Intelligent signal strength regulation method for communication terminal device

Abstract

The application discloses a kind of communication terminal equipment signal strength intelligent regulation and control methods, it is related to the intelligent control and optimization technical field of communication terminal equipment, including strategy generation terminal will channel interference suppression coefficient α, spectrum efficiency optimization coefficient β, link stability coefficient γ and behavior correction factor ε input adaptive control decision model, output dynamic power regulation index δ;The execution control terminal adjusts radio frequency front end power amplifier bias voltage according to dynamic power regulation index δ.The application constructs adaptive control decision model by strategy generation terminal, inputs channel interference suppression coefficient α, spectrum efficiency optimization coefficient β, link stability coefficient γ and behavior correction factor ε in adaptive control decision model, outputs dynamic power regulation index δ, realizes the intelligent regulation and control decision of multi-factor cooperation, avoids the defect that traditional static threshold regulation cannot adapt dynamic scene, so that regulation strategy is more in line with actual business and environmental demand.

Description

Technical Field

[0001] This invention relates to the field of intelligent control and optimization technology for communication terminal equipment, and in particular to a method for intelligent signal strength regulation of communication terminal equipment. Background Technology

[0002] With the iteration of communication technology and the expansion of application scenarios for terminal devices, communication terminals have shifted from basic voice tools to multi-service carriers. Users demand low latency and stability for real-time voice and video streaming services, as well as low power consumption for background transmission services. At the same time, the terminal usage environment is becoming increasingly complex. Surrounding electromagnetic interference, multipath fading, dynamic changes in spectrum occupancy, and differences in user movement trajectories all place higher demands on signal strength control, requiring a balance between service quality, battery life, and chip heat dissipation.

[0003] Currently, traditional communication terminal signal strength regulation is mostly based on static thresholds or single parameters. Early methods relied on RSSI and RSRP feedback from base stations to set fixed rules, such as increasing power when the signal is below -95dBm and decreasing power when it is above -80dBm, which is difficult to adapt to dynamic environments. Although some subsequent improved technologies have introduced spectrum occupancy or single-band interference considerations, they have not achieved multi-dimensional data collaboration and generally ignore user behavior characteristics and the device's own status. They cannot distinguish user mobility differences and service type requirements, nor do they include battery capacity and chip junction temperature in the regulation.

[0004] Existing technologies have significant limitations: First, they lack dynamic adaptability. Static thresholds or single parameters cannot cope with complex electromagnetic environments and user behaviors, easily leading to frequent power fluctuations, increased power consumption, and difficulty in ensuring link stability. Second, they lack multi-factor collaborative optimization. They handle channel interference, spectrum efficiency, and link stability in isolation, without integrating environmental awareness data, user behavior data, and device status data, making it easy to overlook certain aspects during regulation. Third, the matching degree between service priority and device status is low. They cannot dynamically adjust weights according to service importance, nor can they provide targeted regulation when power is low or junction temperature is high, which can easily lead to damage to core service experience or increased equipment wear.

[0005] Therefore, it is essential to invent an intelligent signal strength control method for communication terminal equipment to solve the above problems. Summary of the Invention

[0006] The purpose of this invention is to provide a method for intelligent signal strength control of communication terminal equipment to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for intelligent signal strength control of a communication terminal device, comprising an environmental sensing terminal, a user behavior analysis terminal, a device status acquisition terminal, a strategy generation terminal, and an execution control terminal, specifically including the following steps:

[0008] S1, the environment perception terminal collects electromagnetic environment data in the surrounding area of the communication terminal device through a multi-band radio frequency sensor to form a signal environment comprehensive data set;

[0009] S2, the user behavior analysis terminal collects user movement trajectory data through an accelerometer and a gyroscope, and captures application layer service type data through a network interface to form a user behavior feature data set;

[0010] S3, the policy generation terminal performs pattern recognition on the user behavior feature data set to generate a behavior correction factor ε;

[0011] S4, the policy generation terminal performs time-frequency domain analysis on the signal environment comprehensive data set to obtain a channel interference suppression coefficient α, a spectrum efficiency optimization coefficient β, and a link stability coefficient γ;

[0012] S5, the policy generation terminal inputs the channel interference suppression coefficient α, the spectrum efficiency optimization coefficient β, the link stability coefficient γ, and the behavior correction factor ε into an adaptive control decision model, and outputs a dynamic power control index δ;

[0013] The adaptive control decision model is specifically:

[0014] ,

[0015] Wherein, α is the channel interference suppression coefficient, β is the spectrum efficiency optimization coefficient, γ is the link stability coefficient, ε is the behavior correction factor, η is the decision sensitivity parameter, θ is the decision threshold, δ is the dynamic power control index, e is the natural constant, ω1, ω2 and ω3 are weight coefficients, ω1+ω2+ω3=1 and ω1, ω2 and ω3∈[0, 1];

[0016] S6, the execution control terminal adjusts the bias voltage of the radio frequency front-end power amplifier according to the dynamic power control index δ;

[0017] The adjustment amount of the bias voltage needs to meet:

[0018] ,

[0019] Wherein, C is the remaining capacity of the battery, T is the chip junction temperature, V max is the maximum allowed bias voltage, C max is the nominal capacity of the battery, T a is the ambient temperature, T max is the maximum allowed junction temperature, δ is the dynamic power control index, is the power constraint term, is the temperature constraint term;

[0020] S7, the device state acquisition terminal monitors the battery residual capacity C and the chip junction temperature T in real time and feeds back to the strategy generation terminal.

[0021] Preferably, the signal environment comprehensive data set includes environment interference intensity data, spectrum occupancy data and multipath fading feature data; the environment interference intensity data includes specific frequency band background noise power spectrum density P n (f) and co-channel interference signal amplitude A int ; the spectrum occupancy data includes authorized frequency band occupation time length proportion T occ and unlicensed frequency band conflict times N coll ; the multipath fading feature data includes Doppler shift standard deviation σ f and delay spread τ rms .

[0022] Preferably, the user behavior feature data set includes mobile trajectory data and service type data; the mobile trajectory data includes three-dimensional space displacement vector and mobile speed standard deviation σ v ; the service type data includes real-time voice service identification I voice , video stream service identification I video and background transmission service identification I bg .

[0023] Preferably, the behavior correction factor ε is specifically:

[0024] ,

[0025] wherein v0 is a speed reference value, σ v is the mobile speed standard deviation, μ1, μ2 and μ3 are service type weight coefficients, μ1+μ2+μ3=1 and μ1, μ2 and μ3 ∈ [0, 1].

[0026] Preferably, the channel interference suppression coefficient α is specifically:

[0027] ,

[0028] wherein k p is an environment adaptation slope parameter, P n (f) is the specific frequency band background noise power spectrum density, P th is the noise power threshold, A int is the co-channel interference signal amplitude, A max is the maximum allowed interference amplitude, and e is the natural constant.

[0029] Preferably, the spectrum efficiency optimization coefficient β is specifically:

[0030] ,

[0031] wherein, T occ is the authorized frequency band occupation time length ratio, N coll is the unlicensed frequency band conflict number, λ1 is the authorized frequency band weight factor, and λ2 is the unlicensed frequency band conflict penalty factor.

[0032] Preferably, the link stability coefficient γ is specifically:

[0033] ,

[0034] wherein, σ f is the Doppler shift standard deviation, f c is the carrier frequency, τ rms is the delay spread, and τ0 is the delay spread reference value.

[0035] Preferably, the power constraint term satisfies: when <0.15, the dynamic power regulation index δ output value is limited to not more than 0.4;

[0036] The temperature constraint term satisfies: when >0.7, is forcibly set .

[0037] Technical effects and advantages of the present application:

[0038] The present application collects three-dimensional space displacement vector and moving speed standard deviation σ v by using an accelerometer and a gyroscope through user behavior analysis terminal, combines real-time voice service identifier I voice , video stream service identifier I video and background transmission service identifier I bg captured by a network interface, forms a user behavior feature data set and generates a behavior correction factor ε, so that the regulation strategy can accurately match the user moving state and service type demand, and avoid the problems of real-time service lag, background service power waste and the like caused by the traditional regulation ignoring the user behavior difference;

[0039] The present application constructs an adaptive regulation decision model through a strategy generation terminal, inputs the channel interference suppression coefficient α, the spectrum efficiency optimization coefficient β, the link stability coefficient γ and the behavior correction factor ε into the adaptive regulation decision model, and outputs the dynamic power regulation index δ, so as to realize intelligent regulation decision of multi-factor cooperation, avoid the defects that the traditional static threshold regulation cannot adapt to dynamic scenes, and make the regulation strategy more suitable for actual service and environmental demand.

[0040] The application adjusts the bias voltage of the radio frequency front-end power amplifier accurately according to the bias voltage adjustment formula containing the power constraint term and the temperature constraint term, while guaranteeing the signal strength and service quality, effectively controls the device power consumption and prevents the chip from overheating, and realizes the balance of service experience, battery endurance and device safety. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 The application provides a device connection schematic diagram.

[0042] Figure 2 The application provides a method step flow schematic diagram. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the application.

[0044] The application provides a device connection schematic diagram as shown in the figure. Figure 1 The application provides a device connection schematic diagram as shown in the figure.

[0045] The application provides a device connection schematic diagram as shown in the figure. Figure 2 The application provides a communication terminal device signal strength intelligent regulation method as shown in the figure, and specifically comprises the following steps.

[0046] S1, the environment perception terminal collects electromagnetic environment data in the surrounding area of the communication terminal device through a multi-band radio frequency sensor to form a signal environment comprehensive data set;

[0047] Further, in the above technical solution, the signal environment comprehensive data set comprises environment interference intensity data, spectrum occupation rate data and multipath fading characteristic data; the environment interference intensity data comprises specific frequency band background noise power spectrum density P n (f) and co-channel interference signal amplitude A int ; the spectrum occupation rate data comprises authorized frequency band occupation time length proportion T occ and unlicensed frequency band conflict times N coll ; and the multipath fading characteristic data comprises Doppler shift standard deviation σ f and time delay spread τ rms .

[0048] It is to be known that the specific frequency band background noise power spectrum density P n (f) is acquired by the following method: the multi-band radio frequency sensor carried by the environment perception terminal needs to cover the target communication frequency band of the communication terminal device, such as the 4G LTE 1.8 GHz frequency band and the frequency range is 1710 MHz~1785 MHz, the sensor needs to meet the performance requirements of noise figure ≤3 dB, sampling rate ≥3.6 GHz, the acquisition process needs to be carried out in the silent period of the communication terminal device without signal transmission and the silent time is set to ≥10 ms to cover the statistical characteristics of the noise, at the same time, the target frequency band is continuously scanned and the scanning step is set to 1 kHz; the time domain sampling signal collected by the sensor is transmitted to the signal processing unit and then the fast Fourier transform processing is performed, wherein the FFT point number is set to 1024 points corresponding to the frequency resolution of about 3.5 kHz, and the Hanning window is used to suppress the spectrum leakage, the power values of all frequency points in the target frequency band are extracted after the time domain signal is converted into the frequency domain power distribution, the abnormal values exceeding the average power of the frequency band by 3 dB are removed to exclude the instantaneous pulse interference, and then the average value of the remaining power values is taken as the power spectrum density value of the corresponding frequency point, and finally P n (f) and the function relationship with the frequency are stored into the signal environment comprehensive data set;

[0049] The co-frequency interference signal amplitude A int is acquired by the following method: the multi-band radio frequency sensor of the environment perception terminal and the sensor for collecting P n (f) are the same device and the sampling rate is ≥3.6 GHz, the sensor real-time captures the time domain waveform of the non-target signal in the same frequency band in the working frequency band of the communication terminal device, such as 1710 MHz~1785 MHz, the capture time is set to ≥1 μs to ensure that the minimum period of the interference signal is covered to avoid incomplete waveform acquisition; the captured time domain waveform is transmitted to the signal processing unit and then the peak holding algorithm is used to calculate the absolute value of the interference signal amplitude, wherein the peak holding time is set to 100 ns, and the judgment condition that the amplitude values of the continuous 3 sampling points all exceed the average amplitude of the background noise by 3 dB needs to be met to avoid that the instantaneous noise is misjudged as the interference, only then the peak value is identified as the effective interference amplitude, at the same time, the carrier frequency of the interference signal is recorded synchronously and the measurement accuracy is ±1 kHz, and the occurrence time stamp is recorded and the time accuracy is ±1 μs, finally the effective interference amplitude value is determined as A int and is included in the signal environment comprehensive data set;

[0050] The authorized frequency band occupation time length proportion T occThe following method is used to collect: the multi-band radio frequency sensor of the environment perception terminal monitors the authorized frequency band corresponding to the communication terminal device in real time, such as the 4G LTE 1.8 GHz frequency band 1710 MHz-1785 MHz, and the monitoring period is set to 1 s. In each monitoring period, the sensor identifies whether there is a non-target terminal signal in the frequency band, and the identification method is to distinguish and exclude the period of the target terminal's own signal transmission by the difference between the carrier frequency and the modulation method of the signal and the target terminal signal. At the same time, the cumulative time length t of the authorized frequency band occupied by the non-target signal in the period is counted occ The ratio of t occ to the total time length of the monitoring period 1 s is taken as the authorized frequency band occupation time length ratio of the period. The ratio data of 10 consecutive monitoring periods is collected, and the average value of the maximum value and the minimum value is taken as T occ and stored in the signal environment comprehensive data set.

[0051] The number of unlicensed frequency band conflicts N coll The following method is used to collect: the multi-band radio frequency sensor of the environment perception terminal continuously monitors the unlicensed frequency band that the communication terminal device can access, such as the 5.8 GHz ISM frequency band 5725 MHz-5875 MHz. The monitoring time is set to 1 min, and the sampling interval is set to 10 ms. If the sensor captures 2 or more non-target signals in the unlicensed frequency band at the same time at each sampling time, and the signal amplitude is ≥-60 dBm and the signal bandwidth overlap is ≥50%, it is determined as 1 unlicensed frequency band conflict. In 1 min of monitoring time, the number of conflicts that meet the above determination conditions is counted, and the signal interference of the target terminal itself accessing the unlicensed frequency band is excluded through the access timing and signal characteristics of the target terminal. Finally, N coll is obtained and included in the signal environment comprehensive data set.

[0052] The standard deviation of the Doppler shift σ f The following method is used to collect: the multi-band radio frequency sensor of the environment perception terminal captures the downlink signal between the communication terminal device and the target base station, such as the 1.8 GHz reference signal transmitted by the base station. The signal collection time is set to ≥50 ms, and the sampling rate is set to ≥3.6 GHz to ensure that enough signal samples are collected to reflect the frequency shift change. The collected signal is analyzed in the frequency domain, the signal frequency offset value corresponding to each sampling point is calculated, the difference between the actual receiving frequency and the nominal frequency is calculated based on the nominal frequency of the base station reference signal, and the frequency offset values of all sampling points are calculated. After removing the abnormal frequency offset values outside the range of μ±2σ f , the standard deviation of the frequency offset is recalculated, and finally σ f is obtained and stored in the signal environment comprehensive data set, where μ is the frequency offset average value.

[0053] The time delay spread τ rms The method is as follows: the multi-band radio frequency sensor of the environment perception terminal receives the multipath signals around the communication terminal device, takes the narrowband reference signal transmitted by the target base station as an example, uses the impulse response estimation method to obtain the time domain impulse response of the multipath signal, determines the main path signal with the largest amplitude in the impulse response and all secondary path signals with the amplitude ≥ the amplitude of the main path signal-10dB, records the time delay value of each secondary path signal relative to the main path signal, records the arrival time of the reference as the main path signal and the unit as ns, and sets the sampling rate ≥100MHz to ensure that the time delay measurement resolution ≤10ns; according to the root mean square calculation formula of the time delay spread The root mean square value of the time delay of all secondary path signals is calculated, wherein τ i is the time delay of the i-th secondary path, P i is the power of the i-th secondary path, N is the total number of samples, and finally τ rms is obtained, and is included in the signal environment comprehensive data set.

[0054] S2, the user behavior analysis terminal collects user movement trajectory data through an accelerometer and a gyroscope, captures application layer service type data through a network interface, and forms a user behavior feature data set;

[0055] Further, in the above technical solution, the user behavior feature data set includes movement trajectory data and service type data; the movement trajectory data includes a three-dimensional space displacement vector and a moving speed standard deviation σ v ; the service type data includes real-time voice service identification I voice , video stream service identification I video , and background transmission service identification I bg .

[0056] It should be noted that the three-dimensional space displacement vector The vector is acquired by the following method: the accelerometer and the gyroscope of the user behavior analysis terminal are used to acquire the vector, wherein the accelerometer is set to have a range of ±16g and a measurement accuracy of ±0.01g, the gyroscope is set to have a range of ±2000° / s and a measurement accuracy of ±0.1° / s, and the sampling interval of both is 10ms; a three-dimensional coordinate system is established first, the x-axis points to the horizontal east direction, the y-axis points to the horizontal north direction, and the z-axis points to the vertical upward direction; the accelerometer is used to acquire acceleration data in three directions, and the gyroscope is used to acquire angular velocity data in three directions; the two types of data are transmitted to a data processing unit, and the data is fused by a Kalman filtering algorithm to eliminate cumulative errors; the fused acceleration data is integrated once to obtain velocity data in three directions, and the velocity data is integrated twice to obtain displacement data in three directions; the collection time is set to be ≥100ms, and the displacement difference between the starting time and the ending time in the collection period is taken as the displacement components d x 、d y 、d z of the x-axis, the y-axis and the z-axis respectively, and finally a three-dimensional space displacement vector is formed and stored in the user behavior feature data set.

[0057] The real-time voice service identifier I voice is acquired by the following method: the user behavior analysis terminal captures the application layer data packet of the communication terminal device through a network interface such as a TCP / IP Ethernet interface, performs protocol analysis and feature recognition on the data packet, extracts the port number of the data packet, such as the commonly used port 5060 of VoLTE real-time voice service, i.e. SIP protocol, 5061, i.e. SIPS protocol, the transmission protocol type, such as SIP / H.264 / RTP, analyzes the frame length feature of the data packet, i.e. the frame length of the real-time voice service is usually 20ms / frame, and the corresponding data packet size is about 30-50 bytes and the code rate feature, i.e. the typical code rate is 12.2kbps-23.85kbps; if the captured data packet meets the port number matching, protocol type coincidence, frame length and code rate within the above range at the same time, the real-time voice service identifier I voice is set to "1" to indicate that the current real-time voice service is running, otherwise it is set to "0" to indicate that the real-time voice service is not running, and the value of I voice is stored in the user behavior feature data set.

[0058] The video stream service identifier I videoThe video stream service identifier I video is set to "1" to indicate that the current video stream service is running, otherwise it is set to "0" to indicate that the video stream service is not running, and the value of I video is included in the user behavior feature data set.

[0059] The background transmission service identifier I bg is obtained by the following method: the user behavior analysis terminal captures the application layer data packet of the communication terminal device through the network interface, first excludes the data packet identified as real-time voice service, i.e., I voice =1 and video stream service, i.e., I video =1, and then analyzes the remaining data packets, extracts the port number such as file transfer protocol FTP commonly used port 21 / 22, mail transfer protocol SMTP commonly used port 25, HTTP background transmission commonly used port 80 / 443, transmission rate, i.e., the average transmission rate within 10s is calculated, and the delay characteristic, i.e., the average delay of the data packet from sending to receiving is calculated. If the remaining data packets meet the port number corresponding to the background transmission protocol, the transmission rate fluctuation is ≤10% without obvious real-time bandwidth demand, and the average delay is ≥100ms without low delay requirement, the background transmission service identifier I bg is set to "1" to indicate that the current background transmission service is running, otherwise it is set to "0" to indicate that the background transmission service is not running, and the value of I bg is stored in the user behavior feature data set.

[0060] S3, the policy generation terminal performs pattern recognition on the user behavior feature data set to generate a behavior correction factor ε.

[0061] Further, in the above technical solution, the behavior correction factor ε is specifically:

[0062] ,

[0063] Wherein, v0 is the speed reference value, σ vwherein μ1, μ2 and μ3 are the service type weight coefficients, μ1+μ2+μ3=1 and μ1, μ2 and μ3∈[0, 1].

[0064] It should be noted that the setting of the speed reference value v0 is the reference speed of walking in a typical use scenario of the communication terminal device, and the specific implementation is as follows: in the factory pre-installed debugging stage of the device, at least 10 groups of standard walking data are collected by the accelerometer and the gyroscope, wherein the user moves straight at a speed of 1.0 m / s±0.2 m / s for 30 seconds, the mean value of the speed standard deviation σ v of each group is calculated, and 1.5 times of the mean value is taken as the initial v0 value and ensured to be in the reasonable interval of [0.8, 1.2] m / s; after the device is enabled, the user's moving speed is continuously monitored, and when the mean value of the speed monitored for 24 consecutive hours falls into the interval of [0.3v0, 0.7v0] or [1.3v0, 1.8v0], the speed reference value v0 is automatically updated by 90% quantile value of the speed standard deviation of the period, and the update interval is not less than 72 hours;

[0065] The service type weight coefficients μ1, μ2 and μ3 are determined by the weight values of the priority mapping table preset by the device based on the quality of service level requirement of the communication service: μ1 corresponds to the weight of real-time voice service, which is set to 0.5, because voice service is the most sensitive to time delay jitter, and needs the largest weight to guarantee signal stability; μ2 corresponds to the weight of video stream service, which is set to 0.3, because video service needs a medium weight to balance the bandwidth and time delay requirements; μ3 corresponds to the weight of background transmission service, which is set to 0.2, because background transmission can tolerate higher time delay, so the smallest weight is given; when the device state acquisition terminal monitors that the remaining capacity of the battery C < 0.2×C max , the power saving mode is automatically started, and μ1, μ2 and μ3 are adjusted to 0.6, 0.25 and 0.15 respectively, to preferentially guarantee the continuity of voice service; when the chip junction temperature T > 0.7×T max , the heat protection mode is triggered, μ2 is reduced to 0.2 and μ3 is increased to 0.3, to disperse the data processing load to reduce heat generation.

[0066] S4, the terminal generates a policy by performing time-frequency domain analysis on the signal environment comprehensive data set to obtain a channel interference suppression coefficient α, a spectrum efficiency optimization coefficient β and a link stability coefficient γ.

[0067] Further, in the above technical solution, the channel interference suppression coefficient α is specifically:

[0068] ,

[0069] wherein k p is an environmental adaptation slope parameter, P n (f) is the background noise power spectral density of a specific frequency band, Pth is a noise power threshold, A int is a co-channel interference signal amplitude, e is a natural constant. max is a maximum allowed interference amplitude, e is a natural constant.

[0070] It is to be known that the environment adaptation slope parameter k p is set: the communication terminal device is placed in the background noise power P n (f) from P th -10dB to P th +10dB dynamic environment, measure the response slope of α when the noise changes 1dB, take the average of 20 groups of test data as k p basic value, ensure that k p ∈[0.04, 0.08]dB -1 , such as 4G LTE 1.8GHz frequency band typical value k p =0.05dB -1 ; when the environment sensing terminal detects the working frequency band switching, such as switching from 4G 1.8GHz to 5G 3.5GHz, dynamically adjust according to the formula: , wherein f old is the carrier frequency before switching, f new is the carrier frequency after switching;

[0071] The typical value of the noise power threshold P th is-101dBm / Hz;

[0072] The maximum allowed interference amplitude A max is the upper limit of the co-channel interference signal amplitude that the communication terminal device can tolerate in the nominal working state, and the basic value is determined by the 1dB compression point of the radio frequency receiving link: A max =0.8×P1dB, wherein P 1dB is the 1dB compression point power value of the radio frequency front-end low noise amplifier, which is obtained by actually measuring in the device factory test through a vector network analyzer, such as the typical value P1dB=-15dBm of 4G LTE 1.8GHz frequency band, then A max =-18.2dBm;

[0073] Further, in the above technical solution, the spectrum efficiency optimization coefficient β is specifically:

[0074] ,

[0075] wherein T occ is the proportion of the licensed frequency band occupation time, N coll is the number of unlicensed frequency band conflicts, λ1 is the licensed frequency band weight factor, and λ2 is the unlicensed frequency band conflict penalty factor.

[0076] It should be noted that the licensed frequency band weight factor λ1 is specifically , wherein B auth is the current licensed frequency band bandwidth;

[0077] The unlicensed frequency band conflict penalty factor λ2 is specifically , wherein N max is the maximum number of unlicensed frequency bands supported by the device;

[0078] When the environment-aware terminal detects a carrier frequency switch, then .

[0079] Further, in the above technical solution, the link stability coefficient γ is specifically:

[0080] ,

[0081] , wherein σ f is the standard deviation of the Doppler shift, f c is the carrier frequency, τ rms is the delay spread, τ0 is the delay spread reference value, and e is the natural constant.

[0082] It should be noted that the carrier frequency f c is collected by the following method: the environment-aware terminal acquires the working frequency point configuration parameters of the current communication link in real time through the communication baseband chip, reads the locked target frequency band center frequency value from the radio frequency control register of the baseband chip, and the value is determined by the radio frequency transceiver after frequency synchronization according to the synchronization signal block or channel state information reference signal issued by the network side; during the reading process, the baseband chip accesses the programming register of the local oscillator frequency synthesizer of the radio frequency front end through the digital interface to directly output the nominal carrier frequency value of the current working channel as the value of f c with millihertz level precision;

[0083] The setting of the delay spread reference value τ0 is specifically implemented by the following method: during the actual deployment of the device, the environment-aware terminal continuously collects and statistics historical delay spread τ rms data, when the effective sample size exceeds 100 groups, the 85% quantile value of the sample is calculated, if the deviation of the value from the preset τ0 exceeds ±5ns, then τ0 is automatically updated to the current statistical quantile value; at the same time, when the device working frequency band is switched, τ0 is dynamically adjusted according to the frequency band characteristics, and the adjustment rule is .

[0084] S5, the channel interference suppression coefficient α, the spectrum efficiency optimization coefficient β, the link stability coefficient γ, and the behavior correction factor ε are input into the adaptive control decision model, and the dynamic power control index δ is output.

[0085] Furthermore, in the above technical solution, the adaptive control decision model specifically refers to:

[0086] ,

[0087] Where α is the channel interference suppression coefficient, β is the spectrum efficiency optimization coefficient, γ is the link stability coefficient, ε is the behavior correction factor, η is the decision sensitivity parameter, θ is the decision threshold, δ is the dynamic power regulation index, e is the natural constant, ω1, ω2 and ω3 are weight coefficients, ω1+ω2+ω3=1 and ω1, ω2 and ω3∈[0,1].

[0088] It is important to know that during the pre-delivery debugging phase of the equipment, the decision sensitivity parameter η is adjusted using a gradient search algorithm and the response sensitivity of the dynamic power control index δ during three typical service scenarios: real-time voice, video streaming, and background transmission. The optimal η value, which results in a service interruption rate of less than 1% and a power consumption reduction of ≥15%, is selected as the base value, with a typical range of 0.8 to 1.2. During equipment operation, the parameter η is dynamically corrected based on the real-time status. When the equipment status acquisition terminal detects that the remaining battery capacity C < 0.3 × C... max At that time, according to η′=η×[0.7+0.3×(C / C max [Reduce sensitivity to suppress power consumption when chip junction temperature T > 0.8 × T] max At that time, η is forcibly set to 0.5 to trigger a protective desensitization strategy;

[0089] The typical range of the decision threshold θ is [-1, 0.5], such as θ=-0.3 by default for 4G devices;

[0090] The default values ​​for the weighting coefficients ω1, ω2, and ω3 are set to ω1=0.35, ω2=0.25, and ω3=0.4, respectively, and their allocation follows the priority of stability > interference suppression > spectral efficiency. In actual operation, the weighting coefficients are dynamically adjusted according to the real-time service type and device status: when real-time voice service is activated, ω1 is increased to 1.2 times its original value to enhance anti-interference capability, while ω3 is compressed to 0.9 times to appropriately reduce the stability weight; when video streaming service is activated, ω2 is increased to 1.3 times to prioritize bandwidth requirements; if the device enters low-power mode (i.e., remaining capacity C / C...), the weighting coefficients are adjusted accordingly. max If the value is less than 0.3, then ω2 is reduced to 0.7 times to suppress power consumption during spectrum optimization, and ω3 is increased to 1.1 times to reduce retransmission power consumption by improving stability; if the chip junction temperature exceeds the safety threshold, i.e., T / T max>0.75, ω1 is suddenly reduced to 0.5 times to avoid power amplification aggravating heat, weight normalization processing is performed after each dynamic adjustment, and each weight value is forced to be in the interval [0.15, 0.55] to prevent extreme weight from causing imbalance in regulation.

[0091] S6, the control terminal adjusts the bias voltage of the radio frequency front-end power amplifier according to the dynamic power regulation index δ;

[0092] Further, in the above technical solution, the adjustment amount of the bias voltage needs to satisfy:

[0093] ,

[0094] Wherein, C is the battery remaining capacity, T is the chip junction temperature, V max is the maximum allowed bias voltage, C max is the nominal capacity of the battery, T a is the ambient temperature, T max is the maximum allowed junction temperature, δ is the dynamic power regulation index, is the power constraint term, is the temperature constraint term.

[0095] It should be known that the battery remaining capacity C is obtained by the battery management system built-in the communication terminal device;

[0096] The chip junction temperature T is obtained by the integrated temperature sensor built-in the radio frequency front-end power amplifier chip or the baseband chip of the communication terminal device;

[0097] The ambient temperature Ta is obtained by the NTC thermistor deployed inside the shell of the communication terminal device close to the edge and away from the heat generating elements such as radio frequency power amplifier and processor;

[0098] The maximum allowed bias voltage V max is determined by actual measurement during the device factory test stage, and a vector network analyzer is used to test the performance of the power amplifier, first, the bias voltage V 1dB of the amplifier when reaching 1dB compression point in the target working frequency band, such as 4G LTE 1.8GHz frequency band and 5G 3.5GHz frequency band, is measured, that is, the input bias voltage when the gain of the amplifier decreases by 1dB, then 90% of V 1dB is taken as the initial value of V max , so as to reserve 10% safety redundancy to avoid distortion or damage of the amplifier due to too high bias voltage; for different working frequency bands, V 1dB of the corresponding frequency band needs to be tested and V max is calculated, for example, the measured V 1dB =5V in 4G 1.8GHz frequency band, then V max=4.5V; 5G 3.5GHz band actual V 1dB =5.5V, then V max =4.95V;

[0099] The battery nominal capacity C max The value is set based on the factory specification parameters of the battery carried by the communication terminal device, and the official nominal capacity provided by the battery supplier is taken as the basis value. Before the device is shipped, it needs to be calibrated by the battery management system of the device state acquisition terminal for 3 complete charge-discharge cycles. Each cycle charges from the battery cutoff voltage to the full voltage, and then discharges to the cutoff voltage. The actual capacity at full capacity is recorded each time, and the average of the three actual capacities is taken as C max ;

[0100] The highest allowed junction temperature T max The value is set based on the rated working parameters of the core chip of the communication terminal device, including the RF power amplifier chip and the baseband processing chip. First, extract the rated maximum junction temperature marked in the chip datasheet. For example, the rated maximum junction temperature of the RF power amplifier chip is 125℃, and the rated maximum junction temperature of the baseband chip is 110℃. Then, make redundant adjustment combined with the actual heat dissipation capacity of the device. Take 90% of the rated maximum junction temperature of the chip as the T max of the corresponding chip. For example, the T max of the RF power amplifier chip is 112.5℃, and the T max of the baseband chip is 99℃.

[0101] S7, the device state acquisition terminal monitors the battery remaining capacity C and the chip junction temperature T in real time, and feeds back to the strategy generation terminal.

[0102] Further, in the above technical solution, the power constraint term satisfies: when <0.15, the dynamic power control index δ output value is limited to not more than 0.4;

[0103] The temperature constraint term satisfies: when >0.7, the T is forcibly set.

[0104] It should be noted that when the conflict scenario of <0.15 and δ>0.4 occurs, the conflict processing mechanism is triggered, specifically: when <0.15, the control terminal starts the dynamic clamping circuit, so that the actual output value δ out satisfies ; the strategy generation terminal synchronously activates the emergency power consumption mode, closes the non-core RF channel such as MIMO auxiliary flow, and raises ω3 to 0.8; the device state acquisition terminal performs C re-detection every 5 seconds, and if C > 0.18, exit the conflict handler.

[0105] Finally, it should be noted that the above only for the preferred embodiments of the present application, and is not intended to limit the application, although the foregoing embodiments of the application has been described in detail, for those skilled in the art, it still can be modified, or part of the technical features of the equivalent replacement, within the spirit and principles of the present application, any modification, equivalent replacement, improvement, etc., should be included within the scope of the present application.

Claims

1. A method for intelligent regulation of signal strength of a communication terminal device, characterized in that, The method comprises the following steps: S1, the environment perception terminal collects electromagnetic environment data in the surrounding area of the communication terminal device through a multi-band radio frequency sensor to form a signal environment comprehensive data set; S2, the user behavior analysis terminal collects user movement trajectory data through an accelerometer and a gyroscope and application layer service type data through a network interface to form a user behavior feature data set; S3, the policy generation terminal performs mode recognition on the user behavior feature data set to generate a behavior correction factor ε; S4, the policy generation terminal performs time-frequency domain analysis on the signal environment comprehensive data set to obtain a channel interference suppression coefficient α, a spectrum efficiency optimization coefficient β, and a link stability coefficient γ; S5, the policy generation terminal inputs the channel interference suppression coefficient α, the spectrum efficiency optimization coefficient β, the link stability coefficient γ, and the behavior correction factor ε into an adaptive control decision model to output a dynamic power control index δ; The adaptive control decision model is specifically: ， Wherein, α is the channel interference suppression coefficient, β is the spectrum efficiency optimization coefficient, γ is the link stability coefficient, ε is the behavior correction factor, η is the decision sensitivity parameter, θ is the decision threshold, δ is the dynamic power control index, e is the natural constant, ω1, ω2, and ω3 are weight coefficients, ω1+ω2+ω3=1 and ω1, ω2, and ω3∈[0, 1]; S6, the execution control terminal adjusts the bias voltage of the radio frequency front-end power amplifier according to the dynamic power control index δ; The adjustment amount of the bias voltage needs to satisfy: ， Wherein, C is the battery remaining capacity, T is the chip junction temperature, V max is the maximum allowed bias voltage, C max is the battery nominal capacity, T a is the ambient temperature, T max is the maximum allowed junction temperature, δ is the dynamic power regulation index, is the power constraint term, is the temperature constraint term; S7, the device state acquisition terminal monitors the battery remaining capacity C and the chip junction temperature T in real time and feeds back to the policy generation terminal.

2. The method of claim 1, wherein, The signal environment comprehensive data set comprises environment interference intensity data, frequency spectrum occupation rate data and multipath fading characteristic data; the environment interference intensity data comprises specific frequency band background noise power spectrum density P n (f) and co-channel interference signal amplitude A int ; the frequency spectrum occupation rate data comprises authorized frequency band occupation time length proportion T occ and unlicensed frequency band conflict times N coll ; the multipath fading characteristic data comprises Doppler frequency shift standard deviation σ f and time delay spread τ rms .

3. The method of claim 1, wherein the method further comprises: The user behavior feature data set includes mobile trajectory data and service type data; the mobile trajectory data includes three-dimensional space displacement vector and mobile speed standard deviation σ v ; the service type data includes real-time voice service identifier I voice , video stream service identifier I video and background transmission service identifier I bg .

4. The method of claim 1, wherein, The behavior correction factor ε is specifically: ， where v0 is a speed reference value, σ v is a moving speed standard deviation, μ1, μ2 and μ3 are service type weight coefficients, μ1+μ2+μ3=1 and μ1, μ2 and μ3∈[0,1].

5. The method of claim 1, wherein, The channel interference suppression coefficient α is specifically: ， where k p is the environmental adaptation slope parameter, P n (f) is the specific frequency band background noise power spectral density, P th is the noise power threshold, A int is the co-channel interferer signal amplitude, A max is the maximum allowed interferer amplitude, e is the natural constant.

6. The method of claim 1, wherein, The spectrum efficiency optimization coefficient β is specifically: ， Wherein, T occ is the authorized frequency band occupation time length ratio, N coll is the unlicensed frequency band conflict number, λ1 is the authorized frequency band weight factor, and λ2 is the unlicensed frequency band conflict penalty factor.

7. The method of claim 1, wherein the method further comprises: The link stability coefficient γ is specifically: ， where σ f is the standard deviation of Doppler shift, f c is the carrier frequency, τ rms is the delay spread, τ0is the reference value of delay spread, and e is the natural constant.

8. The method of claim 1, wherein the method further comprises: The power constraint term satisfies: when <0.15, the dynamic power regulation index δ output value is limited to not more than 0.4; The temperature constraint term satisfies: when > 0.7, it is forcibly set .

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