Baseband task processing method and device, network equipment and storage medium

Abstract

The embodiment of the invention discloses a baseband task processing method and device, network equipment and a storage medium. The method comprises the steps of obtaining a first task; the first task is one of a plurality of tasks included in a baseband processing process; determining a first optimization strategy based on the first task, adjusting system parameters according to the first optimization strategy, and performing integration processing on corresponding sub-tasks in the first task according to the adjusted system parameters to execute the first task, or performing integration processing on the corresponding sub-tasks in the process of executing the first task according to the first optimization strategy. And performing clustering processing on the to-be-processed signal.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a baseband task processing method, device, network equipment and storage medium. Background Art

[0002] Baseband processing is a key link in wireless communication systems. It is responsible for converting digital signals into a form suitable for transmission on wireless channels and processing received signals to restore the original data. This process often involves a large number of complex and computationally intensive tasks. Accelerators can be optimized for these specific tasks and share the computing burden of the main processor, thereby significantly improving the processing speed and efficiency of the entire system. At the same time, accelerators can support parallel processing and multi-task scheduling, improving the overall performance and flexibility of the system.

[0003] At present, accelerators usually adopt a user-by-user processing method, that is, independent baseband processing is performed for each user's data. However, in this processing method, the accelerator will implement strict sequential control on the baseband processing process to ensure that each step of the processing is carried out in a predetermined order. This means that during the processing, a process step must be started after the previous process is completed. Although this sequential processing mechanism ensures the accuracy and consistency of data processing, it also brings limitations to processing efficiency. Summary of the invention

[0004] In order to solve the existing technical problems, the embodiments of the present invention provide a baseband task processing method, apparatus, network equipment and storage medium.

[0005] To achieve the above object, the technical solution of the embodiment of the present invention is implemented as follows:

[0006] An embodiment of the present invention provides a baseband task processing method, the method comprising:

[0007] Obtaining a first task; wherein the first task is one of a plurality of tasks included in a baseband processing process;

[0008] Determine a first optimization strategy based on the first task, adjust system parameters according to the first optimization strategy, integrate corresponding subtasks in the first task according to the adjusted system parameters to execute the first task, or, in the process of executing the first task according to the first optimization strategy, cluster the signals to be processed.

[0009] In the above scheme, the system parameters include at least one of the following: the number of users, the number of antennas, the number of symbols, and the number of physical resource blocks (PRBs).

[0010] In the above scheme, adjusting the system parameters according to the first optimization strategy includes: according to the first optimization strategy, adjusting the number of antennas from N1 to 1, and adjusting the number of PRBs to N1 times the original value, where N1 is a positive integer.

[0011] In the above scheme, the corresponding subtasks in the first task are integrated and processed according to the adjusted system parameters to execute the first task, including: in the process of executing the first task according to the adjusted system parameters, subtasks corresponding to N1 antennas are executed at a time.

[0012] In the above scheme, adjusting the system parameters according to the first optimization strategy includes: configuring the system parameters for multiple users according to the first optimization strategy, and adjusting the number of users corresponding to the multiple users to 1, and adjusting the number of PRBs to N2 times the original value, where N2 is the number of the multiple users.

[0013] In the above scheme, the corresponding subtasks in the first task are integrated according to the adjusted system parameters to execute the first task, including: in the process of executing the first task according to the adjusted system parameters, subtasks corresponding to the multiple users are executed at one time.

[0014] In the above scheme, adjusting the system parameters according to the first optimization strategy includes: according to the first optimization strategy, adjusting the number of symbols from N3 to 1, and adjusting the number of users to N3 times the original value, where N3 is a positive integer.

[0015] In the above scheme, the corresponding subtasks in the first task are integrated and processed according to the adjusted system parameters to execute the first task, including: in the process of executing the first task according to the adjusted system parameters, subtasks corresponding to N3 symbols are executed at a time.

[0016] In the above scheme, adjusting the system parameters according to the first optimization strategy includes: according to the first optimization strategy, adjusting the number of PRBs from N4 to 1, and adjusting the number of users to N4 times the original value, where N4 is a positive integer.

[0017] In the above scheme, the corresponding subtasks in the first task are integrated and processed according to the adjusted system parameters to execute the first task, including: in the process of executing the first task according to the adjusted system parameters, subtasks corresponding to N4 PRBs are executed at a time.

[0018] In the above scheme, the clustering process of the signals to be processed includes: uniformly storing all signals of the same type to be processed within the scope of the first task in a memory, so as to uniformly process the signals to be processed according to the signal type.

[0019] In the above scheme, after executing the first task according to the adjusted system parameters, the method further includes: filling resources in the vacant positions and / or resource-unaligned positions in the resource positions occupied by the signals corresponding to the users.

[0020] The embodiment of the present invention further provides a baseband task processing device, the device comprising: a first processing unit and a second processing unit; wherein:

[0021] The first processing unit is used to obtain a first task; the first task is one of the multiple tasks included in the baseband processing process; and is also used to determine a first optimization strategy based on the first task;

[0022] The second processing unit is used to adjust the system parameters according to the first optimization strategy, and integrate the corresponding subtasks in the first task according to the adjusted system parameters to execute the first task, or, in the process of executing the first task according to the first optimization strategy, cluster the signals to be processed.

[0023] The embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the baseband task processing method described in the embodiment of the present invention are implemented.

[0024] An embodiment of the present invention further provides a network device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the baseband task processing method described in the embodiment of the present invention are implemented.

[0025] An embodiment of the present invention further provides a computer program product, including computer program instructions, which enable a computer to execute the steps of the baseband task processing method described in the embodiment of the present invention.

[0026] The baseband task processing method, device, network device and storage medium provided by the embodiment of the present invention include: obtaining a first task; the first task is one of the multiple tasks included in the baseband processing process; determining a first optimization strategy based on the first task, adjusting the system parameters according to the first optimization strategy, integrating the corresponding subtasks in the first task according to the adjusted system parameters to execute the first task, or clustering the signals to be processed during the execution of the first task according to the first optimization strategy. The technical solution of the embodiment of the present invention is adopted to set different optimization strategies for different tasks, and different optimization strategies can correspond to different system parameters. The network device adjusts the system parameters according to the first optimization strategy, so as to execute the first task according to the adjusted system parameters, specifically, the subtasks in the first task are merged according to the adjusted system parameters, that is, one call or execution can complete the work that originally required multiple calls or executions, thereby realizing the refined control of the processing flow; or clustering the signals to be processed according to the first optimization strategy, thereby realizing the unified and efficient optimization of the same type of signals, thereby reducing the additional burden caused by signal type switching. The baseband processing flow is flexibly adjusted according to the usage of computing resources and storage resources, breaking the original pipeline operation between modules, making full use of computing resources and storage resources, and improving processing efficiency and flexibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 Schematic diagram of the task scheduling mechanism for baseband processing;

[0028] Figure 2 A schematic diagram of a flow chart of a baseband task processing method according to an embodiment of the present invention;

[0029] Figure 3 A schematic diagram of scheduling of multi-dimensional conversion in a baseband task processing method according to an embodiment of the present invention;

[0030] Figure 4 A schematic diagram of resource optimization in a baseband task processing method according to an embodiment of the present invention;

[0031] Figure 5 A schematic diagram of the structure of a baseband task processing device according to an embodiment of the present invention;

[0032] Figure 6 The figure is a schematic diagram of the hardware structure of the network device according to the embodiment of the present invention. DETAILED DESCRIPTION

[0033] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] The technical solution of the embodiment of the present invention can be applied to various communication systems, for example: a global system of mobile communication (GSM) system, a long term evolution (LTE) system or a 5G system, etc. Optionally, the 5G system or 5G network may also be referred to as a new radio (NR) system or NR network.

[0035] Exemplarily, the communication system applied in the embodiment of the present invention may include a network device and a terminal device (also referred to as a terminal, a communication terminal, etc.); the network device may be a device that communicates with the terminal device. Among them, the network device can provide communication coverage within a certain area, and can communicate with terminals located in the area. Optionally, the network device may be a base station in each communication system, such as an evolved base station (eNB, Evolutional Node B) in an LTE system, and a base station (gNB) in a 5G system or an NR system.

[0036] It should be understood that the device with communication function in the network / system in the embodiment of the present application can be referred to as a communication device. The communication device may include a network device and a terminal with communication function, and the network device and the terminal device may be the specific devices described above, which will not be repeated here; the communication device may also include other devices in the communication system, such as a network controller, a mobile management entity and other network entities, which are not limited in the embodiment of the present invention.

[0037] It should be understood that the terms "system" and "network" are often used interchangeably in this article. The term "and / or" in this article is only a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0038] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable in appropriate circumstances, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, the process, method, system, product or equipment comprising a series of steps or units need not be limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0039] Before elaborating on the technical solution of the embodiment of the present invention in detail, a brief description of baseband processing is first given.

[0040] During the data transmission process, the baseband data to be processed is transferred from the main processor or other storage device to the accelerator through direct memory access (DMA) or other efficient data transmission mechanisms to reduce the impact of data transmission on the performance of the main processor. After processing the data, the accelerator transmits the processing results back to the main processor or storage device for subsequent processing or storage. When receiving a task, the accelerator processes the data according to the preset algorithm and parameters.

[0041] At present, when the accelerator processes the entire link of the baseband, it will strictly process it in sequence according to the functional division of the subtasks. These steps are relatively independent in the entire link. In the specific functional module, the processing task is subdivided into two parts: the arithmetic operation unit and the matrix operation unit. The arithmetic operation unit is usually simpler and more direct, suitable for processing data that does not require complex calculations, and the matrix operation unit can use the parallelism and correlation of the data to accelerate the processing process through efficient matrix operations. In processing the arithmetic operation unit, the communication tasks of different users are currently separated by user, allowing the system to provide services to multiple users at the same time, and each user has its own independent processing resources (such as processor cores, memory, etc.). The system can dynamically allocate resources according to the needs and priorities of different users, thereby improving processing efficiency and system throughput. Figure 1 This is a diagram of the task scheduling mechanism for baseband processing, such as Figure 1 As shown, Task 1, Task 2 and Task 3 are three consecutive processing units, Task x.1, Task x.2 and Task x.3 (x=1, 2, 3) represent three users respectively, and Mode 1 is to process the users sequentially under the consecutive processing units, that is, first process the subtasks of the three users for Task 1, and after the processing is completed, process the subtasks of the three users for Task 2, and finally process the subtasks of the three users for Task 3. In Mode 2, all the functional modules of User 1 are completed first and then User 2 is processed, that is, first execute the subtasks of Task 1, Task 2 and Task 3 for User 1, then execute the subtasks of Task 1, Task 2 and Task 3 for User 2, and finally execute the subtasks of Task 1, Task 2 and Task 3 for User 3.

[0042] In this processing mode, the accelerator will implement strict sequential control on the baseband processing flow to ensure that each step of the processing is carried out in a predetermined order. This means that during the processing, a process step must be started after the previous process is completed. Although this sequential processing mechanism ensures the accuracy and consistency of data processing, it also brings limitations on processing efficiency.

[0043] Specifically, when the accelerator is processing multi-user data, the processor will fall into a large number of loop statements, repeatedly executing the same functional modules to process each user's resources one by one. This processing method will significantly increase the processing time when resources are limited, especially when processing a large amount of user data.

[0044] In addition, since the processing of each user data is independent of each other, the processor cannot effectively use parallel processing technology to improve efficiency. Even in a multi-core processor architecture, this strict sequential processing mode limits the full performance of the processor. Therefore, this processing method not only affects the processing speed of a single user data, but also reduces the throughput of the entire system, thereby affecting the overall processing efficiency.

[0045] At least based on this, the following embodiments of the present invention are proposed.

[0046] An embodiment of the present invention provides a baseband task processing method. Figure 2 Schematic diagram of the flow of the baseband task processing method according to an embodiment of the present invention; Figure 2 As shown, the method includes:

[0047] Step 101: Obtain a first task; the first task is one of multiple tasks included in the baseband processing process;

[0048] Step 102: Determine a first optimization strategy based on the first task, adjust system parameters according to the first optimization strategy, integrate corresponding subtasks in the first task according to the adjusted system parameters to execute the first task, or, in the process of executing the first task according to the first optimization strategy, cluster the signals to be processed.

[0049] The baseband task processing method of this embodiment is applied to a network device, and the network device may specifically be an access network device, such as a base station.

[0050] The first task in this embodiment refers to a task in a series of processes of baseband processing or baseband signal processing. Exemplarily, in the process of baseband processing or baseband signal processing, it may include: sampling, quantization, channel coding, modulation, demodulation, channel estimation, equalization, descrambling, decoding and other steps, and the above steps are related. For example, the digital signal from the radio frequency unit is encoded, modulated, decoded and other operations are performed to restore the original communication information. Then the first task may refer to the processing task in any of the above steps.

[0051] In this embodiment, the network device performs fine-scale task splitting, and refines a series of baseband processing tasks into a series of independently operable and interrelated tasks (such as the first task); and sets different optimization strategies for different tasks, adjusts the system parameters in the task execution process according to the optimization strategy corresponding to the task (the first optimization strategy), and executes the subtasks within the scope of each first task according to the adjusted system parameters, for example, Figure 1 In the process of executing the first task according to the optimization strategy (first optimization strategy) corresponding to the task, clustering processing is performed on the signal to be processed.

[0052] It can be understood that the embodiment of the present invention sets corresponding optimization strategies for different tasks, and the optimization strategies may include two processing methods: one is to adjust the system parameters, and integrate the subtasks corresponding to the first task according to the adjusted system parameters, that is, a single call can complete the work that originally required multiple calls; the other is to cluster the signals. For example, for data signals and reference signals, a sequential processing mode is usually adopted according to the distribution of resources, while in this embodiment, the same type of signals can be processed on a continuous memory distribution, for example, clustering processing is performed on data signals that occupy more resources.

[0053] Among them, subtasks are tasks for different dimensions divided according to system parameters within the task scope. Optionally, the system parameters include at least one of the following: the number of users, the number of antennas, the number of symbols, and the number of physical resource blocks (PRB, Physical Resource Block). Among them, the number of symbols may specifically refer to the number of orthogonal frequency division multiplexing (OFDM, Orthogonal Frequency Division Multiplexing) symbols. Taking the number of users as an example, within the scope of the first task, each user may correspond to one or more subtasks. Taking the number of antennas as an example, within the scope of the first task, each antenna may correspond to one or more subtasks. In this embodiment, the network device achieves refined control of the baseband processing flow by adjusting the system parameters.

[0054] In this embodiment, for the first processing method:

[0055] The processing dimensions of the network device may include: user, antenna, symbol (OFDM symbol), PRB, etc., as shown in Figure 3 before conversion (left figure).

[0056] User: refers to the terminal device that uses services (such as 5G services), such as smartphones, tablets, etc. Each user corresponds to a unique identifier in the network, which is used for network management and service provision.

[0057] Antenna: Both base stations and user equipment are equipped with antennas for sending and receiving wireless signals. For example, 5G networks support massive multiple input multiple output (MIMO) technology, which means that base stations can use multiple antennas to serve multiple users at the same time, improving data transmission rates and network capacity.

[0058] OFDM Symbol: OFDM is a modulation technology used in 5G, which divides the broadband channel into multiple subcarriers, and transmits data independently on each subcarrier. OFDM symbol is the basic time unit of OFDM transmission.

[0059] PRB: It is the basic spectrum unit used for data transmission in OFDM system. PRB consists of a certain number of subcarriers and is the basic unit of data transmission resources allocated to users or services.

[0060] In the traditional baseband task processing process, the processing of each user's data is independent of each other. When the processor processes multi-user data, it needs to repeatedly execute the same functional module in order to process the data of each user one by one.

[0061] The technical solution of this embodiment sets different optimization strategies for different tasks, and different optimization strategies may correspond to different system parameters. The network device adjusts the system parameters according to the first optimization strategy, thereby executing the first task according to the adjusted system parameters. Specifically, the subtasks in the first task are merged and processed according to the adjusted system parameters, that is, a single call or execution can complete the work that originally required multiple calls or executions, realizing the transformation of the original serial execution tasks to efficient parallel processing, and realizing refined control of the processing flow. The baseband processing flow is flexibly adjusted according to the usage of computing resources and storage resources, breaking the original pipeline operation between modules, making full use of computing resources and storage resources, effectively improving the system processing efficiency and flexibility, and providing solid technical support for the efficient and stable operation of 5G / NR networks.

[0062] In the embodiment of the present invention, the network device performs conversion based on processing dimensions such as user, antenna, symbol (OFDM symbol), PRB, etc., so as to merge the corresponding subtasks in the first task. The specific dimension conversion methods include the following:

[0063] As a first implementation manner, adjusting the system parameters according to the first optimization strategy includes: according to the first optimization strategy, adjusting the number of antennas from N1 to 1, and adjusting the number of PRBs to N1 times the original value, where N1 is a positive integer.

[0064] Correspondingly, the corresponding subtasks in the first task are integrated and processed according to the adjusted system parameters to execute the first task, including: in the process of executing the first task according to the adjusted system parameters, subtasks corresponding to N1 antennas are executed at a time.

[0065] The conversion method of this embodiment can be called converting multi-antenna multi-PRB processing into single-antenna multi-PRB processing.

[0066] A multi-antenna system is a system that equips both the transmitter and receiver of wireless communication with multiple antennas. By flexibly adjusting the spatial resources between multiple antennas, the reliability and transmission rate of the signal are improved. In the traditional baseband processing process, loop statements (such as for loops or while loops) are usually used to traverse all antennas and execute the same functional modules for users under each antenna. These functional modules may include key steps such as channel estimation, precoding / decoding, power allocation, modulation and demodulation, which together constitute the core process of baseband processing. However, as the number of antennas increases, this traditional processing method may face problems such as a sharp increase in computational complexity, excessive consumption of processor resources, and increased processing delays.

[0067] This embodiment proposes a single logic flow parallel multi-antenna processing architecture, which simplifies the complex multi-antenna scenario into a single antenna processing logic framework. When determining the system parameters, the first optimization strategy is determined according to the first task, and the system parameters are adjusted according to the first optimization strategy: the number of antennas is adjusted from the original N1 to 1, and the allocation of physical resource blocks (PRBs) is adjusted accordingly, and the number of PRBs is increased to N1 times the original number. For example, see Figure 3 In the converted method 1, tasks 1, 2, and 3, which originally required three antennas to be implemented, are adjusted to executing tasks 1, 2, and 3 at one time (considering the number of antennas to be 1 and 3 times the number of PRBs). This adjustment actually logically integrates the tasks of multiple antennas into a single processing flow, and completes tasks that originally required multiple iterations through a single processing. This method not only reduces the number of loop traversals and the processor call overhead, but also improves processing efficiency, providing a more flexible and efficient solution for the practical application of MIMO systems.

[0068] Exemplarily, during the second filtering based on the minimum mean square error (MMSE), the filter coefficient is calculated based on the signal-to-noise ratio (SNR) value estimated after the first filtering, and the channel coefficient value after channel estimation and the filter coefficient value are multiplied to obtain the second filtering result. The SNR value of each user is different during the process, so it is necessary to configure according to the actual number of users. The matrix operation module of the network device can process the filtering process of two antennas at a time. Assuming that the number of users is 1 and the original antenna parameters are configured as 4, the number of antennas is adjusted to 1, and the number of PRBs is configured to four times the original number, so as to complete the processing task of multiple antennas at a time. In this example, the first task can be the second filtering task based on MMSE.

[0069] As a second implementation manner, adjusting the system parameters according to the first optimization strategy includes: configuring the system parameters for multiple users according to the first optimization strategy, adjusting the number of users corresponding to the multiple users to 1, and adjusting the number of PRBs to N2 times the original value, where N2 is the number of the multiple users.

[0070] Correspondingly, the corresponding subtasks in the first task are integrated and processed according to the adjusted system parameters to execute the first task, including: in the process of executing the first task according to the adjusted system parameters, subtasks corresponding to the multiple users are executed at one time.

[0071] The conversion method of this embodiment can be called multi-user multi-PRB conversion to single-user multi-PRB processing.

[0072] Multi-user processing refers to the need for the baseband processing unit of a network device to simultaneously process baseband signals from multiple users (or terminals). In traditional multi-user processing, the system often follows a linear, serialized processing logic, that is, a set of parameters is independently assigned to each user, and the same functional modules are executed one by one in a loop. Although this processing method is intuitive and easy to implement, its processing efficiency will decrease significantly as the number of users increases, because the system needs to frequently switch contexts between different users and repeat the same calculation process.

[0073] In this embodiment, instead of allocating a set of system parameters to each user, system parameters are configured for multiple users, and the number of users in the system parameters corresponding to the multiple users is adjusted from N2 to 1, that is, the concept of N2 users is abstracted and integrated into a single user, thereby achieving a leap-forward improvement in processing logic. Specifically, in the parameter configuration stage, the user number parameter is set to 1, indicating that multiple users are regarded as a unified, enhanced "super user." At the same time, in order to accommodate the resource requirements originally dispersed among the users, the number of physical resource blocks (PRBs) is adjusted to N2 times the original number, to ensure that the system can serve all the requirements of the original N2 users at the same time within one processing cycle with higher resource utilization and parallelism. For example, refer to Figure 3 In the converted method 2, the tasks 1, 2 and 3 originally corresponding to the two users are adjusted to execute tasks 1, 2 and 3 at one time (the number of users is regarded as 1 and 2 times the number of PRBs).

[0074] This transformation not only simplifies the complexity of the system, but also greatly improves the execution efficiency of functional modules. In a single processing cycle, the system can seamlessly and in parallel process tasks that originally required multiple iterations to complete, reducing the overhead of context switching and shortening the overall processing time. In addition, due to the centralized management and efficient use of resources, the system can also better deal with the problem of uneven resource allocation, further improving the user experience and the overall performance of the system.

[0075] For example, with respect to the descrambling process (descrambling is the inverse process of scrambling, which refers to the process of restoring a scrambled or encrypted signal to its original form, and requires the receiving end to use a pseudo-random sequence to implement it), in a complex multi-user communication system, the traditional method requires that a descrambling sequence be configured separately for each user, and the descrambling task of each user is processed serially, which results in a longer processing cycle and inefficient use of system resources.

[0076] In order to overcome this limitation, this embodiment proposes the concept of "super user", that is, to configure system parameters for multiple users and convert multiple users into a single user. This "super user" can accommodate the resource requirements originally distributed among the users, and configure the number of physical resource blocks (PRBs) to be N2 times the original. By configuring a descrambling sequence for this "super user", it is possible to process the scrambling and descrambling tasks of multiple users that originally required N2 cycles to complete at one time. This method has significant advantages in improving system processing efficiency and simplifying system structure. In this example, the first task can be a descrambling task.

[0077] As a third implementation, adjusting the system parameters according to the first optimization strategy includes: according to the first optimization strategy, adjusting the number of symbols from N3 to 1, and adjusting the number of users to N3 times the original value, where N3 is a positive integer.

[0078] Correspondingly, the corresponding subtasks in the first task are integrated and processed according to the adjusted system parameters to execute the first task, including: in the process of executing the first task according to the adjusted system parameters, subtasks corresponding to N3 symbols are executed at a time.

[0079] The conversion method of this embodiment can be called multi-symbol multi-user conversion from single-symbol multi-user.

[0080] In the process of multi-symbol multi-user processing, the traditional solution completes the same functional module processing by looping multiple symbols, that is, looping processing symbol by symbol.

[0081] This embodiment logically integrates multiple symbols into a single processing process, and the corresponding number of users is doubled, thereby achieving simultaneous processing of multiple users and symbols. Figure 3 In the converted method 3, it is assumed that the tasks 1, 2 and 3 originally corresponding to the two symbols are adjusted to execute tasks 1, 2 and 3 at one time (the number of symbols is regarded as 1 and 2 times the number of users).

[0082] Exemplarily, in the channel estimation process of Physical Uplink Control Channel (PUCCH) format 3, the user's demodulation reference signal (DMRS) symbol and the local DMRS sequence are multiplied. The number of DMRS symbols per time slot in format 3 is 2, so two multiplications are required to complete the channel estimation process. This embodiment processes multiple DMRS symbols as a single DMRS symbol, that is, the number of symbols is adjusted from 2 to 1, and the corresponding number of users is adjusted to twice the original, so as to complete the channel estimation process of PUCCH format 3 in a single time. In this example, the first task can be the channel estimation task of PUCCH format 3.

[0083] As a fourth implementation, adjusting the system parameters according to the first optimization strategy includes: according to the first optimization strategy, adjusting the number of PRBs from N4 to 1, and adjusting the number of users to N4 times the original value, where N4 is a positive integer.

[0084] Correspondingly, the corresponding subtasks in the first task are integrated and processed according to the adjusted system parameters to execute the first task, including: in the process of executing the first task according to the adjusted system parameters, subtasks corresponding to N4 PRBs are executed at a time.

[0085] The conversion method of this embodiment may be referred to as converting multi-user multi-PRBs into multi-user single PRBs.

[0086] Multi-user multi-PRB processing refers to the situation in which network equipment (such as baseband processing units (BBUs)) in wireless communication systems need to process requests from multiple users at the same time and allocate resources on multiple PRBs to meet these requests. This requires the system to have efficient resource scheduling and allocation capabilities to ensure that multiple users can share wireless resources fairly and efficiently. In traditional multi-user multi-PRB processing, the system usually performs cyclic processing according to the PRB dimension, that is, processing all user requests one by one according to each PRB. This method may cause significant processing delays and reduced efficiency when processing a large number of users and PRBs.

[0087] In this embodiment, the network device converts the dimension of the PRB into the user dimension, and sets the number of PRBs to 1 during parameter configuration, while doubling the number of users. The "doubling of the number of users" here refers to merging user requests originally allocated to multiple PRBs into a single "virtual PRB" for processing, rather than actually increasing the number of physical users, thereby avoiding repeated processing and inefficient cycles in traditional methods.

[0088] Specifically, when configuring system parameters, the number of PRBs is set to 1, and user requests are mapped to corresponding "virtual users" according to user identifiers (IDs). These "virtual users" actually represent user requests that would originally be allocated to different PRBs. For example, the original number of users is 2, and the number of PRBs is N; using the technical solution of this embodiment, the number of PRBs is set to 1, and the number of users is set to 2N, then the 2N users can be regarded as "virtual users", and the mapping relationship between actual users and "virtual users" can be established through the mapping relationship of user IDs. In addition, since the number of PRBs is not actually changed, a mapping relationship between actual PRBs and "virtual users" can be established, and / or a mapping relationship between actual PRBs and actual users can be established. For example, refer to Figure 3 In the method 3 after conversion, it is assumed that the tasks 1, 2 and 3 corresponding to the original two PRBs are adjusted to execute tasks 1, 2 and 3 at one time (the number of PRBs is regarded as 1 and 2 times the number of users).

[0089] Exemplarily, in the SNR calculation process of PUCCH format 3, the average power of channel estimation and the average power of noise are calculated. The SNR is obtained by multiplying the inverse of the noise by the reference signal receiving power (RSRP). Assuming that the number of symbols for each antenna corresponding to each user is 2, the number of symbols is configured to be 2, the PRB is configured to be 1, and the number of users is configured to be: the number of users * the number of RBs for a single user. The power calculation of all users of a single antenna can be realized by calling the matrix operation module once, and then the SNR takes the corresponding power value according to the user arrangement.

[0090] In some optional embodiments of the present invention, after performing the first task according to the adjusted system parameters, the method further comprises: filling resources in the vacant positions and / or resource misaligned positions in the resource positions occupied by the signals corresponding to each user.

[0091] In 5G or NR communication systems, resource alignment usually ensures the orderly allocation and scheduling of different signals on time and frequency resources. The purpose of this orderly allocation is to improve the overall network resource utilization efficiency and improve the system processing efficiency.

[0092] In order to achieve this goal, in this embodiment, in certain specific signal processing or scheduling scenarios, for example, in the process of executing the first task according to the adjusted system parameters and integrating the corresponding subtasks in the first task, some resource positions of the PRB may be vacant or misaligned; in this case, the vacant positions are filled with resources to achieve specific resource configuration or optimization. This resource filling method can flexibly configure and adjust specific resource blocks without interfering with other resource blocks. Exemplarily, 0s can be filled in the vacant positions of the PRB for resource filling, or 0s can be filled in the high position (or head) or low position (or tail) of the PRB for resource alignment when the resources are not aligned. This method can flexibly configure and adjust specific resource blocks without interfering with other resource blocks.

[0093] Exemplarily, resource demapping is the process of mapping the received signal from its position on the resource grid back to the original data stream or channel. Taking the first task of resource demapping as an example, in the process of performing the first task using the technical solution of the embodiment of the present invention, the frequency domain data of all users received are first arranged. Since each user occupies different PRBs, the frequency domain resources that are less than 4 PRBs after arrangement are padded with zeros until 4 PRBs are occupied, and then the resources are uniformly mapped according to 4 PRBs, without distinguishing the number of resources occupied by each specific user, and the resource demapping process of all users is completed in a single time, which improves the processing efficiency compared with the traditional solution that loops according to the number of users.

[0094] Based on this, the technical solution of this embodiment can be used to further integrate network resources and ensure the orderly arrangement and allocation of different resource blocks. This not only avoids the dislocation and confusion of the time and frequency domains when resources are integrated, but also ensures unified processing when there are differences in quantity, and improves the flexibility and efficiency of resource use.

[0095] In this embodiment, for the second processing method:

[0096] The first task may be a processing task for multiple signal types (or symbol types), such as data signals (or symbols occupied by data) and reference signals (or symbols occupied by reference signals). The reference signal is a known signal provided by the transmitter to the receiver for channel estimation or channel detection, which can help the base station understand the channel conditions between the terminal and the base station; the data signal is a signal used to transmit actual information in the communication system, and is used to carry data that needs to be exchanged, such as text, voice, video, etc. The resource distribution of different types of signals has different positions according to different tasks (or task modules).

[0097] When processing different types of signals, traditional processing solutions store the signals in memory according to the resources corresponding to the signals. This is often limited by the physical distribution of resources, and a sequential processing mode is adopted according to the resource distribution, which increases the complexity and time consumption of the processing flow. To address this problem, the embodiment of the present invention proposes a clustering processing strategy, the core idea of ​​which is to break the constraints of traditional resource locations and perform logical rearrangement and integration according to signal types.

[0098] In some optional embodiments, the clustering of the signals to be processed includes: uniformly storing all signals of the same type that need to be processed within the scope of the first task in a memory, so as to uniformly process the signals to be processed according to the signal type.

[0099] Specifically, taking the case where the signal includes a data signal and a reference signal, according to the traditional processing scheme, each type of signal is stored in the memory according to the corresponding resources, that is, the reference signal may be interspersed in the data signal. However, by adopting the technical solution of this embodiment, the reference signal originally interspersed in the data signal is post-processed or pre-processed in the memory, so that the same type of signal (such as a digital signal) can be centrally processed in a continuous memory. Through this adjustment, not only the processing flow is simplified, the additional burden caused by signal type switching is reduced, but also the idleness and waste of resources caused by segmented processing are reduced.

[0100] Figure 4 Schematic diagram of resource optimization in the baseband task processing method according to an embodiment of the present invention; Figure 4 As shown in the figure, taking the first task as channel equalization as an example, the data signal needs to be processed during the channel equalization process. Since the resource memory location of the reference signal (such as DMRS) is interspersed in the middle of the data signal, the traditional solution needs to be processed separately, and multiple stages such as module 1 (data signal), module 2 (reference signal), and module 3 (data signal) are processed in sequence. Among them, the above modules can be called subtasks in the first task.

[0101] The clustering processing strategy proposed in the embodiment of the present invention is used to merge subtasks and place the estimated value of the data signal obtained after channel estimation in a continuous memory location. Therefore, the equalization process can read the data signal continuously, process all data signals at one time (module 1 + module 3), and process the reference signal after the data signal processing is completed. This processing method not only improves the processing efficiency, but also reduces the idleness and waste of resources caused by segmented processing, further improving the overall performance and user experience of the communication system.

[0102] Based on the above embodiments, an embodiment of the present invention further provides a baseband task processing device, which is applied to a network device. Figure 5 Schematic diagram of the structure of the baseband task processing device according to an embodiment of the present invention; Figure 5 As shown, the device comprises: a first processing unit 21 and a second processing unit 22; wherein,

[0103] The first processing unit 21 is used to obtain a first task; the first task is one of the multiple tasks included in the baseband processing process; and is also used to determine a first optimization strategy based on the first task;

[0104] The second processing unit 22 is used to adjust the system parameters according to the first optimization strategy, and integrate the corresponding subtasks in the first task according to the adjusted system parameters to execute the first task, or, in the process of executing the first task according to the first optimization strategy, cluster the signals to be processed.

[0105] In some optional embodiments of the present invention, the system parameters include at least one of the following: the number of users, the number of antennas, the number of symbols, and the number of physical resource blocks (PRBs).

[0106] In some optional embodiments of the present invention, the second processing unit 22 is used to adjust the number of antennas from N1 to 1 and the number of PRBs to N1 times the original value according to the first optimization strategy, where N1 is a positive integer.

[0107] In some optional embodiments of the present invention, the second processing unit 22 is configured to execute subtasks corresponding to N1 antennas at a time during the process of executing the first task according to the adjusted system parameters.

[0108] In some optional embodiments of the present invention, the second processing unit 22 is used to configure system parameters for multiple users according to the first optimization strategy, adjust the number of users corresponding to the multiple users to 1, and adjust the number of PRBs to N2 times the original value, where N2 is the number of the multiple users.

[0109] In some optional embodiments of the present invention, the second processing unit 22 is configured to execute subtasks corresponding to the multiple users at one time during the process of executing the first task according to the adjusted system parameters.

[0110] In some optional embodiments of the present invention, the second processing unit 22 is used to adjust the number of symbols from N3 to 1 and the number of users to N3 times the original value according to the first optimization strategy, where N3 is a positive integer.

[0111] In some optional embodiments of the present invention, the second processing unit 22 is configured to execute subtasks corresponding to N3 symbols at a time during the process of executing the first task according to the adjusted system parameters.

[0112] In some optional embodiments of the present invention, the second processing unit 22 is used to adjust the number of PRBs from N4 to 1 and the number of users to N4 times the original value according to the first optimization strategy, where N4 is a positive integer.

[0113] In some optional embodiments of the present invention, the second processing unit 22 is configured to execute subtasks corresponding to N4 PRBs at a time during the process of executing the first task according to the adjusted system parameters.

[0114] In some optional embodiments of the present invention, the second processing unit 22 is used to uniformly store in memory all signals of the same type that need to be processed within the scope of the first task module, so as to uniformly process the signals to be processed according to the signal type.

[0115] In some optional embodiments of the present invention, the second processing unit 22 is further configured to fill resources in vacant positions and / or resource-unaligned positions in resource positions occupied by signals corresponding to each user.

[0116] In the embodiment of the present invention, the first processing unit 21 and the second processing unit 22 in the device can be implemented by a central processing unit (CPU), a digital signal processor (DSP), a microcontroller unit (MCU) or a field-programmable gate array (FPGA) in the terminal in actual applications.

[0117] It should be noted that: the baseband task processing device provided in the above embodiment only uses the division of the above program modules as an example when performing baseband task processing. In actual applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device is divided into different program modules to complete all or part of the processing described above. In addition, the baseband task processing device provided in the above embodiment and the baseband task processing method embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0118] The embodiment of the present invention also provides a network device. Figure 6 FIG. 1 is a schematic diagram of the hardware structure of the network device according to an embodiment of the present invention. Figure 6 As shown, the network device includes a memory 32, a processor 31, and a computer program stored in the memory 32 and executable on the processor 31. When the processor 31 executes the program, the steps of the baseband task processing method of the embodiment of the present invention are implemented.

[0119] Optionally, the network device may further include at least one network interface 33. The various components in the network device are coupled together via a bus system 34. It is understood that the bus system 34 is used to achieve connection and communication between these components. In addition to the data bus, the bus system 34 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Figure 6 Various buses are labeled as bus system 34 .

[0120] It can be understood that the memory 32 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disk, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), and direct RAM bus random access memory (DRRAM, Direct Rambus Random Access Memory).The memory 32 described in the embodiments of the present invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0121] The method disclosed in the above embodiment of the present invention can be applied to the processor 31, or implemented by the processor 31. The processor 31 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 31 or the instruction in the form of software. The above processor 31 can be a general-purpose processor, a DSP, or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 31 can implement or execute the methods, steps and logic block diagrams disclosed in the embodiment of the present invention. The general-purpose processor can be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present invention, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in the memory 32. The processor 31 reads the information in the memory 32 and completes the steps of the above method in combination with its hardware.

[0122] In an exemplary embodiment, the network device may be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD), FPGA, general purpose processor, controller, MCU, microprocessor, or other electronic components to execute the aforementioned method.

[0123] In an exemplary embodiment, the present invention also provides a computer-readable storage medium, such as a memory 32 including a computer program, and the computer program can be executed by a processor 31 of a network device to complete the steps of the aforementioned method. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disk, or CD-ROM; or it can be various devices including one or any combination of the above memories.

[0124] The computer-readable storage medium provided by the embodiment of the present invention stores a computer program, which, when executed by a processor, implements the steps of the baseband task processing method of the embodiment of the present invention.

[0125] The embodiment of the present application also provides a computer program product, including a computer program, which can be executed by a network device (such as the processor 31 of the network device) to complete the steps of any of the aforementioned baseband task processing methods.

[0126] The methods disclosed in several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0127] The features disclosed in several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0128] The features disclosed in several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

[0129] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0130] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0131] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0132] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium, which, when executed, executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, disks or optical disks.

[0133] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0134] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A baseband task processing method, characterized in that: The method comprises: Obtaining a first task; the first task being one of the multiple tasks included in the baseband processing process; Determine a first optimization strategy based on the first task, adjust system parameters according to the first optimization strategy, integrate corresponding subtasks in the first task according to the adjusted system parameters to execute the first task, or, in the process of executing the first task according to the first optimization strategy, cluster the signals to be processed.

2. The method according to claim 1, characterized in that The system parameters include at least one of the following: the number of users, the number of antennas, the number of symbols, and the number of physical resource blocks (PRBs).

3. The method according to claim 1 or 2, characterized in that: The adjusting the system parameters according to the first optimization strategy includes: According to the first optimization strategy, the number of antennas is adjusted from N1 to 1, and the number of PRBs is adjusted to N1 times the original value, where N1 is a positive integer.

4. The method according to claim 3, characterized in that The step of integrating corresponding subtasks in the first task according to the adjusted system parameters to execute the first task includes: In the process of executing the first task according to the adjusted system parameters, subtasks corresponding to N1 antennas are executed at a time.

5. The method according to claim 1 or 2, characterized in that: The adjusting the system parameters according to the first optimization strategy includes: According to the first optimization strategy, system parameters are configured for multiple users, the number of users corresponding to the multiple users is adjusted to 1, and the number of PRBs is adjusted to N2 times the original value, where N2 is the number of the multiple users.

6. The method according to claim 5, characterized in that The step of integrating corresponding subtasks in the first task according to the adjusted system parameters to execute the first task includes: In the process of executing the first task according to the adjusted system parameters, subtasks corresponding to the multiple users are executed at one time.

7. The method according to claim 1 or 2, characterized in that: The adjusting the system parameters according to the first optimization strategy includes: According to the first optimization strategy, the number of symbols is adjusted from N3 to 1, and the number of users is adjusted to N3 times the original value, where N3 is a positive integer.

8. The method according to claim 7, characterized in that The step of integrating corresponding subtasks in the first task according to the adjusted system parameters to execute the first task includes: In the process of executing the first task according to the adjusted system parameters, subtasks corresponding to N3 symbols are executed at a time.

9. The method according to claim 1 or 2, characterized in that: The adjusting the system parameters according to the first optimization strategy includes: According to the first optimization strategy, the number of PRBs is adjusted from N4 to 1, and the number of users is adjusted to N4 times the original value, where N4 is a positive integer.

10. The method according to claim 9, characterized in that The step of integrating corresponding subtasks in the first task according to the adjusted system parameters to execute the first task includes: In the process of executing the first task according to the adjusted system parameters, subtasks corresponding to N4 PRBs are executed at a time.

11. The method according to claim 1, characterized in that: The clustering process of the signal to be processed comprises: All signals of the same type that need to be processed within the scope of the first task are uniformly stored in memory, so that the signals to be processed are uniformly processed according to the signal type.

12. The method according to any one of claims 1 to 10, characterized in that: After performing the first task according to the adjusted system parameters, the method further includes: Fill the vacant positions and / or resource-unaligned positions in the resource positions occupied by the signals corresponding to the users with resources.

13. A baseband task processing device, characterized in that: The device comprises: a first processing unit and a second processing unit; wherein, The first processing unit is used to obtain a first task; the first task is one of the multiple tasks included in the baseband processing process; and is also used to determine a first optimization strategy based on the first task; The second processing unit is used to adjust the system parameters according to the first optimization strategy, and integrate the corresponding subtasks in the first task according to the adjusted system parameters to execute the first task, or, in the process of executing the first task according to the first optimization strategy, cluster the signals to be processed.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 12 are implemented.

15. A network device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method according to any one of claims 1 to 12 are implemented.

16. A computer program product, characterized in that The method comprises computer program instructions, which enable a computer to execute the steps of the method according to any one of claims 1 to 12.

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