System and method for estimating signal-to-noise ratio (SNR) and noise dispersion from error vector amplitude (EVM).

Abstract

This invention provides an orthogonal amplitude modulation (QAM) modulation system and method for estimating the signal-to-noise ratio (SNR) and noise dispersion from error vector amplitude (EVM) using a fixed lookup table mapping. [Solution] The device includes a receiver that receives data and a circuit which is a system 200, the circuit which receives at least one or more symbols based on the data, uses one or more symbols to determine an error vector amplitude (EVM) value, determines a quadrature amplitude modulation (QAM) size, uses the EVM value and QAM size to determine a signal-to-noise ratio (SNR) value, and adjusts the transmission speed of the transmitter based at least the SNR value.

Description

Technical Field

[0001] Cross - reference to Related Applications This application claims the benefit and priority of U.S. Provisional Patent Application No. 63 / 716454, filed on November 5, 2024, which is incorporated herein by reference in its entirety for all purposes.

[0002] Field of Disclosure The present disclosure generally relates to systems and methods for estimating signal - to - noise ratio (SNR) and noise variance from error vector magnitude (EVM) using mapping of a fixed look - up table, with respect to quadrature amplitude modulation (QAM) modulation systems.

Background Art

[0003] Due to the increasing use of mobile devices, the increasing connectivity and data transfer between all kinds of devices, the market for wireless communication devices has continued to grow. Digital switching technology has facilitated the large - scale deployment of affordable and easy - to - use wireless communication networks. Wireless communication can operate according to various standards such as IEEE802.11x (e.g., Wi - Fi technology), Bluetooth®, Global System for Mobile Communications (GSM), and Code Division Multiple Access (CDMA). By using such technologies, wireless communication devices can connect to local area networks and the Internet without using physical cables and communicate over various frequencies across various spaces and ranges.

[0004] Various purposes, aspects, features, and advantages of this disclosure will be more apparent and better understood by referring to the detailed description made in relation to the accompanying drawings. In the accompanying drawings, similar reference numerals throughout identify corresponding elements. In the drawings, similar reference numerals generally indicate identical elements, functionally similar elements, and / or structurally similar elements. [Brief explanation of the drawing]

[0005] [Figure 1A] This block diagram shows a network environment in several embodiments. [Figure 1B] This block diagram shows computing devices useful in relation to the methods and systems described herein, according to several embodiments. [Figure 1C] This block diagram shows computing devices useful in relation to the methods and systems described herein, according to several embodiments. [Figure 2] This is a block diagram of an exemplary system according to one or more embodiments. [Figure 3A] This figure shows exemplary plots illustrating the nonlinear relationship between SNR and EVN according to one or more embodiments. [Figure 3B] This figure shows an exemplary LUT according to one or more embodiments. [Figure 4A] This figure shows exemplary plots illustrating the nonlinear relationship between SNR and EVN according to one or more embodiments. [Figure 4B] This figure shows an exemplary LUT according to one or more embodiments. [Figure 5] This figure shows an exemplary plot illustrating the relationship between SNR and EVN according to one or more embodiments. [Figure 6A] This figure shows an example of a transmission constellation according to one or more embodiments. [Figure 6B]This figure shows an example of a receiving constellation corresponding to the transmitting constellation in Figure 6A, according to one or more embodiments. [Figure 7A] This figure shows an example of a transmission constellation according to one or more embodiments. [Figure 7B] This figure shows an example of a receiving constellation corresponding to the transmitting constellation in Figure 7A, according to one or more embodiments. [Figure 8] This is a flowchart illustrating the process of estimating SNR and noise variance from EVM according to one embodiment.

[0006] Detailed explanation The following disclosure provides many different embodiments or examples for realizing different features of the subject matter provided. For the sake of brevity of this disclosure, specific examples of components and arrangements are described below. Naturally, these are merely examples and are not intended to be limiting. For example, in the following description, the communication or communicative coupling of a first feature element with a second feature element may include embodiments in which the first feature element directly communicates or is directly coupled with the second feature element, and may also include embodiments in which an additional feature element is interposed between the first and second feature elements so that the first feature element communicates or is indirectly coupled with the second feature element. Furthermore, this disclosure may repeat reference numerals and / or letters in various examples. This repetition is for the sake of brevity and clarity and does not in itself determine the relationships between the various embodiments and / or configurations described.

[0007] The following IEEE standards, including any draft of any IEEE standard(s), namely the Wi-Fi Alliance standards and, but not limited to, the IEEE 802.11a®, IEEE 802.11b®, IEEE 802.11g®, IEEE 802.11n®, IEEE 802.11ac®, and IEEE P802.11be® through IEEE P802.11bn® standards, are incorporated herein by reference in their entirety and form part of this disclosure for all purposes. This disclosure may refer to aspects of these standards(s), but is not limited in any way by these standards(s).

[0008] The following descriptions of this specification and their individual contents may be useful in reading the descriptions of the various embodiments below. That is, - Section A describes network and computing environments that may be useful for carrying out the embodiments described herein, and Section B describes embodiments of systems and methods for estimating the signal-to-noise ratio (SNR) and noise variance from error vector amplitude (EVM).

[0009] A. Computing and network environment Before considering specific embodiments of this solution, it may be beneficial to describe the operating environment and associated system components (e.g., hardware components) in relation to the methods and systems described herein. Referring to Figure 1A, one embodiment of a network environment is shown. In outline, the network environment includes a wireless communication system comprising one or more access points (APs) or network devices 106, one or more stations or wireless communication devices 102, and network hardware components or network hardware 192. The wireless communication device 102 may include, for example, a notebook computer, a tablet, a personal computer, and / or a mobile phone device. Details of one embodiment of each station or wireless communication device 102 and AP or network device 106 will be described in more detail with reference to Figures 1B and 1C. In one embodiment, the network environment may be an ad-hoc network environment, an infrastructure wireless network environment, a subnet environment, etc. The network device 106 or AP may be operably coupled to the network hardware 192 via a local area network connection. In some embodiments, the network device 106 is a 5G base station. Network hardware 192, which may include routers, gateways, switches, bridges, modems, system controllers, and electrical appliances, can provide a local area network connection to the communication system. Each network device 106 or AP may have associated antennas or antenna arrays for communicating with wireless communication devices in its area. Wireless communication devices 102 may register with specific network devices 106 or APs to receive services from the communication system (e.g., via SU-MIMO or MU-MIMO configurations). In the case of direct connections (e.g., point-to-point communication), several wireless communication devices may communicate directly via assigned channels and communication protocols. Some of the wireless communication devices 102 may be mobile or relatively stationary relative to the network devices 106 or APs.

[0010] In some embodiments, the network device 106 or AP includes a device or module (including a combination of hardware and software) that enables the wireless communication device 102 to connect to a wired network using Wireless Fidelity® (WiFi) or other standards. The network device 106 or AP may sometimes be referred to as a wireless access point (WAP). The network device 106 or AP may be implemented (e.g., configured, designed, and / or built) to operate in a wireless local area network (WLAN). In some embodiments, the network device 106 or AP may connect to a router as a standalone device (e.g., via a wired network). In other embodiments, the network device 106 or AP may be a component of a router. The network device 106 or AP may provide multiple device access to the network. The network device 106 or AP may, for example, connect to a wired Ethernet® connection and provide a wireless connection using a radio frequency link to another device 102 to utilize that wired connection. Network devices 106 or APs may be implemented to support standards for transmitting and receiving data using one or more radio frequencies. These standards and frequencies they use may be defined by the IEEE (e.g., the IEEE 802.11 standard). Network devices 106 or APs may be configured and / or used to support public internet hotspots and / or to extend the network's Wi-Fi signal range over the network.

[0011] In some embodiments, the access point or network device 106 may be used in a wireless network (e.g., in a home, car, or building) (e.g., any other type of radio frequency based on IEEE 802.11, Bluetooth, Zigbee®, network protocols, and / or variations thereof). Each of the wireless communication devices 102 may include and / or be coupled to an embedded radio. Such wireless communication devices 102, and / or access point or network device 106, may operate according to various aspects of the disclosure, such as those presented herein, to enhance performance, reduce cost and / or size, and / or enhance broadband application forms. Each wireless communication device 102 may have the ability to function as a client node seeking access to resources (e.g., data, and connections to networked nodes such as servers) via one or more access point or network device 106.

[0012] Network connectivity may include any type and / or form of network, including any of the following: point-to-point networks, broadcast networks, telecommunications networks, data communication networks, and computer networks. The network topology may be bus, star, or ring network topology. The network may consist of any such network topology known to those skilled in the art that is capable of supporting the operations described herein. In some embodiments, different types of data may be transmitted via different protocols. In other embodiments, the same type of data may be transmitted via different protocols.

[0013] The communication device(s) 102 and the access point(s) or network device(s) 106 may be deployed and / or run on such computing device(s) of any type and form, such as a computer, network device or electrical appliance, which can communicate over any type and form of network and perform the operations described herein. Figures 1B and 1C show block diagrams of computing device(s) 100 useful for carrying out one embodiment of the wireless communication device(s) 102 or network device(s) 106. As shown in Figures 1B and 1C, each computing device(s) 100 includes a processor(s) 121 (e.g., a central processing unit) and main memory(s) 122. As shown in Figure 1B, the computing device(s) 100 may include a storage device(s) 128, an installation device(s) 116, a network interface(s) 118, an I / O controller(s) 123, display devices(s) 124a-124n), a keyboard(s) 126, and a pointing device(s) 127 such as a mouse. The storage device 128 may include an operating system and / or software. As shown in Figure 1C, each computing device 100 may also include additional optional elements such as a memory port 103, a bridge 170, one or more input / output devices 130a-130n, and a cache memory 140 that communicates with a central processing unit or processor 121.

[0014] The central processing unit or processor 121 is any logic circuit that responds to and processes instructions fetched from main memory 122. In many embodiments, the central processing unit or processor 121 is provided by a microprocessor device, such as one manufactured by Intel Corporation in Santa Clara, California, by International Business Machines in White Plains, New York, or by Advanced Micro Devices in Sunnyvale, California. The computing device 100 may be based on any of these processors or any other processor capable of operating as described herein.

[0015] The main memory 122 can be one or more memory chips capable of storing data and enabling direct access by the microprocessor or processor 121 to any storage location, such as static RAM (SRAM), dynamic RAM (DRAM), ferroelectric memory (FRAM), NAND flash memory, NOR flash memory, and any variant of a semiconductor drive (SSD). The main memory 122 can be based on any of the memory chips described above, or any other available memory chip capable of operating as described herein. In the embodiment shown in Figure 1B, the processor 121 communicates with the main memory 122 via the system bus 150 (described in more detail later). Figure 1C shows one embodiment of a computing device 100 in which the processor communicates directly with the main memory 122 via a memory port 103. For example, in Figure 1C, the main memory 122 can be DRDRAM.

[0016] FIG. 1C shows an embodiment in which the main processor 121 communicates directly with the cache memory 140 via a secondary bus sometimes called a backside bus. In other embodiments, the main processor 121 communicates with the cache memory 140 using the system bus 150. The cache memory 140 generally has a faster response time than the main memory device 122 and is provided, for example, by SRAM, BSRAM, or EDRAM. In the embodiment shown in FIG. 1C, the processor 121 communicates with various I / O devices 130 via the local system bus 150. Various buses can be used to connect the central processing unit or processor 121 to any of the I / O devices 130, for example, the VESA VL bus, ISA bus, EISA bus, Micro Channel Architecture (MCA) bus, PCI bus, PCI-X bus, PCI-Express bus, or NuBus. For embodiments in which the I / O device is the video display 124, the processor 121 can use an AGP (Advanced Graphics Port) to communicate with the display 124. FIG. 1C shows an embodiment of a computer or computer system 100 in which the main processor 121 can communicate directly with an I / O device 130b via, for example, HyperTransport, RapidIO, or InfiniBand communication technology. Also, FIG. 1C shows an embodiment in which direct communication with the local bus is mixed, that is, the processor 121 communicates directly with the I / O device 130b while communicating with the I / O device 130a using the local interconnect bus.

[0017] A wide variety of I / O devices 130a to 130n may be present in the computing device 100. Input devices include keyboards, mice, trackpads, trackballs, microphones, dials, touchpads, touchscreens, and drawing tablets. Output devices include video displays, speakers, inkjet printers, laser printers, projectors, and dye-sublimation printers. The I / O devices may be controlled by an I / O controller 123, as shown in Figure 1B. The I / O controller can control one or more I / O devices, such as a keyboard 126 and a pointing device 127 (e.g., a mouse or optical pen). Furthermore, the I / O devices may also provide storage devices and / or installation media to the computing device 100. In yet another embodiment, the computing device 100 may provide a USB connection (not shown) for accepting portable USB storage devices, such as the USB flash drive product line of devices manufactured by Twintech Industry, Inc. in Los Alamitos, California.

[0018] Referring again to FIG. 1B, computing device 100 can support any suitable installation device 116, such as a disk drive, CD-ROM drive, CD-R / RW drive, DVD-ROM drive, flash memory drive, tape drives of various formats, USB devices, hard drives, network interfaces, or any other device suitable for installing software and programs. Computing device 100 can further include a storage device, such as one or more hard disk drives or redundant arrays of independent disks, for storing an operating system and other related software, and for storing application software programs, such as any program or software 120 (e.g., configured and / or designed for the system and method) for implementing the systems and methods described herein. If desired, any of the installation devices 116 can also be used as a storage device. Further, the operating system and software can be executed from a bootable medium.

[0019] Furthermore, the computing device 100 may include a network interface 118 for connecting to a network through various connections, which may include, but are not limited to, standard telephone lines, LAN or WAN links (e.g., 802.11, T1, T3, 56kb, X.25, SNA, DECnet), broadband connections (e.g., ISDN, Frame Relay, ATM, Gigabit Ethernet, Ethernet overSonnet), wireless connections, or any or any combination of the above. The connection can be established using various communication protocols (e.g., TCP / IP, IPX, SPX, NetBIOS, Ethernet, ArcNet, SONET, SDH, FDDI (FiberDistributed Data Interface), RS232, IEEE802.11, IEEE802.11a, IEEE802.11b, IEEE802.11g, IEEE802.11n, IEEE802.11ac, IEEE802.11ad, CDMA, GSM, WiMAX, and direct asynchronous connection). In one embodiment, computing device 100 communicates with other computing devices 100' via any type and / or form of gateway or tunneling protocol, such as SSL (Secure Socket Layer) or TLS (Transport Layer Security). The network interface 118 may include a built-in network adapter, network interface card, PCMCIA network card, CardBus network adapter, wireless network adapter, USB network adapter, modem, or any other device suitable for connecting a computing device 100 capable of communicating and performing the operations described herein to any type of network.

[0020] In some embodiments, the computing device 100 may include, or be connected to, one or more display devices 124a-124n. Therefore, any of the I / O devices 130a-130n and / or the I / O controller 123 may include any type and / or form of appropriate hardware, software, or combination of hardware and software to support, enable, or perform the connection and use of the display devices (one or more) 124a-124n by the computing device 100. For example, the computing device 100 may include any type and / or form of video adapter, video card, driver, and / or library for interface with, communicate with, connect to, or otherwise use the display devices (one or more) 124a-124n. In one embodiment, the video adapter may include multiple connectors for interface with the display devices (one or more) 124a-124n. In other embodiments, the computing device 100 may include multiple video adapters, in which case each video adapter is connected to one or more display devices 124a-124n. In some embodiments, some part of the operating system of the computing device 100 may be configured to use the multiple display devices 124a-124n. In further embodiments, the I / O device 130 may act as a bridge between the system bus 150 and an external communication bus, which is, for example, a USB bus, Apple Desktop Bus, RS-232 serial connection, SCSI bus, FireWire bus, FireWire 800 bus, Ethernet bus, AppleTalk bus, Gigabit Ethernet bus, asynchronous transfer mode bus, Fibre Channel bus, optical fiber bus, SAS (Serial Attached SCSI) bus, USB connection, or HDMI bus.

[0021] The computing device 100 of the type shown in Figures 1B and 1C can operate under the control of an operating system that controls task scheduling and access to system resources. The computing device 100 can run any operating system, such as any version of the Microsoft Windows® operating system, various publicly available Unix® and Linux operating systems, any version of MAC OS for Macintosh computers, any embedded operating system, any real-time operating system, any open-source operating system, any proprietary operating system, any operating system for mobile computing devices, or any other operating system that runs on the computing device and can perform the operations described herein. Representative operating systems include, but are not limited to, Android®, produced by Google Inc.; Windows® 7, 8, and 10, produced by Microsoft Corporation in Redmond, Washington; MAC OS, produced by Apple Computer in Cupertino, California; WebOS, produced by Research In Motion (RIM); OS / 2, produced by International Business Machines in Armonk, New York; and Linux, a free and available operating system distributed by Caldera Corp. in Salt Lake City, Utah, or any type and / or form of Unix operating system.

[0022] The computer system or computing device 100 can be any workstation, telephone, desktop computer, laptop or note computer, server, portable computer, mobile phone or other portable communication device, media playback device, game console, mobile computing device, or any other type and / or form of computing device, communication device or media device capable of communication. In some embodiments, the computing device 100 can have various processors, operating systems, and input devices compatible with the device. For example, in one embodiment, the computing device 100 is a smartphone, mobile device, tablet or personal digital assistant. Furthermore, the computing device 100 can be any workstation, desktop computer, laptop or note computer, server, portable computer, mobile phone, any other computer, or any other form of computing device or communication device capable of communication and having sufficient processor power and memory capacity to perform the operations described herein.

[0023] The aforementioned operating environments and configurations will become clear in relation to the systems and methods disclosed herein.

[0024] B. Estimation of signal-to-noise ratio and noise dispersion from error vector amplitude In communication systems, accurate signal quality estimation (e.g., SNR, noise variance) is useful for optimizing performance in various application forms, such as maximum posterior probability (MAP) based detection, iterative demapping of single-input single-output (SISO) and multiplexed input / output (MIMO) systems, least mean squares error (MMSE) receivers, noise whitening circuits, rate adaptation based on signal-to-interference ratio (SINR) and / or SNR feedback, feedback systems, and low-density parity check (LDPC) decoders where the input log-likelihood ratio (LLR) is scaled by noise variance. In particular, SNR estimation plays a crucial role in rate adaptation in wireless communication systems such as WiFi (e.g., 802.11ax / be / bn) and LTE. Rate adaptation allows the system to dynamically adjust transmission parameters (e.g., modulation scheme and encoding scheme) to match the current channel conditions, improving data throughput while maintaining a reliable connection. For example, a higher SNR indicates a cleaner signal with less noise interference, enabling faster and more efficient data transmission. Transmitters can use more complex modulation schemes with higher data rates (e.g., 64-QAM, 256-QAM, and even 1024-QAM) that transmit more bits per symbol. Conversely, a lower SNR indicates poor channel condition, in which case using complex modulation can lead to errors. In such cases, the system can be adapted by using a more robust but lower data rate modulation scheme (e.g., QPSK or BPSK) that is less susceptible to errors, although it has fewer bits per symbol.

[0025] Generally, a receiver estimates the signal-to-noise ratio (SNR) or a related indicator (measure) of the SNR (e.g., EVM) of the received signal and can send this information back to the transmitter, for example, across the entire link or per subcarrier (e.g., in OFDM-based systems such as WiFi and LTE). Based on this feedback, the transmitter can dynamically adjust its transmission speed. In some implementations, EVM can be used instead, and the transmitter decodes the SNR based on the available information received. Generally, different SNR ranges are suited to different modulation and coding schemes (MCS). Each MCS defines a modulation scheme (e.g., BPSK, QPSK, 16-QAM, 64-QAM, 256-QAM, 1024-QAM) with a coding rate that specifies how much error correction is applied to the transmitted data. In some systems, a predefined mapping exists between SNR and MCS, so when the transmitter receives SNR feedback, it selects the most appropriate MCS corresponding to the reported SNR, thereby selecting the best MCS that the current SNR can support with reduced errors. For example, for lower SNRs (e.g., <10dB), the transmitter may use BPSK or QPSK with a lower coding rate (more redundancy) to ensure reliable communication. For medium SNRs (e.g., 15-20dB), the transmitter may switch to 16-QAM or 64-QAM with a medium coding rate to improve throughput. For higher SNRs (e.g., >30dB), the transmitter may use 256-QAM or 1024-QAM with a higher coding rate (less redundancy) to maximize data throughput. Radio channels are dynamic and adapt to changing channel conditions (e.g., due to movement, interference, or environmental factors). For example, as the SNR increases, feedback to the transmitter allows for switching to a higher data rate by using higher-order modulation and a higher coding rate.As the SNR decreases, feedback ensures that the transmitter reduces the data rate by switching to a more robust MCS, thereby maintaining reliability and minimizing errors. This adjustment optimizes performance while balancing maximum throughput with reliability.

[0026] However, accurate SNR estimation is difficult and often relies on approximations, heuristic methods, or pre-signal and measured values ​​during idle periods, which require significant resources and are time-constrained. This is especially true when signal quality can vary from packet to packet. In digital modulation communication systems, EVM is easier to calculate than SNR, but its relationship to SNR is not simple (e.g., not a one-to-one mapping) and varies with QAM size. This limitation leads to inefficiencies in system optimization and feedback mechanisms. Furthermore, since the exact transmitted symbol is unknown at the receiver, data-assisted EVM calculation is impractical, although non-data-assisted (NDA) EVM can be used to measure EVM. NDA-EVM is easier to calculate and does not require knowledge of QAM size, making it a more practical alternative.

[0027] This disclosure addresses the aforementioned challenges by providing a signal quality estimation technique that improves accuracy and reliability, thereby optimizing the performance of communication systems across various application modes. This disclosure provides a technique for estimating SNR and noise dispersion from EVM. Unlike conventional methods that rely on approximations or heuristic mapping, the technique disclosed herein establishes an accurate one-to-one relationship between EVM and SNR for any QAM size by establishing a nonlinear relationship between NDA-EVM and SNR for a given QAM size. In some embodiments, the technique includes a fixed lookup table (LUT) or dictionary pre-computed and stored for efficient retrieval to map the relationship between EVM and SNR, enabling accurate and computationally efficient SNR estimation. This improves signal quality evaluation in various application modes, including, but not limited to, receivers, transmitters, and any system where high-precision signal characterization is used. As used herein, “Lookup Table (LUT)” may mean an array that replaces runtime computation with simpler array indexing operations, an embodiment of an attribute that stores attribute information in columns of identifiers and / or descriptions, a data structure that stores information for one or more related attributes, or any data structure that maps input values ​​to output values.

[0028] With the foregoing in mind, the following drawings and description illustrate various examples of techniques relating to SNR and noise variance estimation from EVM. The following drawings and description are non-limiting examples and may be realized in any of various other configurations, while remaining within the scope of this disclosure. Other embodiments may be used as additions or substitutes. Details that may be apparent to those skilled in the art may be omitted. Some embodiments may be carried out with additional components or steps, and / or without using all of the components or steps described.

[0029] Figure 2 shows a block diagram of an exemplary system 200 according to one or more embodiments. System 200 may be part of a “device” (e.g., a circuit). As used herein, “device” may mean a device (e.g., device 102), a network device (e.g., network device 106), or any device for facilitating and / or forming a wireless communication network. In some embodiments, the device may include a “transmitter,” a “receiver,” and / or various circuit components. As used herein, “transmitter” may mean a radio frequency (RF) transmitter, an optical transmitter, a millimeter-wave transmitter, a baseband signal generator, or any device, circuit, or system capable of generating, encoding, and transmitting radio signals over a communication medium. As used herein, “receiver” may mean an RF receiver, an optical receiver, a millimeter-wave receiver, or any device, circuit, or system capable of receiving, decoding, and processing radio signals from a communication medium.

[0030] In some embodiments, System 200 may be a “circuit” or may include a “circuit.” As used herein, “circuit” may mean any combination of analog or digital circuits, integrated circuits (ICs), system-on-chip (SoC) components, field-programmable gate arrays (FPGAs), microcontrollers, processors, or software, firmware, and / or hardware configured to perform signal transmission, reception, processing, or control functions in a wireless communication system. In some embodiments, System 200 may be a receiver circuit.

[0031] System 200 is shown to include a demodulator 210, a decoder 220, an EVM-NDA unit 230, and a function mapping unit 240. Each of the demodulator 210, decoder 220, EVM-NDA unit 230, and function mapping unit 240 may be, or include, circuitry, firmware, or software that can be configured to process a given data.

[0032] In short, the device includes a receiver configured to receive data. System 200 may be configured to receive one or more symbols (e.g., rx (receive) symbols 21) based on the data. Demodulator 210 may be configured to receive one or more symbols (e.g., rx symbols 21). Demodulator 210 may be configured to send a log-likelihood ratio (LLR) 22 to decoder 220 for further rx (receive) processing 29. Demodulator 210 may be configured to send an estimated symbol vector 24 to EVM-NDA unit 230. EVM-NDA unit 230 may be configured to receive a transmitted symbol vector 23 based on one or more symbols (e.g., rx symbols 21). EVM-NDA unit 230 may be configured to determine an EVM value 25 using one or more symbols (e.g., rx symbols 21). The EVM-NDA unit 230 may be configured to send the EVM value 25 to the function mapping unit 240. The function mapping unit 240 may be configured to receive and / or identify the QAM size 26. The function mapping unit 240 may be configured to determine the SNR value 28 using the EVM value 25 and the QAM size 26. The system 200 and / or its apparatus may be configured to adjust the transmitter's transmission speed based on at least the SNR value 28.

[0033] While a receiver circuit is described and illustrated, System 200 can be implemented for any other device components without departing from the concept and scope. In some embodiments, the device may include a transmitter configured to transmit data. The device may include a transmitter circuit configured to receive one or more symbols based on data received by at least the receiver. The transmitter circuit may be configured to determine an EVM value using one or more symbols. The transmitter circuit may include a function mapping unit 240 configured to receive and / or identify a QAM size (e.g., QAM size 26). The function mapping unit 240 of the transmitter circuit may be configured to determine an SNR value (e.g., SNR value 28) using the EVM value and the QAM size. The transmitter circuit and / or device may be configured to adjust the transmission rate based on at least the SNR value. The transmitter of the device may be configured to transmit data using the transmission rate (e.g., adjusted based on at least the SNR value).

[0034] The device may be configured to receive various types of data. As used herein, “data” may mean digital or analog information, including, but not limited to, bitstreams, encoded symbols, packets, frames, control signals, content, sensor readings, or any information that may be received, transmitted, modulated, processed, or stored in a wireless communication system.

[0035] The receiver of the device may be configured to receive data. The device's system 200 (e.g., receiver circuit) may be configured to receive rx symbols 21 based on data. The demodulator 210 may be configured to process the rx symbols 21 by mapping them to LLR 22, which indicates the probability that each bit is "0" or "1". As used herein, “symbol” may mean a unit of encoded data representing one or more bits that is modulated into a carrier signal for transmission in a wireless communication system, and may include, but is not limited to, QAM symbols, phase-shifted keying (PSK) symbols, or any modulated data representation that can be transmitted, received, and processed in a communication network. The demodulator 210 may be configured to send LLR 22 to the decoder 220. The decoder 220 may be configured to reconstruct the original transmitted data by applying various algorithms (e.g., error correction algorithms, decoding algorithms, etc.). The decoder 220 may be configured to output the reconstructed data to further rx processing 29.

[0036] The demodulator 210 may be configured to process the rx symbol 21 to generate an estimated symbol vector 24. In some embodiments, the estimated symbol vector 24 may be determined based on a decision-directed method that demodulates the received signal to generate an estimate of the transmitted symbol. In some embodiments, the estimated symbol vector 24 may be determined based on a predefined evaluation criterion (e.g., one defined in the IEEE 8802.11 standard). In some embodiments, the rx symbol 21 can be demodulated using the maximum likelihood (or a similar criterion) to generate the estimated symbol vector 24. Meanwhile, the transmitted symbol vector 23 (e.g., representing an expected or known transmitted symbol vector) may be determined based on the rx symbol 21.

[0037] The EVM-NDA unit 230 may be configured to determine the EVM value 25 using the rx symbol 21. In some embodiments, the EVM-NDA unit 230 may be configured to generate the EVM value 25 by processing the transmitted symbol vector 23 and the estimated symbol vector 24. In some embodiments, the EVM-NDA unit 230 may be configured to calculate the EVM value 25 by averaging the Euclidean distance between the transmitted symbol vector 23 and the estimated symbol vector 24. More specifically, the EVM can be a measure of the deviation of the received signal from an ideal transmitted signal, quantifying the amount of distortion in the received signal (e.g., noise, channel effects, etc.). For example, the NDA-EVM is: TIFF2026082764000002.tif9165 It can be defined as follows, where Y is the received signal vector. TIFF2026082764000003.tif6163 This is the estimated transmission symbol vector (e.g., provisional equalization, estimated symbol vector 24, etc.).

[0038] The function mapping unit 240 may be configured to receive and / or identify the QAM size 26. As used herein, the term “QAM size” (which may also be represented herein as “M”) may mean the number of different symbols used in QAM, thereby determining the number of bits represented by each symbol, such as 16-QAM (4 bits per symbol), 64-QAM (6 bits per symbol), or any other size representing the modulation order that defines the data rate and spectral efficiency of the communication system. In some embodiments, the function mapping unit 240 may be configured to identify the QAM size 26 by analyzing characteristics of the received signal, such as the spacing between symbols in the modulation constellation. In some embodiments, the function mapping unit 240 may be configured to receive the QAM size 26 from predefined system parameters or reference signals transmitted with the data. In some embodiments, the function mapping unit 240 may be configured to identify the QAM size 26 from a modulation and coding scheme (MCS) table. As used herein, “MCS table” may mean a lookup table (e.g., an MCS lookup table), a matrix, or any data structure that stores QAM size 26, including, for example, various modulation schemes and coding rates for a particular transmission speed.

[0039] The function mapping unit 240 may be configured to determine an estimated SNR value 28 using the EVM value 25 and the QAM size 26. In some embodiments, the function mapping unit 240 may be configured to determine an estimated SNR value 28 based on an M dependency between the EVM value 25 and the SNR value 28. That is, the function mapping unit 240 may be configured to determine a function of SNR and QAM size M (e.g., EVM 2The function mapping unit 240 may be configured to generate and / or identify an estimated SNR value 28 based on =f(SNR,M)). The function mapping unit 240 may be configured to generate and / or identify an estimated SNR value 28 using a nonlinear relationship between the SNR value 28 and the QAM size 26. In some embodiments, the function mapping unit 240 may be configured to generate and / or identify an estimated SNR value 28 based on the following equation.

[0040]

number

[0041] In some embodiments, the function mapping unit 240 may be configured to generate an estimated SNR 28 by mapping the EVM value 25 to the SNR based on the relationship between the EVM value 25 and the SNR value 28 (e.g., equation (1)). In some embodiments, the function mapping unit 240 may be configured to generate an estimated SNR 28 by inversely mapping the SNR to the EVM value 25 based on the relationship between the EVM value 25 and the SNR value 28 (e.g., equation (1)). As shown above, in some embodiments, the function mapping unit 240 may be configured to calculate an estimated SNR value 28 corresponding to the EVM value 25 based on at least the QAM size 26.

[0042] As will be described in more detail later, the function mapping unit 240 may be configured to determine the estimated SNR value 28 using a lookup table (LUT, e.g., EVM-SNR LUT), interpolation (e.g., linear interpolation), etc. The function mapping unit 240 may be configured to generate the estimated SNR 28 in various ways. In some embodiments, the function mapping unit 240 may be configured to generate the estimated SNR value 28 on a linear scale, a logarithmic scale, etc.

[0043] Receiver circuits, transmitter circuits, etc., or devices thereof may be configured to adjust the transmission rate based on an estimated SNR value 28. As used herein, “transmission rate” means the amount of data transmitted per unit time in a communication system, which may be affected by factors such as modulation scheme, coding rate, signal quality, channel condition, etc. The transmitter of the device may be configured to transmit data using the transmission rate (for example, adjusted based on at least an SNR value 28).

[0044] Referring to Figure 3A, an exemplary plot 300A is shown illustrating a nonlinear relationship between SNR and EVM according to one or more embodiments. In some embodiments, the function mapping unit 240 may be configured to determine an estimated SNR value 28 based on the nonlinear relationship between SNR and EVM shown in plot 300A. In some embodiments, the nonlinear relationship between SNR and EVM shown in plot 300A may be the relationship expressed by equation (1). Plot 300A shows different EVM-SNR relationships depending on the QAM size M (e.g., 16, 64, 256, 1024, 4096). Thus, the function mapping unit 240 may be configured to accurately estimate SNR based on the relationship shown by equation (1) and / or plot 300A.

[0045] Figure 3B shows an exemplary LUT 300B according to one or more embodiments. As used herein, the term “LUT” (for EVM-SNR relations) may mean any data structure that stores a lookup table (e.g., an EVM-SNR lookup table), a matrix, or an EVM-SNR relation (e.g., equation (1), SNR values ​​as a function of EVM and M). In some embodiments, LUT 300B may store values ​​plotted in plot 300A. As shown, LUT 300B stores quantized SNR values ​​(in dB) for a given EVM range (e.g., BPSK in the first column, QPSK in the second column, 16-QAM in the third column, 64-QAM in the fourth column, 256-QAM in the fifth column, 1K-QAM in the sixth column, 4K-QAM in the seventh column, etc.). For example, in response to receiving data in 16-QAM, the function mapping unit 240 may be configured to determine the SNR value by searching the LUT 300B (e.g., the third column).

[0046] Referring to Figure 4A, an exemplary plot 400A is shown illustrating a nonlinear relationship between SNR and EVM according to one or more embodiments. Unlike plot 300A, in plot 400A, the x-axis represents EVM and the y-axis represents SNR. In some embodiments, the function mapping unit 240 may be configured to determine an estimated SNR value 28 based on the nonlinear relationship between SNR and EVM shown in plot 400A. In some embodiments, the nonlinear relationship between SNR and EVM shown in plot 400A may be the relationship expressed by equation (1). Plot 400A shows different EVM-SNR relationships depending on the QAM size M (e.g., 16, 64, 256, 1024, 4096). Thus, the function mapping unit 240 may be configured to accurately estimate SNR based on the relationship shown by equation (1) and / or plot 400A.

[0047] Figure 4B shows an exemplary LUT 400B according to one or more embodiments. LUT 400B may be an EVM-SNR LUT that stores the EVM-SNR relationship (e.g., Equation (1), EVM values ​​as a function of SNR and M). In some embodiments, LUT 400B may store the values ​​plotted in plot 400A. As shown, LUT 400B stores quantized EVM values ​​(in dB) for a given SNR range (e.g., BPSK in the first column, QPSK in the second column, 16-QAM in the third column, 64-QAM in the fourth column, 256-QAM in the fifth column, 1K-QAM in the sixth column, 4K-QAM in the seventh column, etc.). For example, in response to receiving data in 16-QAM, the function mapping unit 240 may be configured to determine the EVM value by searching LUT400B (e.g., the third column).

[0048] As described in relation to Figures 3B and 4B, the techniques disclosed herein (e.g., System 200) can provide an efficient and reliable solution for extracting the precise relationship between EVM and SNR as a function of QAM size. Furthermore, the techniques disclosed herein can find the EVM value for an unknown SNR based on interpolation (e.g., Equation (1), LUT 300B, LUT 400B, etc.), as will be described later, and vice versa.

[0049] Figure 5 shows an exemplary plot 500 illustrating the relationship between SNR and EVM according to one or more embodiments. Plot 500 is shown as an example for M=4096. In plot 500, the nonlinear line 51 ("NDA-EVM (theoretical)") represents an exemplary EVM-SNR relationship based on equation (1), and the dot 52 ("NDA-EVM (simulation)") represents a value obtained from simulation. In some embodiments, the function mapping unit 240 may be configured to determine the SNR value based on interpolation of the nonlinear line 51 (e.g., the EVM-SNR relationship based on equation (1)). In some embodiments, the function mapping unit 240 may be configured to determine a first EVM value (e.g., about 0 dB for dot 55A) and a second EVM value (e.g., about -8 dB for dot 55B) using LUTs (e.g., LUT 300B, LUT 400B, etc.). The function mapping unit 240 may be configured to use interpolation to calculate an SNR value within a range between a first EVM value (e.g., dot 55A) and a second EVM value (e.g., dot 55B). For example, with respect to an unknown point 55C, the function mapping unit 240 may be configured to calculate an SNR value based on interpolation. As shown in Figure 5, the nonlinear line 51 is aligned with dot 52. This makes it possible to accurately determine the EVM value between dots 52.

[0050] As an unrestrictive example, Figure 6A shows an example of a transmit constellation 600A according to one or more embodiments. Transmit constellation 600A is shown as an example with respect to M=4096. Figure 6B shows an example of a receive constellation 600B corresponding to the transmit constellation 600A of Figure 6A, according to one or more embodiments. The receive constellation 600B is shown to have a 20 dB SNR. The SNR of constellation 600B may be determined based on plot 500 (e.g., directly from plot 500, from a LUT associated with plot 500, from interpolation of plot 500, etc.). As another unrestrictive example, Figure 7A shows an example of a transmit constellation 700A according to one or more embodiments. Transmit constellation 700A is shown as an example with respect to M=4096. Figure 7B shows an example of a receive constellation 700B corresponding to the transmit constellation 700A of Figure 7A, according to one or more embodiments. The received constellation 700B is shown to have a 35 dB SNR. The SNR of constellation 700B can be determined based on plot 500 (e.g., directly from plot 500, from a LUT associated with plot 500, from interpolation of plot 500, etc.).

[0051] Figure 8 is a flowchart showing a process 800 for SNR and noise variance estimation from EVM according to one embodiment. In some embodiments, process 800 is performed by one or more processors, such as devices (e.g., device 102, network device 106, etc.), equipment of system 200, etc. In other embodiments, process 800 is performed by other entities. In some embodiments, process 800 includes more steps, fewer steps, or different steps than those shown in Figure 8.

[0052] In step 810, one or more processors may receive data from a receiver. In step 820, one or more processors may receive at least one or more symbols based on the data from a circuit. In some embodiments, in step 820, a circuit (e.g., system 200) receives one or more symbols (e.g., rx symbol 21). In some embodiments, in step 820, a demodulator of the circuit (e.g., demodulator 210) receives one or more symbols, while an EVM-NDA unit (e.g., EVM-NDA unit 230) receives a transmit symbol vector (e.g., transmit symbol vector 23) corresponding to one or more symbols.

[0053] In step 830, one or more processors may use a circuit to determine an error vector amplitude (EVM) value using one or more symbols. In some embodiments, the circuit determines an EVM value (e.g., EVM value 25). In some embodiments, the circuit determines an EVM value based on an estimated symbol vector (e.g., estimated symbol vector 24) and a transmitted symbol vector.

[0054] In step 840, one or more processors may determine the quadrature amplitude modulation (QAM) size through the circuit. In some embodiments, the circuit receives a QAM size (e.g., QAM size 26). In some embodiments, the circuit identifies (determines) the QAM size from a modulation and coding scheme (MCS) table.

[0055] In step 850, one or more processors may use a circuit to determine the signal-to-noise ratio (SNR) value using the EVM value and QAM size. In some embodiments, the circuit determines the SNR value (e.g., estimated SNR 28) based on the EVM value and QAM size. In some embodiments, the circuit calculates the SNR value corresponding to the EVM value based on at least the QAM size. In some embodiments, the circuit identifies the SNR value using a lookup table (LUT) (e.g., LUT 300B, LUT 400B, etc.). In some embodiments, the circuit identifies the SNR value using any such predefined mapping in a table, list, dictionary, or in memory or on the fly.

[0056] In some embodiments, the circuit determines the SNR value by using a LUT to identify a first EVM value (e.g., dot 55A) and a second EVM value (e.g., dot 55B), and then using interpolation to calculate the SNR value within the range between the first and second EVM values. In some embodiments, the circuit determines the SNR value by using a function of the SNR value and the QAM size (e.g., equation (1)). In some embodiments, the circuit determines the SNR value by using a nonlinear relationship between the SNR value and the QAM size.

[0057] In step 860, one or more processors may, by circuitry, adjust the transmitter's transmission speed based on at least the SNR value. In some embodiments, one or more processors may allow the transmitter to transmit data using that transmission speed.

[0058] As described above, this disclosure provides a technique for accurately mapping an NDA EVM to an SNR for a given QAM constellation size. In some embodiments, the technique utilizes a lookup table (one or more) (LUT) to map the EVM to the SNR and / or the SNR to the EVM for a given QAM size (e.g., a QAM size used in WiFi communication based on the 802.11 standard). In some embodiments, the technique includes obtaining / using a LUT that is based on a nonlinear relationship between the SNR, EVM, and QAM constellation size. The technique can be used for link adaptation. For example, in WiFi communication, the EVM can be used as a feedback criterion indicating channel quality, and the transmitter can estimate the SNR based on the QAM size using the SNR-EVM relationship. In some embodiments, the technique includes estimating the SNR using a mapping from the calculated EVM, and then using the SNR as a feedback criterion for link adaptation. This provides a faster and more accurate estimation of the SNR, especially in blind processing situations (e.g., when there is no need to use pilot or other noise estimation procedures).

[0059] Furthermore, the techniques disclosed herein allow for the direct measurement of SNR from packets (e.g., 802.11 WLAN, standards-based packet communication compliant with 3GPP, or non-standard communications using modulation schemes such as BPSK, QPSK, and QAM) without the need for explicit pilots or preambles. For example, in an OFDM system, the techniques disclosed herein can be used for average EVM over subcarrier base, subcarrier group, or the entire subcarrier or a subset of subcarriers. The techniques can be seamlessly applied to single-antenna communication or MIMO. For example, the techniques can be applied on a per-stream basis. In MIMO, a composite EVM (integrated EVM) can first be calculated over all streams, and then this composite value can be converted to the SNR for each stream. The techniques can be used for physical layer abstraction mappings such as the Received Bit Information Rate (RBIR) and the Effective Exponential Signal to Interference Plus Noise Ratio (SINR) index. The technologies disclosed herein can be applied to non-equal QAM communication, beamforming communication, and the like over MIMO streams, as proposed in 802.11bn.

[0060] References to “or” may be interpreted as inclusive, and any term written using “or” may refer to one, plural, or all of the terms written. References to at least one of a conjunctional list of terms may be interpreted as an inclusive OR to refer to one, plural, or all of the terms written. For example, a reference to “at least one of ‘A’ and ‘B’” may include “A” only, “B” only, and both “A” and “B.” References that “include” or are used in conjunction with other open terms may include additional items.

[0061] It should be noted that certain sections of this disclosure may refer to terms such as “First” and “Second” in relation to subsets of transmit spatial streams, sounding frames, responses, and devices to identify or distinguish one from another (singular or plural). These terms are not intended to merely relate entities (e.g., First Device and Second Device) temporarily or sequentially, although in some cases these entities may include such relationships. Or, these terms do not limit the number of conceivable entities (e.g., STA, AP, beamformer, and / or beamformy) that may operate within a system or environment. It should be understood that the systems described above may provide any or more of these components, which may be provided by standalone machines or, in some embodiments, by multiple machines in a distributed system. Furthermore, bit field positions may be modified, and multi-bit words may be used. Furthermore, the systems and methods described above may be provided as one or more computer-readable programs or executable instructions embodied in one or more products (e.g., floppy disks, hard disks, CD-ROMs, flash memory cards, PROMs, RAMs, ROMs, or magnetic tapes). The programs may be implemented in any programming language such as LISP, PERL, C, C++, or C#, or in any bytecode language such as JAVA®. The software programs or executable instructions may be stored as object code in one or more products.

[0062] The above description of the methods and systems will enable those skilled in the art to create and use their embodiments, but those skilled in the art will understand and recognize the existence of variations, combinations, and equivalents of the specific embodiments, methods, and examples described herein. Accordingly, the methods and systems should not be limited by the embodiments, methods, and examples described above, but are limited by all embodiments and methods within the spirit and scope of this disclosure.

Claims

1. It is a device, A receiver configured to receive data, The circuit includes, Receive at least one or more symbols based on the data, Using one or more of the above symbols, the error vector amplitude (EVM) value is determined. Identify the quadrature amplitude modulation (QAM) size, Using the EVM value and the QAM size, the signal-to-noise ratio (SNR) value is determined. A device configured to adjust the transmission speed of a transmitter based at least on the SNR value.

2. The apparatus according to claim 1, wherein, when determining the SNR value, the circuit is configured to calculate the SNR value corresponding to the EVM value based at least on the QAM size.

3. The apparatus according to claim 1, wherein, when determining the SNR value, the circuit is configured to identify the SNR value using a lookup table (LUT).

4. When determining the SNR value, the circuit is used. Using a LUT, the first EVM value and the second EVM value are identified. The apparatus according to claim 1, configured to calculate the SNR within a range between the first EVM value and the second EVM value using interpolation.

5. The apparatus according to claim 1, wherein, when determining the SNR value, the circuit is configured to determine the SNR value using a function of the SNR value and the QAM size.

6. The apparatus according to claim 1, wherein, when determining the SNR value, the circuit is configured to determine the SNR value using a nonlinear relationship between the SNR value and the QAM size.

7. The apparatus according to claim 1, wherein, when determining the QAM size, the circuit is configured to determine the QAM size from a modulation and coding scheme (MCS) table.

8. It is a method, The receiver receives the data, The circuit receives one or more symbols based on at least the data, The circuit uses one or more symbols to determine the error vector amplitude (EVM) value. The circuit described above determines the quadrature amplitude modulation (QAM) size. The circuit described above uses the EVM value and the QAM size to determine the signal-to-noise ratio (SNR) value. A method comprising adjusting the transmission speed of a transmitter based on at least the SNR value using the circuit described above.

9. Determining the aforementioned SNR value is The method according to claim 8, comprising calculating the SNR value corresponding to the EVM value based on at least the QAM size.

10. Determining the aforementioned SNR value is The method according to claim 8, comprising identifying the SNR value using a lookup table (LUT).

11. Determining the aforementioned SNR value is Using a LUT, the first EVM value and the second EVM value are identified. The method according to claim 8, comprising calculating the SNR value within a range between the first EVM value and the second EVM value using interpolation.

12. Determining the aforementioned SNR value is The method according to claim 8, comprising determining the SNR value using a function of the SNR value and the QAM size.

13. Determining the aforementioned SNR value is The method according to claim 8, comprising specifying the SNR value using a nonlinear relationship between the SNR value and the QAM size.

14. Identifying the aforementioned QAM size is The method according to claim 8, comprising determining the QAM size from a modulation and coding scheme (MCS) table.

15. It is a device, Transmitter and The circuit includes, Based on the data received by the receiver, one or more symbols are received, Using one or more of the above symbols, the error vector amplitude (EVM) value is determined. Identify the quadrature amplitude modulation (QAM) size, Using the EVM value and the QAM size, the signal-to-noise ratio (SNR) value is determined. The transmission speed is adjusted based at least on the aforementioned SNR value. A device configured to transmit data using the transmission speed via the aforementioned transmitter.

16. The apparatus according to claim 15, wherein, when determining the SNR value, the circuit is configured to calculate the SNR value corresponding to the EVM value based on at least the QAM size.

17. The apparatus according to claim 15, wherein, when determining the SNR value, the circuit is configured to identify the SNR value using a lookup table (LUT).

18. When determining the SNR value, the circuit is used. Using a LUT, the first EVM value and the second EVM value are identified. The apparatus according to claim 15, configured to calculate the SNR within a range between the first EVM value and the second EVM value using interpolation.

19. The apparatus according to claim 15, wherein, when determining the SNR value, the circuit is configured to determine the SNR value using a function of the SNR value and the QAM size.

20. The apparatus according to claim 15, wherein, when determining the SNR value, the circuit is configured to determine the SNR value using a nonlinear relationship between the SNR value and the QAM size.

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