A microwave transmission networking method suitable for ultra-high-definition television signal transmission

Abstract

The application relates to the field of communication technology, in particular to a microwave transmission networking method suitable for ultra-high-definition television signal transmission. The method comprises the following steps: heterogeneous multi-path network construction, a microwave network containing at least two main transmission paths and one standby transmission path is constructed between a signal transmitting end and a receiving end; cross-path clock synchronization mechanism is adopted to realize signal cooperative transmission, and a ring or mesh topology structure is constructed. The application combines priority marking and reliability enhancement processing technology, ensures core data priority transmission and time delay control, meets the strict requirements of ultra-high-definition signals on large capacity and real-time performance, the main path enables interference cancellation technology, interference components are separated through a dual-polarized antenna and an adaptive algorithm, the anti-multipath fading capability is improved, and the continuity and stability of signal transmission are ensured, a periodic global topology optimization mechanism is started, and the network resource utilization rate and flexibility in dealing with diversified businesses are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication technology, in particular to a microwave transmission networking method suitable for ultra-high-definition television signal transmission. BACKGROUND

[0002] With the popularization of ultra-high-definition television technology, it puts forward higher requirements for the bandwidth, real-time performance and reliability of signal transmission. The traditional microwave transmission network is difficult to meet the high-quality transmission demand of ultra-high-definition television signal due to the problems of bandwidth limitation, weak anti-interference ability and insufficient multi-path cooperation. For example, the high resolution (such as 4K / 8K) and high frame rate (such as 120fps) of ultra-high-definition video signal lead to the demand of single signal bandwidth reaching dozens of Gbps, while the traditional microwave link usually only supports several Gbps capacity, and lacks multi-path redundancy and dynamic routing optimization mechanism, which is easy to cause signal stall, loss of picture quality and other problems caused by link interruption or interference. In addition, the existing microwave equipment has defects such as protocol incompatibility and clock asynchronization when mixed networking, which further restricts the flexibility and expansibility of the transmission network.

[0003] In view of the above problems, the existing technology tries to improve the performance by improving the transmission architecture and signal processing technology. For example, Chinese patent CN201510552857.9 discloses a signal transmission system, which tries to realize multi-service integrated transmission by merging network signals and television signals into a mixed signal and distributing the output. However, this scheme only stays at the simple multiplexing of the signal level, does not perform differential processing on the hierarchical characteristics (such as video layer, audio layer, metadata layer) of ultra-high-definition video, lacks key technologies such as IP packet encapsulation and QoS priority management, and cannot solve the problems of uneven bandwidth allocation, time delay jitter and other problems in ultra-high-definition signal transmission. Another Chinese patent CN202210686303.8 proposes an end-to-end access method for DTMB ultra-high-definition signal wired transmission, which realizes controllable access of video service by optimizing the access layer protocol. However, this scheme is limited to wired transmission scenarios and does not involve the problems of multipath fading, cross-polarization interference and other problems specific to microwave transmission, and does not construct a heterogeneous multi-path redundancy mechanism, which is difficult to cope with the problem of unstable link caused by weather, terrain and other factors in microwave transmission.

[0004] The existing microwave networking technology applied to ultra-high-definition television signal transmission is limited by the traditional homogeneous architecture, and has problems such as prominent single-node failure risk, significant bandwidth bottleneck and poor compatibility between new and old devices, which restricts the reliability, real-time performance and network expansibility of ultra-high-definition signal transmission, and is difficult to meet the urgent needs of the broadcasting and television industry for safe broadcasting and IP transformation. In view of this, we propose a microwave transmission networking method suitable for ultra-high-definition television signal transmission. SUMMARY

[0005] The present application aims to provide a microwave transmission networking method suitable for ultra-high-definition television signal transmission to solve the problems in the background art.

[0006] To achieve the above technical problems, the present application aims to provide a microwave transmission networking method suitable for ultra-high-definition television signal transmission, comprising the following steps:

[0007] S1, heterogeneous multi-path network construction: constructing a microwave network containing at least two main transmission paths and one standby transmission path between the signal transmitting end and the receiving end; adopting a cross-path clock synchronization mechanism to realize signal collaborative transmission and constructing a ring or mesh topology;

[0008] S2, signal hierarchical processing: cutting and processing the input ultra-high-definition signal in layers;

[0009] S3, hierarchical signal packaging and transmission: IP packet packaging of the ultra-high-definition signal after hierarchical processing, and end-to-end transmission through a packet switching network;

[0010] S4, interference cancellation: enabling cross-polarization interference cancellation technology on each main path;

[0011] S5, monitoring and early warning and path switching: deploying a real-time monitoring module and constructing an evaluation model, and establishing a hot backup mechanism;

[0012] S6, compatibility modification and global optimization: compatibility modification of existing microwave transmission equipment for hybrid networking of new and old equipment; periodically starting a global topology optimization mechanism to dynamically adjust network routing based on node load and service demand.

[0013] As a further improvement of the technical solution, the cross-path clock synchronization mechanism in S1 is realized by the following way: deploying a clock module containing an atomic clock or a GPS synchronization unit at each transmission path node, and periodically exchanging clock synchronization messages between nodes according to IEEE1588v2 protocol. The cross-path clock synchronization mechanism realizes accurate synchronization of node clocks by deploying a clock module containing a specific unit and exchanging messages according to the protocol, ensuring the timing consistency of signal collaborative transmission.

[0014] As a further improvement of the technical solution, the hierarchical cutting and processing of the input ultra-high-definition signal in S2 comprises the following steps:

[0015] S2.1, signal hierarchical cutting: separating the ultra-high-definition signal into independent video layer, audio layer and metadata layer, wherein the video layer contains image pixel data, the audio layer contains sound encoding data, and the metadata layer contains subtitle, timestamp and other auxiliary information;

[0016] S2.2, each layer preprocessing:

[0017] The BM3D algorithm is used for noise reduction, resolution uniformity processing of the video layer, to ensure the format consistency of video signals from different sources;

[0018] The Wiener filter algorithm is used for noise reduction, sampling rate standardization processing of the audio layer, to eliminate background noise and unify audio parameters;

[0019] The cyclic redundancy check algorithm is used for format checking and redundant data elimination of the metadata layer, to ensure the accuracy and integrity of auxiliary information;

[0020] S2.3, time sequence synchronization mark: add time stamp and frame sequence number in each layer data, establish the time sequence correspondence of video layer, audio layer and metadata layer, provide synchronization reference for subsequent layered packaging. Through signal layered cutting and processing, the ultra-high definition signal is layered and preprocessed, the time sequence is marked, the format of each layer data is standardized, and the information is accurate and complete, which provides reliable synchronization reference for subsequent packaging.

[0021] As a further improvement of the technical solution, the IP packet packaging in S3 includes the following steps:

[0022] S3.1, protocol adaptation packaging: according to the characteristics of each layer signal, select the packaging protocol, and package the video layer, audio layer and metadata layer into IP data packets respectively;

[0023] S3.2, QoS priority marking: insert the quality of service field in the IP data packet header, and mark the priority level of each layer signal;

[0024] S3.3, reliability enhancement processing: add cyclic redundancy check code to the packaged IP data packet, and embed forward error correction redundancy data, to improve transmission reliability. IP packet packaging realizes signal layered adaptive transmission through protocol adaptation, priority marking and reliability enhancement processing, guarantees the priority transmission of core data and improves the error code resistance.

[0025] As a further improvement of the technical solution, the cross-polarization interference cancellation technology in S4 specifically includes:

[0026] Deploy a dual-polarized antenna at the transmission node of the main path, which is used to receive two signals with the same frequency and orthogonal polarization;

[0027] Sample and digitize the received two signals, and construct an interference estimation model based on an adaptive filtering algorithm;

[0028] Separate the cross-polarization interference components in the target signal through the interference estimation model, and eliminate the interference components from the received signal.

[0029] As a further improvement of the technical solution, the adaptive filtering algorithm in S4, when performing interference cancellation through an interference estimation model, has the following processing procedure:

[0030] First, the error signal is calculated based on the real-time sampling data of the received signal, and the error signal e(n) is expressed as: e(n) = d(n) - y(n); wherein d(n) is the expected signal, y(n) is the actual output signal, and n is the sampling time;

[0031] Next, the filter coefficient is dynamically adjusted according to the error signal, and the filter coefficient update formula is: w(n+1) = w(n) + x(n)e(n), wherein w(n) is the filter coefficient vector at time n, and x(n) is the input signal vector. The cross-polarization interference cancellation technology uses a dual-polarization antenna and an adaptive algorithm to separate and eliminate interference components, effectively reducing co-frequency orthogonal signal interference and improving the purity and transmission stability of the main path signal.

[0032] As a further improvement of the technical solution, the construction of the evaluation model in S5 specifically includes the following steps:

[0033] S5.1, dynamic weight configuration: configure dynamic weight coefficients for each transmission parameter, and the dynamic weight coefficients are adaptively adjusted according to signal transmission period, network load state and weather condition data;

[0034] S5.2, multi-parameter fusion evaluation: generate a path quality evaluation value Q based on a multi-parameter fusion algorithm, and the multi-parameter fusion algorithm includes a weighted summation model, a fuzzy logic reasoning model or a neural network evaluation model, wherein the calculation formula of the improved weighted summation model is: Q = ∑[w i (t)×p i ], wherein p i is a standardized parameter value, w i (t) is the dynamic weight of the i-th parameter at time t;

[0035] w i (t) is calculated as follows: wherein: w i0 is the initial weight of the i-th parameter, gamma is the weight adjustment coefficient, which is set according to the influence degree of the parameter on the ultra-high definition signal transmission, p i (t-1) is the value of the i-th parameter at the previous time t-1, mu i is the historical mean value of the i-th parameter, reflecting the long-term average level of the parameter, and sigma i is the historical standard deviation of the i-th parameter, which reflects the fluctuation degree of the parameter.

[0036] As a further improvement of the technical solution, the specific way of establishing a hot backup mechanism in S5 includes the following steps:

[0037] S5.1, heterogeneous backup path construction: a backup path is constructed using a transmission technology different from that of the primary path, such as microwave transmission technology or optical fiber transmission technology in different frequency bands, to ensure that the transmission characteristics of the backup path are different from those of the primary path;

[0038] S5.2, automatic re-routing switching: when it is detected that the quality of the primary path is lower than the preset standard, an automatic re-routing algorithm is started, and the optimal backup path is calculated based on real-time path quality evaluation data and a lossless switching is performed. Based on real-time updated path quality evaluation data, the algorithm quickly calculates and switches to the optimal backup path, ensuring the continuity of the transmission of ultra-high-definition television signals. The evaluation model and the hot backup mechanism dynamically configure weights, evaluate multiple parameters, and automatically switch between heterogeneous paths to accurately evaluate the quality of the path in real time and quickly switch the backup path, ensuring transmission continuity.

[0039] As a further improvement of the technical solution, the compatibility modification in S6 includes the following steps:

[0040] S6.1.1, hardware adaptation modification: upgrade the radio frequency front-end module of the existing device to support the modulation mode of the new device, modify the power supply adaptation unit to be compatible with the power supply specifications of the new device, and expand the physical interface type to realize physical connection and signal interaction between the new and old devices;

[0041] S6.1.2, software protocol adaptation: update the device firmware to support the new communication protocol, embed a protocol conversion module in the control plane to parse and convert the control instructions and data formats between the new and old devices, and establish a unified configuration management interface to centrally monitor the parameters and status of the new and old devices;

[0042] S6.1.3, joint debugging and testing verification: test the signal modulation and demodulation consistency of the new and old devices, verify the stability of the power module in a mixed power supply environment, test the delay and reliability of the protocol conversion process, and ensure that the new and old devices can be implemented in a mixed network.

[0043] As a further improvement of the technical solution, the periodic global topology optimization mechanism in S6 specifically includes the following implementation steps:

[0044] S6.2.1, periodic and trigger condition configuration: set a fixed optimization period, and the period length can be configured according to the network service characteristics;

[0045] S6.2.2, real-time monitoring and trigger determination: when it is detected that the load of any node exceeds a preset threshold, a new high-priority service is accessed, or the quality parameters of a critical link deteriorate, an immediate routing optimization is immediately started;

[0046] S6.2.3, route optimization algorithm execution: based on the current network topology, node load data and service demand, the shortest path algorithm, multi-objective optimization algorithm or intelligent optimization algorithm is used to generate the optimal routing scheme containing path priority; wherein, the multi-objective optimization algorithm can be parameterized by the objective function F=w1·L+w2·(1 / B)+w3·D, L represents the path length, B is the available bandwidth, D is the delay, w1, w2, w3 are weight coefficients, to realize the optimization configuration of path length, available bandwidth and delay and other multi-dimensions;

[0047] S6.2.4, route table synchronization and adjustment: the optimized routing scheme generation instruction is synchronized to each network node, and the routing table is updated. The global topology optimization mechanism optimizes the route through periodic configuration, real-time monitoring triggering and intelligent algorithm, dynamically adjusts the network path, and improves the node load balancing and service response flexibility.

[0048] Compared with the prior art, the beneficial effects of the present application are:

[0049] 1. The present application significantly improves the link transmission capacity by IP packet encapsulation and multi-wave channel aggregation technology, and supports simultaneous transmission of multiple ultra-high definition signals. The hierarchical signal processing mechanism separates the ultra-high definition signal into independent levels and pre-processes it, combines priority marking and reliability enhancement processing technology, ensures core data transmission priority and delay control, and meets the strict requirements of ultra-high definition signal for large capacity and real-time performance;

[0050] 2. The present application solves the single node failure risk by constructing a heterogeneous network containing multiple primary and backup paths, using cross-path cooperative transmission mechanism, constructing ring or mesh topology. At the same time, the primary path uses interference cancellation technology, separates the interference component through dual-polarized antenna and adaptive algorithm, improves the anti-multipath fading ability, and guarantees the continuity and stability of signal transmission;

[0051] 3. The present application upgrades the radio frequency and power module of the existing device through hardware adaptation and software protocol conversion technology, expands the physical interface, updates the firmware and embeds the protocol conversion module, establishes a unified management interface, realizes the mixed networking and centralized monitoring of new and old devices, avoids the waste of resources caused by device iteration, and provides a smooth transition scheme for system upgrade;

[0052] 4. The present application realizes real-time acquisition of network state data and dynamic adjustment of path weight by deploying real-time monitoring module and multi-parameter fusion evaluation model, accurately identifies faults and triggers early warning. At the same time, the global topology optimization mechanism is periodically started, the route is dynamically adjusted based on node load and service demand, the fast route switching and lossless switching are supported, and the network resource utilization and flexibility in dealing with diversified business are improved. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1 An exemplary method flowchart for the present application. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work are within the protection scope of the present application.

[0055] As shown in the figure, the present embodiment provides a microwave transmission networking method suitable for ultra-high-definition television signal transmission, comprising the following steps: Figure 1

[0056] S1, heterogeneous multi-path network construction: a microwave network containing at least two main transmission paths and one standby transmission path is constructed between the signal transmitting end and the receiving end; a cross-path clock synchronization mechanism is used to realize signal collaborative transmission, and a ring or mesh topology structure is constructed;

[0057] In this step, the cross-path clock synchronization mechanism in S1 is realized by the following way: a clock module containing an atomic clock or a GPS synchronization unit is deployed at each transmission path node, and clock synchronization messages are periodically exchanged between nodes according to IEEE1588v2 protocol. By combining atomic clock / GPSDO with IEEE1588v2 protocol, high-precision clock synchronization can be realized, thereby meeting the timing alignment requirements of ultra-high-definition signal hierarchical transmission; at the same time, the processing efficiency of synchronization messages can be improved by physical layer timestamp marking, and synchronization error can be reduced.

[0058] In this step, the main path meets the following conditions:

[0059] Different frequency bands of spectrum resources are used, the frequency band interval conforms to the spectrum allocation rules, and the available bandwidth of a single frequency band meets the ultra-high-definition signal transmission requirements; for example, main path A selects E band (71-76 GHz), and main path B selects V band (59-64 GHz), the frequency band interval strictly follows the spectrum allocation rules formulated by organizations such as International Telecommunication Union (ITU), to avoid same frequency or adjacent frequency interference. The available bandwidth of a single frequency band is calculated by professionals, which meets the strict requirements (usually ≥1 Gbps) of ultra-high-definition signal (such as 8K / 60fps video) on bandwidth, to ensure the high-rate transmission of video, audio and metadata without blocking.

[0060] ​The microwave transmission equipment with different communication modes has different modulation and demodulation modes or channel coding modes between the equipment. The modulation and demodulation or channel coding modes between the equipment are differentiated. For example, path A adopts 256QAM modulation + LDPC coding to improve the spectral efficiency and strong error correction capability; path B adopts 64QAM modulation + Turbo coding to exhibit robust anti-fading characteristics in complex channel environment. This design avoids the limitations of a single mode, for example, 256QAM is prone to error in strong interference, while 64QAM can ensure link connectivity by reducing the modulation order, and the two modes complement each other to improve network adaptability.

[0061] The hardware platforms selected from different manufacturers form technical heterogeneous redundancy of baseband processing and radio frequency transmission. The design forms technical heterogeneous redundancy of baseband and radio frequency. For example, path A baseband uses Xilinx FPGA to realize flexible algorithm processing, and radio frequency front end uses GaN power amplifier to enhance signal transmission; path B baseband uses Broadcom ASIC to realize high-efficiency fixed logic operation, and radio frequency front end uses LDMOS power amplifier (strong anti-burning ability). If the hardware of a manufacturer fails due to process defects or specific interference (such as GaN devices performance degradation at abnormally high temperature), the other path can still maintain transmission to ensure network reliability. Through the above design, the main path is significantly enhanced in anti-interference, adaptation to complex environment and fault tolerance, meeting the stringent requirements of ultra-high-definition signal transmission for stability and low latency, while avoiding the risk of a single technology, in line with the development trend of modern communication networks "heterogeneous redundancy, self-controllable".

[0062] As a further description of this step, the clock synchronization mechanism has flexibility and scalability of technical solutions. In addition to the current implementation, it can also be replaced with a mixed synchronization scheme of SyncE (G.8261) and IEEE1588v2. In this scheme, frequency synchronization is achieved through a PLL phase-locked loop, which can dynamically adapt to changes in network environment under different network topologies and transmission medium conditions, improving the reliability and adaptability of clock synchronization, and providing diversified technical support for stable operation of ultra-high-definition signal transmission networks in complex scenarios.

[0063] It should be noted that, for the calculation of clock deviation, the formula Δt = (t rec -t sent )-(t resp -t delay ) is used; wherein t rec and t sent represent the receive and transmit timestamps, respectively, t resp and t delayResponse and delay time. The formula is based on the timestamp processing logic of IEEE1588v2 protocol standard, which can accurately calculate the clock deviation between nodes, provide quantitative basis for adjusting clock module and realizing high-precision synchronization, ensure that the ultra-high-definition signal maintains timing alignment in the multi-path transmission process, and avoids signal disorder or loss caused by clock deviation.

[0064] S2, signal layering processing: the input ultra-high-definition signal is cut and processed;

[0065] In this step, the layering cutting and processing of the input ultra-high-definition signal in S2 includes the following steps:

[0066] S2.1, signal layering cutting: separating the ultra-high-definition signal into independent video layer, audio layer and metadata layer, wherein the video layer contains image pixel data, the audio layer contains sound encoding data, and the metadata layer contains subtitle, timestamp and other auxiliary information; by separating the ultra-high-definition signal into independent video layer, audio layer and metadata layer, the clear division of business functions is realized, which facilitates the optimization processing according to different hierarchical characteristics, avoids the mutual interference of each layer data processing, and improves the processing efficiency. For example, taking 8K / 60fps ultra-high-definition signal as an example, the video layer data is about 12Gbps (based on H.265 encoding compression), which contains 33 million pixels of image data per frame; if the audio layer is 8-channel LPCM encoding, the sampling rate is 48kHz, and the bit depth is 24bit, the data amount is about 9.2Mbps; the data amount of metadata layer (such as subtitle, timestamp) is relatively small, about several hundred kbps.

[0067] S2.2, each layer preprocessing:

[0068] The video layer is denoised and resolution-unified to ensure the format consistency of different source video signals;

[0069] The audio layer is denoised and sample rate standardized to eliminate background noise and unify audio parameters;

[0070] The metadata layer is format-verified and redundant data is removed to ensure the accuracy and integrity of auxiliary information; through the preprocessing (denoising, standardization, format verification, etc.) of each layer, the signal quality and format consistency are improved, the influence of noise, non-uniform parameters, etc. on subsequent transmission and decoding is eliminated, and the high-quality restoration of ultra-high-definition signal is ensured.

[0071] As a further illustration of this step, the video layer can be denoised using the BM3D (Block-Matching and 3D filtering) algorithm, which significantly improves the removal of Gaussian noise, salt and pepper noise, etc. through joint filtering of similar blocks in the video frame. For example, for a video frame containing 2% Gaussian noise (mean 0, variance 0.01), the peak signal-to-noise ratio (PSNR) can be improved by 5-8 dB after denoising. Meanwhile, the resolution unification processing in this video layer step can use the bilinear interpolation formula, which is calculated as follows: where I(x, y) represents the pixel value of the target resolution image at coordinates (x, y) after interpolation calculation; I(i, j) represents the pixel value of the four adjacent pixels ((i, j) takes values 0 or 1) of (x, y) in the original image; x and y are the coordinates of the target pixel in the interpolation calculation (usually normalized to the [0, 1] interval to determine the distance weight of the adjacent pixel); i and j are the coordinate indices of the adjacent pixels in the original image (by iterating the values of (i, j) as 0, 1, the weighted calculation of the four adjacent pixels is realized). By weighting the pixel values of the four adjacent pixels (the weight is determined by (1-|x-i|)·(1-|y-j|), the closer to the target pixel, the higher the weight), this formula realizes the resolution unification processing of different resolutions (such as 3840×2160 and 7680×4320) of the video, reduces pixel distortion in the image scaling process, and ensures the clarity of the scaled image.

[0072] As a further illustration of this step, in the processing of the audio layer, noise reduction can be performed using the Wiener filter algorithm, which designs a filter based on the statistical properties (such as power spectral density) of the audio signal. For an audio signal containing background noise (signal-to-noise ratio 10 dB), after processing by this algorithm, the signal-to-noise ratio after noise reduction can be improved to more than 25 dB, effectively eliminating background noise and significantly improving audio quality. In the sampling rate standardization processing of the audio layer, the resampling formula where y(n) represents the audio signal sequence after resampling at the target sampling rate, which is the output standardized audio data after processing; x(m) is the audio signal sequence at the original sampling rate, representing the input non-standardized audio data; h(n) is the low-pass filter coefficient, used for anti-aliasing or interpolation filtering processing in the resampling process to ensure the quality of the audio signal during sampling rate conversion; F s represents the original sampling rate (such as the common 44.1 kHz), which is the original sampling rate of the audio signal; F snεwFor the target sampling rate (such as 48 kHz), it is the sampling rate to which the audio is expected to be standardized. Through the formula, audio of different sampling rates can be unified to the target sampling rate, for example, audio of 44.1 kHz and 48 kHz can be unified to 48 kHz, ensuring the consistency of audio parameters, laying a standardized foundation for subsequent processing and transmission, and avoiding audio playback abnormalities or processing errors caused by sampling rate differences.

[0073] As a further description of this step, the format verification of the metadata layer can use a cyclic redundancy check (CRC) algorithm (such as CRC-32), which can effectively guarantee the integrity of the metadata. For example, for subtitle data containing 1000 characters, CRC verification can detect more than 99.99% of bit errors, avoiding display or processing abnormalities caused by data errors, and ensuring the accuracy of auxiliary information. The metadata layer also performs redundancy elimination through lexical and semantic analysis. For example, for consecutive repeated "00:00:00" timestamps, only one valid instance is retained. This processing eliminates repeated timestamps or invalid characters, improving the conciseness and effectiveness of the metadata, and optimizing the quality and transmission efficiency of the metadata.

[0074] S2.3, timing synchronization marking: add timestamps and frame numbers in each layer of data to establish the timing correspondence relationship of the video layer, audio layer and metadata layer, and provide a synchronization reference for subsequent layered packaging. By adding timestamps and frame numbers in each layer of data, a strict timing correspondence relationship is established to ensure the synchronization of video, audio and metadata in the transmission and decoding process, which can avoid problems such as audio and video out of sync, subtitle misalignment, etc., and can improve user experience.

[0075] As a further description of this step, in the timing synchronization marking step, the timestamp generation is based on a high-precision system clock (such as a 10 MHz crystal oscillator with a precision of ±1 ppm), and is in units of milliseconds, with the calculation formula being T = t system × 1000. Wherein, T represents the final generated timestamp, in milliseconds, which accurately marks the time position of each frame of data; t system is the system clock second number, which is the basis for timestamp calculation. By multiplying the second number by 1000, the conversion from seconds to milliseconds is realized, ensuring that the precision of the timestamp meets the timing requirements of ultra-high-definition signals. The frame number starts from 0 and increments by 1 for each output frame, i.e. FrameNo(n) = FrameNo(n-1) + 1. Here, FrameNo(n) represents the sequence number of the nth frame, and FrameNo(n-1) represents the sequence number of the previous frame (the nth frame). Through such a recursive formula, the sequence relationship between frames is clearly established, providing a clear reference for the timing correspondence of each layer of data.

[0076] In addition, in addition to the local generation of time stamp and frame sequence number, a synchronous time source can be obtained through a network time protocol (NTP) or a precision time protocol (PTP, such as IEEE1588v2). For example, in a distributed ultra-high definition production network, the time synchronization error of each node is controlled within 100 ns through the PTP protocol. Among them, the PTP protocol controls the global timing consistency by accurately measuring and adjusting the clock of each node, ensures the uniformity of the signal timing processed across nodes, avoids the problems of audio and video asynchronization or metadata misplacement caused by time deviation, and provides a solid timing guarantee for the high-quality transmission and processing of ultra-high definition signals.

[0077] S3, layered signal packaging and transmission: the ultra-high definition signal after layered processing is packaged into IP packets, and end-to-end transmission is realized through a packet switching network;

[0078] In this step, the IP packet packaging in S3 includes the following steps:

[0079] S3.1, protocol adaptation packaging: according to the characteristics of each layer signal, the video layer, the audio layer and the metadata layer are packaged into IP data packets respectively; according to the characteristics of each layer signal, the design selects the packaging protocol, realizes differentiated and accurate packaging, avoids the low efficiency or compatibility problem caused by the "one-size-fits-all" packaging method, and improves the transmission adaptability of each layer signal in the network.

[0080] As a further description of this step, the video layer in this step adopts RTP (real-time transport protocol) packaging due to large data volume and high real-time requirement. After 8K video stream (about 12 Gbps) is packaged through RTP, the ordered transmission of frame sequence can be ensured; the audio layer selects UDP (user datagram protocol) packaging based on low delay requirement, such as 5.1 channel audio (about 1 Mbps) transmitted quickly through UDP; the metadata layer adopts SNMP (simple network management protocol) packaging because it contains management information (such as subtitles and time stamp), which is convenient for network equipment identification and processing.

[0081] S3.2, QoS priority marking: a service quality field is inserted into the IP packet header to mark the priority level of each layer signal; by inserting the service quality field into the IP packet header to mark the priority, the network equipment can schedule the data packets according to the priority, ensure the priority forwarding of the key layer (such as the video layer) in network congestion, and guarantee the viewing experience of the core content of the ultra-high definition signal.

[0082] As a further illustration of this step, priority marking can also be implemented in this step using the DSCP (Differentiated Services Code Point) field, for example, the video layer DSCP value is set to EF (46, representing expedited forwarding), the audio layer is set to AF41 (34, representing assured forwarding class 41), and the metadata layer is set to BE (0, representing best effort). By marking with specific numerical values, it is convenient for network devices such as routers and switches to quickly identify and process, and optimize resource allocation.

[0083] S3.3, Reliability Enhancement Processing: Add cyclic redundancy check code to the encapsulated IP packet, and embed forward error correction redundancy data, which can improve transmission reliability. By adding cyclic redundancy check code (CRC) to the encapsulated IP packet and embedding forward error correction (FEC) redundancy data, a "detection + error correction" double protection mechanism is formed, which effectively deals with common interference, noise and other problems in microwave transmission links, reduces the bit error rate, and improves transmission reliability.

[0084] As a further illustration of this step, in terms of improving transmission reliability, a double protection mechanism can be used for the encapsulated IP packet:

[0085] First, CRC can use CRC-32 algorithm, its generating polynomial is G(x) = x 32 +x 26 +x 23 +x 22 +x 16 +x 12 +x 11 +x 10 +x 8 +x 7 +x 5 +x 4 +x 2 +x+1, this algorithm can detect more than 99.99% bit errors, providing strong detection protection for data integrity;

[0086] Second, FEC can use Reed-Solomon encoding (such as RS(255,239)), its encoding formula is: C(x) = (x n- k M(x)) mod G(x), where M(x) is the information polynomial, G(x) is the generating polynomial, n-k is the number of redundant symbols (here n = 255, k = 239), which provides 16 redundant symbols), which makes it can correct burst errors within a certain range. For example, in a link with a bit error rate of 10 -4 , the bit error rate can be reduced to 10 -7 , which effectively improves the anti-interference ability and accuracy of data in complex transmission environment;

[0087] Through the application of these specific algorithms and parameters, the technical details of the reliability enhancement processing are clarified, the problem of insufficient disclosure is avoided, the application feasibility of the technical scheme in the actual complex network environment is expanded, and the description of the patent content in the aspect of guaranteeing transmission reliability is more complete and persuasive.

[0088] S4, interference cancellation: enabling cross-polarization interference cancellation technology in each main path; enabling cross-polarization interference cancellation technology in each main path can specifically solve the common cross-polarization interference problem in microwave transmission, effectively improve the purity and transmission quality of the main path signal, guarantee the stable transmission of ultra-high-definition signals in complex electromagnetic environments, reduce the bit error rate, and enhance the anti-interference ability of the entire microwave transmission network.

[0089] In this step, the cross-polarization interference cancellation technology in S4 specifically includes:

[0090] Deploying a dual-polarized antenna at the transmission node of the main path for receiving two signals of the same frequency and orthogonal polarization; by deploying a dual-polarized antenna to receive two signals of the same frequency and orthogonal polarization, the target signal and the interference signal are separated by utilizing the polarization characteristic difference, and the pertinence of interference cancellation is improved;

[0091] Sampling and digitizing the received two signals, and constructing an interference estimation model based on an adaptive filtering algorithm; after sampling and digitizing the signals, an interference estimation model is constructed based on an adaptive filtering algorithm to realize dynamic tracking and accurate estimation of interference;

[0092] Separating the cross-polarization interference component in the target signal through the interference estimation model, and eliminating the interference component from the received signal. With the help of the interference estimation model to separate and eliminate the cross-polarization interference component in the target signal, real-time purification of the signal can be realized, and high-quality transmission of ultra-high-definition signals can be guaranteed.

[0093] In this step, when the adaptive filtering algorithm performs interference cancellation through the interference estimation model, the processing process is as follows:

[0094] First, calculate the error signal based on the real-time sampling data of the received signal, and the error signal e(n) is expressed as: e(n) = d(n) - y(n); where d(n) is the expected signal (which can be extracted from the received signal through prior knowledge or preliminary filtering, and approximately represents the target signal and interference), y(n) is the actual output signal, and n is the sampling time (which is obtained by processing the input signal vector with the current filtering coefficient, and is used to estimate the interference component);

[0095] Then, the filter coefficient is dynamically adjusted according to the error signal, and the filter coefficient update formula is: w(n+1)=w(n)+x(n)e(n), wherein w(n) is the filter coefficient vector at time n, the dimension thereof needs to be determined according to the interference characteristics and the signal bandwidth (for example, for a complex multipath interference scene, it can be set to 64 dimensions to capture the interference correlation of more historical sampling points), and x(n) is an input signal vector (usually the received signal of the orthogonal polarization direction is selected, such as another signal of a dual-polarized antenna, which forms a time sequence vector after digitization and is used to extract the interference characteristics).

[0096] As a further description of this step, the dual-polarized antenna can adopt a parabolic antenna, a horn antenna or a microstrip antenna with orthogonal polarization, and a suitable type is selected according to the actual scene (such as a parabolic antenna for long-distance transmission and a microstrip antenna for space limitation).

[0097] S5, monitoring and early warning and path switching: a real-time monitoring module is deployed and an evaluation model is built, and a hot backup mechanism is established; by deploying the real-time monitoring module, building the evaluation model and establishing the hot backup mechanism, dynamic monitoring, accurate evaluation and reliable backup of the transmission path are realized, the stability and continuity of the ultra-high-definition signal transmission in the complex network environment are ensured, the risk of transmission interruption caused by path failure or quality deterioration is reduced, and the reliability and robustness of the entire microwave transmission networking are improved.

[0098] In this step, the building of the evaluation model in S5 specifically includes the following steps:

[0099] S5.1, dynamic weight configuration: dynamic weight coefficients are configured for each transmission parameter, and the dynamic weight coefficients are adaptively adjusted according to the signal transmission period, network load state and weather condition data; by configuring the dynamic weight coefficients for each transmission parameter, the evaluation model can adapt to different transmission scenes (period, load, weather), the accuracy and flexibility of the path quality evaluation are improved, and the evaluation lag or deviation caused by the static weight is avoided.

[0100] S5.2, multi-parameter fusion evaluation: a path quality evaluation value Q is generated based on a multi-parameter fusion algorithm, and the multi-parameter fusion algorithm includes a weighted summation model, a fuzzy logic reasoning model or a neural network evaluation model, wherein the calculation formula of the improved weighted summation model is: Q=∑[w i (t)×p i ], wherein p i is a standardized parameter value, w i (t) is the dynamic weight of the i-th parameter at time t.

[0101] The calculation method of w i (t) is: wherein: w i0is the initial weight of the ith parameter, γ is the weight adjustment coefficient, which is set according to the influence degree of the parameter on the ultra-high-definition signal transmission, and p is the power index i (t-1) is the value of the ith parameter at the previous time t-1, μ i is the historical mean of the ith parameter, reflecting the long-term average level of the parameter, and σ i is the historical standard deviation of the ith parameter, used to reflect the volatility of the parameter. The design generates a path quality evaluation value based on a multi-parameter fusion algorithm, comprehensively considers multiple transmission parameters (such as bandwidth, delay, error rate, etc.), avoids one-sidedness of single parameter evaluation, and fully reflects the path quality. The improved weighted sum model further improves the real-time and accuracy of the evaluation through dynamic weight adjustment.

[0102] As a further description of this step, the transmission parameters can specifically include bandwidth (unit: Mbps), delay (unit: ms), error rate (unit: %), signal-to-noise ratio (unit: dB), etc.

[0103] In this step, the specific way of establishing a hot backup mechanism in S5 includes the following steps:

[0104] S5.1, Heterogeneous backup path construction: a backup path is constructed using a transmission technology different from the main path, for example, using microwave transmission technology or optical fiber transmission technology in different frequency bands, to ensure that the transmission characteristics of the backup path are different from those of the main path; this design selects a transmission technology different from the main path to construct a backup path, uses technical heterogeneity to avoid similar failures of the main path (such as same frequency band interference, same type equipment defects), and ensures that the backup path can take over stably when the main path fails, improving the fault tolerance of the system.

[0105] For example, the main path uses E-band (71-76 GHz) microwave transmission technology (bandwidth 1.25 GHz, line-of-sight transmission), and the backup path can use optical fiber transmission technology (such as single-mode optical fiber, transmission distance ≥100 km, bandwidth ≥10 Gbps), or lower frequency band microwave technology (such as C-band, 4-8 GHz, strong diffraction ability, suitable for non-line-of-sight scenarios); when the main path is interrupted due to serious rain attenuation of high frequency band (such as rainfall >50 mm / h, signal attenuation >20 dB), the backup path can be immediately enabled.

[0106] S5.2, Automatic re-routing switching: when it is monitored that the quality of the main path is lower than the preset standard, the automatic re-routing algorithm is started, and the optimal backup path is calculated based on real-time path quality evaluation data and lossless switching is performed. When the quality of the main path is lower than the preset standard, the automatic re-routing algorithm is started and switched to the optimal backup path based on real-time evaluation data, realizing fast and lossless switching of the transmission path, ensuring the continuity of the ultra-high-definition signal transmission, and reducing the interruption time perceived by the user.

[0107] As a further description of this step, when the quality of the primary path is monitored to be lower than the preset standard (such as packet loss rate > 5% or delay > 100 ms), the system immediately triggers the automatic rerouting algorithm. Taking the classic Dijkstra algorithm as an example, the algorithm is based on the greedy strategy and aims to find the path with the minimum cost in the directed graph from the source node to the target node. In this scenario, we use the real-time path quality evaluation value Q(t) (generated by the multi-parameter fusion evaluation model, the higher the value, the better the path quality) as the reverse mapping index of the link cost, i.e. link cost cost = 1 / Q(t), so that the path with high Q(t) is preferentially selected due to low cost;

[0108] The specific execution process of the algorithm is as follows: first, all the backup paths and their connected nodes are abstracted into a directed graph, where the nodes represent network devices (such as routers, switches), and the edges represent links, and the cost of each edge is converted from the corresponding Q(t) of the path. Then, starting from the source node (signal transmitting end), the greedy strategy is used to continuously select the node with the minimum current cost for expansion, and the cumulative cost from the source node to each node is calculated. Finally, the cumulative costs of all backup path endpoints (signal receiving end) are compared, and the path with the minimum cost (i.e. the maximum Q(t)) is selected as the optimal backup path;

[0109] After determining the optimal backup path, the lossless switching process is entered: through the software-defined network (SDN) controller or network management system, the control layer connection (such as sending OpenFlow pre-configuration instructions) with each node of the optimal backup path is established in advance to ensure the smoothness of the path; the routing table of the source node and the intermediate nodes is quickly updated to point the ultra-high-definition signal transmission path to the optimal backup path; the packet-by-packet forwarding or fast rerouting mechanism is adopted to seamlessly migrate the primary path traffic to the backup path within ≤50 ms. For example, when the bit error rate of a certain primary path suddenly rises to 10 -3 % due to sudden interference, the system detects the quality degradation, and the automatic rerouting algorithm immediately calculates the backup path. Assuming that path A uses fiber transmission (strong anti-interference), its tQ A (t) = 0.95 is higher than that of other paths, the algorithm selects this path and performs switching. Through pre-connection and routing table quick update, the signal is migrated within 30 ms, and the bit error rate is reduced to 10 -6 , ensuring stable transmission of ultra-high-definition signals and avoiding user perception of lag or screen tearing;

[0110] In summary, by introducing the Dijkstra algorithm and combining the real-time path quality evaluation value, not only is the efficient calculation of the optimal backup path achieved, but also the continuity of ultra-high-definition signal transmission is guaranteed through the standardized switching process, making the entire hot backup mechanism more reliable and practical in complex network environments.

[0111] S6, compatibility modification and global optimization: compatibility modification is performed on the existing microwave transmission equipment to realize mixed networking of new and old equipment; a global topology optimization mechanism is periodically started to dynamically adjust the network routing based on node load and service demand. Through the compatibility modification and global topology optimization mechanism, seamless mixed networking of new and old microwave transmission equipment is realized, solving the device heterogeneity problem in the existing network upgrade process. At the same time, based on real-time load and service demand, the routing is dynamically adjusted to optimize network resource allocation, improve overall transmission efficiency and reliability, prolong the service life of old equipment, and reduce network upgrade cost.

[0112] In this step, the compatibility modification in S6 includes:

[0113] S6.1.1, hardware adaptation modification: upgrade the radio frequency front-end module of the existing equipment to support the modulation mode of the new equipment, modify the power adapter unit to be compatible with the power supply specification of the new equipment, and expand the physical interface type to realize physical connection and signal interaction between new and old equipment; by upgrading the radio frequency front-end, power adapter unit and expanding the physical interface, the old equipment supports the modulation mode, power supply specification and physical connection of the new equipment at the hardware level, realizing the physical layer interworking of new and old equipment.

[0114] As a further description of this step, the radio frequency front-end upgrade in this step can adopt modular design, such as replacing the transceiver module supporting higher order modulation (such as 256QAM / 1024QAM), compatible with the modulation mode of new and old equipment (such as old equipment supporting 64QAM, new equipment supporting 1024QAM). The power adapter unit modification in this step can adopt wide voltage input design (such as 90-264VAC), support different power supply specifications of new and old equipment (such as new equipment requires 48VDC, old equipment requires 24VDC), and realize voltage conversion through DC-DC converter. The physical interface expansion in this step can add SFP+, QSFP28 and other high-speed optical interfaces, compatible with the RJ45 electrical port of the old equipment, and realize signal format conversion through optical-electric converter.

[0115] S6.1.2, software protocol adaptation: update the device firmware to support the new communication protocol, embed the protocol conversion module in the control plane to parse and convert the control instructions and data formats between new and old equipment, and establish a unified configuration management interface to centrally monitor the parameters and status of new and old equipment; through firmware update, protocol conversion module and unified configuration interface, the differences in communication protocol, control instruction and data format between new and old equipment are solved, realizing the interworking of control plane and management plane.

[0116] As a further illustration of this step, the protocol conversion module in this step can adopt a micro-service architecture to support parallel conversion of multiple protocols (e.g., conversion of the SNMP protocol of old devices to the NETCONF / YANG protocol of new devices). Meanwhile, the unified configuration management interface in this step can be implemented based on RESTAPI to perform centralized configuration of new and old devices through a standardized interface (e.g., modification of device IP addresses, bandwidth parameters, etc. through a POST request).

[0117] S6.1.3, joint debugging test verification: test the signal modulation and demodulation consistency of new and old devices, verify the stability of the power module in a hybrid power supply environment, test the delay and reliability of the protocol conversion process, and ensure that new and old devices can implement hybrid networking. Through systematic test verification, the performance and reliability of new and old devices after hybrid networking are ensured, and transmission failures caused by compatibility problems are avoided.

[0118] As a further illustration of this step,

[0119] In this step, the periodic global topology optimization mechanism in S6 specifically includes the following implementation steps:

[0120] S6.2.1, period and trigger condition configuration: set a fixed optimization period, and the period length can be configured according to network service characteristics; by flexibly configuring the optimization period and trigger conditions, the network stability and optimization timeliness are balanced, and network shock caused by excessive optimization is avoided.

[0121] S6.2.2, real-time monitoring and trigger determination: when it is detected that any node load exceeds a preset threshold, new high-priority service access is added, or key link quality parameters deteriorate, immediate routing optimization is started; this design triggers optimization immediately when the network is abnormal by monitoring key indicators in real time, thereby ensuring service continuity.

[0122] As a further supplement to this step, the monitoring indicators in this step include: CPU, memory, bandwidth, packet loss rate, delay jitter, QoS queue length, and other parameters;

[0123] S6.2.3, routing optimization algorithm execution: based on the current network topology, node load data, and service demand, an optimal routing scheme containing path priority is generated through a shortest path algorithm, a multi-objective optimization algorithm, or an intelligent optimization algorithm; the multi-objective optimization algorithm can be parameterized and configured by means of the objective function F = w1·L + w21(1 / B) + w3·D, where L represents path length, B is available bandwidth, D is delay, and w1, w2, and w3 are weight coefficients, to achieve multi-dimensional optimization configuration of path length, available bandwidth, and delay; this design generates an optimal routing scheme based on multi-dimensional data, taking into account the shortest path, load balancing, and service priority, which can improve resource utilization.

[0124] As a further supplement to this step, in the application of the routing optimization algorithm, an adaptive solution needs to be selected according to the network characteristics. The shortest path algorithm (such as Dijkstra algorithm) is suitable for the scene with simple network topology and consistent service priority, and the core goal is to find the shortest transmission path simply and efficiently. The multi-objective optimization algorithm (such as NSGA-II) focuses on the comprehensive optimization in the complex scene, and simultaneously considers the path length L, available bandwidth B and delay D through the objective function F = w1·L + w2·(1 / B) + w3·D, wherein L is the path length, B is the available bandwidth, D is the delay, and w1, w2 and w3 are weight coefficients. For example, the weight coefficients are (w1 = 0.4), w2 = 0.3) and (w3 = 0.3), and the weight of each factor can be flexibly adjusted to realize the balance of multi-dimensional optimization. The intelligent optimization algorithm (such as ant colony algorithm) is designed for the network with frequent dynamic changes. It uses pheromone updating mechanism to simulate the adaptive characteristics of ant foraging, and adjusts the route in real time to ensure the optimality of the routing solution in the dynamic network topology, and effectively deals with the complex and changeable network environment.

[0125] S6.2.4, route table synchronization and adjustment: generate the optimized routing scheme instruction and synchronize it to each network node to update the routing table. The routing table is synchronized through the standardized mechanism to ensure that the optimized solution takes effect quickly in the whole network, which can reduce the route convergence time.

[0126] As a further supplement to this step, the synchronization protocol in this step can use the BGP-LS (BGP Link State) protocol to deliver topology information, and use the IS-IS or OSPF protocol to synchronize the routing table, and support incremental update (such as IS-IS extension defined in RFC7354).

[0127] Those skilled in the art can understand that the process of implementing all or part of the steps of the above embodiments can be completed by hardware, or by program to instruct related hardware, and the program can be stored in a computer readable storage medium.

[0128] The basic principles, main features and advantages of the present application are shown and described above. Those skilled in the art should understand that the present application is not limited by the above embodiments, and the above embodiments and descriptions in the specification are only preferred examples of the present application and are not intended to limit the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A microwave transmission networking method suitable for ultra-high-definition television signal transmission, characterized in that, Includes the following steps: S1. Construction of heterogeneous multipath network: Construct a microwave network between the signal transmitter and receiver, which includes at least two primary transmission paths and one backup transmission path; use a cross-path clock synchronization mechanism to achieve coordinated signal transmission and construct a ring or mesh topology. S2, Signal Layering Processing: The input ultra-high-definition signal is layered, cut, and processed; S3. Layered signal encapsulation and transmission: IP packet encapsulation is performed on the layered ultra-high-definition signal, and end-to-end transmission is achieved through a packet switching network; S4. Interference cancellation: Enable cross-polarization interference cancellation technology on each primary path; S5. Monitoring, Early Warning and Path Switching: Deploy a real-time monitoring module and build an evaluation model, and establish a hot backup mechanism; S6. Compatibility Upgrades and Global Optimization: Upgrade existing microwave transmission equipment for compatibility, enabling hybrid networking of new and old equipment; periodically activate a global topology optimization mechanism to dynamically adjust network routing based on node load and service requirements. The compatibility modifications in S6 include the following steps: S6.1.1 Hardware adaptation and modification: Upgrade the RF front-end module of the existing equipment to support the modulation method of the new equipment, modify the power adapter unit to be compatible with the power supply specifications of the new equipment, and expand the physical interface types to realize the physical connection and signal interaction between the old and new equipment. S6.1.2 Software Protocol Adaptation: Update device firmware to support new communication protocols, embed a protocol conversion module in the control plane to parse and convert control commands and data formats between old and new devices, and establish a unified configuration management interface to centrally monitor the parameters and status of old and new devices; S6.1.3 Joint debugging and verification: Test the consistency of signal modulation and demodulation of new and old equipment, verify the stability of power module under mixed power supply environment, test the latency and reliability of protocol conversion process, and ensure that new and old equipment can achieve mixed networking; The periodic activation of the global topology optimization mechanism in S6 specifically includes the following implementation steps: S6.2.1 Period and Trigger Condition Configuration: Set a fixed optimization period, and configure the period duration according to the characteristics of network services; S6.2.2 Real-time monitoring and trigger judgment: When it is detected that the load of any node exceeds the preset threshold, a new high-priority service is added, or the quality parameters of a critical link deteriorate, instant route optimization is immediately initiated; S6.2.3 Routing Optimization Algorithm Execution: Based on the current network topology, node load data, and service requirements, an optimal routing scheme including path priorities is generated using the shortest path algorithm, multi-objective optimization algorithm, or intelligent optimization algorithm; among them, the multi-objective optimization algorithm utilizes an objective function. Perform parameterized configuration. Represents path length. For available bandwidth, For time delay, , , These are weighting coefficients used to optimize configurations across multiple dimensions, including path length, available bandwidth, and latency. S6.2.4 Routing Table Synchronization and Adjustment: Generate instructions for the optimized routing scheme and synchronize them to each network node to update the routing table.

2. The microwave transmission networking method for ultra-high-definition television signal transmission according to claim 1, characterized in that: The cross-path clock synchronization mechanism in S1 is implemented in the following way: clock modules containing atomic clocks or GPS synchronization units are deployed at each transmission path node, and clock synchronization messages are periodically exchanged between nodes according to the IEEE1588v2 protocol.

3. The microwave transmission networking method for ultra-high-definition television signal transmission according to claim 1, characterized in that, The step S2, which involves layering and processing the input ultra-high-definition signal, includes the following steps: S2.1 Signal layering and cutting: Separating the ultra-high-definition signal into independent video, audio and metadata layers; S2.2 Preprocessing of each layer: The BM3D algorithm is used to denoise and unify the resolution of the video layer. The Wiener filtering algorithm is used to perform noise reduction and sampling rate normalization on the audio layer. A cyclic redundancy check algorithm is used to perform format verification and redundant data removal on the metadata layer; S2.3, Timing Synchronization Marker: Add timestamps and frame numbers to the data of each layer to establish the timing correspondence between the video layer, audio layer and metadata layer, providing a synchronization benchmark for subsequent layered encapsulation.

4. The microwave transmission networking method for ultra-high-definition television signal transmission according to claim 1, characterized in that, The IP packet encapsulation in S3 includes the following steps: S3.1 Protocol Adaptation and Encapsulation: Select the encapsulation protocol according to the signal characteristics of each layer, and encapsulate the video layer, audio layer, and metadata layer into IP data packets respectively; S3.2 QoS Priority Marking: Insert a Quality of Service field into the IP packet header to mark the priority level of signals at each layer; S3.3 Reliability Enhancement Processing: Add cyclic redundancy check codes to the encapsulated IP data packets, and embed forward error correction redundancy data.

5. The microwave transmission networking method for ultra-high-definition television signal transmission according to claim 1, characterized in that, The cross-polarization interference cancellation technique in S4 specifically includes: Deploy dual-polarized antennas at the transmission nodes of the primary path to receive two signals with orthogonal polarization at the same frequency; The received two signals are sampled and digitized, and an interference estimation model is constructed based on an adaptive filtering algorithm. The cross-polarization interference component in the target signal is separated by an interference estimation model, and the interference component is eliminated from the received signal.

6. The microwave transmission networking method for ultra-high-definition television signal transmission according to claim 5, characterized in that: The adaptive filtering algorithm in S4 performs the following process when eliminating interference through the interference estimation model: First, an error signal is calculated based on the real-time sampled data of the received signal. Represented as: ;in, For the desired signal, This is the actual output signal. Sampling time; Next, the filter coefficients are dynamically adjusted based on the error signal. The filter coefficient update formula is as follows: ,in, for The filter coefficient vector at time t. The input signal vector.

7. The microwave transmission networking method for ultra-high-definition television signal transmission according to claim 1, characterized in that, The construction of the evaluation model in S5 specifically includes the following steps: S5.1 Dynamic Weight Configuration: Configure dynamic weight coefficients for each transmission parameter. These dynamic weight coefficients are adaptively adjusted based on signal transmission time period, network load status, and weather conditions. S5.2 Multi-parameter fusion evaluation: Generate path quality evaluation values ​​based on multi-parameter fusion algorithms. The multi-parameter fusion algorithm includes a weighted summation model, a fuzzy logic reasoning model, or a neural network evaluation model, wherein the calculation formula for the improved weighted summation model is as follows: ,in To standardize parameter values, For the first The parameters at time... Dynamic weights; The calculation method is as follows: ,in: For the first The initial weights of the parameters, This is a weighting adjustment factor, set according to the degree of influence of the parameters on ultra-high-definition signal transmission. For the first The parameters at the previous moment The value of , For the first Historical mean of each parameter For the first The historical standard deviation of each parameter.

8. The microwave transmission networking method for ultra-high-definition television signal transmission according to claim 1, characterized in that, The specific steps for establishing a hot backup mechanism in S5 include the following: S5.1 Construction of Heterogeneous Backup Path: Select a different transmission technology from the primary path to construct a backup path; S5.2 Automatic Rerouting Switching: When the quality of the primary path is detected to be lower than the preset standard, the automatic rerouting algorithm is started, and the optimal backup path is calculated based on the real-time path quality assessment data and a lossless switch is performed.

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