A method, device and application thereof for estimating effective received power of target users and rough ranging in a micro-frequency hopping multiple access communication system

Abstract

The present application relates to the technical fields of wireless communication, low-power wide-area Internet of Things and digital baseband signal processing, and discloses a method and device for estimating effective receiving power of a target user in a micro-frequency hopping multiple access communication system, and application thereof, wherein a received signal is processed through two branches: a time domain is used to obtain total receiving power containing multi-user interference power; and after baseband is matched with a target root, complete point DFT / FFT is performed, a target user signal-to-interference ratio is estimated from a correlation peak power and a background power, effective power of the target user is inversely calculated by using the correlation peak power and the background power, and path loss ranging is performed by replacing TotalRSSI with Target / EffectiveRSSI. The background power is obtained by taking a point from a point result, accumulating the point and right shifting, and thus a divider is not needed; 2ndmFH coexistence and high SINR segmentation are supported. According to the present application, other users do not need to be detected one by one, RSSI user attribution can be restored, structural ranging deviation caused by concurrent users can be eliminated, and high-precision and low-power hardware implementation advantages are combined.

Description

Technical Field

[0001] This invention relates to the fields of wireless communication, low-power wide-area Internet of Things and digital baseband signal processing, and in particular to a method, apparatus and application for estimating the effective received power of a target user and coarse ranging in a micro frequency hopping multiple access communication system. Background Technology

[0002] With the rapid development of Internet of Things (IoT) technology, Low-Power Wide-Area Network (LPWAN) has become a core infrastructure for connecting massive numbers of terminal devices. In typical application scenarios such as smart metering, environmental monitoring, smart cities, industrial automation, logistics tracking, smart agriculture, and wearable devices, tens of thousands of terminal devices need to achieve low-power, long-distance, and low-cost wireless data transmission on limited spectrum resources. These scenarios pose severe challenges to the concurrent access capabilities, spectrum efficiency, and terminal power consumption of communication systems.

[0003] To address these challenges, MicroFrequency Hopping Multiple Access (mFHMA) technology, as an emerging physical layer multiple access scheme, has attracted widespread attention in recent years. Unlike traditional frequency hopping communication systems, mFHMA technology uses prime-length micro-frequency hopping symbols. By assigning different micro-frequency hopping pattern parameters or root parameters to different users, multiple users can simultaneously perform asynchronous concurrent transmission within the same frequency resource block and the same time interval. Compared to traditional frequency division multiple access (FDMA), time division multiple access (TDMA), or code division multiple access (CDMA) schemes based on orthogonal resource allocation, mFHMA technology can significantly improve the system's user access capacity and spectrum utilization without increasing spectrum bandwidth and time resources, making it particularly suitable for IoT scenarios with massive concurrent terminal access.

[0004] In mFHMA systems, the receiver often needs to simultaneously acquire, track, demodulate, and assess link quality for multiple concurrently transmitting target users. Among these, the Received Signal Strength Indicator (RSSI) is one of the most fundamental and critical physical layer measurements in wireless communication systems. RSSI measurements are widely used in key functions such as Automatic Gain Control (AGC), Transmit Power Control (TPC), link quality assessment, coverage analysis, interference detection, channel load assessment (e.g., Listen-Before-Talk, LBT), and coarse ranging based on received signal strength. Especially in IoT applications where high-precision positioning is not required, RSSI-based coarse ranging has become an important means of roughly estimating terminal geographic locations and network topology awareness due to its simple implementation, lack of additional hardware overhead, and extremely low power consumption.

[0005] In traditional wireless communication systems (such as IEEE 802.11 series Wi-Fi, IEEE 802.15.4 ZigBee, LoRa, BLE, etc.), the basic assumption of RSSI ranging is that the received signal strength measured by the receiver at a certain moment mainly consists of the signal power of the target transmitter and the receiver's thermal noise. Under this assumption, RSSI can approximately reflect the received signal power of the target user. Therefore, based on known transmit power, antenna gain, system loss, and a predetermined path loss propagation model (such as the free space model, logarithmic distance path loss model, etc.), a rough distance between the target terminal and the receiver can be calculated through path loss inversion.

[0006] However, in the scenario of multi-user concurrent reception of mFHMA, the basic assumptions of traditional RSSI ranging no longer hold, and existing technologies face the following technical problems:

[0007] First, there is the issue of indistinguishability of concurrent user power. In an mFHMA system, multiple users perform asynchronous concurrent transmissions using the same frequency resources and the same time interval. The total received power measured in the time domain by the receiver's analog front-end or digital RSSI measurement module... It is a linear superposition of the power of all concurrent user signals, the power of external interference, and the power of receiver thermal noise, i.e. ,in The actual received signal power of target user k. This represents the equivalent interference power posed to the target user by other concurrent users and external interference. The receiver noise power is such that the receiver cannot distinguish the source of each power component in the total power in the time domain. Therefore, the directly measured TotalRSSI is essentially the "total power shared by all users" rather than the "power of the target user". This is a fundamental physical layer measurement defect.

[0008] Second, coarse ranging based on TotalRSSI suffers from systematic bias and "spurious distance changes." Since TotalRSSI includes the power of other concurrent users, directly substituting TotalRSSI as the received signal strength of the target user into the path loss model for ranging will result in severe and systematic ranging errors. Specifically, when the target user's distance from the receiver remains constant, as the number of other concurrent users increases or their transmit power increases, TotalRSSI will increase accordingly, causing the path loss model to judge the target user as closer. This anomalous phenomenon—"the farther the target user is, the stronger the other users are, the closer the ranging result"—leads to the absence of a stable mapping relationship between the ranging result and the true distance. More seriously, even if the target user remains stationary, fluctuations in the power of other concurrent users or their access failures can cause drastic "spurious changes" in the RSSI ranging result, rendering TotalRSSI-based ranging completely unusable in mFHMA scenarios.

[0009] Third, the approach of detecting all concurrent users one by one is not feasible in engineering. Theoretically, if the receiver can detect, demodulate, and estimate the received power of all concurrent users one by one, the power of the target user can be obtained by subtracting the power of other users from the TotalRSSI. However, in typical mFHMA application scenarios, the number of concurrent users may reach dozens or even hundreds, and the transmission between users is asynchronous, with different timing deviations, carrier frequency deviations, and channel conditions. Detecting all users one by one not only requires extremely high computational complexity and hardware overhead, but also introduces huge processing latency and power consumption, which seriously deviates from the basic requirements of low power consumption and low cost of IoT terminals. Therefore, existing technologies urgently need a technical means to recover the effective power of the target user directly from the TotalRSSI without relying on detecting all concurrent users one by one.

[0010] Fourth, existing background noise estimation methods are not suitable for the mFHMA correlation domain structure. In traditional correlation detection or matched filtering systems, background noise / interference power is usually estimated by averaging the non-correlation peak regions, but these schemes often use coarse estimation or rely on FFT with an integer power of 2 as the number of points. In mFHMA systems, the micro-frequency hopping symbol length is a prime number P, and complete correlation processing requires the use of P-point DFT / FFT to maintain the correlation structure and processing gain unique to prime lengths. If the number of points of traditional FFT is directly applied (e.g., ...), the results may be unsatisfactory. Background estimation at P-points would destroy the correlation integrity of prime number length signs; existing technologies lack a background power estimation scheme that can fully utilize the correlation output structure of P-points and be implemented with low complexity in fixed-point hardware.

[0011] Fifth, existing SINR estimation and RSSI measurement are separate. In conventional receiver architectures, signal-to-interference-and-noise ratio (SINR) estimation and RSSI measurement are usually two independent processing paths. The former is completed in the baseband correlation domain, while the latter is completed in the time domain by a dedicated RSSI module. Existing technologies lack a systematic solution to organically integrate these two independent observations and jointly infer the effective power of the target user.

[0012] Therefore, those skilled in the art urgently need a target user effective received power estimation and coarse ranging technology solution for mFHMA multi-user concurrent reception scenarios. Summary of the Invention

[0013] The core technical problem solved by this invention is: under the condition that multiple micro-frequency hopping users receive signals simultaneously and asynchronously, how to accurately estimate the effective received power of a specified target user from the Total RSSI measured by the receiver, which includes the power of multiple users, without having to demodulate or estimate the power of all other concurrent users one by one, and thereby obtain a coarse ranging result less affected by concurrent users.

[0014] For those skilled in the art, solving the aforementioned core technical problems has significant technical value and importance, specifically reflected in the following aspects:

[0015] On the one hand, those skilled in the art must solve the aforementioned core technical problem because its existence fundamentally negates the usability of traditional RSSI ranging methods in mFHMA multiple access systems. If this core technical problem is not solved, all functions in the mFHMA system that rely on RSSI for link quality assessment, power control, coverage analysis, and coarse ranging will fail or produce serious deviations. This will greatly limit the engineering deployment and commercial application of mFHMA technology in IoT high-concurrency scenarios.

[0016] On the other hand, once this core issue is resolved, the following key technological bottlenecks can be overcome:

[0017] Firstly, it enables the mFHMA system to obtain stable target user RSSI measurements across the entire load range, breaking the vicious cycle of "the more concurrent users, the less accurate the ranging."

[0018] Secondly, it enables the receiver to obtain RSSI measurement results with clear user affiliation without significantly increasing computational complexity and hardware overhead, breaking through the architectural bottleneck of "TotalRSSI cannot be decomposed into user-level RSSI" in traditional receiver architecture.

[0019] Third, it provides reliable per-user link quality feedback for transmit power control, adaptive modulation and coding, multi-user scheduling and interference management in mFHMA systems, breaking through the closed-loop control bottleneck of "link quality is imperceptible under multi-user concurrency".

[0020] To address the aforementioned core technical problems, this invention designs a method, apparatus, and application for estimating the effective received power of a target user and coarse ranging in a micro-frequency hopping multiple access communication system. The aim is to leverage the user-discriminable correlation characteristics of the mFHMA system itself—that is, the signals of different root users form significantly different correlation output patterns after target root matching (the target user forms a coherent concentrated peak, while other users form a dispersed background)—by establishing a mathematical connection between two complementary observations: TotalRSSI (answering "how loud is the entire channel") and correlation domain SINR (answering "how strong is the target user relative to the other received components"). This allows TotalRSSI to be "reassigned" to the target user, achieving a fundamental shift from "everyone's RSSI" to "my RSSI."

[0021] The overall technical approach of the entire technical solution is as follows:

[0022] The first layer utilizes the frequency domain correlation output of the P-point after target root matching to estimate the SINR of the target user based on the ratio of the target correlation peak power to the dispersed background power, thus solving the problem of "how to identify the signal quality of the target user in concurrent superposition".

[0023] The second layer algebraically fuses TotalRSSI and the target user SINR, utilizing [the following] in the linear power domain. and The joint relationship leads to the conclusion This addresses the problem of "how to reassign the total channel power to a designated user";

[0024] The third layer uses the recovered target / effective RSSI to replace Total RSSI for path loss calculation and coarse ranging, eliminating structural distance deviations caused by the power of other concurrent users from the source.

[0025] To achieve the above objectives and technical approach, the specific technical solution of this invention is a method for estimating the effective received power of a target user and coarse ranging in a micro-frequency hopping multiple access communication system, the method comprising the following steps:

[0026] Step A: Receive a received signal containing the target user signal and at least one other concurrent user signal and / or noise, and obtain the total received power of the received signal. ;

[0027] Step B: Based on the micro-frequency hopping pattern parameters corresponding to the target user, the micro-frequency hopping pattern parameters include the micro-frequency hopping symbol length P, where P is a prime number, perform matched correlation processing on the received signal, and perform frequency domain transformation on the signal after matched correlation processing to obtain frequency domain correlation output;

[0028] Step C: Determine the target correlation peak power corresponding to the target user based on the frequency domain correlation output. The background power is determined based on the power of at least some frequency domain points other than the target correlation peak. ;

[0029] Step D: Based on the target related peak power and the background power Determine the signal-to-interference-plus-noise ratio (SIR) that characterizes the target user signal relative to other received components. ;

[0030] Step E: Based on the total received power and the signal-to-interference-plus-noise ratio Determine the effective received signal power corresponding to the target user. ;as well as

[0031] Step F: Based on the effective received signal power corresponding to the target user Determine the distance information corresponding to the target user. .

[0032] Preferably, the micro-frequency hopping pattern parameters include the micro-frequency hopping symbol length. The It is a prime number; the frequency domain transform is a complete... Point Discrete Fourier Transform or Fast Fourier Transform .

[0033] Preferably, in step C, the background power is determined. include:

[0034] make ,and ;

[0035] Exclude the frequency points containing the target correlation peak from the frequency domain correlation output, and select exactly from the remaining frequency points. The background set consists of individual frequency points. ;

[0036] The background set The power accumulation at each frequency point is obtained ;as well as

[0037] The Move right The background set is obtained by taking the position. The average power at each frequency point is used as the background power. .

[0038] Preferably, excluding the frequency point where the target correlation peak is located from the frequency domain correlation output further includes:

[0039] Exclude one or more protected frequency points near the target correlation peak; these protected frequency points constitute a protected area set G.

[0040] From the remaining frequency points after removing the frequency points containing the target-related peaks and the protected area set G, select exactly... The background set consists of individual frequency points. .

[0041] Preferably, the protected area set G is determined based on the energy leakage range caused by residual frequency offset, timing deviation, phase noise, emitter shaping filter, or window function; when the leakage range increases, the protected area set G is adaptively widened; when the number of residual frequency points is insufficient... The protected area set G is adaptively narrowed over time.

[0042] Preferably, in step D, the target correlation peak power is used as the reference. and the background power Determine the signal-to-interference-plus-noise ratio include:

[0043]

[0044] in, Based on the micro-frequency hopping symbol length Frequency domain transformation normalization method, correlator implementation method, and general function for receiver calibration determination.

[0045] Preferably, under ideal matching conditions, the expression for the general function F is:

[0046]

[0047] in, The length of the micro-frequency hopping symbol is given.

[0048] Preferably, the general function This can be achieved through one of the following methods: analytical formula calculation, pre-defined lookup table lookup, fixed-point ratio conversion, or receiver calibration curve mapping.

[0049] Preferably, the method relates the target peak power. The background power Or the aforementioned signal-to-interference-plus-noise ratio The effective received signal power is determined by performing one or more of the following processes: cross-symbol averaging, median filtering, exponential smoothing, zero-truncation of negative values, saturation limiting, or fixed-point scaling.

[0050] Preferably, in step E, the total received power is used as the basis for the calculation. and the signal-to-interference-plus-noise ratio Determine the effective received signal power corresponding to the target user. include:

[0051] Calculated in the linear power domain according to the following expression:

[0052]

[0053] in, The total received power, The signal-to-interference-plus-noise ratio is denoted as .

[0054] Preferably, step E further includes:

[0055] Preset signal-to-interference-plus-noise ratio threshold ;

[0056] When the signal-to-interference-plus-noise ratio ≥ At that time, directly use the total received power. The effective received signal power corresponding to the target user ;

[0057] When the signal-to-interference-plus-noise ratio At that time, according to Calculate the effective received signal power .

[0058] Preferably, step E is followed by:

[0059] The effective received signal power Convert to its logarithmic form As an indication of the effective received signal strength of the target user:

[0060]

[0061] in, These are constants related to power units, analog / digital gain, analog-to-digital conversion scales, and receiver calibration.

[0062] Preferably, in step F, the effective received signal power corresponding to the target user is used as a reference. Determine the distance information corresponding to the target user include:

[0063] According to the effective received signal power Target user transmit power Transmit antenna gain Receiver antenna gain and system losses Calculate path loss :

[0064]

[0065] in, The effective received signal power The logarithmic form; and

[0066] According to the predetermined path loss propagation model, the path loss... The mapping yields the coarse distance between the target user and the receiver. .

[0067] Preferably, the predetermined path loss propagation model is one of the following: free space propagation model, logarithmic distance path loss model, segmented path loss model, environmental calibration curve, lookup table mapping, or machine learning regression mapping.

[0068] Preferably, the micro-frequency hopping signal includes secondary micro-frequency hopping or equivalent phase scrambling processing;

[0069] The matching-related processing in step B includes completing the matching or compensation processing corresponding to the secondary micro-frequency hopping or equivalent phase scrambling processing.

[0070] In step C, the target correlation peak power is determined. and the background power The squared amplitude of the frequency domain correlation output Determined, that is:

[0071]

[0072] .

[0073] Preferably, in step C, the position of the target correlation peak is determined. include:

[0074] The location of the maximum power of the frequency domain correlation output is searched within a predetermined search window and taken as the location of the target correlation peak. ;

[0075] When the frequency domain correlation output has multiple significant peaks, the position of the target correlation peak is determined by combining the known timing deviation and / or carrier frequency offset search window. .

[0076] Preferably, the method further includes: based on the total received power and the signal-to-interference-plus-noise ratio and pre-calibrated noise power The equivalent interference power is determined according to the following expression. :

[0077] ;

[0078] And / or based on the effective received signal power and the pre-calibrated noise power The signal-to-noise ratio is determined according to the following expression:

[0079] ;

[0080] And / or based on the equivalent interference power and the pre-calibrated noise power The interference-to-noise ratio is determined according to the following expression:

[0081] .

[0082] Preferably, the total received power The methods of obtaining it include:

[0083] Within the predetermined time window length Internal complex baseband sampling signal Calculated according to the following expression:

[0084] ;

[0085] Alternatively, the output of the received signal strength indicator module already present in the analog front-end or digital receiver can be used to convert the power value into a linear power domain value through gain status, quantization scale, and calibration constant.

[0086] Preferably, the method further includes:

[0087] Steps B to E are performed on multiple target users respectively to obtain the effective received signal power for each target user; and

[0088] For each demodulated or detected target user, output the effective received signal strength indication for the target user, for one or more of the following purposes: transmit power control, near-far effect diagnosis, coverage statistics, motion trend judgment, link budget analysis, interference level assessment, or ranging confidence assessment in a combined positioning system.

[0089] Preferably, the matching-related processing in step B includes:

[0090] Based on the target user's micro-frequency hopping parameter Generate local reference micro-frequency hopping symbols ;

[0091] Complex baseband sampling of the received signal Multiplying point-by-point by the conjugate of the local reference micro-frequency hopping symbol yields the matching sequence; and

[0092] Perform the frequency domain transformation on the matching sequence to obtain the frequency domain correlation output. for:

[0093]

[0094] in, For complete Point Discrete Fourier Transform, .

[0095] Preferably, the present invention also discloses a device for estimating the effective received power of a target user and coarse ranging in a micro-frequency hopping multiple access communication system. The device is used to implement the method and includes:

[0096] The total power acquisition module is configured to receive a received signal containing a target user signal and at least one other concurrent user signal and / or noise, and acquire the total received power of the received signal. ;

[0097] The target matching and frequency domain transformation module is configured to perform matching correlation processing on the received signal according to the micro-frequency hopping pattern parameters corresponding to the target user, and to perform frequency domain transformation on the signal after matching correlation processing to obtain frequency domain correlation output;

[0098] The peak and background statistics module is configured to determine the target correlation peak power corresponding to the target user based on the frequency domain correlation output. The background power is determined based on the power of at least some frequency domain points other than the target correlation peak. ;

[0099] The signal-to-interference-plus-noise ratio (SIR / NOT) determination module is configured to determine the target correlation peak power. and the background power Determine the signal-to-interference-plus-noise ratio (SIR) that characterizes the target user signal relative to other received components. ;

[0100] The target user effective power determination module is configured to determine the total received power based on the total received power. and the signal-to-interference-plus-noise ratio Determine the effective received signal power corresponding to the target user. ;as well as

[0101] The distance determination module is configured to determine the distance based on the effective received signal power corresponding to the target user. Determine the distance information corresponding to the target user .

[0102] Preferably, the peak and background statistics module includes:

[0103] A background frequency selector is configured to exclude the frequency point containing the target correlation peak from the frequency domain correlation output, and select exactly the frequency point from the remaining frequency points. The background set consists of individual frequency points. ,in, , The length of the micro-frequency hopping symbol and It is a prime number. , , ;

[0104] An accumulator configured to add the background set The power accumulation at each frequency point is obtained ,Right now:

[0105] ;

[0106] as well as,

[0107] The shifter is configured to shift the... Move right The background set is obtained by taking the position. The average power at each frequency point is used as the background power. ,Right now:

[0108] .

[0109] Preferably, the peak and background statistics module further includes:

[0110] The protected area setting unit is configured to set a protected area set G containing one or more protected frequency points near the target correlation peak. The background frequency point selector selects the exact frequency points from the remaining frequency points after removing the frequency point where the target correlation peak is located and the protected area set G. The background set consists of individual frequency points. .

[0111] Preferably, the signal-to-interference-plus-noise ratio (SINR) determination module includes:

[0112] The computing unit is configured according to Calculate the signal-to-interference-plus-noise ratio. ,in Based on the micro-frequency hopping symbol length Frequency domain transformation normalization method, correlator implementation method, and general function for receiver calibration determination.

[0113] Preferably, the computing unit operates under ideal matching conditions according to... Calculate the signal-to-interference-plus-noise ratio. .

[0114] Preferably, the target user effective power determination module includes:

[0115] A multiplier configured to calculate the total received power. With the aforementioned signal-to-interference-plus-noise ratio The product;

[0116] Adder, configured to calculate 1 and the signal-to-interference-plus-noise ratio. and; and

[0117] Divider or lookup table, configured for calculation The ratio;

[0118] The target user effective power determination module is according to Determine the effective received signal power .

[0119] Preferably, the target user effective power determination module further includes:

[0120] A comparator configured to compare the signal-to-interference-plus-noise ratio. With the predetermined threshold Size;

[0121] When the signal-to-interference-plus-noise ratio ≥ At that time, the target user effective power determination module directly uses the total received power. The effective received signal power corresponding to the target user ;

[0122] When the signal-to-interference-plus-noise ratio < At that time, the target user effective power determination module according to Calculate the effective received signal power .

[0123] Preferably, the present invention also discloses a receiving chip, which includes the aforementioned device.

[0124] Preferably, the present invention also discloses a receiver for a micro frequency hopping multiple access communication system, which includes the aforementioned receiver chip, as well as an RF front-end circuit, an analog-to-digital converter, and a digital baseband processor.

[0125] Preferably, the present invention also discloses a wireless communication device, which includes the aforementioned receiver, and further includes an antenna, a power management unit, and a communication interface.

[0126] Compared with the prior art, the technical solution disclosed in this application has the following non-obvious technical features:

[0127] Technical Feature 1: A Fundamental Shift in Technical Approach – From “Distinguishing User Power” to “Reconstructing User Power”; The mainstream approach to solving the multi-user power separation problem in existing technologies is to use Multi-User Detection (MUD) or Successive Interference Cancellation (SIC). The core logic of these methods is to detect, estimate, and eliminate the power contribution of other users one by one. This application completely breaks away from this conventional technical approach and creatively adopts a strategy of “direct reconstruction without distinguishing one by one”. Without estimating the power of any other users, it directly “strips” the target user’s power from the total power by utilizing only the mathematical relationship between the target user’s own correlation domain SINR and Total RSSI. This technical approach of “bypassing individual estimation and directly reaching the target power” has not been taught or inspired by any existing technology.

[0128] Technical Feature Two: A Fusion Back-Depth Framework for Two Independent Observations (Total RSSI and Correlation Domain SINR); In conventional receiver architectures, time-domain RSSI measurement and baseband correlation domain SINR estimation are two completely independent processing paths. The former is used for gain control and coarse signal detection, while the latter is used for demodulation and link quality assessment. There is no organic mathematical coupling between the two. This application creatively establishes an analytical relationship between these two independent observations—through and The two basic equations are combined to decompose the originally "indivisible" TotalRSSI into two parts: user power and interference noise power. This technical approach of "connecting two independent physical layer measurements through mathematical relationships to solve the problem of a third type of indirect measurable quantity" has not been disclosed in existing mFHMA related technical literature and patents.

[0129] Feature 3: Upholding integrity Point DFT / FFT and exact match Non-obvious combinations of background points; in the field of digital signal processing, when it is necessary to reduce the implementation complexity of FFT, the usual practice for those skilled in the art is to directly reduce the number of FFT points (e.g., from...). Points reduced to (Point); On the contrary, this application insists on implementing the complete Point DFT / FFT is used to preserve the correlation structure and processing gain of prime-length micro-frequency hopping symbols. Then, from the already obtained complete P-point results, exactly the exact points are actively and selectively selected. The average is calculated from the background points; that is, the average of the background points in this application. It is not used for the FFT transform itself, but for controlling the number of statistical points in the background averaging. This approach of "keeping the number of transform points unchanged and taking the number of statistical points as a power of 2" is fundamentally different from the conventional technique of "reducing the number of transform points to simplify calculation". Its motivation and specific operation path are not obvious to those skilled in the art. Existing technology usually teaches how to reduce the number of FFT points to improve efficiency, but does not teach the technical solution of accurately selecting an integer power of 2 points for averaging after the complete transform to achieve a hardware implementation without a divider.

[0130] Feature 4: Fixed-point implementation of "precise rightward shift for averaging" of background points The coexistence of point-to-point complete gain processing is discussed. In fixed-point digital signal processing, using right shift to achieve division by a power of 2 is a conventional technique; however, the inventiveness of this application lies in: firstly recognizing the necessity of adhering to complete gain processing. Point DFT / FFT was used to preserve the relevant properties of prime number length; secondly, a creative choice was made to extract the appropriate value from the P-point result. Instead of compressing the transformation itself into points, it focuses on points rather than compressing the transformation itself into points. Point; only utilize at the last minute The property of powers of 2 enables right-shifted averaging; there is a progressive causal relationship between these three layers of logic: because To ensure that the numbers are prime and the relevant structure must be preserved, therefore, it is necessary to do... Point transformation; because The average after point transformation needs to be simplified, so we cleverly select... One point; because The averaging of individual points can be achieved by right shifting, thus making the hardware efficient. The overall solution combining the three is not a conventional choice for those skilled in the art when faced with low-power implementation requirements. On the contrary, the conventional choice is often to directly sacrifice transformation accuracy in exchange for implementation simplification. The path of "preserving transformation accuracy first and then optimizing statistical implementation" in this application is not taught in the prior art.

[0131] Feature 5: Adaptive architecture for high SINR segmented processing and accurate back-calculation of low and medium SINR; Existing SINR estimation technologies typically use the same algorithm across the entire range. When SINR is high, the ratio of the correlation peak to the background may saturate due to factors such as fixed-point bandwidth and residual frequency offset, leading to a decrease in SINR estimation accuracy. This application creatively sets a high SINR judgment threshold. When SINR exceeds the threshold, TotalRSSI is directly used as the effective power of the target user. Accurate back-calculation is only performed by relying on the correlation domain SINR in the low and medium SINR range. The underlying technical logic of this adaptive segmented processing is that TotalRSSI in the low and medium SINR range is the "uncleanest" (other users and noise account for a large proportion), and it is most necessary to rely on the correlation domain to "extract" the target power. In the high SINR range, the target user already accounts for the vast majority of the total power, and TotalRSSI itself is already a good approximation. This segmented adaptive strategy of "making the most accurate calculation when it is most necessary and making a reasonable approximation when the impact is not significant" reflects a deep understanding of the physical characteristics of mFHMA concurrent scenarios, rather than a simple engineering trade-off.

[0132] Feature Six: Compatibility with Secondary Micro Frequency Hopping (2ndmFH); Secondary micro frequency hopping (2ndmFH) is a superposition modulation or phase perturbation processing of a basic mFHMA signal. Existing RSSI ranging schemes often fail or need to disable the 2ndmFH function when encountering such signals due to phase changes. The inventiveness of this application at the principle level lies in the fact that the statistics of correlation peak power and background power depend only on the square of the amplitude of the frequency domain correlation output. It does not depend on the absolute phase information of the relevant output at all; therefore, regardless of whether 2ndmFH is applied, as long as the corresponding matching or compensation processing is completed, the statistical characteristics of the squared amplitude remain unchanged; this statistical strategy of "discarding phase and only taking power" makes the technical solution of this application naturally coexist with 2ndmFH without having to disable the 2ndmFH function; this compatibility feature is not obvious, because when faced with the phase change introduced by 2ndmFH, those skilled in the art usually think of "eliminating phase influence", while this application "bypasses phase dependence" and chooses a completely different technical path;

[0133] Feature 7: A three-layer inter-layer coupled overall architecture; the innovation of this application is not a simple addition of the above features, but an organic coupling of three technical links (target SINR estimation, target power back-calculation, and coarse ranging); the output of the first layer ( ) precisely serves the input requirements of the second layer; the output of the second layer ( It accurately serves the input requirements of the third layer; there are strict dependencies and mathematical transitive relationships between the three layers, and the absence or inaccuracy of any link will lead to the failure of the final ranging result; this "layer-by-layer and interlocking" overall architecture has not been disclosed in the existing mFHMA system, and those skilled in the art would not naturally think of adopting such a structurally complete multi-layer decomposition scheme when facing the problem of multi-user concurrent ranging.

[0134] Compared with the prior art, the present invention has the following beneficial effects:

[0135] 1. Under the condition of multiple micro-frequency hopping users receiving simultaneously and asynchronously on the same frequency, this invention can accurately estimate the effective received power of a specified target user from the TotalRSSI containing the power of all concurrent users, successfully recover the user affiliation of RSSI, and solve the fundamental problem of "non-affiliation" in traditional RSSI measurement in multi-user concurrent scenarios.

[0136] 2. This invention can fundamentally avoid the structural error in traditional RSSI coarse ranging where "the stronger the other concurrent users are, the closer the ranging result estimates the target user" and eliminate "false distance changes" caused by other users joining / leaving or power fluctuations, so that the coarse ranging result remains stable when the concurrent load changes dynamically.

[0137] 3. This invention uses the natural distinction between coherent peaks and scattered background in the relevant domain after target root matching to estimate the target user SINR. It does not require identifying, demodulating or estimating the power of each other concurrent user. Compared with traditional multi-user detection or serial interference cancellation schemes, the computational complexity and hardware overhead are greatly reduced, and the processing latency is significantly shortened.

[0138] 4. This invention adheres to the principle of completeness. Pointed DFT / FFT processing preserves the complete correlation structure and maximum processing gain of prime-length micro-frequency-hopping symbols, and correlation performance is not degraded by low-complexity background statistics implementation; simultaneously, by... Take exactly the result This background point achieves high efficiency in statistical implementation. No successful solution has yet been found in existing technologies to balance both aspects.

[0139] 5. This invention, by excluding the target peak and the optional protected area... Just take exactly the point frequency domain result For each background point, the arithmetic mean of the background power is converted into a summation and then shifted to the right. Bit shifting operations can be efficiently implemented in fixed-point ASICs, FPGAs, or digital basebands without the need for a general divider, greatly reducing hardware implementation area and power consumption, and has significant engineering implementation value.

[0140] 6. This invention effectively reduces the impact of residual frequency offset, timing deviation, phase noise, emission shaping filtering, and window function-induced target energy leakage on the target peak by setting up a protected area near the target peak. The contamination of SINR estimation improves the robustness and reliability of SINR estimation;

[0141] 7. The SINR conversion in this invention retains the general function. The form can be flexibly adapted to different FFT normalization methods, processing gain, window functions, fixed bit widths and receiver calibration methods, and has good system compatibility and engineering adaptability.

[0142] 8. The high SINR segmentation processing mechanism of this invention directly approximates the target user signal with TotalRSSI when the target user signal is dominant. This effectively avoids the inaccuracy of SINR estimation in the high-end saturation region, while maintaining a stable output of TargetRSSI across the entire dynamic range, and further reducing the computational complexity in high SINR scenarios.

[0143] 9. After completing the matching process corresponding to the second micro-frequency hopping (2ndmFH), this invention uses the square of the relevant output amplitude. As a statistical measure, it does not depend on the absolute phase of the relevant output, so it can coexist naturally with the 2ndmFH function without having to turn off 2ndmFH processing for RSSI estimation, ensuring that the system can still obtain accurate effective RSSI for the target user when 2ndmFH is enabled.

[0144] 10. In addition to being used for path loss and coarse ranging, the Target / Effective RSSI obtained by this invention can also be reused for various functions such as transmit power control, link quality assessment, near-far effect judgment, coverage analysis, interference diagnosis, and ranging confidence assessment in integrated positioning systems, and has broad engineering reuse value. Attached Figure Description

[0145] Figure 1 This is a flowchart of the method described in this invention, used to illustrate the convergence relationship between the Total RSSI branch and the target root-related branch;

[0146] Figure 2 This is a schematic diagram of the frequency domain correlation power at point P as described in this invention, used to illustrate... Nature reserves, background bins and appropriate selection The meaning of each background point;

[0147] Figure 3 This is the multi-user power decomposition diagram described in this invention, used to illustrate the power distribution of... and Reverse deduction Relationship;

[0148] Figure 4 This is a schematic diagram illustrating the compatibility of the three-layer structure and 2ndmFH ("secondary micro frequency hopping") described in this invention;

[0149] Figure 5 This is an example table of errors for approximating the target user power with Total RSSI when the SINR is high, as described in this invention.

[0150] Figure 6 This is a definition table of variables and symbols described in this invention. Detailed Implementation

[0151] The following is in conjunction with the appendix Figures 1 to 6 The main technical features of the present invention will be described in detail below;

[0152] In the technical solution of this invention, based on target root matching Full frequency domain correlation processing is performed by the receiver based on the target user's micro-frequency hopping root parameters. Generate a local reference micro-frequency hopping symbol, multiply the received signal by the local reference symbol point-by-point using its conjugate, and then perform a complete... Pointed DFT / FFT frequency domain transform yields a length of Frequency domain correlation output ,in The length of the micro-frequency hopping symbol is a prime number; this processing is the foundation and prerequisite of the entire technical solution, and only by adhering to the complete... Only by performing point-domain frequency transformation can the unique correlation structure and complete processing gain of prime-length micro-frequency hopping symbols be preserved, enabling the target user signal to form a significant coherent concentrated peak in the correlation domain, while simultaneously dispersing the signal energy of other root users into a flat background; if a non- Point transformation or truncation will destroy the distinction between relevant peaks and background, causing the foundation of all subsequent steps—SINR estimation, power inversion and ranging—to fail.

[0153] In the technical solution of this invention, from Just take exactly from the complete result Estimating the background power of each background point is to let and After excluding the frequency points where the target-related peaks are located (and the optional protection zones), from the remaining... Intentionally and precisely selecting just the right point in the frequency domain correlation output. The background set consists of individual frequency points. and this After accumulating the power at each point, shift to the right. The arithmetic mean of these points is obtained as the background power. This estimation is the key engineering innovation that distinguishes this application from existing technologies. It creatively decouples the "statistical number of background average points" from the "number of points in the frequency domain transformation"—keeping the number of transformation points constant. Points (ensuring relevant performance), statistical point count. (Ensuring hardware implementation); By limiting the number of statistical points to integer powers of 2, the arithmetic average operation is transformed into a simple right shift operation after accumulation, completely eliminating the need for a general-purpose divider. When implemented in fixed-point ASIC / FPGA, only a small number of adders and shift registers are added, resulting in extremely low area and power consumption; This feature directly addresses the core demands of low power consumption and low cost for IoT terminals.

[0154] In the technical solution of this invention, the protected area near the target peak is set at the location of the target-related peak. A set of protected areas containing one or more protected frequencies is set up nearby. (by mold) (Processing boundaries), in selecting the background set First, remove protected areas from the available frequency points. All frequencies within; this setting ensures background power In practical systems, residual carrier frequency offset, symbol timing deviation, phase noise, transmit shaping filter roll-off, and window function effects all contribute to energy leakage of the target signal from its peak to adjacent frequencies. If these leakage frequencies are included in the background, It may be overestimated, leading to an underestimation of SINR, which in turn causes a systematic error such as an underestimation of the target effective power and a remote ranging distance; the establishment of the protection zone effectively isolates the pollution of background statistics by peak energy leakage, which is a key measure to ensure the robustness of the project.

[0155] In the technical solution of the present invention, by and A general function for estimating the target user's SINR It is to establish The general functional relationship, where For the target user's SINR estimate, For the target related peak power, The background average power, Where is the symbol length of the micro-frequency hopping; under ideal matching conditions, an embodiment of this function is as follows: This general function can be implemented in various ways, such as analytical formulas, lookup tables, fixed-point scaling, or receiver calibration curves; this general function is the core algorithmic abstraction of the first-layer technical link (target root correlation → target user SINR); it establishes observable physical quantities in the correlation domain ( and Link quality parameters with target user The quantitative mapping between them transforms the qualitative observation of "how high the correlation peak is and how flat the background is" into a quantitative estimate of "how strong the target signal is relative to the interference noise"; this relationship is preserved as a general function. Instead of a fixed formula, this approach offers significant engineering flexibility—different receiver implementations (different FFT normalizations, window functions, and fixed-point bit widths) can be calibrated to achieve their respective characteristics. Mapping, without changing the overall architecture;

[0156] In the technical solution of this invention, the algebraic fusion method of jointly back-calculating the effective power of the target user using TotalRSSI and SINR establishes two fundamental equations in the linear power domain: (Total power is the sum of its components) and (SINR is the ratio of signal power to interference noise power); by solving the simultaneous equations, we obtain... Using estimated values As the final estimate of the effective received power of the target user; this algebraic fusion method is the second-layer technical step (TotalRSSI + target user SINR → →Target / Effective RSSI) is a core mathematical tool; it combines "Total RSSI (how loud is the entire channel)" and " (How strong is the target user relative to other components?) Two observations from different sources with complementary physical meanings were organically integrated; the ingenuity of this method lies in the fact that it does not require any solution. or To find the absolute value, we only need to know the sum of the two. This allows for a closed-loop system, thus bypassing the infeasible path of "estimating the power of other users one by one." It is through this mathematical transformation that this application achieves the essential shift from "everyone's RSSI" to "my RSSI."

[0157] In the technical solution of this invention, the high SINR segmentation processing mechanism is based on a preset signal-to-interference-plus-noise ratio threshold. ;when ≥ At that time, directly use TotalRSSI ( (This is an approximation of the effective power of the target user) ≈ ;when < At that time, according to This mechanism enables precise reverse engineering; it significantly reduces implementation complexity while maintaining measurement accuracy across the entire dynamic range; its underlying physical logic is: under high SINR conditions, the target user signal already accounts for the vast majority of the total power (when SINR=20dB). ≈99%, with an error of only 0.043dB), at this point, TotalRSSI itself is an excellent approximation of the target power, without the need for complex back-calculation based on the correlation domain SINR; while in the low to medium SINR range (SINR=0dB)... With only 50% accuracy and an error as high as 3dB, TotalRSSI is most "unclean" and requires the most precise extraction of the target power. This segmentation strategy cleverly avoids the problem of inaccurate estimation of the ratio of correlation peak to background due to fixed-point bit width saturation under high SINR, and achieves full dynamic range coverage of "accurate low and mid-range and simple high-end range".

[0158] In the technical solution of this invention, based on the square of the amplitude The power statistics are compatible with 2ndmFH when determining the target relevant peak power. and background power At that time, the statistical measure used was the frequency domain correlation output. square of amplitude The signal is not the complex value of the output itself or its phase component; regardless of whether the received signal has undergone secondary micro-frequency hopping or equivalent phase scrambling processing, as long as the corresponding matching or compensation is completed, the same amplitude squared statistical method is used; this compatibility ensures that the technical solution of this application can coexist naturally with the secondary micro-frequency hopping (2ndmFH) function; 2ndmFH will introduce additional phase perturbation or transitions into the signal. If the SINR estimation of this application depends on phase information (such as calculating the real part of coherence or phase difference), the introduction of 2ndmFH will destroy the accuracy of the estimation, and may even require disabling the 2ndmFH function; The statistics are completely independent of phase—phase perturbation only affects the argument of the complex number, not the square of its modulus; this statistical strategy of "discarding phase and only taking power" makes this application compatible with 2ndmFH in principle, reflecting the far-sightedness of the scheme design.

[0159] In the technical solution of this invention, the path loss ranging process of replacing TotalRSSI with Target / EffectiveRSSI involves recovering the effective received power of the target user. Convert to its logarithmic form and will (Instead of the Total RSSI directly measured by the receiver) Substitute into the path loss equation Then, the coarse distance is obtained by mapping through a predetermined propagation model. This process is the core operation of the third-layer technical stage (Target / Effective RSSI → Path Loss → Coarse Distance), which separates the technical efforts of the first two layers (from Total RSSI) The results are transformed into final engineering practical value; the essence of this process is "exchanging the right distance input for the right ranging output"—only when the effective power input to the path loss model is the target user's own power is it truly effective. When the inverted distance is not the TotalRSSI which includes the power of other users, it can truly reflect the geometric distance from the target user to the receiver. Any practice of continuing to use TotalRSSI in the path loss ranging stage will render all the efforts of the first two layers futile. Therefore, this feature is the key "last mile" step to ensure the accuracy of the final ranging result.

[0160] In the technical solution of this invention, the low-complexity fixed-point hardware implementation architecture is at the hardware implementation level. Point frequency domain correlation output The components are obtained by sum of squares Peak detector saves and The background selection controller skips the protected address, specifically the one that... Power accumulation at each valid address; arithmetic right shift of the accumulation result. Position obtained SINR is calculated using a lookup table or fixed-point divider; target power is used. The architecture demonstrates that the technical solution of this application is not merely at the algorithm level, but has a clear hardware implementation path that can be implemented in low-power ASICs / FPGAs. The entire hardware architecture only requires the addition of peak / background statistics, a small amount of control logic, and simple arithmetic units (multipliers, adders, shifters, comparators, and lookup tables), without the need for general-purpose dividers, large-capacity memory, or high-precision floating-point units. This is crucial for IoT receiver chips with extremely limited power consumption and area, directly determining the engineering feasibility and commercial promotion value of this invention.

[0161] The following is in conjunction with the appendix Figures 1 to 6 The embodiments of the present invention will be described in detail below;

[0162] refer to Figure 1 This document illustrates a general flowchart of a method for estimating the effective received power of a target user and coarse ranging in a micro-frequency hopping multiple access communication system according to one or more embodiments of this application. This method is applicable to mFHMA communication scenarios where multiple micro-frequency hopping users transmit simultaneously and asynchronously at the same frequency, such as smart metering, environmental monitoring, asset tracking, and industrial wireless sensor networks in low-power wide-area IoT. The receiver receives data containing the target user's... The system takes complex baseband samples from at least one other concurrent user and noise, and performs effective received power estimation and coarse ranging for the target user through two processing branches: the first branch obtains the total received power in the time domain or from an existing RSSI unit. The second branch uses the target user root to complete the matching, and then executes the full process. Point DFT / FFT to extract target correlation peak power and background power Then, the SINR of the target user is calculated. The effective received power of the target user is obtained by combining the two results. This is then converted into Target / Effective RSSI, path loss, and coarse distance. For example... Figure 1 As shown, the method of this embodiment includes the following steps: steps A to F.

[0163] In one or more embodiments, step A configures the receiver to receive a baseband signal containing the target user k, at least one other root user, and noise, and measures the total received power within a specified symbol window. Specifically, the receiving end obtains complex baseband samples that include the target user, other concurrent users, and noise. Within a predetermined time window of length L, the total received power can be calculated using the following formula:

[0164] .

[0165] In one or more embodiments, step A may also use the output of an existing RSSI module in an analog front-end or digital receiver, converted to a linear power domain power value through gain state, quantization scale, and calibration constant. All power decomposition and addition / subtraction operations are preferably performed in the linear power domain and cannot be directly performed in the dBm domain. , and Perform algebraic addition and subtraction.

[0166] In one or more embodiments, the noise power N can be pre-calibrated according to bandwidth, noise figure, receiver gain state, and temperature; however, this application calculates the effective power of the target user. It is not required that the solution be obtained separately in real time. or Only the total received power is needed. A closed loop can be achieved by matching the target user's SINR.

[0167] In one or more embodiments, in step B, the receiver calls the target root. The local reference completes point-by-point matching. Assume the micro-frequency hopping symbol length is a prime number. The micro-frequency hopping root used by target user k is The receiver is based on known, configured, or detected information. Generate local reference micro-frequency hopping symbols Complex baseband sampling of the received signal. The matching sequence is obtained by multiplying the conjugate of the local reference micro-frequency hopping symbol point by point.

[0168] In one or more embodiments, step B performs a P-point DFT / FFT on the matching result to obtain a frequency domain correlation output. Specifically:

[0169]

[0170] It must be clarified here that the frequency domain correlation processing length is... Point, not Point. Adopting a complete The point transformation is used to preserve the correlation structure, peak position, and processing gain of the prime-length micro-frequency hopping symbol. In this application, these statistics are used only as background data to facilitate averaging in digital hardware shifting; they should not be confused with each other. (Reference) Figure 2 , Figure 2 It shows A schematic diagram of point frequency domain correlation power, target peak, protected area and background point selection.

[0171] In one or more embodiments, step C determines the position of the target relevance peak within the search window. And obtain the target related peak power. . Specifically:

[0172]

[0173]

[0174] When the target user is present, after matching with the target root, the target signal undergoes coherent accumulation, and its energy is concentrated in a specific correlation bin. Concurrent users using other roots have micro-frequency hopping patterns that do not match the target root, and cannot form the same coherent peak at the same correlation position as the target user. Their energy is mainly dispersed across multiple correlation bins, manifesting as a dispersed correlation background. This background, along with receiver noise, external interference, and implementation imperfections, constitutes the equivalent interference noise background from the target user's perspective. Therefore, this method does not require detecting, demodulating, or estimating the power of all other users individually.

[0175] In one or more embodiments, step C is excluded. and optional protected areas, taking exactly what's left from the remaining bins. A background point, After accumulating, shift right by SF bits to obtain . refer to Figure 2 Specifically, let:

[0176]

[0177]

[0178] exist Among the frequency domain correlation output points, the target peak is first excluded. Further exclusion of protected areas near the peak can be achieved. Then, from the remaining candidate points, select exactly... The background set consists of individual frequency points. :

[0179]

[0180] Accumulation:

[0181]

[0182] Shift to the right to calculate the average:

[0183]

[0184] Therefore, in fixed-point ASIC, FPGA, or digital baseband implementations, this can be obtained without a general divider. The exact arithmetic mean of the background points. This design is not mathematical rounding, but rather derived from available... The number of statistical points can be actively selected in the results, allowing background estimation to be completed using accumulators and shifters. Considering residual frequency offset, fractional timing deviation, phase noise, emission shaping, window functions, or quantization-induced target energy leakage, a protection set can be defined:

[0185]

[0186] Press Handle boundary conditions and remove from the entire set. Then choose There are [number] points. As long as the remaining candidate points are not less than [number] points. It is still possible to maintain "appropriate" The structure is "point, accumulated and then shifted right by SF bits".

[0187] In one or more embodiments, step D is performed via F( , ,P) In this process, the target user, after correlation matching, has coherent processing gain, while other root users and noise mainly form incoherent or low-correlation background. Therefore, and The relationship includes the target user's SINR information. To avoid locking the sovereign term to a certain normalization, window function, or implementation scale, the general form should be written as:

[0188]

[0189] in, For the target user's signal-to-interference-plus-noise ratio; function Based on the mFH processing gain, The normalization method, correlator implementation, window and receiver calibration of point DFT / FFT can be determined through analytical formulas, lookup tables, fixed-point scaling conversions or calibration curves.

[0190] In an ideal matching embodiment:

[0191]

[0192] This formula is used as an example to illustrate the conversion of mFH processing gain and should not be construed as the only SINR (Signal to Interference plus Noise Ratio) estimation formula in this application. Engineering implementations may also include zero-truncation of negative values, saturation limiting, fixed-point scaling, filtering, or multi-symbol averaging.

[0193] In one or more embodiments, step E will and convergence, calculation When SINR is high, it can be directly taken. In the linear power domain, the total received power relationship and the target user SINR definition are as follows:

[0194]

[0195]

[0196] From the second equation, we have Substitute into the first form:

[0197]

[0198] Thus, the effective received power of the target user is obtained:

[0199]

[0200] Estimated values ​​used in actual systems:

[0201]

[0202] That is, the effective received signal power of the target user recovered from the Total RSSI, which includes all concurrent users.

[0203] refer to Figure 3 , Figure 3 This diagram illustrates the decomposition of total power across multiple users and effective power of the target user. and Reverse deduction The relationship.

[0204] In one or more embodiments, step F completes the receiver calibration conversion to obtain... Then calculate the path loss and coarse distance. Its logarithmic form can be defined as:

[0205]

[0206] in, This provides constants related to power units, analog / digital gain, ADC scales, and receiver calibration.

[0207] This quantity should be stored separately from the underlying Total RSSI: Total RSSI is used for global functions such as channel load and LBT, while Target / Effective RSSI is used for target user link assessment and coarse ranging. Further, the coarse distance is obtained based on a predetermined propagation model.

[0208]

[0209]

[0210] For example, the logarithmic distance path loss model is:

[0211]

[0212]

[0213] in For reference distance, For reference path loss, This is the environmental path loss index.

[0214] Free space models, piecewise models, environmental calibration curves, lookup tables, machine learning regression, or other mappings of received power to distance can also be used.

[0215] This method is positioned as a coarse ranging method, allowing for propagation errors caused by multipath, obstruction, antenna directivity, and human influence; its direct technical value is to eliminate or reduce the structural bias of other concurrent user power being mistakenly counted as the target user power.

[0216] In one or more embodiments, step E further includes high SINR segmentation processing: setting a preset signal-to-interference-plus-noise ratio threshold. ;when ≥ At that time, directly use the total received power Effective received signal power for the target user ;when < At that time, according to )calculate.

[0217] refer to Figure 5 , Figure 5 A table showing examples of errors when approximating target user power with Total RSSI at high SINR is provided. When SINR is 10 dB, / Approximately 90.9%, As The power error is only 0.41 dB; when the SINR is 20 dB, / The accuracy is approximately 99.0%, with an error of only 0.043 dB. Therefore, in the high SINR region, the target users already account for the vast majority of the total power, directly... Approximately It is both simple and robust. In the low to medium SINR range, Total RSSI is the least representative of the target user, and the relevant domain must be relied upon to "extract" the target signal from the background.

[0218] In one or more embodiments, the protected area set G is determined based on the energy leakage range caused by residual frequency offset, timing deviation, phase noise, emission shaping filtering, or window function; the protected area set G is adaptively widened when the leakage range increases, and when the number of remaining frequency points is insufficient. Time-adaptive narrowing of the protected area set G, or cross-symbol supplementary statistics.

[0219] In one or more embodiments, if the frequency domain correlation output has multiple significant peaks, the location of the target correlation peak can be determined by combining the known timing deviation and / or carrier frequency offset search window. Instead of simply taking the global maximum value.

[0220] In one or more embodiments, the method targets the relevant peak power. Background power Or signal interference-to-noise ratio The effective received signal power is determined by performing one or more of the following processes: cross-symbol averaging, median filtering, exponential smoothing, zero-truncation, saturation limiting, or fixed-point scaling.

[0221] In one or more embodiments, the micro-frequency hopping signal includes secondary micro-frequency hopping (2ndmFH) or equivalent phase scrambling processing. The matching correlation processing in step B includes performing matching or compensation processing corresponding to the secondary micro-frequency hopping or equivalent phase scrambling processing; the target correlation peak power is determined in steps C and D. and background power The squared amplitude of the output based on frequency domain correlation Sure.

[0222] refer to Figure 4 , Figure 4 The three-layer invention structure and the 2ndmFH compatibility diagram are shown. Since the statistics are... Since it does not depend on the absolute phase of the correlated output, this method can coexist with the second micro-frequency hopping and does not require the 2ndmFH to be turned off specifically for RSSI estimation.

[0223] In one or more embodiments, calibration noise is utilized. Further, the equivalent interference power is obtained:

[0224]

[0225] and / or signal-to-noise ratio:

[0226]

[0227] and / or interference noise ratio:

[0228]

[0229] Used to determine whether noise is limited or interference is limited.

[0230] In one or more embodiments, steps B to E are performed on multiple target users respectively to obtain the effective received signal power of each target user; and an effective received signal strength indication of each demodulated or detected target user is output for one or more of the following purposes: transmit power control, near-far effect diagnosis, coverage statistics, motion trend judgment, link budget analysis, interference level assessment, or ranging confidence assessment in a combined positioning system.

[0231] In one or more embodiments, in a multi-antenna or multi-gateway scenario, the effective RSSI of the target user is calculated for each receiving branch, and then selection merging, weighting or positioning fusion are performed.

[0232] In one or more embodiments, the method is illustrated using a micro-frequency hopping symbol length P=31 as an example. Since P=31 is a prime number, then:

[0233]

[0234]

[0235] The receiver performs a 31-point DFT / FFT on the signal after the target root is matched, and obtains Confirm in the search window. and calculate Let the width of the protected area be... Then the set of protected areas G contains , , , , There are a total of 5 frequency points (the boundaries are processed modulo 31). From the remaining 31 − 5 = 26 candidate frequency points, exactly 16 frequency points are selected to form the background set. The selection rule can be continuous, segmented, uniform, pseudo-random, or a predetermined rule based on hardware addressing convenience. 16 internal frequency points Accumulation Then shift right by 4 bits to get .

[0236] Depend on and calculate:

[0237]

[0238] If the calculation result is negative, it is truncated to zero; if it is too large, saturation limiting is applied. Then calculate:

[0239]

[0240] like ≥ (For example If so, take directly. Then calculate:

[0241]

[0242] Based on:

[0243]

[0244] And the logarithmic distance path loss model:

[0245]

[0246] The coarse distance is obtained, and the meaning of each variable can be found in the following reference. Figure 6 Variable and symbol definition table.

[0247] In one or more embodiments, the method aims to ensure the target root parameter. Width of protected area SINR threshold The atomicity of configuration parameters such as path loss model during the update process can be ensured by the receiver baseband processor through read-modify-write sequences or semaphore mechanisms to perform configuration register updates.

[0248] Specifically, the process includes: acquiring the configuration register lock or semaphore; reading the current configuration data at the target address; performing a bitwise AND operation between the data to be written and the configuration mask to obtain the first temporary data; performing a bitwise AND operation between the current data and the inverse of the configuration mask to obtain the second temporary data; performing a bitwise OR operation between the first and second temporary data to generate the final configuration data; writing the final configuration data to the target configuration register; and releasing the configuration register lock or semaphore. This avoids changes to the root parameter or protected area parameter during symbol processing, which could lead to inconsistencies in peak search, background selection, and SINR conversion.

[0249] In one or more embodiments, the method executes an error handling procedure in response to an abnormal condition. The abnormal condition includes at least one of the following: failure to search for the target relevance peak, or insufficient number of remaining candidate background frequency points. , Zero or close to zero Errors include negative values ​​or overflows, missing path loss model parameters, and failed permission verification. The error handling process includes at least one of the following operations: terminating the current estimation, logging errors, performing system state rollback, maintaining the previous valid RSSI value, narrowing the protection zone width, supplementing background statistics across symbols, and outputting a low confidence flag.

[0250] In one or more embodiments, the method, through the coordinated operation of steps S101 to S108 described above, recovers the effective received power of the target user from the Total RSSI, which includes the power of all concurrent users, under mFHMA multi-user concurrent reception conditions, and thereby obtains a coarse range less affected by concurrent users. This scheme can recover RSSI user affiliation without detecting other users one by one, eliminates structural ranging bias caused by concurrent users, and has the advantages of high estimation accuracy and low-power hardware implementation.

[0251] refer to Figure 1 and Figure 4 This paper illustrates a block diagram of a target user effective received power estimation and coarse ranging device in a micro frequency hopping multiple access communication system according to one or more embodiments of this application. The device is applied at the receiver of an mFHMA communication system to implement the aforementioned method embodiments. The device includes: a total power acquisition module, a target matching and frequency domain transformation module, a peak value and background statistics module, a signal-to-interference-plus-noise ratio (SINR) determination module, a target user effective power determination module, and a distance determination module.

[0252] In one or more embodiments, the total power acquisition module is configured to receive a received signal comprising a target user signal and at least one other concurrent user signal and / or noise, and acquire the total received power of the received signal. Specifically, the total power acquisition module can sample complex baseband signals within a predetermined time window length L. Calculate according to the following formula:

[0253]

[0254] Alternatively, the output of the existing RSSI module in the analog front-end or digital receiver can be converted into a linear power domain power value through gain state, quantization scale, and calibration constant.

[0255] In one or more embodiments, the target matching and frequency domain transformation module is configured to perform matching correlation processing on the received signal according to the micro-frequency hopping pattern parameters corresponding to the target user, and to perform frequency domain transformation on the signal after matching correlation processing to obtain a frequency domain correlation output. Specifically, the target matching and frequency domain transformation module includes a local reference generation unit and a P-point transformation unit. The local reference generation unit performs micro-frequency hopping root parameter transformation on the target user k. Generate local reference micro-frequency hopping symbols The P-point conversion unit samples the complex baseband of the received signal. Multiplying pointwise by the conjugate of the local reference micro-frequency hopping symbol and performing a full P-point DFT / FFT yields:

[0256]

[0257] In one or more embodiments, the peak and background statistics module is configured to determine the target correlated peak power corresponding to the target user based on the frequency domain correlation output. The background power is determined based on the power at at least some frequency domain points other than the target correlation peak. Specifically, the peak and background statistics module includes a peak detector, a background frequency selector, an accumulator, and a shifter. The peak detector is configured to determine the peak within a search window. , and save The background frequency selector is configured to exclude the frequency point containing the target correlation peak from the frequency domain correlation output, and select exactly the frequency point from the remaining frequency points. The background set consists of individual frequency points. ,in P is a prime number and The accumulator is configured to collect the background set. The power accumulation at each frequency point is obtained The shifter is configured to... Shift right by SF bits to obtain the background set. The average power at each frequency point is used as the background power. .

[0258] In one or more embodiments, the signal-to-interference-plus-noise ratio (SIR) determination module is configured to determine the target correlation peak power. and background power Determine the signal-to-interference-plus-noise ratio (SIR) that characterizes the target user signal relative to other received components. Specifically, the signal-to-interference-plus-noise ratio (SIR) determination module includes a calculation unit configured to:

[0259]

[0260] Calculate the signal-to-interference-plus-noise ratio ,in Based on the micro-frequency hopping symbol length The frequency domain transform normalization method, correlator implementation method, and general function determined by receiver calibration. Under ideal matching conditions, the computation unit follows:

[0261]

[0262] Calculate the signal-to-interference-plus-noise ratio .

[0263] In one or more embodiments, the target user effective power determination module is configured to determine the total received power. H-Signal Interference-to-Noise Ratio Determine the effective received signal power corresponding to the target user Specifically, the target user effective power determination module includes multipliers, adders, and dividers or lookup tables. The multipliers are configured to calculate... and The product of 1 and 2; the adder is configured to calculate 1 and 2. The sum; the divider or lookup table is configured to calculate 1+ The ratio. The target user effective power determination module is based on:

[0264]

[0265] Determine the effective received signal power .

[0266] In one or more embodiments, the distance determination module is configured to determine the effective received signal power corresponding to the target user. Determine the distance information corresponding to the target user Specifically, the distance determination module includes an RSSI conversion unit, a path loss calculation unit, and a distance mapping unit. The RSSI conversion unit is configured according to:

[0267]

[0268] Convert the effective received signal power into logarithmic form.

[0269] The path loss calculation unit is based on:

[0270]

[0271] Calculate path loss.

[0272] The distance mapping unit is based on a predetermined path loss propagation model, derived from path loss. The mapping yields the coarse distance between the target user and the receiver. .

[0273] In one or more embodiments, the peak and background statistics module further includes a protected area setting unit, configured to set a protected area set G containing one or more protected frequency points near the target correlation peak, and the background frequency point selector selects exactly the frequency points from the remaining frequency points after removing the frequency point where the target correlation peak is located and the protected area set G. The background set consists of individual frequency points. The protected area set G is determined based on the energy leakage range caused by residual frequency offset, timing deviation, phase noise, emission shaping filtering, or window function; when the leakage range increases, the protected area set G is adaptively widened; when the number of remaining frequency points is insufficient... Time-adaptive narrowing of the protected area set G.

[0274] In one or more embodiments, the target user effective power determination module further includes a comparator configured to compare the signal-to-interference-plus-noise ratio. With the predetermined threshold The size. When ≥ At that time, the target user effective power determination module directly uses the total received power. The effective received signal power corresponding to the target user ;when At that time, the target user effective power determination module follows Calculate the effective received signal power .

[0275] In one or more embodiments, the computation unit of the signal-to-interference-plus-noise ratio (SINR) determination module implements the general function in one of the following ways. : Analytical formula calculation, pre-defined lookup table lookup, fixed-point ratio conversion, or receiver calibration curve mapping.

[0276] In one or more embodiments, the apparatus further includes a filtering module configured to filter the target correlation peak power. Background power Or signal interference-to-noise ratio Perform cross-sign averaging, median filtering, exponential smoothing, zero-truncation for negative values, saturation limiting, or fixed-point scaling.

[0277] In one or more embodiments, the device further includes a 2ndmFH matching module configured to perform matching or compensation processing corresponding to the secondary micro-frequency hopping or equivalent phase scrambling when the micro-frequency hopping signal includes secondary micro-frequency hopping or equivalent phase scrambling processing. The peak and background statistics module outputs the amplitude squared based on the frequency domain correlation. Determine the target-related peak power and background power .

[0278] Specifically, with Taking =31 as an example, =4, =16. Background frequency selector in exclusion After the protected area G, 16 frequency points are selected from the remaining frequency points to form a... Accumulator calculation:

[0279]

[0280] Shifter calculation:

[0281]

[0282] Calculation unit calculation:

[0283]

[0284] The target user effective power determination module calculates:

[0285]

[0286] The distance determination module is based on The path loss model outputs a coarse distance. This architecture only adds peak / background statistics, a small amount of control and conversion logic, making it suitable for low-power baseband.

[0287] In one or more embodiments, to ensure the atomicity of configuration register updates within the device, the device can be connected to the configuration register via a bus interface. When updating configurations such as target root parameters, protected area width, and SINR threshold, the baseband processor executes the update through a read-modify-write sequence or a semaphore mechanism. Specifically, this includes: acquiring the configuration register lock; reading the current configuration data; performing a bitwise AND operation between the data to be written and the configuration mask; performing a bitwise AND operation between the current data and the inverse of the configuration mask; performing a bitwise OR operation between the two temporary data sets to generate the final data; writing the final data to the target configuration register; and releasing the configuration register lock. This avoids concurrent conflicts between configuration updates and signal processing.

[0288] In one or more embodiments, the device executes an error handling procedure. Abnormal conditions include target relevance peak search failure, insufficient background candidate frequencies, etc. Zero Errors include overflow and permission verification failure. The error handling process includes at least one of the following: terminating the current operation, logging the error, rolling back the state, maintaining the previous valid value, and outputting a low confidence flag. Through the coordinated work of the above modules, the effective received power of the target user can be restored and coarse ranging can be completed under the condition of multi-user concurrent reception of mFHMA, which significantly improves the stability and hardware implementation efficiency of RSSI ranging in concurrent scenarios.

[0289] refer to Figure 1 and Figure 4 This diagram illustrates a block diagram of a receiver chip according to one or more embodiments of this application. The receiver chip is used in a receiver of a micro-frequency hopping multiple access communication system and includes the aforementioned target user effective received power estimation and coarse ranging device. The receiver chip may be a digital baseband chip, an integrated RF baseband chip, or a SoC chip, and includes a total power acquisition module, a target matching and frequency domain transformation module, a peak and background statistics module, a signal-to-interference-plus-noise ratio (SINR) determination module, a target user effective power determination module, and a distance determination module.

[0290] In the receiving chip, the total power acquisition module is connected to the analog-to-digital converter or digital front end to receive complex baseband samples. And calculate the total received power. The target matching and frequency domain transformation module includes a local reference generator and a P-point DFT / FFT engine, configured to match the target root parameters. A local reference is generated, and point-by-point conjugate multiplication and P-point frequency domain transformation are performed. The peak and background statistics module includes a peak detector, a background address controller, an accumulator, and a shifter. The background address controller skips the target peak address and the protected area address, selecting exactly the appropriate value from the remaining addresses. A valid address controls the accumulator's... The sum is accumulated, and the result is shifted right by SF bits by a shifter to obtain the final result. The signal-to-interference-plus-noise ratio (SIR) determination module includes a lookup table or a fixed-point divider, configured to calculate... The target user effective power determination module includes multipliers, adders, dividers, or lookup tables, configured to calculate... The distance determination module includes a path loss calculation unit and a distance mapping lookup table, configured to output coarse distances. .

[0291] In one or more embodiments, the receiving chip further includes a configuration register set and a bus interface. The configuration register set is used to store target root parameters. Micro-frequency hopping symbol length P, protected area width SINR threshold Path loss model parameters, etc. The bus interface is used for communication with an external digital baseband processor or microcontroller. The receiver chip may also include a multi-user parallel processing unit, configured to perform matching, frequency domain transformation, peak and background statistics, SINR determination, and effective power determination for multiple target users respectively.

[0292] In one or more embodiments, the receiving chip further includes a 2ndmFH matching compensation unit, configured to first complete the corresponding matching or compensation when the micro-frequency hopping signal contains secondary micro-frequency hopping or equivalent phase interference processing, and then perform statistical analysis. .

[0293] Specifically, the P-point DFT / FFT engine in the receiver chip performs a full transform on P=31 points. The peak detector stores... and The background address controller skips protected addresses and accumulates the power of exactly 16 valid addresses. The accumulation result is then arithmetically right-shifted by 4 bits to obtain... The signal-to-interference-plus-noise ratio (SIR) determination module can be calculated using a lookup table or a fixed-point divider.

[0294]

[0295] Target power calculation can be used It uses a lookup table or piecewise linear approximation. This structure adds only peak / background statistics, a small amount of control and conversion logic, making it suitable for low-power baseband chips.

[0296] In one or more embodiments, to ensure the atomicity of the configuration registers inside the receiving chip, the chip performs configuration updates through a read-modify-write sequence or a semaphore mechanism. Specifically, this includes: acquiring a configuration register lock; reading the current configuration data; performing a bitwise AND operation between the data to be written and the configuration mask; performing a bitwise AND operation between the current data and the inverse of the configuration mask; performing a bitwise OR operation between two temporary data sets to generate the final data; writing the final data to the target configuration register; and releasing the configuration register lock. In response to a failed authorization verification, the chip can terminate the configuration writing and record an error log.

[0297] In one or more embodiments, the receiving chip executes an error handling process, including at least one of terminating the current operation, logging an error log, rolling back the state, and outputting a low confidence flag. Through the integration of the above modules, the receiving chip can achieve effective RSSI estimation and coarse ranging for the target user with low hardware overhead under mFHMA multi-user concurrent reception conditions, recover RSSI user attribution, and eliminate structural ranging bias caused by concurrent users.

[0298] refer to Figure 1This diagram illustrates a block diagram of a receiver for a micro frequency hopping multiple access communication system according to one or more embodiments of this application. The receiver includes the aforementioned receiver chip, as well as radio frequency front-end circuitry, an analog-to-digital converter, and a digital baseband processor. This receiver is applied to mFHMA communication systems, such as low-power wide-area IoT base stations, gateways, aggregation nodes, or terminal devices.

[0299] In one or more embodiments, the radio frequency front-end circuitry is configured to receive antenna signals, perform low-noise amplification, filtering, down-conversion, and gain control, and output analog baseband or intermediate frequency signals. The analog-to-digital converter is configured to convert analog signals into digital signals and output complex baseband samples. The digital baseband processor is connected to the receiver chip and configured to perform at least some of the following operations: synchronization, demodulation, decoding, protocol processing, total power acquisition, target root matching, P-point frequency domain transformation, peak and background statistics, SINR determination, target user effective power determination, and range determination. The receiver chip includes a total power acquisition module, a target matching and frequency domain transformation module, a peak and background statistics module, a signal-to-interference-plus-noise ratio (SINR) determination module, a target user effective power determination module, and a range determination module.

[0300] In one or more embodiments, the receiver further includes a multi-antenna receiving branch, each receiving branch calculating the effective RSSI for the target user and performing selective combining, weighted combining, or location fusion. In some embodiments, the receiver further includes an RSSI module for providing Total RSSI, which can be stored separately from the effective RSSI for the target user. Total RSSI is used for global functions such as channel load and LBT, while Target / Effective RSSI is used for target user link assessment and coarse ranging.

[0301] Specifically, the RF front-end receives mFHMA multi-user concurrent signals, and the analog-to-digital converter outputs... The digital baseband processor calculates within a time window of length L. The receiving chip performs a P=31-point DFT / FFT on the signal after matching the target root to determine... and ,calculate and Output and coarse distance At high SINR, it can be directly used... approximate If 2ndmFH is enabled, the corresponding matching compensation will be completed first, and then the statistics will be calculated. .

[0302] In one or more embodiments, to ensure the atomicity of receiver configuration updates, the digital baseband processor updates the configuration register in the receiver chip through a read-modify-write sequence or semaphore mechanism. Specifically, this includes: acquiring a configuration register lock; reading the current configuration data; performing bitwise AND and OR operations to generate the final data; writing to the target configuration register; and releasing the configuration register lock. In response to a failed authorization verification, an error handling procedure is executed.

[0303] In one or more embodiments, in response to abnormal conditions, the receiver chip executes an error handling procedure, including at least one of terminating the current operation, logging an error log, rolling back the state, and outputting a low confidence flag. With this structure, the receiver can recover the effective power of the target user from the Total RSSI and complete coarse ranging under mFHMA multi-user concurrent reception conditions, thereby improving the reliability of link assessment, power control, and coverage analysis.

[0304] refer to Figure 4 This diagram illustrates a block diagram of a wireless communication device according to one or more embodiments of this application. The wireless communication device includes the aforementioned micro-frequency hopping multiple access communication system receiver, and further includes an antenna, a power management unit, and a communication interface. The wireless communication device can be an Internet of Things (IoT) terminal, a smart meter, an environmental monitoring node, an asset tracker, an industrial sensor, a gateway, or a base station device.

[0305] In one or more embodiments, the antenna is configured to receive mFHMA multi-user concurrent signals. A receiver, connected to the antenna, includes an RF front-end circuit, an analog-to-digital converter, a receiver chip, and a digital baseband processor. A power management unit is configured to provide power and power consumption management for the receiver, digital baseband processor, and communication interface. The communication interface is configured to output target user effective RSSI, coarse range, link quality, power control information, near-far effect diagnostic information, coverage statistics, or positioning assistance information. The receiver chip includes a total power acquisition module, a target matching and frequency domain transformation module, a peak and background statistics module, a signal-to-interference-plus-noise ratio (SIR / NOT) determination module, a target user effective power determination module, and a range determination module.

[0306] In one or more embodiments, the wireless communication device further includes a display, a sensor, or a mobile carrier. The receiver is mounted within the mobile carrier, sensor, or display. The sensor may include a temperature sensor, a humidity sensor, an accelerometer, a GPS module, etc. The wireless communication device may use RSSI coarse distance as an auxiliary constraint, confidence index, or anomaly detection measure for time delay ranging, but does not require RSSI to forcibly correct for higher-precision time delay measurements.

[0307] Specifically, in a smart meter reading scenario, the wireless communication device receives concurrent mFHMA signals from multiple meter terminals. For the target meter k, the receiver acquires... Perform target root matching and P-point DFT / FFT to determine and ,calculate and ,get and coarse distance At high SINR, directly using approximate If 2ndmFH is enabled, the corresponding matching compensation will be completed first, and then the statistics will be calculated. The communication interface will and Report to the network management platform.

[0308] In one or more embodiments, to ensure the atomicity of configuration updates in wireless communication devices, the digital baseband processor updates the configuration register in the receiver chip through a read-modify-write sequence or semaphore mechanism. Specifically, this includes: acquiring a configuration register lock; reading the current configuration data; performing a bitwise AND operation between the data to be written and the configuration mask; performing a bitwise AND operation between the current data and the inverse of the configuration mask; performing a bitwise OR operation between two temporary data sets to generate the final data; writing the final data to the target configuration register; and releasing the configuration register lock. In response to a failed authorization verification, an error handling procedure is executed.

[0309] In one or more embodiments, in response to abnormal conditions, the wireless communication device executes an error handling procedure, including at least one of terminating the current operation, logging an error log, rolling back the state, and outputting a low confidence flag. Through this structure, the wireless communication device can obtain a clear target user's effective RSSI and coarse range under mFHMA multi-user concurrent reception conditions, improving the reliability of power control, link quality assessment, coverage statistics, and positioning assistance, while maintaining the advantages of low power consumption and low-cost hardware implementation.

[0310] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, the phrase "comprising an element defined as..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0311] The above technical solutions only embody the preferred technical solutions of the present invention. Any modifications that may be made by those skilled in the art to certain parts thereof embody the principles of the present invention and fall within the protection scope of the present invention.

Claims

1. A method for estimating the effective received power of a target user and coarsely ranging in a micro-frequency hopping multiple access communication system, characterized in that, The method includes the following steps: Step A: Receive a received signal containing the target user signal and at least one other concurrent user signal and / or noise, and obtain the total received power of the received signal. ; Step B: Based on the micro-frequency hopping pattern parameters corresponding to the target user, the micro-frequency hopping pattern parameters include the micro-frequency hopping symbol length P, where P is a prime number, perform matched correlation processing on the received signal, and perform frequency domain transformation on the received signal after matched correlation processing to obtain frequency domain correlation output; Step C: Determine the target correlation peak power corresponding to the target user based on the frequency domain correlation output. The background power is determined based on the power of at least some frequency domain points other than the target correlation peak. ; Step D: Based on the target related peak power and the background power Determine the signal-to-interference-plus-noise ratio (SIR) that characterizes the target user signal relative to other received components. ; Step E: Based on the total received power and the signal-to-interference-plus-noise ratio Determine the effective received signal power corresponding to the target user. ;as well as Step F: Based on the effective received signal power corresponding to the target user Determine the distance information corresponding to the target user. .

2. The method according to claim 1, characterized in that, In step C, the background power is determined. include: make ,and ; Exclude the frequency points containing the target correlation peak from the frequency domain correlation output, and select exactly from the remaining frequency points. The background set consists of individual frequency points. ; The background set The power accumulation at each frequency point is obtained ;as well as The Move right The background set is obtained by taking the position. The average power at each frequency point is used as the background power. ; Excluding the frequency point where the target correlation peak is located from the frequency domain correlation output also includes: Exclude one or more protected frequency points near the target correlation peak; these protected frequency points constitute a protected area set G. From the remaining frequency points after removing the frequency points containing the target-related peaks and the protected area set G, select exactly... The background set consists of individual frequency points. ; The protected area set G is determined based on the energy leakage range caused by residual frequency offset, timing deviation, phase noise, emitter shaping filter, or window function; when the leakage range increases, the protected area set G is adaptively widened; when the number of residual frequency points is insufficient... The protected area set G is adaptively narrowed over time.

3. The method according to claim 1 or 2, characterized in that, Step E further includes: Preset signal-to-interference-plus-noise ratio threshold ; When the signal-to-interference-plus-noise ratio ≥ At that time, directly use the total received power. The effective received signal power corresponding to the target user ; When the signal-to-interference-plus-noise ratio At that time, according to Calculate the effective received signal power ; Step E is followed by: The effective received signal power Convert to its logarithmic form This serves as an indication of the effective received signal strength for the target user.

4. The method according to claim 1 or 2, characterized in that, In step F, the effective received signal power corresponding to the target user is used. Determine the distance information corresponding to the target user The process includes: According to the effective received signal power Target user transmit power Transmit antenna gain Receiver antenna gain and system losses Calculate path loss :as well as According to the predetermined path loss propagation model, the path loss... The mapping yields the coarse distance between the target user and the receiver. .

5. The method according to claim 1 or 2, characterized in that, Also includes: According to the total received power and the signal-to-interference-plus-noise ratio and pre-calibrated noise power Determine the equivalent interference power ; And / or based on the effective received signal power and the pre-calibrated noise power Determine the signal-to-noise ratio ; And / or based on the equivalent interference power and the pre-calibrated noise power Determine the interference-to-noise ratio .

6. The method according to claim 1 or 2, characterized in that, Also includes: Perform steps B to E for each of the multiple target users to obtain the effective received signal power for each target user. as well as For each demodulated or detected target user, output the effective received signal strength indication for the target user, for one or more of the following purposes: transmit power control, near-far effect diagnosis, coverage statistics, motion trend judgment, link budget analysis, interference level assessment, or ranging confidence assessment in a combined positioning system.

7. A device for estimating the effective received power of a target user and for coarse ranging in a micro-frequency hopping multiple access communication system, characterized in that, The apparatus is used to implement the method as described in any one of claims 1 to 6, and includes: The total power acquisition module is configured to receive a received signal containing a target user signal and at least one other concurrent user signal and / or noise, and acquire the total received power of the received signal. ; The target matching and frequency domain transformation module is configured to perform matching correlation processing on the received signal according to the micro-frequency hopping pattern parameters corresponding to the target user, and to perform frequency domain transformation on the signal after matching correlation processing to obtain frequency domain correlation output; The peak and background statistics module is configured to determine the target correlation peak power corresponding to the target user based on the frequency domain correlation output. The background power is determined based on the power of at least some frequency domain points other than the target correlation peak. ; The signal-to-interference-plus-noise ratio (SIR / NOT) determination module is configured to determine the target correlation peak power. and the background power Determine the signal-to-interference-plus-noise ratio (SIR) that characterizes the target user signal relative to other received components. ; The target user effective power determination module is configured to determine the total received power. and the signal-to-interference-plus-noise ratio Determine the effective received signal power corresponding to the target user. ;as well as The distance determination module is configured to determine the distance based on the effective received signal power corresponding to the target user. Determine the distance information corresponding to the target user .

8. A receiving chip, characterized in that, Includes the apparatus as described in claim 7.

9. A receiver for a micro-frequency hopping multiple access communication system, characterized in that, It includes the receiver chip as described in claim 8, as well as the radio frequency front-end circuit, the analog-to-digital converter, and the digital baseband processor.

10. A wireless communication device, characterized in that, The receiver of the micro frequency hopping multiple access communication system as described in claim 9 also includes an antenna, a power management unit, and a communication interface.

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