetooth, radar, satellite, cellular communications, and / or other forms of wireless communications. In various embodiments, receiver 200 includes at least one of an amplifier 202, a first filter 204, an analog-to-digital converter (ADC) 206, a second filter 208, a signal processor 210, a control module 214, an analyzer 216, a firmware engine 218, one or more demodulators 212a, 212b, 212c, and / or the like.

[0034] In various implementations, receiver 200 is configured to receive a first signal. For example, the first signal may be received from a transmitting antenna or a wireless communication device. The first signal may include an RF signal, which may include, but is not limited to, a cellular signal, a Wi-Fi signal, a GPS signal, a Bluetooth signal, a radio signal, a TV signal, a 5G signal, and / or the like. In some cases, the first signal may be received and processed by amplifier 202. For example, the term "amplifier" may refer to a device that increases the amplitude or power of a signal (e.g., by using a transistor or an operational amplifier). Amplifier 202 may include, but is not limited to, a low-noise amplifier (LNA), a power amplifier (PA), a variable-gain amplifier (VGA), a broadband amplifier, a gain-block amplifier, a logarithmic amplifier, and / or the like. For example, the term "low-noise amplifier" may refer to a device that amplifies a low-power signal without significantly degrading its signal-to-noise ratio (SNR). An LNA may be configured to minimize excess noise and boost the desired signal to a level suitable for further processing without significantly degrading the SNR.

[0035] In some embodiments, first filter 204 is coupled to amplifier 202 via first node 220. For example, the term "filter" may refer to a device that modifies the frequency spectrum of a signal. The term "node" may refer to a point in a circuit where two or more components can be connected. In some cases, first filter 204 may be configured to filter the first signal by allowing signals within a certain frequency range to pass while attenuating frequencies outside that range. First filter 204 may include, but is not limited to, a bandpass filter (BPF), a digitally tunable filter, a reflectionless filter, an ultra-wideband (UWB) filter, and / or the like. The term "bandpass filter" may refer to a device that allows signals within a specific frequency range to pass while reducing the strength of signals outside that range. For example, first filter 204 helps receiver 200 select a desired signal frequency band (e.g., a 2.4 GHz or 5 GHz band) from a wide frequency spectrum, depending on the system's operating requirements and desired performance characteristics.

[0036] In various examples, the first filter 204 can be coupled to the ADC 206 via the second node 222. For example, the term "analog-to-digital converter" can refer to a device that converts an analog signal into a digital signal. The ADC 206 can be configured to sample the filtered first signal and convert it into a digital format for further processing. In some embodiments, the ADC 206 can be coupled to the second filter 208. For example, the second filter 208 can include a decimation filter. The term "decimation filter" can refer to a type of filter that reduces the sampling rate of a signal by discarding some of the samples of the signal. The second filter 208 can be configured to selectively reduce the data point rate in the first signal to reduce the computational load on downstream processing units (e.g., the signal processor 210). In some cases, the second filter 208 can be configured to reduce the sampling rate of the digital signal generated by the ADC 206.

[0037] Depending on the implementation, the second filter 208 can be coupled to a signal processor 210 via a third node 224. The term "signal processor" can refer to a device or circuit that performs various mathematical or computational algorithms on a signal. For example, the signal processor 210 can include, but is not limited to, a digital processor, a digital rotator, a fast Fourier transform (FFT) processor, a digital mixer, a digital filter, a modulator, a demodulator, and / or the like. In some examples, the signal processor 210 is configured to adjust the frequency of a digital signal to a desired baseband frequency for demodulation.

[0038] According to some embodiments, signal processor 210 may be coupled to one or more demodulators (e.g., 212a, 212b, ..., 212c) to demodulate the processed digital signal into a format suitable for subsequent decoding and interpretation. The term "demodulator" may refer to a device that extracts information from a carrier wave by reversing the modulation process. Depending on the implementation, the demodulators (e.g., 212a, 212b, ..., 212c) may employ various types of demodulation schemes, such as phase modulation (PM), amplitude modulation (AM), frequency modulation (FM), quadrature amplitude modulation (QAM), and / or the like. In some cases, the output from signal processor 210 may be split into multiple paths leading to each demodulator to accommodate different signal types and modulation schemes. This multipath routing allows the system to process multiple signal types simultaneously, thereby increasing throughput and the ability to handle various communication protocols, particularly in environments with a wide range of wireless signal types and standards.

[0039] In various implementations, a control module 214 may be coupled to the amplifier 202. The term "control module" may refer to a device responsible for managing and regulating the operation of other components within the system (e.g., the receiver 200). The control module 214 may be configured to perform various functions, such as automatic gain control (AGC), signal strength measurement, adaptive frequency management, and / or the like. For example, the control module 214 may be configured to dynamically adjust signal processing parameters (e.g., the gain applied to the first signal) to maintain an optimal signal level for subsequent processing.

[0040] Depending on the implementation, the control module 214 may be configured to measure the signal strength at one or more nodes. For example, the control module 214 may be configured to measure a first signal strength at the first node 220. As an example, the first signal strength may be associated with a first frequency range. The first signal strength may include a wideband RSSI. The term "received signal strength indicator" or "RSSI" may refer to a measurement of the power present in a received signal. Wideband RSSI measures the total power of all signals (e.g., noise, interference, broadcast signals) present across a wide frequency range, thereby providing an overall assessment of signal conditions for identifying the presence of strong signals and prevalent interference.

[0041] In some embodiments, the control module 214 may be configured to measure a second signal strength at the second node 222. The second signal strength may be associated with a second frequency range. The second frequency range may be narrower than the first frequency range. For example, the second signal strength may include a narrowband RSSI, which measures signal strength within a narrow frequency range or a selected frequency band, thereby allowing for a detailed assessment of channel quality and communication availability. In other examples, the control module 214 may be configured to measure a third signal strength at the third node 224. The third signal strength may include a digital RSSI, which measures the power of the digital signal. The digital RSSI may be obtained after one or more digital processing stages (e.g., filtering, decimation, digital down-conversion, and / or the like). The digital RSSI facilitates assessment of signal integrity and quality after digital processing, thereby assisting in adjusting digital processing parameters to improve signal reception and digital gain control. In some embodiments, the control module 214 may be configured to adjust the gain of the amplifier 202 based at least on the first signal strength, the second signal strength, and the third signal strength.

[0042] In various embodiments, the analyzer 216 may be coupled to the receiver 200 and operate in conjunction with it. The term "analyzer" may refer to a device configured to analyze the spectral composition of an electronic signal. For example, the analyzer 216 may be configured to provide a visual representation and comprehensive analysis of signal characteristics across a bandwidth. In some instances, the analyzer 216 acquires a digital signal from the receiver and calculates the power spectral density, thereby providing insight into the power distribution within the spectrum. The analyzer 216 helps identify the presence of undesired signals and assists in making informed decisions about frequency allocation, thereby promoting more efficient spectrum management. In some embodiments, the receiver 200 and the analyzer 216 are integrated into a single chip, streamlining the design and minimizing the physical footprint. This on-chip integration enhances the efficiency of the receiver system by reducing signal loss and latency, thereby benefiting applications that require fast and accurate spectrum analysis.

[0043] In some instances, the control module 214 may be coupled to the analyzer 216. The output of the analyzer 216 may be provided to the control module 214 to make informed decisions. For example, if the analyzer 216 identifies a frequency band with a high level of interference, the control module 214 may specifically adjust the gain of the signals within that frequency band to minimize the impact of interference on signal quality. If the analyzer 216 detects an underutilized frequency band with low signal strength, the control module 214 may increase the gain of the signals in that frequency band to enhance reception. This synergistic relationship enables the receiver 200 to dynamically adapt to changing RF conditions, thereby optimizing both the reception quality of the current signal and the overall spectral efficiency of the system.

[0044] In various embodiments, the analyzer 216 may be coupled to a firmware engine 218. The firmware engine 218 may process the spectrum data output from the analyzer 216 for comprehensive signal analysis and spectrum management. For example, the firmware engine 218 may act as a central controller for the receiver 200 and manage hardware components and parameter settings based on the spectrum representation provided by the analyzer 216. The firmware engine 218 may also provide a user interface for the operator to monitor and control the receiver 200, such as adjusting the frequency range, resolution bandwidth, and detection threshold. By utilizing the data from the analyzer 216, the firmware engine 218 may perform frequency allocation and interference management to optimize spectrum usage and improve communication quality. Depending on the implementation, the firmware engine 218 may support real-time spectrum analysis, allowing the system to adapt to rapid changes in the RF environment.

[0045] Figure 3 is a simplified diagram illustrating an analyzer 300 according to an embodiment of the present technology. This diagram provides an example only, which should not unduly limit the scope of the claims. Those skilled in the art will recognize many variations, alternatives, and modifications. In various embodiments, the analyzer 300 may be coupled to a receiver (e.g., Figure 2The analyzer 300 is a receiver 200 (e.g., a receiver 200) that receives an input signal from the receiver and performs spectrum analysis to evaluate the frequency and power characteristics of the received signal. The analyzer can be integrated with the receiver as part of a unified system or can operate as a separate module within a larger system. In some cases, the receiver and analyzer 300 can be integrated into a single chip to minimize physical footprint and streamline signal transmission paths.

[0046] In various embodiments, the analyzer 300 may receive a first signal from a receiver. For example, the first signal may include in-phase (I) and quadrature (Q) data representing both the magnitude and angle of the signal. The I / Q data may be derived directly from the output of the receiver's ADC and contain raw signal data that can be used for demodulation and interpretation. In some implementations, the analyzer 300 may be configured to convert the raw I / Q data into spectrum data to perform frequency domain analysis on the received signal, thereby providing a detailed analysis of the frequency content and power distribution within the spectrum. For example, the spectrum data may reveal the presence of noise, interference, modulation, harmonics, and other features that affect signal quality and performance. Spectrum analysis enables detection of signal anomalies and available communication channels, thereby facilitating enhanced signal clarity and integrity to improve wireless communication performance.

[0047] At module 302, a windowing function can be applied to the first signal. For example, the windowing function can be used to reduce the effects of discontinuities in the signal. For example, the windowing function includes a weighting function that gradually reduces the signal to near zero at the beginning and end of a sampling period, which reduces the effects of sudden changes or cuts in the time domain signal that may cause spectral leakage. Spectral leakage can occur when energy "leaks" from one frequency interval into another, which is generally attributed to the finite duration of the signal being transformed. Spectral leakage can cause the power of the signal to spread across the spectrum, thereby generating spurious components that are not present in the original signal.

[0048] As an example, the first signal may include 16-bit I / Q samples, which are complex numbers representing both the magnitude and angle of the signal. A windowing function may be applied to each I / Q sample by multiplying the windowing function by a corresponding window value. This process helps preserve the spectral integrity of the signal, allowing for a more accurate representation of its frequency components. Depending on the implementation, the window values ​​may be stored in a lookup table or calculated on the fly. Windowing functions may include, but are not limited to, rectangular windows, Hanning windows, Gaussian windows, Blackman-Harris windows, and / or the like.

[0049] In various embodiments, module 304 may apply a fast Fourier transform (FFT) to the windowed signal. For example, module 304 may generate a second signal based on the first signal using an FFT. The first signal may include a time domain signal and the second signal may include a frequency domain signal. For example, the term "time domain signal" may refer to a representation of the amplitude of a signal as the amplitude of the signal changes over time, which illustrates the behavior of the signal and the amplitude changes at different time stamps. The term "frequency domain signal" may refer to a representation of the amplitude of a signal distributed across various frequencies, which indicates the spectral composition of the signal and the strength of its frequency components. In some instances, the second signal may include a first frequency component. The term "frequency component" may refer to a component in a frequency domain signal that corresponds to a certain frequency within the entire spectrum. The term "fast Fourier transform" may refer to an algorithm that converts a time domain signal into a frequency domain representation by calculating a discrete Fourier transform (DFT) and its inverse transform. This transform facilitates observation and analysis of the frequency components of a signal, thereby enabling identification and quantification of individual frequency components within a complex signal.

[0050] In some embodiments, the FFT operation decomposes the signal into a plurality of frequency bins (e.g., 32, 64, 128, 256, etc.), each of which represents a specific frequency component within the overall bandwidth of the signal. The output of the FFT is a sequence of complex numbers, where each number indicates the amplitude and phase of the signal at the corresponding frequency bin. For example, the magnitude of each complex number represents the power or amplitude of the signal, and the angle represents the phase or delay of the signal. By performing the FFT, the analyzer 300 can identify and analyze individual frequency components, thereby providing valuable information for tasks such as power estimation, signal identification, and interference analysis.

[0051] According to some embodiments, module 308 may be configured to calculate the magnitude of the FFT output. The term "magnitude" may refer to the strength / intensity of a frequency component within a signal, which represents the power of the signal at the corresponding frequency. For example, module 308 may be configured to calculate a first magnitude associated with a first frequency component at a first timestamp. The first magnitude can be calculated by converting a complex number from the FFT into a real value representing the strength or power of the signal at the corresponding frequency. The magnitude value quantifies how much signal is present at a particular frequency, which serves as an important indicator for power estimation. In some embodiments, module 308 may be configured to calculate a second magnitude associated with the first frequency component at a second timestamp. Time information (e.g., the first and second timestamps) enables analyzer 300 to track spectral changes over time, thereby allowing dynamic spectrum analysis to be performed by considering both transient and sustained changes across the spectrum. Depending on the implementation, the first and second timestamps may be characterized by predetermined time intervals (e.g., 5 μs, 10 μs, 20 μs, 40 μs, etc.).

[0052] In various embodiments, the magnitude values ​​calculated at module 308 may be accumulated over multiple FFT frames. For example, the first magnitude and the second magnitude may be stored in memory 310. Memory 310 may include volatile memory and / or non-volatile memory, such as random access memory (RAM), read-only memory (ROM), flash memory, and / or the like. For example, memory 310 may use volatile memory for fast access and non-volatile memory for long-term data retention and recovery. In some cases, a memory controller 306 may be coupled to memory 310 and configured to manage communications and data transfers between memory 310 and other components of analyzer 300. Memory controller 306 may include, but is not limited to, a memory interface, a memory buffer, a memory arbiter, a memory timing generator, and / or the like.

[0053] In some embodiments, module 312 may retrieve the first and second magnitudes from memory 312 and calculate a third magnitude associated with the first frequency component. For example, the third magnitude may be determined by calculating an average based on at least the first and second magnitudes, thereby effectively smoothing the spectrum of the signal over time. The accumulation process—by integrating magnitude values ​​across consecutive FFT frames—reduces random noise and minimizes the effects of transient spectral artifacts, thereby achieving a stable and reliable spectral representation. In some cases, analyzer 300 may generate a spectral representation of the first signal based on at least the third magnitude. Through magnitude accumulation and time averaging, the spectral representation improves power estimation for optimizing frequency allocation and enhancing overall communication quality. This process not only promotes more efficient spectrum utilization, but also supports advanced communication technologies such as adaptive frequency hopping (AFH), RSSI calibration acceleration, AGC optimization, and / or the like.

[0054] In some implementations, module 314 may be configured to convert the third magnitude from a linear scale to a logarithmic (decibel) scale. This conversion facilitates intuitive understanding and representation of signal power levels because a logarithmic scale more accurately reflects the wide dynamic range of signals within a wireless communication environment. Logarithmic representation is useful for visualizing the dynamic range of the spectrum, thereby enabling informed decisions regarding frequency allocation and network optimization. Additionally, the decibel scale simplifies the process of setting threshold levels for signal detection and interference avoidance, further streamlining spectrum management tasks.

[0055] Depending on the implementation, module 316 may be configured to perform gain compensation, thereby adjusting the magnitude of the signal based on the gains applied at various stages of the receiver. For example, the third magnitude may be based on the gain adjustment applied to the first signal at the input terminal. This process aligns the measured signal power with its original value by taking into account the amplification or attenuation introduced by the components of the receiver. By compensating for changes in gain, module 316 maintains the integrity of the power estimate across the spectrum, regardless of the dynamic adjustment of the AGC in response to fluctuating signal conditions. Gain compensation allows direct comparison of signal strength across different conditions and periods, providing a consistent basis for spectrum analysis. In various instances, module 316 is coupled to a control module of the receiver (e.g., Figure 2 The system works closely with the control module 214 of the analyzer 300 to dynamically adjust the gain settings based on the spectrum analysis provided by the analyzer 300. This collaboration enables the system to maintain an optimal signal-to-noise ratio (SNR) and adapt to changing RF conditions by modifying the receiver gain in real time.

[0056] Figure 4 4 is a simplified diagram illustrating an analyzer 400 according to an embodiment of the present technology. This diagram merely provides an example, which should not unduly limit the scope of the claims. Those skilled in the art will recognize many variations, alternatives, and modifications.

[0057] As shown, the analyzer 400 may include an input 402 that may receive signals from various sources. For example, the input 402 may be configured to receive a first signal from a receiver. The first signal may include a signal received by the receiver (e.g., Figure 2 The analyzer 400 may be configured to convert the raw I / Q data into spectrum data to perform frequency domain analysis on the received signal, thereby providing a detailed analysis of the frequency content and power distribution within the spectrum.

[0058] In various embodiments, the analyzer 400 further includes a processor 404 coupled to the input 402. The processor 404 may include, but is not limited to, a microprocessor, a microcontroller, a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or other devices that execute signal processing algorithms and functions. Depending on the embodiment, the processor 404 may also incorporate specialized hardware accelerators to enhance specific tasks (such as FFT calculations or magnitude calculations) to ensure real-time processing capabilities for complex signal environments.

[0059] In some examples, the processor 404 may be configured to apply a windowing function to the first signal to reduce discontinuities and sudden changes in the signal. The processor 404 may be further configured to generate a second signal based on the first signal by an FFT. For example, the first signal may include a time domain signal and the second signal may include a frequency domain signal. In some examples, the second signal may include a first frequency component. The processor 404 may calculate one or more magnitude values ​​associated with the first frequency component. For example, the processor 404 may be configured to calculate a first magnitude associated with the first frequency component at a first timestamp. The first magnitude can be calculated by converting a complex number from the FFT into a real value representing the intensity or power of the signal at the corresponding frequency. In some embodiments, the processor 404 may be configured to calculate a second magnitude associated with the first frequency component at a second timestamp. Depending on the implementation, the first and second timestamps may be characterized by predetermined time intervals (e.g., 5 μs, 10 μs, 20 μs, 40 μs, etc.).

[0060] According to some embodiments, the magnitude values ​​calculated by processor 404 may be accumulated over multiple FFT frames. For example, memory 408 may be coupled to processor 404 and configured to store the first magnitude and the second magnitude. Memory 408 may include volatile memory and / or non-volatile memory, such as random access memory (RAM), read-only memory (ROM), flash memory, and / or the like. Memory 408 may use volatile memory for fast access and non-volatile memory for long-term data retention and recovery. For example, volatile memory may be configured to store intermediate calculation results and instructions currently being executed by processor 404. Non-volatile memory may be configured to store spectrum analysis results, user preferences, and / or software including signal processing algorithms and firmware updates. In some cases, memory 408 may be configured to store instructions for performing various signal processing functions, such as FFT calculations, digital filtering, mathematical operations, and / or the like. In some embodiments, the memory architecture may be designed to enhance the efficiency of data flow between processor 404 and memory 408. For example, memory 408 may further include a memory controller configured to manage communications and data transfers between memory 408 and processor 404 .

[0061] In various embodiments, the processor 404 may retrieve the first and second magnitudes from the memory 408 and calculate a third magnitude associated with the first frequency component. For example, the third magnitude may be determined by calculating an average based on at least the first and second magnitudes. The processor 404 may generate a spectral representation of the first signal based at least on the third magnitude, which improves power estimation for optimizing frequency allocation and enhancing overall communication quality. In some cases, the processor 404 may be configured to convert the third magnitude from a linear scale to a logarithmic scale to facilitate understanding and representation of the power estimate of the signal. In other examples, the processor 404 may be configured to perform gain compensation based on the magnitude of a gain adjustment signal applied at various stages of the receiver. Depending on the application, the processor 404 may support various advanced communication technologies, such as adaptive frequency hopping (AFH), RSSI calibration acceleration, AGC optimization, and / or the like.

[0062] In some embodiments, a user interface 406 may be coupled to the processor 404. The user interface 406 allows real-time feedback and control, thereby enabling a user to interact with the analyzer 400. For example, the user interface 406 may include a display (e.g., a liquid crystal display (LCD), a light emitting diode (LED), or an organic light emitting diode (OLED)) to allow a user to view the spectrum representation and analysis results. The user interface 406 may further include, but is not limited to, a keyboard, a mouse, a touch screen, a speaker, a microphone, or other input and output devices that allow a user to adjust operating settings and parameters based on a particular application and user preferences.

[0063] In various embodiments, the analyzer 400 further includes an output 410 coupled to the processor 404. The output 410 can be configured to transmit the second signal or the analysis results to other components or external devices. In some cases, the output 410 can be configured to output the spectrum representation generated by the processor 404. The output 410 can include, but is not limited to, a connector, a cable, a transmitter, a modulator, or other devices that facilitate transmitting and encoding signals. Depending on the implementation, the output 410 can support various communication protocols and standards, such as USB, HDMI, Ethernet, Wi-Fi, Bluetooth, and / or the like.

[0064] While the above is a complete description of specific embodiments, various modifications, alternative constructions, and equivalents may be used. Therefore, the above description and illustrations should not be taken as limiting the scope of the present technology, which is defined by the appended claims.

Claims

1. A device comprising: an input configured to receive a first signal; a processor coupled to the input, the processor configured to: generating a second signal based on the first signal, the second signal including a first frequency component; calculating a first magnitude associated with the first frequency component at a first time stamp; calculating a second magnitude associated with the first frequency component at a second time stamp; calculating a third magnitude associated with the first frequency component by calculating an average based on at least the first magnitude and the second magnitude; and A memory is coupled to the processor, the memory being configured to store at least the first magnitude and the second magnitude. 2 . The apparatus of claim 1 , wherein the processor is further configured to apply a windowing function to the first signal.

3. The apparatus of claim 1, further comprising a memory controller configured to manage data transfers between the processor and the memory. The apparatus of claim 1 , wherein the first timestamp and the second timestamp are characterized by a predetermined time interval. The apparatus of claim 1 , wherein the first signal comprises a time-domain signal and the second signal comprises a frequency-domain signal.

6. The apparatus of claim 1, wherein the processor is further configured to generate a spectral representation of the first signal based at least on the third magnitude.

7. The apparatus of claim 1, wherein the processor is further configured to convert the third magnitude from a linear scale to a logarithmic scale.

8. The apparatus of claim 1, wherein the processor is further configured to adjust the third magnitude based on a gain applied to the first signal.

9. A device comprising: A receiver configured to receive a first signal, the receiver comprising: an amplifier configured to amplify the first signal; a first filter coupled to the amplifier via a first node, the first filter configured to filter the first signal; an analog-to-digital converter ADC coupled to the first filter via a second node; and a control module configured to measure a first signal strength at the first node and a second signal strength at the second node; and an analyzer coupled to the receiver, the analyzer configured to: generating a second signal based on the first signal, the second signal including a first frequency component; calculating a first magnitude associated with the first frequency component at a first time stamp; calculating a second magnitude associated with the first frequency component at a second time stamp; and A third magnitude associated with the first frequency component is calculated by calculating an average based on at least the first magnitude and the second magnitude.

10. The apparatus of claim 9, wherein the receiver further comprises a signal processor coupled to the ADC through a third node, and the control module is configured to measure a third signal strength at the third node.

11. The apparatus of claim 10, wherein the control module is configured to adjust a gain of the amplifier based on at least the first signal strength, the second signal strength, and the third signal strength.

12. The apparatus of claim 9, wherein: The ADC is configured to convert the first signal into a digital signal; and The receiver further includes a second filter coupled to the ADC, the second filter configured to reduce a sampling rate of the digital signal.

13. The apparatus of claim 9, wherein the analyzer further comprises a memory configured to store at least the first magnitude and the second magnitude. The apparatus of claim 9 , wherein the first timestamp and the second timestamp are characterized by a predetermined time interval.

15. The apparatus of claim 9, wherein the first signal strength is associated with a first frequency range, the second signal strength is associated with a second frequency range, and the second frequency range is narrower than the first frequency range.

16. The apparatus of claim 9, wherein the analyzer is further configured to generate a spectral representation of the first signal based at least on the third magnitude.

17. The apparatus of claim 9, wherein the control module is coupled to the analyzer.

18. An apparatus comprising: an input configured to receive a first signal; a processor coupled to the input, the processor configured to: generating a second signal based on the first signal, the second signal including a first frequency component; calculating a first magnitude associated with the first frequency component at a first time stamp; calculating a second magnitude associated with the first frequency component at a second time stamp; calculating a third magnitude associated with the first frequency component by calculating an average based on at least the first magnitude and the second magnitude; and generating a spectral representation of the first signal based at least on the third magnitude; a memory coupled to the processor, the memory configured to store at least the first magnitude and the second magnitude; and An output, coupled to the processor, is configured to output the spectral representation.

19. The apparatus of claim 18, further comprising a memory controller configured to manage data transfers between the processor and the memory.

20. The apparatus of claim 18, wherein the first timestamp and the second timestamp are characterized by a predetermined time interval.

Images