Time delay processing method and device and medium

Abstract

The embodiment of the invention relates to a time delay processing method and device and a medium, and the method comprises the steps: obtaining a plurality of pre-generated training sequences corresponding to a plurality of radio frequency channels, and enabling the training sequences not to interfere with each other; simultaneously, respectively inserting the plurality of training sequences into the target time slots of the corresponding radio frequency channels; obtaining combined data corresponding to the plurality of training sequences in the target time slot at a combined feedback port corresponding to the plurality of radio frequency channels; calculating time delay data of the combined data and each training sequence to obtain multiple pieces of time delay data corresponding to the multiple radio frequency channels; and carrying out time delay alignment processing on the multiple radio frequency channels according to the multiple pieces of time delay data. According to the technical scheme, the time delay data of the multiple radio frequency channels can be determined at the same time based on a set of path data, the time delay acquisition efficiency of each radio frequency channel is improved, and therefore the time delay alignment efficiency of the multiple radio frequency channels is improved.

Description

Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to a delay processing method, apparatus and medium. Background Technology

[0002] In the development of wireless communication systems, with the continuous increase in bandwidth requirements, the output power required by radio frequency (RF) equipment has also increased accordingly. To meet the high output power of the antenna port, multiple internal RF channels can be combined in hardware to achieve superimposed output of multi-channel power. However, the time delay difference between RF channels will have a certain impact on the combined signal, causing problems such as output power attenuation and poor in-band flatness, preventing the equipment from reaching its optimal operating state.

[0003] In related technologies, in order to eliminate the impact of inter-channel delay difference on the quality of the combined output signal, a fixed training sequence is constructed, the training sequence is sent to each RF channel in sequence, and the feedback signal from each RF channel is received in sequence. Based on the time required to receive the feedback signal each time, the delay of different RF channels is estimated. Then, the delay difference between RF channels is calculated based on the delay, and the delay alignment processing of multiple RF channels is performed based on the delay difference.

[0004] However, the above delay calculation method requires sending training sequences to each radio frequency channel multiple times and calculating the delay of each radio frequency channel multiple times, resulting in low delay acquisition efficiency for each radio frequency channel. This affects the efficiency of delay alignment processing for multiple radio frequency channels. Summary of the Invention

[0005] In order to solve the above-mentioned technical problems, or at least partially solve the above-mentioned technical problems, this disclosure provides a delay processing method, apparatus and medium.

[0006] This disclosure provides a latency processing method, comprising the following steps: acquiring a plurality of pre-generated training sequences corresponding to multiple radio frequency channels, wherein each training sequence is non-interfering with the others; simultaneously inserting the plurality of training sequences into the target time slots of the corresponding radio frequency channels; acquiring combined data corresponding to the plurality of training sequences in the target time slots at the combined feedback port corresponding to the multiple radio frequency channels; calculating the latency data of the combined data and each training sequence to obtain a plurality of latency data corresponding to the multiple radio frequency channels; and performing latency alignment processing on the multiple radio frequency channels based on the plurality of latency data.

[0007] Optionally, before acquiring the pre-generated multiple training sequences corresponding to the multiple radio frequency channels, the method includes: acquiring the reference combining power and the actual combining power of the combining feedback port for each preset monitoring period, wherein the reference combining power is calculated by summing the multiple branch transmission powers corresponding to the multiple radio frequency channels; calculating the power difference between the actual combining power and the reference combining power for each preset monitoring period; and determining that the multiple radio frequency channels meet the preset delay calibration conditions based on the power difference.

[0008] Optionally, the preset time delay calibration condition includes: a preset number of consecutive power differences all exceeding a preset power difference threshold.

[0009] Optionally, before obtaining the pre-generated multiple training sequences corresponding to the multiple radio frequency channels, the method further includes: obtaining the signal transmission parameters of each radio frequency channel and obtaining the number of channels of the multiple radio frequency channels; and generating the multiple training sequences corresponding to the multiple radio frequency channels based on the signal transmission parameters and the number of channels.

[0010] Optionally, calculating the latency data of the combined data and each training sequence includes: extracting a combined data segment from the combined data, determining the start and end positions of the combined data segment in the target time slot; extracting a training sequence segment corresponding to the combined data segment from each training sequence based on the start and end positions; and calculating the latency data of the combined data and each training sequence based on the combined data segment and each training sequence segment.

[0011] Optionally, the latency data includes integer latency, and calculating the latency data of the combined data and each training sequence includes: performing cross-correlation calculation on the combined data and each training sequence, determining the position of the maximum correlation peak in each training sequence based on the calculation result, and determining the integer latency of each training sequence based on the position of the maximum correlation peak.

[0012] Optionally, the step of performing delay alignment processing on the multiple radio frequency channels based on the multiple delay data includes: calculating the integer delay difference of each radio frequency channel based on the multiple integer delays corresponding to the multiple radio frequency channels; and writing the corresponding integer delay difference into the shift register corresponding to each radio frequency channel.

[0013] Optionally, the resource particle positions of the independent training sequences are completely different, and the latency data also includes fractional latency. The calculation of the merged data and the latency data of each training sequence further includes: aligning the merged data with the integer latency of each training sequence according to the integer latency of each training sequence; calculating the phase difference information of the effective resource particles of the merged data after alignment of each training sequence with the corresponding integer latency; and determining the fractional latency of each training sequence according to the phase difference information.

[0014] Optionally, the step of performing delay alignment processing on the multiple radio frequency channels based on the multiple delay data includes: fitting a phase difference curve corresponding to the fractional delay difference of each radio frequency channel based on the multiple phase difference information corresponding to the multiple radio frequency channels; converting the phase difference curve into candidate filter coefficients in the time domain, and extracting the effective filter coefficients within the candidate filter coefficients; and generating a filter in each radio frequency channel based on the corresponding effective filter coefficients.

[0015] Optionally, before obtaining the pre-generated multiple training sequences corresponding to the multiple radio frequency channels, each radio frequency channel undergoes delay alignment processing based on a pre-set initial delay difference.

[0016] This disclosure also provides a delay processing apparatus, comprising: a first acquisition module for acquiring a plurality of pre-generated training sequences corresponding to multiple radio frequency channels, wherein each training sequence is non-interfering with the others; a sequence insertion module for simultaneously inserting the plurality of training sequences into the target time slots of the corresponding radio frequency channels; a second acquisition module for acquiring combined data corresponding to the plurality of training sequences in the target time slots at the combined feedback port corresponding to the multiple radio frequency channels; a delay calculation module for calculating the delay data of the combined data and each training sequence to obtain a plurality of delay data corresponding to the multiple radio frequency channels; and a delay processing module for performing delay alignment processing on the multiple radio frequency channels based on the plurality of delay data.

[0017] Optionally, it also includes: a delay calibration condition judgment module, used to: obtain the reference combining power and the actual combining power of the combining feedback port for each preset monitoring period according to a preset monitoring period, wherein the reference combining power is calculated by summing the transmission power of multiple branch lines corresponding to the multi-RF channel; calculate the power difference between the actual combining power and the reference combining power for each preset monitoring period; and determine that the multi-RF channel meets the preset delay calibration condition based on the power difference.

[0018] Optionally, the preset time delay calibration condition includes: a preset number of consecutive power differences all exceeding a preset power difference threshold.

[0019] Optionally, it further includes: a training sequence generation module, configured to: obtain signal transmission parameters for each of the radio frequency channels and obtain the number of channels for the multiple radio frequency channels; and generate the multiple training sequences corresponding to the multiple radio frequency channels based on the signal transmission parameters and the number of channels.

[0020] Optionally, the latency calculation module is specifically used for: extracting a combined data segment from the combined data, determining the start and end positions of the combined data segment in the target time slot; extracting a training sequence segment corresponding to the combined data segment from each training sequence based on the start and end positions; and calculating the latency data between the combined data and each training sequence based on the combined data segment and each training sequence segment.

[0021] Optionally, the latency data includes integer latency, and the latency calculation module is specifically used for: performing cross-correlation calculation on the combined data and each training sequence, determining the position of the maximum correlation peak in each training sequence based on the calculation result, and determining the integer latency of each training sequence based on the position of the maximum correlation peak.

[0022] Optionally, the delay calculation module is specifically used to: calculate the integer delay difference of each radio frequency channel based on the multiple integer delays corresponding to the multiple radio frequency channels; and write the corresponding integer delay difference into the shift register corresponding to each radio frequency channel.

[0023] Optionally, the resource particle positions of the independent training sequences are completely different, and the latency data also includes fractional latency. The latency calculation module is further configured to: align the combined data with the integer latency of each training sequence according to the integer latency of each training sequence; calculate the phase difference information of the effective resource particles of the combined data after each training sequence is aligned with the corresponding integer latency; and determine the fractional latency of each training sequence according to the phase difference information.

[0024] Optionally, the delay calculation module is specifically used to: fit a phase difference curve corresponding to the fractional delay difference of each radio frequency channel based on the multiple phase difference information corresponding to the multiple radio frequency channels; convert the phase difference curve into candidate filter coefficients in the time domain, and extract the effective filter coefficients within the candidate filter coefficients; and generate a filter in each radio frequency channel based on the corresponding effective filter coefficients.

[0025] Optionally, before obtaining the pre-generated multiple training sequences corresponding to the multiple radio frequency channels, each radio frequency channel undergoes delay alignment processing based on a pre-set initial delay difference.

[0026] This disclosure also provides a delay processing apparatus, including a memory, a transceiver, and a processor: the memory is used to store a computer program; the transceiver is used to transmit and receive data under the control of the processor; the processor is used to read the computer program in the memory and perform the following operations: acquiring a plurality of pre-generated training sequences corresponding to multiple radio frequency channels, wherein each training sequence is non-interfering with the others; simultaneously inserting the plurality of training sequences into the target time slots of the corresponding radio frequency channels; acquiring combined data corresponding to the plurality of training sequences in the target time slots at the combined feedback port corresponding to the multiple radio frequency channels; calculating the delay data of the combined data and each training sequence to obtain a plurality of delay data corresponding to the multiple radio frequency channels; and performing delay alignment processing on the multiple radio frequency channels according to the plurality of delay data.

[0027] Optionally, the processor is further configured to perform the following operations: obtain a reference combined power and the actual combined power of the combined feedback port for each preset monitoring period, wherein the reference combined power is calculated by summing the transmission power of multiple branch lines corresponding to the multi-RF channels; calculate the power difference between the actual combined power and the reference combined power for each preset monitoring period; and determine that the multi-RF channels meet preset delay calibration conditions based on the power difference.

[0028] Optionally, the preset time delay calibration condition includes: a preset number of consecutive power differences all exceeding a preset power difference threshold.

[0029] Optionally, the processor is further configured to perform the following operations: obtain signal transmission parameters for each of the radio frequency channels and obtain the number of channels for the multiple radio frequency channels; and generate the multiple training sequences corresponding to the multiple radio frequency channels based on the signal transmission parameters and the number of channels.

[0030] Optionally, the processor is further configured to perform the following operations: extracting a combined data segment from the combined data, determining the start and end positions of the combined data segment in the target time slot; extracting a training sequence segment corresponding to the combined data segment from each training sequence based on the start and end positions; and calculating the time delay data between the combined data and each training sequence based on the combined data segment and each training sequence segment.

[0031] Optionally, the latency data includes integer latency, and the processor is further configured to perform the following operations: perform cross-correlation calculation on the combined data and each training sequence, determine the position of the maximum correlation peak in each training sequence based on the calculation result; and determine the integer latency of each training sequence based on the position of the maximum correlation peak.

[0032] Optionally, the processor is further configured to perform the following operations: calculate the integer delay difference of each of the multiple radio frequency channels based on the multiple integer delays corresponding to the multiple radio frequency channels; and write the corresponding integer delay difference into the shift register corresponding to each of the multiple radio frequency channels.

[0033] Optionally, the resource particle positions of the independent training sequences are completely different, and the latency data also includes fractional latency. The processor is further configured to perform the following operations: align the combined data with the integer latency of each training sequence according to the integer latency of each training sequence; calculate the phase difference information of the effective resource particles of the combined data after each training sequence is aligned with the corresponding integer latency; and determine the fractional latency of each training sequence according to the phase difference information.

[0034] Optionally, the processor is further configured to perform the following operations: fitting a phase difference curve corresponding to the fractional delay difference of each of the multiple radio frequency channels based on the multiple phase difference information corresponding to the multiple radio frequency channels; converting the phase difference curve into candidate filter coefficients in the time domain, and extracting the effective filter coefficients within the candidate filter coefficients; and generating a filter in each of the radio frequency channels based on the corresponding effective filter coefficients.

[0035] Optionally, before obtaining the pre-generated multiple training sequences corresponding to the multiple radio frequency channels, each radio frequency channel undergoes delay alignment processing based on a pre-set initial delay difference.

[0036] This disclosure also provides a processor-readable storage medium storing a computer program for executing the above-described delay processing method.

[0037] This disclosure also provides a computer program product, including a computer program, wherein the computer program performs the above-described delay processing method when executed by a processor.

[0038] The technical solution provided in this disclosure has the following advantages compared with the prior art:

[0039] Multiple pre-generated training sequences corresponding to multiple radio frequency (RF) channels are acquired, ensuring that each training sequence is independent of the others. These training sequences are then inserted into the target time slots of their respective RF channels. At the combining feedback port corresponding to each RF channel, combined data corresponding to the training sequences in the target time slots is acquired. The delay data between the combined data and each training sequence is then calculated to obtain multiple delay data corresponding to each RF channel. Delay alignment is then performed on the multiple RF channels based on this multiple delay data. In this technical solution, the delay data of multiple RF channels can be determined simultaneously based on a single combined combining data, improving the efficiency of delay acquisition for each RF channel and thus enhancing the efficiency of delay alignment for multiple RF channels. Attached Figure Description

[0040] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0041] Figure 1 A flowchart illustrating a delay processing method provided in an embodiment of this disclosure;

[0042] Figure 2 This is a schematic diagram of a dual-path delay alignment processing scenario provided by an embodiment of the present disclosure;

[0043] Figure 3 A flowchart illustrating another delay processing method provided in this embodiment of the disclosure;

[0044] Figure 4 A flowchart illustrating another delay processing method provided in this embodiment of the present disclosure;

[0045] Figure 5 A flowchart illustrating a latency processing scenario provided in an embodiment of this disclosure;

[0046] Figure 6 This is a schematic diagram of the structure of a delay processing device provided in an embodiment of the present disclosure;

[0047] Figure 7 This is a schematic diagram of another delay processing device provided in an embodiment of the present disclosure. Detailed Implementation

[0048] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0049] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0050] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0051] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0052] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0053] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this disclosure.

[0054] As mentioned above, to meet the requirement of high output power for the Radio Remote Unit (RRU), multiple RF channels can be combined to superimpose the output signals and thus increase the output power. However, in practice, due to hardware conditions and the influence of the equipment environment and link signals during operation, there will be time delay differences between different branch channels. These time delay differences will cause some signals to be canceled out during the signal combining process, resulting in the combined output signal power not reaching the theoretical maximum value. In severe cases, this can lead to a deterioration in the carrier flatness of the combined output signal, resulting in carrier dips and other phenomena.

[0055] The proposed related technology involves determining the delay of each RF channel one by one based on a pre-constructed set of training sequences, and then performing delay alignment based on the delay difference between RF channels. This method is obviously time-consuming, resulting in low efficiency in delay calculation.

[0056] To address the aforementioned technical problems, this disclosure provides a delay processing method. In this method, multiple non-interfering training sequences are generated for each radio frequency (RF) channel. These training sequences are then inserted into each RF channel. Combined data is received at the combining feedback port of the combining channel. Based on the combined data and the corresponding training sequences, the delay of multiple RF channels can be calculated simultaneously. The delay difference between each RF channel can be obtained based on this delay, enabling delay alignment processing of the multiple RF channels. This ensures that the combined data from the aligned multiple RF channels has higher output power and higher in-band flatness, thus improving communication quality.

[0057] The method will be described below with reference to specific embodiments.

[0058] The technical solutions provided in this disclosure can be applied to a variety of systems. For example, applicable systems may include Long Term Evolution (LTE) systems, LTE Frequency Division Duplex (FDD) systems, LTE Time Division Duplex (TDD) systems, Long Term Evolution Advanced (LTE-A) systems, Universal Mobile Telecommunications System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX) systems, 5G New Radio (NR) systems and their evolved communication systems, and 6G (sixth generation mobile communication technology) systems. These systems may include terminal equipment and network equipment. The systems may also include a core network component, such as the Evolved Packet Core (EPC) or the 5G Core Network (5GC).

[0059] The terminal devices involved in the embodiments of this disclosure can be devices that provide voice and / or data connectivity to users, handheld devices with wireless connectivity, or other processing devices connected to a wireless modem. The names of the terminal devices may differ in different systems; for example, in 5G or 6G systems, the terminal device may be called User Equipment (UE). Wireless terminal devices can be USB storage devices, other personal computer memory devices, and dongles. They can also communicate with one or more core networks (CNs) via a Radio Access Network (RAN). Wireless terminal devices can be mobile terminal devices, such as mobile phones (or "cellular" phones) and computers with mobile terminal devices. For example, they can be portable, pocket-sized, handheld, computer-embedded, or vehicle-mounted mobile devices that exchange voice and / or data with the radio access network. Examples of such devices include Personal Communication Service (PCS) telephones, cordless phones, Session Initiated Protocol (SIP) phones, Wireless Local Loop (WLL) stations, Personal Digital Assistants (PDAs), personal computers, tablets, and Machine-type Communication (MTC) terminal devices. Wireless terminal devices can also be referred to as systems, subscriber units, subscriber stations, mobile stations, mobile terminals, remote stations, access points, remote terminals, access terminals, user terminals, user agents, user devices, and wireless access devices and routers / modems that meet the limitations of this definition, but are not limited to these specific embodiments in this disclosure.

[0060] The network device involved in this disclosure can be a base station, which may include multiple cells providing services to terminals. Depending on the specific application, the base station may also be called an access point, or a device in the access network that communicates with wireless terminal devices through one or more sectors on the air interface, or other names. The network device can be used to exchange received air frames with Internet Protocol (IP) packets, acting as a router between the wireless terminal device and the rest of the access network, where the rest of the access network may include an Internet Protocol (IP) communication network. The network device can also coordinate the attribute management of the air interface. For example, the network device involved in this disclosure can be an evolved Node B (eNB or e-NodeB) in a long term evolution (LTE) system, a 5G base station (gNB) in a next generation system, or a Home evolved Node B (HeNB), relay node, femto, pico, network testing equipment, etc., and is not limited in this disclosure. In some network architectures, network devices may include centralized unit (CU) nodes and distributed unit (DU) nodes, which may also be geographically separated.

[0061] Network devices and terminal devices can each use one or more antennas to perform multiple-input multiple-output (MIMO) transmission. MIMO transmission can be single-user MIMO or multi-user MIMO. Depending on the configuration and number of antenna combinations, MIMO transmission can be 2D-MIMO, 3D-MIMO, FD-MIMO, or massive-MIMO, and can also be diversity transmission, precoding transmission, or beamforming transmission, etc.

[0062] Figure 1 This is a flowchart illustrating a latency processing method provided in an embodiment of the present disclosure. The method can be executed by a latency processing device, which can be implemented in software and / or hardware, and is generally integrated into a network device. Figure 1 As shown, the method includes:

[0063] Step 101: Obtain multiple pre-generated training sequences corresponding to the multi-RF channels, wherein each training sequence does not interfere with the others.

[0064] In some possible embodiments, before obtaining the pre-generated multiple training sequences corresponding to the multiple radio frequency channels, it can be determined that the multiple radio frequency channels meet a preset delay calibration condition. Only after meeting the preset delay calibration condition is the generation of multiple training sequences performed; if the preset delay calibration condition is not met, multiple training sequences are not generated, thereby reducing the computational burden. The process of determining whether multiple radio frequency channels meet the preset delay calibration condition is illustrated below with specific examples:

[0065] In some possible examples, the transmission power of multiple RF channels within each monitoring period is obtained according to a preset monitoring period. These multiple transmission powers can be the actual transmission power of multiple RF channels obtained in real time, or the theoretical transmission power determined according to the channel conditions of multiple RF channels. The reference combined power is obtained by summing the multiple transmission powers. For example, in a dual RF channel scenario, if the transmission power of RF channel 1 and RF channel 2 is P, then the reference combined power is 2P.

[0066] It also monitors the actual combined power of the combined feedback port in each preset monitoring cycle. The cycle length of the preset monitoring cycle can be set according to the needs of the scenario. It calculates the power difference between the actual combined power and the reference combined power in each preset monitoring cycle, and determines whether the multi-RF channels meet the preset delay calibration conditions based on the power difference.

[0067] In different application scenarios, the aforementioned preset delay calibration conditions vary. As one possible example, when a preset number of consecutive power differences exceed a preset power difference threshold, it is determined that multiple RF channels meet the preset delay calibration conditions. The preset number can be set according to the needs of the scenario. That is, in this example, if the power difference exceeds the preset power difference threshold in multiple consecutive preset monitoring cycles, it is determined that the preset delay calibration conditions are met. In some possible examples, the number of times the power difference exceeds the preset power difference threshold within a preset time period is counted. If it exceeds a preset number threshold, it is determined that multiple RF channels meet the preset delay calibration conditions. The preset number threshold can be calibrated based on experimental data.

[0068] In some possible examples, as the device's operating time increases, many factors such as the RRU device environment and Digital Pre-Distortion (DPD) iterations will affect the link status, causing changes in the time delay difference between branches. Therefore, the operating time of the device containing multiple radio frequency channels can also be counted, and when the operating time exceeds the preset time threshold, a time delay calibration command can be obtained.

[0069] In one embodiment of this disclosure, multiple pre-generated training sequences corresponding to multiple radio frequency channels are obtained. To prevent interference between training sequences during subsequent combining, this embodiment ensures that the multiple training sequences do not interfere with each other. This non-interference can be achieved in various ways, such as ensuring the multiple training sequences are spatially separated or frequency-separated. The training sequences may include any known sequence such as a demodulation reference signal (DMRS).

[0070] In some possible embodiments, multiple training sequences can be separated in terms of frequency, for example, the resource element (RE) positions of each training sequence are completely different, to ensure that the training sequences do not interfere with each other.

[0071] In this embodiment, the generation of multiple training sequences can be any generation method that ensures that the multiple training sequences do not interfere with each other. In actual execution, considering the actual transmission conditions of the RF channel link, the training sequences can also be generated in combination with the actual transmission conditions of the link to ensure that the sequence bandwidth, sampling rate and other characteristics of the training sequences are consistent with the actual transmitted signal characteristics, thereby further ensuring the reliability of the calculation delay.

[0072] In one embodiment of this disclosure, signal transmission parameters for each radio frequency (RF) channel are obtained. These signal transmission parameters may include features such as actual downlink data power, sampling rate, and maximum bandwidth. Then, the number of multiple RF channels is obtained. Based on the signal transmission parameters and the number of channels, a training sequence corresponding to each RF channel is generated. The number of training sequences corresponding to multiple RF channels is consistent with the number of channels. The training sequences corresponding to multiple RF channels do not interfere with each other, and the signal transmission parameters of the training sequences are consistent with the signal transmission parameters of each RF channel, ensuring the reliability of subsequent calculation delay.

[0073] Step 102: Simultaneously insert multiple training sequences into the target time slots of the corresponding radio frequency channels.

[0074] In one embodiment of this disclosure, in order to ensure the simultaneous calculation of the delay of multiple radio frequency channels, it is necessary to ensure that multiple training sequences are sent simultaneously. Thus, the delay of multiple training sequences can be determined by comparing the combined data with each training sequence. In this embodiment, multiple training sequences are inserted into the target time slots of the corresponding radio frequency channels. The target time slots can be idle time slots for transmitting signals in the radio frequency channels, etc.

[0075] Step 103: At the combined feedback port corresponding to the multi-RF channel, obtain the combined data corresponding to multiple training sequences in the target time slot.

[0076] After inserting multiple training sequences into the target time slots of their respective RF channels, the multiple training sequences are combined in the combining channel. In the target time slot, the multiple training sequences are combined without interfering with each other. Therefore, it is ensured that the subsequent delay calculation based on the combined data and the training sequences will not be affected by other training sequences.

[0077] In this embodiment, the combined data corresponding to multiple training sequences in the target time slot is obtained at the combined feedback port corresponding to the multiple radio frequency channels, so as to facilitate the subsequent delay calculation based on the combined data.

[0078] Step 104: Calculate the latency data of the combined data and each training sequence to obtain multiple latency data corresponding to the multi-RF channels.

[0079] After acquiring the combined data, the latency data of the combined data and each training sequence are calculated to obtain multiple latency data corresponding to multiple radio frequency channels. Thus, multiple latency data of multiple radio frequency channels can be acquired simultaneously with one combined data stream, improving the latency acquisition efficiency.

[0080] In the embodiments of this disclosure, the latency data can be calculated based on the combined data and the training sequence as a whole, or it can be calculated based on a portion of the combined data and the training sequence. That is, to improve the consistency between the training sequence and the actual signal transmitted in the radio frequency signal, the sequence bandwidth of the training sequence may be relatively wide. Calculating the latency data based on the entire training sequence may result in a large computational load. Therefore, combined data segments can be extracted from the combined data, and the start and end positions of the combined data segments in the target time slot can be determined. Based on the start and end positions, training sequence segments corresponding to the combined data segments are extracted from each training sequence. Based on the combined data segments and each training sequence segment, the latency data of the combined data and each training sequence is calculated. That is, the training sequence is extracted at the same time slot position as the combined data segments, ensuring that the combined data used for calculation corresponds synchronously with the training sequence, thus ensuring the reliability of the calculated latency. For example, if the extracted combined data segment is located at points 0-4095 in the target time slot, then the training sequence segment is located at points 0-4095 in the target time slot.

[0081] Of course, in actual execution, it is also necessary to ensure that the combined data used in the calculation of latency is valid data, that is, to determine that the transmission power of the corresponding combined data is within the preset power range, so as to avoid the failure of combined data due to transmission abnormalities. The preset power range can be set according to the needs of the scenario. The preset power range is the possible output power range of the combined data in the normal working mode of the combined channel.

[0082] It is important to emphasize that in all embodiments involving the calculation of latency data of combined data and each training sequence, the calculation can be based on the overall calculation of combined data and each training sequence, or it can be calculated by extracting segments of combined data and each training sequence as described in the above embodiments. Regardless of whether the overall calculation or the segment calculation is used, the calculation method is the same. Therefore, in all subsequent embodiments for calculating latency data, the combined data involved can be the entire combined data or a segment of combined data extracted from the combined data. Similarly, the training sequence involved can be the entire training sequence or a segment of training data extracted from the training sequence.

[0083] Step 105: Perform time delay alignment processing on multiple radio frequency channels based on multiple time delay data.

[0084] It is easy to understand that the purpose of this disclosure is to improve the signal transmission power of multiple radio frequency channels. Therefore, after calculating multiple delay data, it is necessary to perform delay alignment processing on the multiple radio frequency channels, that is, to calculate the delay difference between each radio frequency channel and perform delay alignment processing on the data transmitted by multiple radio frequency channels based on the delay difference.

[0085] Among them, the time delay difference is related not only to the signal transmission link, but also to the equipment structure design and process flow at the time of manufacture, as well as factors such as internal temperature and humidity during equipment operation. Therefore, in one embodiment of this disclosure, before obtaining the pre-generated multiple training sequences corresponding to multiple radio frequency channels, each radio frequency channel is subjected to time delay alignment processing according to the pre-set initial time delay difference.

[0086] In this embodiment, an initial delay difference can be pre-stored in the device. This initial delay difference can be written into an electrically erasable programmable read-only memory (EEPROM), thus establishing a fixed delay difference. This allows each RF channel to undergo delay alignment processing based on its corresponding initial delay difference before pre-distortion processing. In this embodiment, during device initialization, delay alignment processing is performed on each RF channel based on the initial delay difference to ensure the device quickly enters its optimal operating state. During device operation, delay alignment processing is performed using the aforementioned delay processing method to ensure the stability of the device's output performance. Therefore, delay alignment processing based on the pre-written initial delay difference allows for rapid calculation and compensation of the inherent delay of the channels after device startup without requiring operations such as writing and reading training sequences, ensuring the device quickly enters its optimal operating state. Furthermore, during device operation, the output power status of the current combined channel can be intuitively characterized by real-time monitoring of the combining and splitting power, enabling calibration of abnormal channels and ensuring the stability of the device's output performance during operation.

[0087] The following example, using a multi-RF channel including two RF channels, illustrates the delay processing method of this disclosure. Figure 2 As shown, delay alignment is implemented for the two data streams before channel combining to ensure that the output power of the combined data is as high as possible to meet the performance requirements of combined transmission. An example is shown below:

[0088] In this embodiment, the signal to be transmitted is first subjected to Crest Factor Reduction (CFR), which reduces the peak-to-average power ratio (PAR). PAR is the ratio of the maximum instantaneous power to the average power of a signal. A high PAR can cause the power amplifier to operate in a non-linear region when amplifying the signal, resulting in signal distortion. CFR reduces the peak value of the signal by modifying the phase or amplitude, thereby reducing the PAR and improving system performance and power amplifier efficiency. After CFR processing, two split signals are copied and transmitted through RF channel 1 and RF channel 2. During transmission, after digital pre-distortion (DPD) processing, the signals are combined after passing through a power amplifier (PA) to generate combined data. When the power amplifier (PA) operates at high power levels, it often exhibits non-linear characteristics, which can lead to signal distortion and spectrum regeneration, i.e., generating additional frequency components outside the original signal spectrum. This distortion reduces signal quality and increases adjacent channel interference. DPD addresses this problem by pre-distorting the signal before it enters the power amplifier. The predistortion algorithm inversely simulates the nonlinear characteristics of a power amplifier by introducing a distortion function at an early stage that is opposite to the power amplifier's distortion, thereby achieving linearization at the power amplifier's output. Thus, even when the power amplifier operates in the nonlinear region, the output signal maintains high quality and efficiency.

[0089] When the transmission power of multiple branches of RF channel 1 and RF channel 2 is W1 respectively, the actual combined power W2 of the combined data output by the combined feedback port is monitored for multiple consecutive preset monitoring cycles. Theoretically, the closer W2 is to the superimposed power 2W1 of RF channel 1 and RF channel 2, the better. In this embodiment, the power difference between 2W1 and W2 exceeds the preset power difference threshold for multiple consecutive preset monitoring cycles. Then, training sequence 1 and training sequence 2 are added to the target time slots of RF channel 1 and RF channel 2. The training sequence 1 and training sequence 2 do not interfere with each other. After inserting the training sequence, the combined data corresponding to the target time slot is obtained at the combined feedback port. Based on the combined data, calculations are performed with training sequence 1 and training sequence 2 respectively to calculate the time delay difference between training sequence 1 and training sequence 2. Thus, time delay compensation is performed on RF channel 1 and RF channel 2 based on the time delay difference.

[0090] Therefore, in the delay processing method of this embodiment, the training sequences used by the RF channels as branch channels are all consistent with the actual downlink signal bandwidth, sampling rate, and other signal transmission parameters of the RF channels, and the training sequences between channels do not interfere with each other. Each set of training sequences is simultaneously inserted into each branch channel in a specific time slot, and the combined data fed back after power superposition is obtained from the combining feedback point. The delay of each branch channel can be estimated simultaneously using a set of combined data. Using the method of simultaneously sending training sequences to each branch channel and capturing combined data from the combining feedback point for combining alignment is more computationally efficient than the method of sequentially sending and receiving training sequences to each channel, as delay alignment of multiple RF channels can be achieved with only one transmission and reception.

[0091] In summary, the delay processing method of this disclosure involves acquiring multiple pre-generated training sequences corresponding to multiple radio frequency (RF) channels, wherein each training sequence is independent of the others. Simultaneously, the multiple training sequences are inserted into the target time slots of their respective RF channels. At the combining feedback port corresponding to the multiple RF channels, combined data corresponding to the multiple training sequences in the target time slots is acquired. Then, the delay data of the combined data and each training sequence is calculated to obtain multiple delay data corresponding to the multiple RF channels. Delay alignment processing is performed on the multiple RF channels based on this multiple delay data. In this technical solution, the delay data of multiple RF channels can be determined simultaneously based on a single combined combining data, improving the delay acquisition efficiency of each RF channel and thus improving the efficiency of delay alignment for multiple RF channels.

[0092] Based on the above embodiments, the latency data of the combined data and each training sequence can include at least integer latency, such as integer latency and fractional latency. Integer latency refers to the latency caused when the latency difference is exactly an integer multiple of the sampling period. This latency causes the received combined data to be offset by an integer number of sampling points in the time domain relative to the ideal situation. Fractional latency refers to the latency caused when the latency difference is not an integer multiple of the sampling period, but rather a fractional value between two sampling points.

[0093] In some possible embodiments, such as Figure 3 As shown, when the latency data includes integer latency, the latency data of the combined data and each training sequence is calculated, including:

[0094] Step 301: Calculate the cross-correlation between the combined data and each training sequence, and determine the position of the maximum correlation peak in each training sequence based on the calculation results.

[0095] Step 302: Determine the integer delay of each training sequence based on the position of the maximum correlation peak.

[0096] It's easy to understand that in multi-RF channel transmission scenarios, the received combined data is compared with a predefined training sequence for correlation analysis. In this analysis, a correlation peak will appear between the training sequence and the combined data. The height of this peak reflects the similarity between the combined data and the training sequence. Since the training sequence is known and its position in the target time slot is fixed, the position of the maximum correlation peak indicates how long the training sequence has been delayed before reaching the combined feedback port. This delay is usually referred to as the "integer delay".

[0097] In actual execution, due to noise and other interference, smaller correlation peaks may appear when calculating the cross-correlation between the combined data and each training sequence. Therefore, it is necessary to check the peak-to-average ratio (PAR), which is the ratio of the height of the largest correlation peak to the average height of all correlation values. The PAR is used to evaluate the significance of the correlation peaks, ensuring that the detected peaks are indeed due to the presence of the training sequence rather than random noise. If the PAR meets the preset PAR threshold, it means that the detected largest peak is reliable, and the location of the training sequence can be considered found. Next, based on the location of the largest correlation peak, the delay of the combined data relative to the training sequence can be determined.

[0098] The method for calculating the cross-correlation between the combined data and each training sequence can include any algorithm that calculates the correlation between the combined data and the training sequence. As an example, the cross-correlation between the combined data and each training sequence can be calculated using the following formula (1):

[0099]

[0100] In formula (1), f(n) represents the combined data involved in the delay calculation, t(n) represents the training sequence involved in the delay calculation, r(m) represents the cross-correlation value of f(n) and t(n) at a delay of m, and N is the length of the training sequence involved in the delay calculation. The process of calculating the correlation is to take the conjugate of t(n) after a delay of m points and multiply it by f(n) point by point. The length of the obtained cross-correlation sequence is 2N-1, where n can be 0 to N-1, indicating that the cross-correlation of f(n) and t(n) is calculated point by point in formula (1). In this embodiment, starting from the first point of f(n), the conjugate of t(n) after sliding m points is multiplied by f(n). Starting from the second point of f(n), the conjugate of t(n) after sliding m points is multiplied by f(n). Starting from the third point of f(n), the conjugate of t(n) after sliding m points is multiplied by f(n)... where m can range from -(N-1) to (N-1), for a total of 2N-1 values. Calculate r(m) for f(n) at each point, where f(n) and t(n) slide to the aforementioned -(N-1) to (N-1) positions respectively. The sign of m indicates whether the signal delay is leading or lagging; that is, if r(m) has a maximum value when m>0, it means f(n) leads t(n); if r(m) has a maximum value when m<0, it means f(n) lags t(n). In this example, the m0 corresponding to the maximum value among the multiple obtained r(m) is taken as the position of the maximum correlation peak. As mentioned above, the position of the maximum correlation peak is the position where the combined data and the corresponding training sequence have the maximum correlation. Therefore, the integer delay of each training sequence is determined based on the position of the maximum correlation peak. Since the length of the training sequence and the corresponding combined data is N and the position of the maximum correlation is m0, the integer delay between f(n) and t(n) can be expressed as m0-N.

[0101] Furthermore, after calculating the integer delay of the combined data and each RF channel, delay alignment can be performed on the integer delay. Based on the multiple integer delays corresponding to the multiple RF channels, the integer delay difference of each RF channel is calculated. For example, a reference RF channel is selected among the multiple RF channels. Using the integer delay corresponding to the reference RF channel as a reference, the difference between the integer delay of each other RF channel and the integer delay corresponding to the reference RF channel is calculated as the integer delay difference of the corresponding RF channel. After calculating the integer delay difference, the corresponding integer delay difference is written into the shift register of each RF channel to achieve the initial delay alignment processing of the multiple RF channels.

[0102] It can be understood that by writing the aforementioned integer time delay difference into a shift register, the shift register can shift the data to be input into the corresponding RF channel in the time domain according to the integer time delay difference, thereby achieving compensation for the integer time delay difference of the relevant data.

[0103] In some possible embodiments, when the latency data includes both integer and fractional latencies, in addition to calculating the integer latency, it is also necessary to calculate the fractional latency. The integer latency can be calculated using the method shown in the above embodiments, or other calculation methods, which are not limited here. The following will combine... Figure 4 The steps for calculating the fractional latency of the combined data and each training sequence are illustrated, wherein the resource elements (REs) corresponding to the independent training sequences are located at completely different positions. The steps include:

[0104] Step 401: Align the combined data with the integer delay of each training sequence according to the integer delay of each training sequence.

[0105] In this embodiment, the merged data is first aligned with the integer delay of each training sequence according to the integer delay of each training sequence. For example, in the above embodiment, the merged data is moved according to m0 of each training sequence to achieve alignment of the merged data with the integer delay of each training sequence.

[0106] Step 402: Calculate the phase difference information of the effective resource particles of each training sequence and the corresponding integer delay-aligned combined data.

[0107] In this embodiment, each training sequence and its corresponding integer time delay-aligned combined data are converted into the frequency domain. The effective resource particles (REs) of each training sequence and its corresponding integer time delay-aligned combined data are calculated. In the frequency domain, RE refers to a subcarrier and a symbol period within a time slot. The effective RE refers to the RE that carries information in actual transmission, that is, the RE allocated for transmitting the training sequence or combined data. The effective REs corresponding to the training sequence are extracted from the combined data in the frequency domain, so that the focus can be on analyzing the frequency domain characteristics of the training sequence.

[0108] It is important to emphasize that the REs of different training sequences are different. Therefore, when extracting the effective REs of the combined data after integer delay alignment, the training sequences do not affect each other.

[0109] In this embodiment, each effective RE contains an amplitude and a phase. The phase information reflects the starting point of the fluctuation of the corresponding effective RE at that frequency. By comparing the phase of the effective resource particles in the training sequence and the combined data at the same frequency, the phase difference information between them can be obtained.

[0110] Step 403: Determine the fractional delay of each training sequence based on the phase difference information.

[0111] After obtaining the phase difference information, the fractional delay of each training sequence is determined based on the phase difference information. The phase difference information can then be used as the fractional delay to further perform delay alignment processing on multiple radio frequency channels.

[0112] Before calculating the fractional delay, the amplitude difference between the effective RE of each training sequence and the corresponding combined data can be calculated to determine whether the amplitude difference is less than a preset amplitude threshold. If it is less than the preset amplitude threshold, the corresponding combined data is considered to be valid, and then the next step of fractional delay calculation can be performed.

[0113] In one embodiment of this disclosure, based on multiple phase difference information corresponding to multiple RF channels, a phase difference curve corresponding to the fractional delay difference of each RF channel is fitted. Specifically, a reference RF channel can be determined among the multiple RF channels. Using the phase difference information corresponding to the reference RF channel as a benchmark, a target phase difference is calculated between the phase difference information of each other RF channel and the phase difference information corresponding to the quasi-RF channel. This target phase difference reflects the fractional delay difference of the corresponding RF channel. By fitting the target phase difference of each other RF channel, a phase difference curve corresponding to the fractional delay difference of each RF channel is obtained. This phase difference curve reflects the fractional delay difference between RF channels in the frequency domain.

[0114] The method described above for calculating and fitting the phase difference curve can be any fitting algorithm. As one possible example, considering the phase difference... It is a linear variation with frequency ω given a constant fractional time delay difference Δt. Therefore, the fitted phase difference A first-order polynomial with frequency ω, based on the above As can be seen from the linear relationship with ω, the slope k of the first-order polynomial can be obtained by fitting the fractional time delay difference Δt.

[0115] In some possible embodiments, the phase difference information of all valid REs is effectively utilized to accurately estimate the fractional delay difference. In this embodiment, the phase difference information of all valid RE positions is used during fractional delay calculation to fit the phase difference curve corresponding to the fractional delay difference for each RF channel.

[0116] In this example, the above can be calculated using the following formula (2). The linear relationship with ω, where, in formula (2), the phase difference information of the combined data and the effective RE of each training sequence is taken as input, where, since the combined data and each training sequence are aligned with integer delays beforehand, the fractional delay between the combined data and each training sequence is constant, and thus, the phase difference between the combined data and the effective RE of each training sequence is... It has a linear relationship with frequency ω, therefore the fitted phase difference For a first-order polynomial of frequency ω, we can obtain the slope k and intercept b corresponding to the first-order polynomial. The slope k and intercept b can be considered as the least-squares solution when fitting the phase difference curve.

[0117] A = (W T W) -1 W T Φ Formula (2)

[0118] Where A = [k, b] T W is a matrix constructed in the frequency domain from the combined data and the frequency values ​​(which can be regarded as ω) of different effective REs of each training sequence, and Φ is the phase difference. (The phase difference between the combined data and the effective RE of each training sequence) is constructed by the matrix of the coefficients of the first-order polynomial model of the frequency ω. The first-order polynomial coefficients k,b of the combined data and each training sequence can be fitted by the above formula (2). The phase difference curve corresponding to the fractional delay difference between channels (e.g., between each other RF channel and the reference RF channel) can be obtained by subtracting the first-order polynomial coefficients k,b of each group.

[0119] After obtaining the phase difference curve, it is transformed into candidate filter coefficients in the time domain, and the effective filter coefficients within the candidate filter coefficients are extracted. A filter is then generated in each RF channel based on the corresponding effective filter coefficients. In this embodiment, the fractional delay is determined based on the phase difference information between each training sequence and the effective RE position of the corresponding combined data, further improving the accuracy of the determined fractional delay difference for each channel.

[0120] In other words, the phase difference curve reflects the fractional delay difference between RF channels. However, the fractional delay difference corresponding to the phase difference curve is in the frequency domain. Therefore, it needs to be converted into a compensation value in the time domain. This can be achieved by using methods such as the inverse operation of the Fast Fourier Transform to transform the phase difference curve into candidate filter coefficients in the time domain. Effective filter coefficients are then extracted. That is, after converting the phase difference curve from the frequency domain to the time domain, the resulting filter coefficients may contain a large number of data points. However, only a portion of these are actually "effective" coefficients used for signal compensation. This is because the fractional delay difference is usually finite, and the influence of filter coefficients exceeding a certain range on the signal is negligible. Therefore, it is necessary to extract this effective portion of the filter coefficients to construct the actual filter. This filter is used to preprocess the data to be transmitted on the corresponding RF channel to compensate for the fractional delay difference between channels. The filter is a linear phase filter that uses a finite number of effective filter coefficients to generate the output, thus accurately introducing the required fractional delay difference compensation without introducing additional phase distortion.

[0121] To facilitate understanding, a specific embodiment is provided below to illustrate a possible implementation process of the delay processing in this disclosure:

[0122] like Figure 5 As shown, after the device containing multiple RF channels is started, the initial delay difference pre-stored in each channel can be read. In this embodiment, the pre-stored calibration coefficients of each channel can be pre-stored, and the initial delay difference can be calculated based on the pre-stored calibration coefficients. The pre-stored calibration coefficients usually refer to values ​​pre-calculated and stored during the device manufacturing or system debugging stage, which are used to compensate for delay deviations caused by hardware imperfections and environmental changes. The preset calibration coefficients can be stored in electrically erasable programmable read-only memory (EEPROM). During the device startup process, these preset calibration coefficients are loaded into the FPGA. For example, if the preset calibration coefficients are used to compensate for phase errors, then in the digital signal processing stage of the corresponding RF channel, these coefficients will be used to rotate the corresponding data, etc.

[0123] Before pre-distortion processing, delay alignment is performed based on the initial delay difference. Therefore, after device startup, the inherent delay difference (initial delay difference) of the channel can be quickly calculated and compensated without requiring write / read sequence operations, ensuring the device quickly enters its optimal operating state.

[0124] Furthermore, the system monitors in real time whether the actual combined power output from the combining feedback port is abnormal. For example, if the power difference between the actual combined power and the reference combined power exceeds a preset power difference threshold within multiple consecutive detection cycles, the actual combined power is determined to be abnormal. In this embodiment, the output power status of the current combining channel is intuitively characterized through real-time monitoring during equipment operation, enabling the calibration of abnormal channels and ensuring the stability of the output performance during equipment operation.

[0125] If an anomaly occurs, integer delay calculation is performed first. The corresponding training sequence is simultaneously written to each RF channel. In this embodiment, a combined data segment is extracted from the combined data, and it is determined whether the combined power of the combined data segment is within a preset power range. If so, the combined data segment is determined to be valid. A training sequence segment at the same time slot position as the combined data segment is identified in each training sequence. Sequence correlation calculation is performed between the combined data segment and each training sequence segment to determine whether the peak-to-average power ratio (PAPR) meets a preset PAPR threshold. If it does, the position of the maximum correlation peak in each training sequence is determined. The integer delay of each training sequence is determined based on the position of the maximum correlation peak, and the integer delay difference of each RF channel is determined based on the integer delay. The integer delay difference can be written to the FPGA to facilitate integer delay difference compensation processing for the data to be transmitted on the RF channels.

[0126] Furthermore, based on the integer delay of each training sequence, the combined data is aligned with the integer delay of each training sequence, and fractional delay calculation is performed based on the aligned data. The combined data of each training sequence aligned with its corresponding integer delay is converted to the frequency domain. In this embodiment, to ensure the validity of the combined data aligned with the integer delay, the amplitude difference between each training sequence and the combined data aligned with its corresponding integer delay in the frequency domain can also be calculated. If the amplitude difference is less than a preset amplitude difference threshold, the phase difference information of each effective resource particle in the frequency domain is calculated. Based on the multiple phase difference information corresponding to multiple RF channels, a phase difference curve corresponding to the fractional delay difference of each RF channel is fitted. The fitting error is determined based on the phase difference curve to see if it is within a preset error range. If it is within the preset error range, the phase difference curve is determined to be reliable. Thus, the phase difference curve is converted into candidate filter coefficients in the time domain, and the effective filter coefficients within the candidate filter coefficients are extracted. The effective filter coefficients are written into the corresponding FPGA to facilitate fractional delay difference compensation processing for the data to be transmitted in the RF channels.

[0127] In summary, the delay processing method of this disclosure can perform delay alignment of multiple channels based on the correlation delay difference between radio frequency channels. Furthermore, it can obtain the fractional delay difference by fitting the phase difference through the effective RE position, thereby improving the delay alignment accuracy of multiple channels and increasing the combined output power.

[0128] To implement the above embodiments, this disclosure also proposes a time delay processing device.

[0129] Figure 6 This is a schematic diagram of a latency processing device provided in an embodiment of the present disclosure. The device can be implemented by software and / or hardware, and is generally integrated into a network device. Figure 6 As shown, the device includes: a first acquisition module 610, a sequence insertion module 620, a second acquisition module 630, a delay calculation module 640, and a delay processing module 650, wherein...

[0130] The first acquisition module 610 is used to acquire multiple pre-generated training sequences corresponding to multiple radio frequency channels, wherein each training sequence does not interfere with the others;

[0131] The sequence insertion module 620 is used to simultaneously insert multiple training sequences into the target time slots of the corresponding radio frequency channels.

[0132] The second acquisition module 630 is used to acquire the combined data corresponding to multiple training sequences in the target time slot at the combined feedback port corresponding to the multiple radio frequency channels;

[0133] The delay calculation module 640 is used to calculate the delay data of the combined data and each training sequence to obtain multiple delay data corresponding to the multi-RF channels;

[0134] The delay processing module 650 is used to perform delay alignment processing on multiple radio frequency channels based on multiple delay data.

[0135] In one embodiment of this disclosure, it further includes: a time delay calibration condition determination module, used for:

[0136] The reference combined power and the actual combined power of the combined feedback port are obtained for each preset monitoring period according to the preset monitoring period. The reference combined power is calculated by summing the transmission power of multiple branch lines corresponding to multiple radio frequency channels.

[0137] Calculate the power difference between the actual combined power and the reference combined power for each preset monitoring cycle;

[0138] The power difference determines whether the multiple radio frequency channels meet the preset delay calibration conditions.

[0139] In one embodiment of this disclosure, the preset time delay calibration condition includes: a preset number of consecutive power differences all exceeding a preset power difference threshold.

[0140] In one embodiment of this disclosure, it further includes: a training sequence generation module, configured to: obtain signal transmission parameters for each radio frequency channel and obtain the number of channels for the multiple radio frequency channels; and generate multiple training sequences corresponding to the multiple radio frequency channels based on the signal transmission parameters and the number of channels.

[0141] In one embodiment of this disclosure, the latency calculation module is specifically used for: extracting a combined data segment from the combined data, determining the start and end positions of the combined data segment in the target time slot; extracting a training sequence segment corresponding to the combined data segment from each training sequence based on the start and end positions; and calculating the latency data between the combined data and each training sequence based on the combined data segment and each training sequence segment.

[0142] In one embodiment of this disclosure, the latency data includes integer latency, and the latency calculation module is specifically used for:

[0143] Cross-correlation calculation is performed between the combined data and each training sequence, and the position of the maximum correlation peak in each training sequence is determined based on the calculation results.

[0144] The integer delay of each training sequence is determined based on the position of the maximum correlation peak.

[0145] In one embodiment of this disclosure, the latency calculation module is specifically used for:

[0146] Calculate the integer delay difference for each radio frequency channel based on the multiple integer delays corresponding to the multiple radio frequency channels;

[0147] Write the corresponding integer delay difference into the shift register for each RF channel.

[0148] In one embodiment of this disclosure, the resource particle positions of the independent training sequences are completely different, and the latency data further includes fractional latency. The latency calculation module is also used for:

[0149] Based on the integer delay of each training sequence, the merged data is aligned with the integer delay of each training sequence respectively;

[0150] Calculate the phase difference information of the effective resource particles of each training sequence after aligning it with the corresponding integer time delay in the combined data;

[0151] The fractional delay of each training sequence is determined based on the phase difference information.

[0152] In one embodiment of this disclosure, the latency calculation module is specifically used for:

[0153] Based on the multiple phase difference information corresponding to the multiple radio frequency channels, fit the phase difference curve corresponding to the fractional delay difference of each radio frequency channel;

[0154] The phase difference curve is transformed into candidate filter coefficients in the time domain, and the effective filter coefficients within the candidate filter coefficients are extracted.

[0155] In each RF channel, a filter is generated based on the corresponding effective filter coefficients.

[0156] In one embodiment of this disclosure, before acquiring a plurality of pre-generated training sequences corresponding to the multiple radio frequency channels, each radio frequency channel is subjected to delay alignment processing based on a pre-set initial delay difference.

[0157] It should be noted that the apparatus provided in this embodiment of the invention can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail here.

[0158] It should be noted that the division of units in the embodiments of this disclosure is illustrative and only represents one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of this disclosure can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units.

[0159] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this disclosure.

[0160] It should be noted that the apparatus provided in this embodiment can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail here.

[0161] This disclosure also proposes a delay processing apparatus. For example... Figure 7 The schematic diagram shown illustrates another delay processing device, which includes a memory 700, a transceiver 710, and a processor 720: the memory 700 stores computer programs; the transceiver 710 transmits and receives data under the control of the processor; and the processor 720 reads the computer program from the memory and performs the following operations:

[0162] Obtain multiple pre-generated training sequences corresponding to multiple radio frequency channels, wherein each training sequence does not interfere with the others;

[0163] Simultaneously, multiple training sequences are inserted into the target time slots of the corresponding radio frequency channels;

[0164] At the multiplexing feedback port corresponding to the multiple radio frequency channels, acquire the combined data corresponding to multiple training sequences in the target time slot;

[0165] Calculate the latency data of the combined data and each training sequence to obtain multiple latency data corresponding to the multi-RF channels;

[0166] Time delay alignment is performed on multiple radio frequency channels based on multiple time delay data.

[0167] Among them, Figure 7In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (represented by a processor) and memory (represented by a memory). The bus architecture can also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides the interface. The transceiver can be multiple components, including transmitters and receivers, providing a unit for communicating with various other devices over transmission media, including wireless channels, wired channels, optical fibers, etc. The processor is responsible for managing the bus architecture and general processing, and the memory 700 can store data used by the processor 720 during operation.

[0168] The processor 720 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor 720 can also adopt a multi-core architecture.

[0169] In one possible implementation of this disclosure, the processor 720 is further configured to perform the following operations:

[0170] The reference combined power and the actual combined power of the combined feedback port are obtained for each preset monitoring period according to the preset monitoring period. The reference combined power is calculated by summing the transmission power of multiple branch lines corresponding to multiple radio frequency channels.

[0171] Calculate the power difference between the actual combined power and the reference combined power for each preset monitoring cycle;

[0172] The power difference determines whether the multiple radio frequency channels meet the preset delay calibration conditions.

[0173] In one possible implementation of this disclosure, preset delay calibration conditions include:

[0174] A preset number of consecutive power differences exceed the preset power difference threshold.

[0175] In one possible implementation of this disclosure, the processor 720 is further configured to perform the following operations:

[0176] Obtain the signal transmission parameters for each RF channel and the number of channels in the multi-RF channel;

[0177] Based on the signal transmission parameters and the number of channels, multiple training sequences corresponding to multiple radio frequency channels are generated.

[0178] In one possible implementation of this disclosure, the processor 720 is further configured to perform the following operations:

[0179] Extract the combined data segment from the combined data and determine the start and end positions of the combined data segment in the target time slot;

[0180] Based on the start and end positions, extract the training sequence segment corresponding to the merged data segment from each training sequence;

[0181] Calculate the latency data between the combined data segment and each training sequence segment.

[0182] In one possible implementation of this disclosure, the latency data includes integer latency, and the processor 720 is further configured to perform the following operations:

[0183] Cross-correlation calculation is performed between the combined data and each training sequence, and the position of the maximum correlation peak in each training sequence is determined based on the calculation results.

[0184] The integer delay of each training sequence is determined based on the position of the maximum correlation peak.

[0185] In one possible implementation of this disclosure, the processor 720 is further configured to perform the following operations:

[0186] Calculate the integer delay difference for each radio frequency channel based on the multiple integer delays corresponding to the multiple radio frequency channels;

[0187] Write the corresponding integer delay difference into the shift register for each RF channel.

[0188] In one possible implementation of this disclosure, the resource particle positions of the independent training sequences are completely different, the latency data also includes fractional latency, and the processor 720 is further used to perform the following operations:

[0189] Based on the integer delay of each training sequence, the merged data is aligned with the integer delay of each training sequence respectively;

[0190] Calculate the phase difference information of the effective resource particles of each training sequence after aligning it with the corresponding integer time delay in the combined data;

[0191] The fractional delay of each training sequence is determined based on the phase difference information.

[0192] In one possible implementation of this disclosure, the processor 720 is further configured to perform the following operations:

[0193] Based on the multiple phase difference information corresponding to the multiple radio frequency channels, fit the phase difference curve corresponding to the fractional delay difference of each radio frequency channel;

[0194] The phase difference curve is transformed into candidate filter coefficients in the time domain, and the effective filter coefficients within the candidate filter coefficients are extracted.

[0195] In each RF channel, a filter is generated based on the corresponding effective filter coefficients.

[0196] In one possible implementation of this disclosure, each radio frequency channel is time-delay aligned according to a pre-set initial time delay difference before acquiring multiple pre-generated training sequences corresponding to multiple radio frequency channels.

[0197] It should be noted that the apparatus provided in this embodiment of the invention can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Therefore, the parts and beneficial effects that are the same as those in the method embodiment will not be described in detail here.

[0198] This disclosure also provides a processor-readable storage medium storing a program for causing the processor to execute the aforementioned power service processing method based on a communication system. The processor-readable storage medium can be any available medium or data storage device accessible to the processor, including but not limited to magnetic storage (e.g., floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (e.g., CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (e.g., ROMs, EPROMs, EEPROMs, non-volatile memory (NAND flash), solid-state drives (SSDs)).

[0199] To implement the above embodiments, this disclosure also proposes a computer program product, including a computer program, wherein the computer program executes the above-described delay processing method when executed by a processor.

[0200] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, apparatus, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0201] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus, and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-executable instructions. These computer-executable instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0202] These processor-executable instructions may also be stored in a processor-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the processor-readable memory produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0203] Obviously, those skilled in the art can make various modifications and variations to this disclosure without departing from its spirit and scope. Therefore, if such modifications and variations fall within the scope of the claims of this disclosure and their equivalents, this disclosure is also intended to include such modifications and variations.

Claims

1. A delay processing method, characterized in that, Includes the following steps: Obtain multiple pre-generated training sequences corresponding to multiple radio frequency channels, wherein each training sequence is independent of the others; Simultaneously, the multiple training sequences are inserted into the target time slots of the corresponding radio frequency channels; At the combining feedback port corresponding to the multiple radio frequency channels, the combined data corresponding to the multiple training sequences in the target time slot is obtained; Calculate the latency data of the combined data and each of the training sequences to obtain multiple latency data corresponding to the multi-RF channels; The multiple radio frequency channels are time-delay aligned based on the multiple time-delay data.

2. The method as described in claim 1, characterized in that, Before the sound acquires multiple pre-generated training sequences corresponding to the multiple radio frequency channels, the process includes: According to the preset monitoring period, the reference combined power and the actual combined power of the combined feedback port are obtained for each preset monitoring period, wherein the reference combined power is calculated by summing the multiple branch transmission powers corresponding to the multi-RF channel; Calculate the power difference between the actual combined power and the reference combined power for each preset monitoring cycle; The power difference determines whether the multi-RF channel meets the preset delay calibration conditions.

3. The method as described in claim 2, characterized in that, The preset delay calibration conditions include: A preset number of consecutive power differences exceed the preset power difference threshold.

4. The method as described in claim 1, characterized in that, Before obtaining the pre-generated multiple training sequences corresponding to the multiple radio frequency channels, the method further includes: Obtain the signal transmission parameters of each of the radio frequency channels, and obtain the number of channels of the multiple radio frequency channels; Based on the signal transmission parameters and the number of channels, the plurality of training sequences corresponding to the plurality of radio frequency channels are generated.

5. The method as described in claim 1, characterized in that, The calculation of the time delay data of the combined data and each of the training sequences includes: Extract a segment of the combined data from the combined data, and determine the start and end positions of the combined data segment in the target time slot; Based on the start and end positions, extract the training sequence segment corresponding to the merged data segment from each training sequence; Based on the combined data segment and each training sequence segment, calculate the latency data between the combined data and each training sequence.

6. The method as described in claim 1, characterized in that, The latency data includes integer latency, and calculating the latency data of the combined data and each training sequence includes: The cross-correlation between the combined data and each training sequence is calculated, and the position of the maximum correlation peak in each training sequence is determined based on the calculation results. The integer delay of each training sequence is determined based on the position of the maximum correlation peak.

7. The method as described in claim 6, characterized in that, The step of performing delay alignment processing on the multiple radio frequency channels based on the multiple delay data includes: Calculate the integer delay difference for each of the multiple radio frequency channels based on the multiple integer delays corresponding to the multiple radio frequency channels; Write the corresponding integer delay difference into the shift register corresponding to each of the radio frequency channels.

8. The method as described in claim 6, characterized in that, The resource particle positions of each of the independent training sequences are completely different, and the latency data also includes fractional latency. The calculation of the combined data and the latency data of each training sequence further includes: Based on the integer delay of each training sequence, the combined data is aligned with the integer delay of each training sequence respectively; Calculate the phase difference information of the effective resource particles of each training sequence and the corresponding integer delay-aligned combined data; The fractional delay of each training sequence is determined based on the phase difference information.

9. The method as described in claim 8, characterized in that, The step of performing delay alignment processing on the multiple radio frequency channels based on the multiple delay data includes: Based on the multiple phase difference information corresponding to the multiple radio frequency channels, a phase difference curve corresponding to the fractional delay difference of each radio frequency channel is fitted; The phase difference curve is transformed into candidate filter coefficients in the time domain, and the effective filter coefficients within the candidate filter coefficients are extracted. A filter is generated in each of the radio frequency channels based on the corresponding effective filter coefficients.

10. The method according to any one of claims 1-9, characterized in that, Before acquiring the pre-generated multiple training sequences corresponding to the multiple radio frequency channels, each radio frequency channel is subjected to delay alignment processing based on a pre-set initial delay difference.

11. A time delay processing device, characterized in that, include: The first acquisition module is used to acquire multiple pre-generated training sequences corresponding to multiple radio frequency channels, wherein each training sequence does not interfere with the others; A sequence insertion module is used to simultaneously insert the multiple training sequences into the target time slots of the corresponding radio frequency channels; The second acquisition module is used to acquire the combined data corresponding to the multiple training sequences in the target time slot at the combined feedback port corresponding to the multiple radio frequency channels; A latency calculation module is used to calculate the latency data of the combined data and each training sequence to obtain multiple latency data corresponding to the multi-RF channels; The delay processing module is used to perform delay alignment processing on the multiple radio frequency channels based on the multiple delay data.

12. A time delay processing device, characterized in that, Includes memory, transceiver, and processor: The memory is used to store computer programs; the transceiver is used to send and receive data under the control of the processor. Processor, configured to read the computer program in the memory and perform the following operations: Obtain multiple pre-generated training sequences corresponding to multiple radio frequency channels, wherein each training sequence is independent of the others; Simultaneously, the multiple training sequences are inserted into the target time slots of the corresponding radio frequency channels; At the combining feedback port corresponding to the multiple radio frequency channels, the combined data corresponding to the multiple training sequences in the target time slot is obtained; Calculate the latency data of the combined data and each of the training sequences to obtain multiple latency data corresponding to the multi-RF channels; The multiple radio frequency channels are time-delay aligned based on the multiple time-delay data.

13. The apparatus as claimed in claim 12, characterized in that, The processor is also used to perform the following operations: The reference combined power and the actual combined power of the combined feedback port are obtained for each preset monitoring period according to the preset monitoring period. The reference combined power is calculated by summing the multiple branch transmission powers corresponding to the multiple radio frequency channels. Calculate the power difference between the actual combined power and the reference combined power for each preset monitoring cycle; The power difference determines whether the multi-RF channel meets the preset delay calibration conditions.

14. The apparatus as claimed in claim 13, characterized in that, The preset delay calibration conditions include: A preset number of consecutive power differences exceed the preset power difference threshold.

15. The apparatus as claimed in claim 12, characterized in that, The processor is also used to perform the following operations: Obtain the signal transmission parameters of each of the radio frequency channels, and obtain the number of channels of the multiple radio frequency channels; Based on the signal transmission parameters and the number of channels, the plurality of training sequences corresponding to the plurality of radio frequency channels are generated.

16. The apparatus as claimed in claim 12, characterized in that, The processor is also used to perform the following operations: Extract a segment of the combined data from the combined data, and determine the start and end positions of the combined data segment in the target time slot; Based on the start and end positions, extract the training sequence segment corresponding to the merged data segment from each training sequence; Based on the combined data segment and each training sequence segment, calculate the latency data between the combined data and each training sequence.

17. The apparatus as claimed in claim 12, characterized in that, The latency data includes integer latency, and the processor is further configured to perform the following operations: The cross-correlation between the combined data and each training sequence is calculated, and the position of the maximum correlation peak in each training sequence is determined based on the calculation results. The integer delay of each training sequence is determined based on the position of the maximum correlation peak.

18. The apparatus as claimed in claim 17, characterized in that, The processor is also used to perform the following operations: Calculate the integer delay difference for each of the multiple radio frequency channels based on the multiple integer delays corresponding to the multiple radio frequency channels; Write the corresponding integer delay difference into the shift register corresponding to each of the radio frequency channels.

19. The apparatus as claimed in claim 17, characterized in that, The resource particle positions of the various training sequences are completely different and do not interfere with each other. The latency data also includes fractional latency. The processor is further configured to perform the following operations: Based on the integer delay of each training sequence, the combined data is aligned with the integer delay of each training sequence respectively; Calculate the phase difference information of the effective resource particles of each training sequence and the corresponding integer delay-aligned combined data; The fractional delay of each training sequence is determined based on the phase difference information.

20. The apparatus as claimed in claim 19, characterized in that, The processor is also used to perform the following operations: Based on the multiple phase difference information corresponding to the multiple radio frequency channels, a phase difference curve corresponding to the fractional delay difference of each radio frequency channel is fitted; The phase difference curve is transformed into candidate filter coefficients in the time domain, and the effective filter coefficients within the candidate filter coefficients are extracted. A filter is generated in each of the radio frequency channels based on the corresponding effective filter coefficients.

21. The apparatus according to any one of claims 12-20, characterized in that, Before acquiring the pre-generated multiple training sequences corresponding to the multiple radio frequency channels, each radio frequency channel is subjected to delay alignment processing based on a pre-set initial delay difference.

22. A processor-readable storage medium, characterized in that, The processor-readable storage medium stores a computer program for executing the delay processing method according to any one of claims 1-10.

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