Multi-path fading compensation method for DVB-T2 signal, receiver, equipment and medium

Abstract

The invention relates to a multipath fading compensation method for a DVB-T2 signal, a receiver, equipment and a medium, and the method comprises the steps: carrying out the filtering processing of a DVB-T2 original broadcast signal received by a plurality of receiving ends of an MIMO receiving system, converting the DVB-T2 original broadcast signal into a digital signal, building a self-adaptive filter based on a recursive least square algorithm, and carrying out the filtering of the DVB-T2 original broadcast signal, the method comprises the following steps: performing multipath fading compensation on a digital signal by using an adaptive filter and taking the minimum error signal as a target to obtain a preliminary compensation signal, performing performance evaluation on the preliminary compensation signal according to a preset evaluation index, and if the preliminary compensation signal does not reach a preset performance standard, optimizing parameters in the adaptive filter to obtain a final compensation signal; and carrying out multipath fading compensation on the preliminary compensation signal until the preliminary compensation signal reaches a preset performance standard, and carrying out digital-to-analog conversion on the preliminary compensation signal to obtain a final recovery signal. According to the method, the stability and adaptability of the multipath fading compensation performance of the broadcast signal are effectively improved without depending on additional hardware investment.

Description

Technical Field

[0001] The present application relates to the technical field of digital video broadcasting, and in particular to a multipath fading compensation method, receiver, device and medium for DVB-T2 signals. Background Art

[0002] DVB-T2 (Digital Video Broadcasting-Second Generation Terrestrial) is the second generation standard for digital terrestrial television broadcasting. It improves spectrum utilization and signal quality, supports higher data transmission rates and stronger signal anti-interference capabilities. In practical applications, the DVB-T2 system still faces significant challenges from multipath fading, which is caused by the diversity of signal paths formed by reflection and refraction of signals encountered by various obstacles during transmission. The signal distortion and interference caused by the multipath effect, especially in urban areas with densely populated buildings and mountainous areas with complex terrain, greatly affect the stable reception and audio-visual quality of broadcast signals.

[0003] In the prior art, a variety of methods have been developed to compensate for multipath fading, such as using space diversity technology, frequency diversity technology, and time diversity technology. These technologies achieve redundant transmission of signals by increasing hardware complexity or sacrificing system resources, thereby enhancing the robustness of received signals. Although these methods improve reception performance to a certain extent, they often require additional hardware support, increasing system cost and complexity.

[0004] In addition, there are solutions that use various adaptive filtering techniques, such as minimum mean square error (MMSE) filters and Wiener filters. These filters attempt to weaken or eliminate the effects of multipath interference by dynamically processing the received signal. However, these techniques usually rely on accurate prior knowledge of the signal environment, and their performance and adaptability are often limited under highly dynamic and rapidly changing signal conditions. Summary of the invention

[0005] Based on this, it is necessary to provide a multipath fading compensation method, receiver, device and medium for DVB-T2 signals that can provide higher performance stability and faster adaptability without relying on additional hardware investment in response to the above technical problems.

[0006] A multipath fading compensation method for a DVB-T2 signal, the method comprising:

[0007] Acquire an original broadcast signal, where the original broadcast signal is a DVB-T2 signal received by multiple receiving ends of a MIMO receiving system;

[0008] After filtering the original broadcast signal, convert it into a digital signal;

[0009] An adaptive filter is constructed based on a recursive least squares algorithm, and the adaptive filter is used to perform multipath fading compensation on the digital signal to obtain a preliminary compensation signal, wherein the adaptive filter performs cyclic compensation on the data signal with the goal of minimizing the error signal;

[0010] The performance of the preliminary compensation signal is evaluated according to the preset evaluation index. If the preliminary compensation signal does not meet the preset performance standard, the parameters in the adaptive filter are optimized and then the preliminary compensation signal is compensated for multipath fading until the preliminary compensation signal meets the preset performance standard. Then, it is digital-to-analog converted to obtain the final recovery signal.

[0011] In one embodiment, filtering the original broadcast signal includes:

[0012] Amplifying the original broadcast signal using a low noise amplifier to obtain a broadcast signal with an improved signal-to-noise ratio;

[0013] The broadcast signal with improved signal-to-noise ratio is filtered by using a bandpass filter to retain the signal within a predetermined frequency band, thereby completing the filtering process.

[0014] In one embodiment, when converting the signal after filtering into a digital signal: the sampling frequency is set to be greater than twice the highest frequency of the original broadcast signal.

[0015] In one embodiment, when the adaptive filter is used to perform multipath fading compensation on the digital signal:

[0016] Initialize the weight vector and the inverse of the error covariance matrix;

[0017] For each time step, calculating a gain vector of the digital signal based on a forgetting factor;

[0018] The weight vector is updated based on the gain vector, and the output signal of the current time step is calculated according to the updated weight vector and the digital signal;

[0019] Obtaining an error signal at a current time step according to a difference between the output signal and an expected output signal;

[0020] updating the inverse of the error covariance matrix according to the error signal and the gain vector to obtain the inverse of the error covariance matrix of the current time step;

[0021] It is determined whether the error signal is minimum according to the inverse of the error covariance matrix. If it is not minimum, the weight vector is adaptively adjusted using the error signal until the inverse of the error covariance matrix converges.

[0022] In one embodiment, when the performance of the preliminary compensation signal is evaluated, the preset evaluation indicators include signal-to-noise ratio, bit error rate, and signal-to-interference ratio.

[0023] In one embodiment, when optimizing the parameters in the adaptive filter, the forgetting factor and the weight vector updating mechanism are optimized.

[0024] The present application also provides a receiver for DVB-T2 signals, the receiver comprising: a MIMO receiving module, a pre-processing module, an adaptive filter, a demodulator and a decoder;

[0025] The MIMO receiving module is used to receive the original broadcast signal of DVB-T2;

[0026] The pre-processing module is used to filter the original broadcast signal and convert it into a digital signal;

[0027] The adaptive filter is used to use a recursive least squares algorithm to perform cyclic multipath fading compensation on the data signal with the goal of minimizing the error signal to obtain a preliminary compensation signal, and to perform performance evaluation on the preliminary compensation signal according to a preset evaluation index. If the preliminary compensation signal does not meet the preset performance standard, the parameters in the adaptive filter are optimized, and then the preliminary compensation signal is subjected to multipath fading compensation until the preliminary compensation signal meets the preset performance standard, and then the preliminary compensation signal is subjected to digital-to-analog conversion to obtain a final recovery signal;

[0028] The demodulator and the decoder are used to process the final recovered signal in sequence to obtain the receiver output signal.

[0029] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0030] Acquire an original broadcast signal, where the original broadcast signal is a DVB-T2 signal received by multiple receiving ends of a MIMO receiving system;

[0031] After filtering the original broadcast signal, convert it into a digital signal;

[0032] An adaptive filter is constructed based on a recursive least squares algorithm, and the adaptive filter is used to perform multipath fading compensation on the digital signal to obtain a preliminary compensation signal, wherein the adaptive filter performs cyclic compensation on the data signal with the goal of minimizing the error signal;

[0033] The performance of the preliminary compensation signal is evaluated according to the preset evaluation index. If the preliminary compensation signal does not meet the preset performance standard, the parameters in the adaptive filter are optimized and then the preliminary compensation signal is compensated for multipath fading until the preliminary compensation signal meets the preset performance standard. Then, it is digital-to-analog converted to obtain the final recovery signal.

[0034] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0035] Acquire an original broadcast signal, where the original broadcast signal is a DVB-T2 signal received by multiple receiving ends of a MIMO receiving system;

[0036] After filtering the original broadcast signal, convert it into a digital signal;

[0037] An adaptive filter is constructed based on a recursive least squares algorithm, and the adaptive filter is used to perform multipath fading compensation on the digital signal to obtain a preliminary compensation signal, wherein the adaptive filter performs cyclic compensation on the data signal with the goal of minimizing the error signal;

[0038] The performance of the preliminary compensation signal is evaluated according to the preset evaluation index. If the preliminary compensation signal does not meet the preset performance standard, the parameters in the adaptive filter are optimized and then the preliminary compensation signal is compensated for multipath fading until the preliminary compensation signal meets the preset performance standard. Then, it is digital-to-analog converted to obtain the final recovery signal.

[0039] The multipath fading compensation method, receiver, device and medium for DVB-T2 signals are as follows: the DVB-T2 original broadcast signal received by multiple receiving ends of the MIMO receiving system is filtered and converted into a digital signal; an adaptive filter is constructed based on a recursive least squares algorithm; the adaptive filter is used to compensate the digital signal for multipath fading with the goal of minimizing the error signal to obtain a preliminary compensation signal; the preliminary compensation signal is then evaluated for performance according to a preset evaluation index; if the preliminary compensation signal does not meet the preset performance standard, the parameters in the adaptive filter are optimized, and then the preliminary compensation signal is compensated for multipath fading until the preliminary compensation signal meets the preset performance standard; the preliminary compensation signal is converted into digital-to-analog format to obtain the final recovery signal. This method effectively improves the stability and adaptability of the multipath fading compensation performance of the DVB-T2 signal without relying on additional hardware investment. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 Schematic diagram of a multipath fading compensation method for DVB-T2 signals in one embodiment;

[0041] Figure 2 It is a schematic diagram of a process of converting an original broadcast signal into a digital signal after filtering the original broadcast signal in one embodiment;

[0042] Figure 3 A schematic diagram of a process of performing multipath fading compensation in one embodiment;

[0043] Figure 4 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0045] Existing DVB-T2 multipath fading compensation technologies, including spatial diversity, frequency diversity, and time diversity, enhance the system's anti-interference ability by increasing the redundancy of signal transmission, but these methods usually require additional hardware resources and high operating costs. For example, spatial diversity technology requires multiple antennas to work simultaneously, which not only increases equipment costs, but also increases energy consumption and system complexity. Although frequency diversity and time diversity technologies can improve the signal reception quality to a certain extent, they have high requirements for bandwidth and time delay, which limits their application in scenarios with tight bandwidth resources or high real-time requirements.

[0046] In addition, although adaptive filtering technologies such as Wiener Filtering and Minimum Mean Square Error (MMSE) filtering can be dynamically adjusted according to the statistical characteristics of the received signal, these technologies usually rely on accurate prior knowledge of the signal environment, making it difficult for them to quickly adapt to non-ideal or rapidly changing signal environments. Especially in areas with densely populated high-rise buildings in cities or areas with complex terrain, the multipath effect changes rapidly and unpredictably. The adjustment response of existing adaptive filtering technologies often lags behind environmental changes and cannot effectively deal with instantaneous severe signal fading.

[0047] In summary, although existing multipath fading compensation technologies are effective under certain conditions, their performance is not stable under highly dynamic, resource-constrained or extreme multipath conditions, and often requires sacrificing system resources or increasing operating costs.

[0048] In response to the above problems, Figure 1 As shown, in this application, a multipath fading compensation method for DVB-T2 signals is proposed, which specifically includes the following steps:

[0049] Step S100: acquiring an original broadcast signal, where the original broadcast signal is a DVB-T2 signal received by multiple receiving terminals of a MIMO receiving system.

[0050] Step S110: After filtering the original broadcast signal, convert it into a digital signal.

[0051] Step S120, constructing an adaptive filter based on a recursive least squares algorithm, and using the adaptive filter to perform multipath fading compensation on the digital signal to obtain a preliminary compensated signal, wherein the adaptive filter performs cyclic compensation on the data signal with the goal of minimizing the error signal.

[0052] Step S130, performing a performance evaluation on the preliminary compensation signal according to a preset evaluation index. If the preliminary compensation signal does not reach the preset performance standard, the parameters in the adaptive filter are optimized, and then the preliminary compensation signal is compensated for multipath fading until the preliminary compensation signal reaches the preset performance standard. Then, the preliminary compensation signal is converted into digital-to-analog format to obtain a final recovery signal.

[0053] In this application, an efficient technical solution is proposed that can dynamically, real-time and adaptively compensate for multipath fading to optimize the operating performance and user experience of the DVB-T2 system. This method is based on the adaptive filtering technology of recursive least squares (RLS), aiming to fill this gap in the prior art and provide a solution strategy that does not rely on complex hardware or excessively sacrifice system resources, effectively coping with the challenges brought by multipath fading.

[0054] In step S100, multiple antenna technology (Multiple Input Multiple Output, MIMO) is used to enhance the signal reception quality and the anti-interference capability of the system.

[0055] Specifically, the signal captured by each receiving antenna of the MIMO system can be expressed as the superposition of signals after reflection and refraction along multiple different paths. The different characteristics of these paths (such as path loss and delay) lead to differences in amplitude and phase of the signal replicas. The received signal model can be expressed as:

[0056]

[0057] In the above formula, s(t) is the received signal, a i and τ i are the attenuation coefficient and time delay of the ith path, respectively, and n(t) is the noise term.

[0058] In step S110, filtering the original broadcast signal includes: firstly amplifying the original broadcast signal with a low noise amplifier to obtain a broadcast signal with improved signal-to-noise ratio, and then filtering the broadcast signal with improved signal-to-noise ratio with a bandpass filter to retain the signal within a predetermined frequency band to complete the filtering process.

[0059] In this embodiment, the received signal is first amplified by a low noise amplifier (LNA) to improve the signal-to-noise ratio (SNR). The amplified signal enters a bandpass filter (BPF), which is designed to attenuate interfering signals and noise outside the frequency band to ensure that only signals in the target frequency band are sent to the next processing stage. The transfer function of the bandpass filter can be expressed as:

[0060]

[0061] In the above formula, f c is the cutoff frequency of the filter and τ is the intrinsic delay caused by the filter.

[0062] Specifically, the received signal is first amplified by a low noise amplifier (LNA) to improve the signal-to-noise ratio (SNR). During the amplification process, special attention is paid to adjusting the gain of the amplifier to optimize the signal quality and minimize the noise introduced by the amplification process. The amplified signal enters the bandpass filter (BPF), which is designed to attenuate signals and external noise in non-target frequency bands to ensure that only signals within the predetermined frequency band can pass. The transfer function of the bandpass filter is customized according to the preset cutoff frequency and filtering characteristics to ensure effective suppression of surrounding electromagnetic interference.

[0063] Furthermore, the signal after preliminary filtering needs to be converted into a digital format for more complex digital signal processing, and this conversion is completed by an analog-to-digital converter (ADC). The key to selecting an ADC lies in its sampling rate and resolution. These two parameters directly affect the quality and efficiency of the final signal processing. The sampling rate is usually set to more than twice the highest frequency of the signal to avoid aliasing.

[0064] Furthermore, the digital signal is synchronized and analyzed in the time domain through a specific processing algorithm. This process includes signal delay estimation and correction. Through algorithm optimization, the signal data received by different antennas are adjusted and synchronized in real time to reduce time offset and phase error, thus preparing for subsequent multipath fading compensation.

[0065] like Figure 2 As shown in the figure, it is the whole signal preprocessing process.

[0066] In step S120, an adaptive filter is constructed based on a recursive least squares (RLS) algorithm.

[0067] The basic mathematical model of the RLS filter can be expressed as:

[0068] y(n)=w T (n)x(n)

[0069] In the above formula, y(n) is the output at time n, w(n) is the weight vector of the filter coefficients at time n, and x(n) is the input signal vector, that is, the signal that needs to be compensated for multipath fading.

[0070] Here, the goal of the adaptive filter is to adjust the coefficients w(n) so that the output y(n) is as close as possible to the desired signal d(n). The error signal e(n) is defined as:

[0071] e(n)=d(n)-y(n)

[0072] Specifically, the core of the sparse update rule of the RLS filter is to minimize the linear least squares cost function, which is dynamically adjusted over time to adapt to signal changes. The coefficient update rule is expressed as:

[0073] w(n+1)=w(n)+k(n)e(n)

[0074]

[0075] In the above formula, k(n) is the gain vector, P(n) is the inverse of the covariance matrix, λ is the forgetting factor used to determine the influence of past data on the current estimate, and n represents the time step.

[0076] In the DVB-T2 system, since the signal propagates on multiple paths, each path may cause different time delays and amplitude attenuation, resulting in the receiver receiving the superposition of these path effects. The RLS algorithm effectively identifies and compensates for these multipath effects by dynamically adjusting its filter coefficients to restore the original characteristics of the signal. By updating the filter coefficients in real time, RLS can quickly adapt to changes in the signal environment and reduce signal distortion caused by multipath effects.

[0077] The signal to be compensated for multipath fading can be further expressed as:

[0078]

[0079] In the above formula, a i and τ i Represent the attenuation and delay of the i-th path respectively, and n(t) is the noise. The RLS algorithm minimizes the error between the output and the expected signal by updating its weight vector w(n). This update process takes into account the time-varying and non-stationary characteristics of the signal, which is very suitable for processing the transmission problem of DVB-T2 signals in complex multipath environments.

[0080] In this embodiment, when an adaptive filter is used to perform multipath fading compensation on a digital signal: first, the weight vector and the inverse of the error covariance matrix are initialized. For each time step, the gain vector of the digital signal is calculated based on the forgetting factor, the weight vector is updated based on the gain vector, and the output signal of the current time step is calculated based on the updated weight vector and the digital signal. The error signal of the current time step is obtained based on the difference between the output signal and the expected output signal. The inverse of the error covariance matrix is ​​updated based on the error signal and the gain vector to obtain the inverse of the error covariance matrix of the current time step. It is determined whether the error signal is minimum based on the inverse of the error covariance matrix. If it is not minimum, the weight vector is adaptively adjusted using the error signal until the inverse of the error covariance matrix converges. The entire multipath fading compensation process, such as Figure 3 shown.

[0081] Specifically, for each time step n, the gain vector k(n) is calculated using the following formula:

[0082]

[0083] In the above formula, x(n) represents the input signal vector of the current time step, and λ represents the forgetting factor, which is used to adjust the influence of old data on the new estimation.

[0084] Furthermore, the weight vector w(n+1) is updated using the following formula:

[0085] w(n+1)=w(n)+k(n)e(n)

[0086] In the above formula, e(n) represents the error signal at time step n, that is, the difference between the expected output and the current output of the algorithm.

[0087] Furthermore, the inverse of the error covariance matrix P(n+1) is updated using the following formula:

[0088]

[0089] In this embodiment, by updating the inverse of the error covariance matrix in real time, this method improves the adaptability of the algorithm to signal mutations and enhances the filtering performance.

[0090] After the compensation by the adaptive filter, in step S130, the coefficients in the adaptive filter are further optimized according to the performance judgment result of the compensated signal, and the optimized adaptive filter is used for compensation.

[0091] In this embodiment, according to the result of updating the weight vector w(n+1), the filtering parameters are dynamically adjusted to compensate for the signal distortion caused by multipath fading in real time, thereby improving the accuracy of signal processing and the response speed of the system; if the signal quality after RLS algorithm processing reaches a preset threshold, the processed signal continues to be transmitted to the next system module; otherwise, the RLS algorithm parameters are adjusted and the signal processing is performed again to ensure that the output signal quality meets the system requirements.

[0092] Specifically, after completing the adaptive filtering process, the performance evaluation phase is entered to verify the compensation effect of the recursive least squares (RLS) algorithm on multipath fading. The first step of performance evaluation is to set evaluation indicators, including signal-to-noise ratio (SNR), bit error rate (BER), and signal-to-interference ratio (SIR).

[0093] Then, processed signal samples are collected from the output of the processing algorithm, covering a variety of signal scenarios from high-density multipath interference to low-interference environments. Next, these samples are analyzed in detail using advanced signal analysis tools to automatically calculate indicators such as SNR, BER, and SIR to evaluate the consistency of signal processing and the performance of the filtering algorithm. The analysis results are compared with preset performance standards to determine whether the RLS algorithm has effectively improved signal quality.

[0094] Furthermore, based on the analysis results, if the signal processing does not meet the preset performance standards, the parameters of the RLS algorithm are adjusted, including the forgetting factor, the weight vector update mechanism, etc., to optimize the compensation effect of the algorithm.

[0095] In this embodiment, the forgetting factor is used to balance the algorithm's sensitivity to new and old data. Its value is usually set between 0 and 1: when λ=1, the algorithm considers all historical data and there is no forgetting effect. When λ<1, the impact of older data is reduced, making the algorithm pay more attention to recent data. The dynamic adjustment of the forgetting factor is usually based on the rate of change of the signal or the change of the error. For example, an automatic adjustment mechanism based on a predetermined threshold can be set: if the error decreases, the λ value may be increased to slow down the response to new data and maintain a more stable performance. If the error increases, the λ value is reduced to quickly adapt to the new data environment.

[0096] At the same time, all test data and analysis results are recorded and formed into a detailed performance evaluation report, which includes the achievement of performance indicators, statistical analysis of algorithm performance, and improvement suggestions. In addition, the conclusions of the performance evaluation are fed back to the system design team for further optimization and algorithm adjustment. This feedback mechanism ensures the continuous improvement of the signal processing system and the steady improvement of performance.

[0097] In the above-mentioned multipath fading compensation method for DVB-T2 signals, the DVB-T2 original broadcast signal received by multiple receiving ends of the MIMO receiving system is filtered and converted into a digital signal, an adaptive filter is constructed based on the recursive least squares algorithm, and the adaptive filter is used to compensate the digital signal for multipath fading with the goal of minimizing the error signal to obtain a preliminary compensation signal, and then the performance of the preliminary compensation signal is evaluated according to the preset evaluation index. If the preliminary compensation signal does not meet the preset performance standard, the parameters in the adaptive filter are optimized, and then the preliminary compensation signal is compensated for multipath fading until the preliminary compensation signal meets the preset performance standard, and then it is converted into digital-to-analog to obtain the final recovery signal. This method proposes an adaptive filtering technology based on the recursive least squares algorithm. This technology can improve the efficiency and accuracy of multipath fading compensation by dynamically adjusting the filtering parameters and compensating for the signal distortion caused by multipath fading in real time, reduce the dependence on hardware resources, improve the adaptability and flexibility of the system, and optimize the overall system performance. Compared with traditional compensation methods, such as spatial diversity and frequency diversity, this method does not require additional hardware support, and improves the signal processing process through software algorithms to achieve cost and energy reduction. At the same time, the rapid adaptability of the RLS algorithm effectively responds to environmental changes and improves the system's adaptability to complex multipath environments, thereby improving signal stability and reception quality, and improving the end-user's audio-visual experience. Overall, this method overcomes the limitations of existing technologies through an efficient, low-cost and highly adaptable solution, and achieves more stable and reliable transmission and reception of DVB-T2 signals.

[0098] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0099] In this embodiment, based on the multipath fading compensation method for DVB-T2 signals, a receiver for DVB-T2 signals is proposed, and the receiver includes: a MIMO receiving module, a preprocessing module, an adaptive filter, a demodulator and a decoder. Among them, the MIMO receiving module is used to receive the original broadcast signal of DVB-T2, the preprocessing module is used to filter the original broadcast signal and convert it into a digital signal, the adaptive filter is used to use the recursive least squares algorithm to perform multipath fading compensation on the data signal cyclically with the goal of minimizing the error signal to obtain a preliminary compensation signal, and the preliminary compensation signal is evaluated according to the preset evaluation index. If the preliminary compensation signal does not meet the preset performance standard, the parameters in the adaptive filter are optimized, and then the preliminary compensation signal is compensated for multipath fading until the preliminary compensation signal meets the preset performance standard, and then it is converted into digital-to-analog to obtain the final recovery signal. The demodulator and the decoder are used to process the final recovery signal in turn to obtain the receiver output signal.

[0100] For specific limitations on the adaptive filter, please refer to the above limitations on the multipath fading compensation method for DVB-T2 signals, which will not be repeated here.

[0101] In fact, the multipath fading compensation method for DVB-T2 signals is implemented at the receiving end, that is, the above-mentioned adaptive filter hardware module is integrated into the existing DVB-T2 receiving equipment. This includes adjusting the front end of the receiver to support the new filter configuration and ensuring the compatibility of the filter with other components such as the demodulator and decoder.

[0102] In this embodiment, the strategy adopted in integrating the adaptive filter hardware module into the existing DVB-T2 receiving device includes:

[0103] Before any actual work begins, a detailed technical evaluation is performed, including a compatibility analysis of the receiver's existing hardware and software. This involves evaluating whether the technical specifications of the new filter match the interface standards of existing system components (such as demodulators and decoders). Necessary hardware changes are determined, such as adapters or converters for the filter connection ports, and new signal amplification or conditioning circuits that may need to be added.

[0104] Further, after confirming that the new filter is compatible with the existing system hardware, design and implement the required hardware modifications. This may include rewiring, replacing connectors, or installing new circuit boards. Perform preliminary functional tests on the newly integrated hardware components to ensure that they do not conflict with the rest of the receiver at the physical and electrical levels.

[0105] Next, the receiver firmware is updated to support the control and data processing of the new filter. This includes writing new drivers and modifying existing signal processing algorithms to adapt to the characteristics of the new filter. Finally, software-level integration testing is performed to ensure that the new code is not only compatible with the new filter, but also works seamlessly with the existing demodulation and decoding process.

[0106] Comprehensive testing is performed at the system level, including testing of the entire process of signal capture, filtering, demodulation, and decoding. Focus on evaluating the impact of new filters on system performance, such as signal-to-noise ratio, bit error rate, and receiving sensitivity. Adjust system parameters such as filter configuration, signal amplification level, and demodulator settings based on test results to ensure optimal performance of the overall system.

[0107] The performance of the new system is verified in the actual operating environment, and actual operating data is collected for analysis to ensure that the new system performs well under all predetermined operating conditions. Necessary optimization is carried out based on operating data and user feedback to continuously improve the stability and efficiency of the system.

[0108] In the above process, when confirming whether the new filter is compatible with the existing system hardware, the interface standardization is usually carried out first to ensure that the input and output signal levels and formats of the new filter module are consistent with the interfaces of the existing demodulator and decoder. This includes adjusting the output voltage level and impedance of the filter to match the input requirements of the demodulator, so as to avoid signal overload or signal weakness affecting the demodulation effect. Next, the clock synchronization of the new filter module is precisely controlled to ensure that the signal output by the filter is strictly synchronized with the clock system of the demodulator and decoder. This is usually achieved by integrating a phase-locked loop (PLL) in the filter module to ensure that the synchronization accuracy of signal processing can be maintained even in complex broadcast environments. A programmable logic controller (PLC) is then introduced to dynamically adjust the operating parameters of the filter, such as bandwidth and cutoff frequency. This enables the filter to automatically adjust its operating state according to the characteristics of the received signal, which not only improves the flexibility of signal processing, but also reduces compatibility issues caused by fixed equipment configuration. An intermediate interface layer is added, which acts as a buffer between the filter and the demodulator to balance and adjust the signal from the filter output to the demodulator input. This layer can monitor the signal quality in real time and adjust the gain or attenuation of the signal as needed to ensure that the signal delivered to the demodulator is always in the best condition. Finally, a comprehensive system test is performed, including but not limited to signal continuity test, signal interference test and long-term stability test. These tests help identify and solve compatibility issues and ensure that the new filter can work with other components in the receiver front end without introducing additional interference or signal distortion.

[0109] After integrating the adaptive filter into the existing DVB-T2 receiving equipment, the performance of the receiving equipment needs to be evaluated. The process includes benchmark testing, real-time scenario testing, performance indicator quantification, system stability and reliability testing, and user feedback collection.

[0110] Specifically, before integrating new technologies, a benchmark test is first performed to record the system's performance data when adaptive filtering technology is not enabled, including indicators such as signal quality, data throughput, and error rate.

[0111] Specifically, the performance of the new system is tested under a variety of actual receiving conditions, that is, scenario testing is carried out, such as in urban, rural and mountainous areas, and other environments with obvious multipath effects. The compensation effect of the adaptive filter in various environments is recorded and analyzed.

[0112] Specifically, quantitatively evaluate key performance indicators such as signal-to-noise ratio (SNR), bit error rate (BER), and signal distortion. Use statistical and signal analysis tools to compare the performance differences before and after adjustments.

[0113] Specifically, long-term running tests are used to evaluate the stability and reliability of the system. The performance of the system during continuous operation is monitored, including the thermal stability of the hardware and the memory leak issues of the software.

[0114] Specifically, we collected feedback from actual users to understand the impact of technology upgrades on user experience, including users' subjective evaluation of improvements in image and sound quality, as well as their satisfaction with system response speed.

[0115] Through the above-mentioned meticulous integration strategy and comprehensive performance evaluation, the effectiveness and adaptability of adaptive filtering and multipath compensation technology in DVB-T2 system can be ensured. This not only improves the technical performance of the system, but also enhances the overall satisfaction of users, thus promoting the commercial success and long-term sustainable development of the technology.

[0116] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a multipath fading compensation method for DVB-T2 signals is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0117] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0118] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0119] Acquire an original broadcast signal, where the original broadcast signal is a DVB-T2 signal received by multiple receiving ends of a MIMO receiving system;

[0120] After filtering the original broadcast signal, convert it into a digital signal;

[0121] An adaptive filter is constructed based on a recursive least squares algorithm, and the adaptive filter is used to perform multipath fading compensation on the digital signal to obtain a preliminary compensation signal, wherein the adaptive filter performs cyclic compensation on the data signal with the goal of minimizing the error signal;

[0122] The performance of the preliminary compensation signal is evaluated according to the preset evaluation index. If the preliminary compensation signal does not meet the preset performance standard, the parameters in the adaptive filter are optimized and then the preliminary compensation signal is compensated for multipath fading until the preliminary compensation signal meets the preset performance standard. Then, it is digital-to-analog converted to obtain the final recovery signal.

[0123] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0124] Acquire an original broadcast signal, where the original broadcast signal is a DVB-T2 signal received by multiple receiving ends of a MIMO receiving system;

[0125] After filtering the original broadcast signal, convert it into a digital signal;

[0126] An adaptive filter is constructed based on a recursive least squares algorithm, and the adaptive filter is used to perform multipath fading compensation on the digital signal to obtain a preliminary compensation signal, wherein the adaptive filter performs cyclic compensation on the data signal with the goal of minimizing the error signal;

[0127] The performance of the preliminary compensation signal is evaluated according to the preset evaluation index. If the preliminary compensation signal does not meet the preset performance standard, the parameters in the adaptive filter are optimized and then the preliminary compensation signal is compensated for multipath fading until the preliminary compensation signal meets the preset performance standard. Then, it is digital-to-analog converted to obtain the final recovery signal.

[0128] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0129] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0130] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A multipath fading compensation method for DVB-T2 signals, characterized in that: The method comprises: Acquire an original broadcast signal, where the original broadcast signal is a DVB-T2 signal received by multiple receiving ends of a MIMO receiving system; After filtering the original broadcast signal, convert it into a digital signal; An adaptive filter is constructed based on a recursive least squares algorithm, and the adaptive filter is used to perform multipath fading compensation on the digital signal to obtain a preliminary compensation signal, wherein the adaptive filter performs cyclic compensation on the data signal with the goal of minimizing the error signal; The performance of the preliminary compensation signal is evaluated according to the preset evaluation index. If the preliminary compensation signal does not meet the preset performance standard, the parameters in the adaptive filter are optimized and then the preliminary compensation signal is compensated for multipath fading until the preliminary compensation signal meets the preset performance standard. Then, it is digital-to-analog converted to obtain the final recovery signal.

2. The multipath fading compensation method according to claim 1, characterized in that: The filtering process of the original broadcast signal includes: Amplifying the original broadcast signal using a low noise amplifier to obtain a broadcast signal with an improved signal-to-noise ratio; The broadcast signal with improved signal-to-noise ratio is filtered by using a bandpass filter to retain the signal within a predetermined frequency band, thereby completing the filtering process.

3. The multipath fading compensation method according to claim 2, characterized in that: When converting the signal that has completed the filtering process into a digital signal: the sampling frequency is set to be greater than twice the highest frequency of the original broadcast signal.

4. The multipath fading compensation method according to claim 3, characterized in that: When the adaptive filter is used to perform multipath fading compensation on the digital signal: Initialize the weight vector and the inverse of the error covariance matrix; For each time step, calculating a gain vector of the digital signal based on a forgetting factor; The weight vector is updated based on the gain vector, and the output signal of the current time step is calculated according to the updated weight vector and the digital signal; Obtaining an error signal at a current time step according to a difference between the output signal and an expected output signal; updating the inverse of the error covariance matrix according to the error signal and the gain vector to obtain the inverse of the error covariance matrix of the current time step; It is determined whether the error signal is minimum according to the inverse of the error covariance matrix. If it is not minimum, the weight vector is adaptively adjusted using the error signal until the inverse of the error covariance matrix converges.

5. The multipath fading compensation method according to claim 4, characterized in that: When performing performance evaluation on the preliminary compensation signal, the preset evaluation indicators include signal-to-noise ratio, bit error rate, and signal-to-interference ratio.

6. The multipath fading compensation method according to claim 5, characterized in that: When optimizing the parameters in the adaptive filter, the forgetting factor and the weight vector updating mechanism are optimized.

7. A receiver for DVB-T2 signals, characterized in that: The receiver comprises: a MIMO receiving module, a pre-processing module, an adaptive filter, a demodulator and a decoder; The MIMO receiving module is used to receive the original broadcast signal of DVB-T2; The pre-processing module is used to filter the original broadcast signal and convert it into a digital signal; The adaptive filter is used to use a recursive least squares algorithm to perform cyclic multipath fading compensation on the data signal with the goal of minimizing the error signal to obtain a preliminary compensation signal, and to perform performance evaluation on the preliminary compensation signal according to a preset evaluation index. If the preliminary compensation signal does not meet the preset performance standard, the parameters in the adaptive filter are optimized, and then the preliminary compensation signal is subjected to multipath fading compensation until the preliminary compensation signal meets the preset performance standard, and then the preliminary compensation signal is subjected to digital-to-analog conversion to obtain a final recovery signal; The demodulator and the decoder are used to process the final recovered signal in sequence to obtain the receiver output signal.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images