A data transmission method and device, electronic equipment and storage medium

Abstract

The application discloses a data transmission method and device, electronic equipment and storage medium. The method comprises the following steps: acquiring an antenna set corresponding to a target data stream; wherein the antenna set is obtained by target antenna grouping; the target antenna comprises a sending end antenna and a receiving end antenna; determining a first vector and a second vector according to channel state information of the antenna set; wherein the first vector is a sending direction vector of a sending end signal; the second vector is a receiving direction vector of a receiving end signal; determining the number of resource blocks corresponding to the target data stream; and transmitting the target data stream based on the first vector, the second vector and the number of resource blocks. The technical scheme can realize reliable data transmission, has the advantages of low cost, flexible deployment, strong anti-interference and prominent disaster resistance and destruction resistance.

Description

Technical Field

[0001] This invention relates to the field of wireless technology, and more particularly to a data transmission method, apparatus, electronic device, and storage medium. Background Technology

[0002] The East-to-West Data Utilization Project is a major strategic project to optimize the national computing power resource allocation and promote the balanced development of the digital economy. The implementation of this project relies heavily on an efficient, stable, and low-latency cross-regional data transmission network. Reliable data transmission channels are the core foundation for ensuring computing power scheduling and data interaction.

[0003] Currently, cross-regional data transmission services in the East-West Computing Project primarily rely on wired connections via fiber optic communication. Fiber optic communication offers advantages such as large bandwidth, high operational stability, and controllable data transmission latency, meeting the demands of large-scale data transmission in conventional scenarios and making it the mainstream communication method for current computing network construction. However, in actual engineering construction and business operation, traditional wired fiber optic transmission methods have significant technical shortcomings, making them difficult to adapt to the needs of computing network construction across all regions and scenarios. Firstly, construction and deployment costs are high, and implementation is difficult. Secondly, network deployment flexibility is poor, and disaster recovery and fault tolerance capabilities are weak.

[0004] In summary, existing wired fiber optic communication transmission solutions suffer from high costs, poor deployment flexibility, and weak anti-interference and disaster resistance capabilities, making them unable to fully meet the diverse, highly reliable, and highly adaptable transmission requirements of the East-to-West Data and Computing Project. Summary of the Invention

[0005] This invention provides a data transmission method, apparatus, electronic device, and storage medium that can achieve reliable data transmission and has the advantages of low cost, flexible deployment, strong anti-interference, and outstanding disaster prevention and damage resistance.

[0006] According to one aspect of the present invention, a data transmission method is provided, the method comprising: Obtain the antenna set corresponding to the target data stream; wherein, the antenna set is obtained by grouping the target antennas; the target antennas include transmitting antennas and receiving antennas; Based on the channel state information of the antenna set, a first vector and a second vector are determined; wherein, the first vector is the transmission direction vector of the transmitting end signal; and the second vector is the reception direction vector of the receiving end signal. Determine the number of resource blocks corresponding to the target data stream; The target data stream is transmitted based on the first vector, the second vector, and the number of resource blocks.

[0007] According to another aspect of the present invention, a data transmission apparatus is provided, the apparatus comprising: An antenna set acquisition module is used to acquire the antenna set corresponding to the target data stream; wherein, the antenna set is obtained by grouping the target antennas; the target antennas include transmitting antennas and receiving antennas; The vector determination module is used to determine a first vector and a second vector based on the channel state information of the antenna set; wherein the first vector is the transmission direction vector of the transmitting end signal; and the second vector is the reception direction vector of the receiving end signal. The resource block quantity determination module is used to determine the number of resource blocks corresponding to the target data stream; The transmission module is used to transmit the target data stream based on the first vector, the second vector, and the number of resource blocks.

[0008] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform a data transmission method according to any embodiment of the present invention.

[0009] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement a data transmission method according to any embodiment of the present invention.

[0010] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements a data transmission method as described in any embodiment of the present invention.

[0011] The technical solution of this invention involves obtaining the antenna set corresponding to the target data stream; determining a first vector and a second vector based on the channel state information of the antenna set; determining the number of resource blocks corresponding to the target data stream; and transmitting the target data stream based on the first vector, the second vector, and the number of resource blocks. This technical solution enables reliable data transmission and has advantages such as low cost, flexible deployment, strong anti-interference capabilities, and outstanding disaster prevention and mitigation capabilities.

[0012] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart of a data transmission method provided according to Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the system model provided in Embodiment 1 of this application; Figure 3 A flowchart of a data transmission process provided in Embodiment 2 of the present invention; Figure 4 This is a schematic diagram of a data transmission method provided in Embodiment 3 of the present invention; Figure 5 The system and rate variation with transmission power are provided in Embodiment 3 of this application; Figure 6 The minimum service rate versus transmission power is shown in Embodiment 3 of this application. Figure 7 This is a schematic diagram of the structure of a data transmission device provided in Embodiment 4 of the present invention; Figure 8 This is a schematic diagram of the structure of an electronic device that implements a data transmission method according to an embodiment of the present invention. Detailed Implementation

[0015] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0016] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0017] Example 1 Figure 1 This is a flowchart of a data transmission method according to Embodiment 1 of the present invention. This embodiment is applicable to situations involving data transmission. The method can be executed by a data transmission device, which can be implemented in hardware and / or software and can be configured in a device. For example, the device can be a backend server or other device with communication and computing capabilities. Figure 1 As shown, the method includes: S110. Obtain the antenna set corresponding to the target data stream; wherein, the antenna set is obtained by grouping the target antennas; the target antennas include transmitting antennas and receiving antennas.

[0018] In this solution, "East-to-West Computing" refers to transmitting high-computation, latency-insensitive computing services from the eastern region to the western region via satellite or wired networks. This effectively alleviates the power load pressure on the eastern region caused by large-scale computing operations. This solution focuses on high-computation, latency-insensitive services, relying on satellite communication networks to achieve the scheduling and processing of such services via East-to-West computing. Typical applications include batch transcoding of film and television materials, statistical analysis of historical financial data, batch parsing of remote sensing images, and summary analysis of server logs.

[0019] In this embodiment, traditional terrestrial and satellite communication systems exhibit no significant uplink or downlink traffic bias, with data transmission volumes at both the ground and satellite ends being essentially balanced. There is no discrepancy between large-volume transmissions at one end and small-volume data transmissions at the other. However, in the East-to-West data processing application scenario, service traffic exhibits a clear asymmetry: the eastern region generates a massive amount of data, while the western region undertakes the primary computational tasks. This results in a unidirectional traffic pattern where the eastern region transmits a large amount of data to the western region, while the western region returns a small amount of the processed data. If existing general technical solutions are used to configure ground equipment (such as base stations and antennas) of similar specifications and quantities at both ends, it will result in a serious waste of resources: if both ends are equipped with high-specification, high-bandwidth, high-capacity transmission equipment, the west will not need radio frequency units with high transmission capacity, resulting in idle hardware resources; if both ends use low-cost, low-bandwidth, lightweight transmission equipment, the large-volume data transmission in the east will cause the equipment to exceed its load limit and fail to operate normally; if a differentiated configuration is used, with the east using a high-capacity transmission architecture and the west using a lightweight transmission architecture, on the one hand, existing communication algorithms are mostly uplink-downlink coupled designs, which cannot adapt to asymmetric traffic scenarios; on the other hand, the hardware capabilities of the western receiving end are insufficient, making it difficult to stably handle the massive data from the east. In summary, the communication solution must be designed to take into account the asymmetric transmission characteristics of east-to-west computing, with large volumes of data transmitted from the east and small volumes transmitted from the west. This proposal focuses on the east-to-west computing service scenario and carries out a dedicated design in the communication link between the terminal and the satellite, thereby differentiating it from traditional terrestrial and satellite communication modes.

[0020] in, Figure 2 This is a schematic diagram of the system model provided in Embodiment 1 of this application, as shown below. Figure 2 As shown, the first point is the computation job generation points in the east, assuming a total of [number missing]. There are computational job generation points, and the set of job generation points is . Satellite communication operators have configured an eastern convergence core for these job generation points, defined as It is used to collect computation requests initiated by job generation points and send all collected data to the satellite earth station. Transmitted to the western aggregation core via satellite communication network And complete the computational work in the west.

[0021] In this embodiment, the aggregation core is responsible for aggregating task requests from all job generation points. Each job generation point submits a job application in the form of a message, the message content of which includes at least the service number, service data, calculation algorithm, target return value, key, and verification code. To ensure transmission security, some jobs employ encryption algorithms or convolutional coding to process the messages; the transmission method in this scheme is fully compatible with such encoding methods. This scheme only requires the receiving end to obtain a binary sequence of 0s or 1s or other higher-order base sequences; the service information within the sequence is decoded and parsed by high-computing equipment using the key. The aggregation core and the satellite earth station only serve as data channels, responsible for data forwarding and transmission.

[0022] In this scheme, the entire communication link is divided into two segments: one is the eastern high-volume aggregation core. As the transmitting end, satellite earth station As the receiving end; secondly, after switching the transmission direction, using a satellite earth station. For the sending end, the western low-flow aggregation core As the receiving end. Among them, satellite earth station. It only forwards data and does not perform any related calculations; the calculation process is only completed in the devices at the eastern and western ends. The following section focuses on the aggregation core. To satellite earth station The data transmission process will be used as an example for illustration.

[0023] The target data stream refers to the ordered sequence of data continuously transmitted from the sender to the receiver.

[0024] In this embodiment, the antenna set is obtained by grouping the target antennas; the target antennas include transmitting antennas and receiving antennas.

[0025] Specifically, the target antennas can be scheduled and divided in three ways: average allocation, random allocation, and full allocation, thereby filtering and obtaining the set of antennas that carry the target data stream.

[0026] S120. Based on the channel state information of the antenna set, determine a first vector and a second vector; wherein, the first vector is the transmission direction vector of the transmitting end signal; and the second vector is the reception direction vector of the receiving end signal.

[0027] In this scheme, channel state information is a set of parameters used to characterize the real-time transmission quality of wireless communication links, including key indicators such as channel fading, signal delay, phase offset, interference intensity, signal-to-noise ratio, and channel capacity. It can intuitively reflect the quality of the wireless channel between the antenna and the peer device, and the communication system can dynamically complete antenna selection, resource allocation, power regulation, and link adaptation based on this information.

[0028] The first vector is the signal transmission direction vector of the transmitting end, which is used to pre-encode the transmission signal corresponding to the target data stream, adjust the beam direction, phase and amplitude of the antenna transmission signal, and concentrate the signal energy towards the receiving end; the second vector is the signal reception direction vector of the receiving end, which is used to merge the received signal, selectively filter effective signals, and suppress noise and clutter interference.

[0029] Specifically, the channel state information of all antennas in the antenna set is collected and integrated to construct a channel state matrix; then the channel state matrix is ​​decomposed and calculated to finally obtain the first vector and the second vector.

[0030] Furthermore, based on pre-set transmission constraints (such as minimum channel gain threshold, maximum bit error rate, and antenna quantity limit), the matrix elements obtained from channel matrix decomposition are used to filter and determine the first vector at the transmitting end and the second vector at the receiving end. Using this transmit / receive vector combination, the theoretical maximum channel gain and transmission rate can be achieved under current channel conditions, ensuring that the link transmission capacity precisely matches the service requirements of large-volume data transmission from the east to the west in the East-to-West data processing scenario. For example, when transmitting batch transcoded video and film footage, the system will prioritize the transmit / receive vector corresponding to the largest singular value to ensure high-speed, low-bit-error transmission of large volumes of data.

[0031] Optionally, based on the channel state information of the antenna set, the first vector and the second vector are determined, including: Singular value decomposition is performed on the channel state information of the antenna set to obtain the target matrix; Based on the elements in the target matrix, determine the first vector and the second vector.

[0032] In this scheme, singular value decomposition (SVD) is the mainstream matrix operation method. The system constructs a channel matrix based on channel state information collected by multiple antennas, and then decomposes this matrix into a target matrix using SVD. The resulting target matrix intuitively reflects the transmission gain of each sub-channel.

[0033] Specifically, singular value decomposition is performed on the channel state information matrix of the antenna set to obtain the target matrix; then, based on the elements in the target matrix, the first vector and the second vector are extracted and determined.

[0034] By performing singular value decomposition on the channel state information of the antenna set and selecting the transmit and receive vectors by combining matrix elements, the transmission characteristics of multi-antenna channels can be fully explored, the optimal transmit and receive directions can be accurately matched, the channel gain can be effectively improved, the transmission interference can be suppressed, the link transmission capacity can be maximized under existing hardware and channel conditions, and the antenna resources can be rationally scheduled to ensure stable and efficient transmission of data streams with different traffic specifications.

[0035] S130. Determine the number of resource blocks corresponding to the target data stream.

[0036] In this scheme, the number of resource blocks refers to the total number of physical resource units allocated to the target data stream. It directly determines the available bandwidth and transmission capacity of the link to match the transmission requirements of different traffic levels in the East-to-West data processing scenario.

[0037] Specifically, based on the target data stream's service type, data volume, and transmission latency requirements, combined with the current channel status and available system resources, the corresponding number of resource blocks is dynamically calculated and determined using a preset resource allocation algorithm.

[0038] Optionally, determining the number of resource blocks corresponding to the target data stream includes: Obtain the size of the data packets corresponding to the target data stream; The number of resource blocks corresponding to the target data stream is calculated based on the data packet size and the pre-set number of information bits for the resource blocks.

[0039] Information bits: refers to the total net data bits that a single resource block can carry and effectively transmit in a single transmission.

[0040] Specifically, assume the system has K target data streams, and the size of the data packet corresponding to each target data stream is... (Unit: bit), generated by the aggregation core and satellite earth station In the link between them, a single resource block (RB) can carry S bits. This scheme requires each computing request to have its own dedicated resource block sequence. Based on this, the number of resource blocks required for the k-th computing request can be derived: ; in, This indicates rounding up. For RBs that cannot be filled, error detection and correction codes can be added to improve transmission reliability.

[0041] Ultimately, the core converges. The number of resource blocks to be transferred is: .

[0042] The required number of resource blocks is calculated based on the data packet size and the number of bits carried by a single resource block. This allows for precise allocation of time-frequency resources in conjunction with the volume of business data, ensuring the integrity and stable transmission of data streams while avoiding resource idleness and waste, thus significantly improving system resource utilization.

[0043] S140. Based on the first vector, the second vector, and the number of resource blocks, transmit the target data stream.

[0044] In this scheme, the transmitting end maps the target data stream to the physical resources corresponding to the number of resource blocks, and completes modulation and framing; the first vector is used to precode the framed signal to form a precoded signal; the precoded signal is transmitted through the antenna array and transmitted to the receiving end on the time-frequency resources corresponding to the allocated resource blocks; the receiving end uses the second vector to merge the received signal, and then completes demodulation and decoding to recover the target data stream.

[0045] The technical solution of this invention involves obtaining the antenna set corresponding to the target data stream; determining a first vector and a second vector based on the channel state information of the antenna set; determining the number of resource blocks corresponding to the target data stream; and transmitting the target data stream based on the first vector, the second vector, and the number of resource blocks. By implementing this technical solution, reliable data transmission can be achieved, offering advantages such as low cost, flexible deployment, strong anti-interference capabilities, and outstanding disaster prevention and mitigation capabilities.

[0046] Example 2 Figure 3 This is a flowchart illustrating a data transmission process according to Embodiment 2 of the present invention. The relationship between this embodiment and the above embodiments is a detailed description of the antenna set determination process. Figure 3 As shown, the method includes: S310. When the target data stream is a single data stream, the target antenna is divided into an antenna set corresponding to the target data stream.

[0047] In this scheme, for single-stream data scenarios, low-antenna architectures such as MISO (Multipe Input Single Output) and SISO (Single Input Single Output) can effectively use multiple antennas as a single antenna, thereby achieving higher channel gain. Meanwhile, MIMO (Multipe Input Multiple Output) can construct multiple independent, optimal parallel channels. Therefore, when the target data stream is a single-stream data stream, all antennas in the target antenna can be assigned to the antenna set corresponding to the target data stream.

[0048] S320. Based on the channel state information of the antenna set, determine a first vector and a second vector; wherein, the first vector is the transmission direction vector of the transmitting end signal; and the second vector is the reception direction vector of the receiving end signal.

[0049] In this scheme, we assume a convergence core. have One antenna, satellite earth station have The channel state information of the antenna set is as follows: ; The Singular Value Decomposition (SVD) decomposition of channel state information is as follows: ; Among them, when When, satisfy .

[0050] In this scheme, the determination of the first vector and the second vector is shown in Table 1.

[0051] Table 1 The optimal strategy for SISO systems (including MISO and SIM systems) is to utilize the virtual channel with maximum gain: at the transmitter (convergence core). ): Select the first right singular vector As a transmission direction vector, it concentrates signal energy towards the receiver, achieving beamforming. Receiver (satellite earth station) ): Select the first left singular vector As the receiving direction vector, the received signals are weighted and combined to maximize the received signal-to-noise ratio. At this point, the channel gain obtained by the system is the maximum singular value. This is the theoretically optimal value under these channel conditions. Both the transmitter and receiver operate at full power to fully utilize this optimal channel and enhance the link's transmission capacity.

[0052] For MIMO systems, in multi-stream parallel transmission scenarios, the system can utilize multiple independent virtual channels to achieve parallel transmission: the number of independent channels that can transmit simultaneously is... The gain corresponding to an independent channel is a set of singular values ​​arranged in descending order. , , , , The sending end sequentially uses all right singular vectors. , , , As the transmission direction vectors for different data streams; the receiving end then sequentially uses all left singular vectors. , , , As the receiving direction vector for the corresponding data stream, it enables multi-channel parallel transmission. Both the transmitting and receiving ends follow the principle of equal power plane, distributing power evenly across all independent channels to maximize overall transmission efficiency.

[0053] S330. Determine the number of resource blocks corresponding to the target data stream.

[0054] S340. Based on the first vector, the second vector, and the number of resource blocks, transmit the target data stream.

[0055] The technical solution of this invention, when the target data stream is a single-channel data stream, divides the target antenna into an antenna set corresponding to the target data stream; determines a first vector and a second vector based on the channel state information of the antenna set; determines the number of resource blocks corresponding to the target data stream; and transmits the target data stream based on the first vector, the second vector, and the number of resource blocks. By implementing this technical solution, by dividing a dedicated antenna set for a single-channel target data stream, determining the transmit / receive direction vector based on its channel state information, and accurately allocating the number of resource blocks in conjunction with the data packet size, the coordinated optimization of antenna, signal processing, and time-frequency resources is achieved; it not only fully exploits the channel gain advantages of multiple antennas, improving transmission stability and anti-interference capability, but also allows for on-demand configuration of transmission resources, avoiding waste, and significantly improving the overall resource utilization efficiency of the system while ensuring the transmission performance of a single-channel data stream.

[0056] Example 3 Figure 4 This is a schematic diagram of a data transmission method provided in Embodiment 3 of the present invention. The relationship between this embodiment and the above embodiments is a detailed description of the antenna set determination process. Figure 4 As shown, the method includes: S410. When the target data stream is a multi-stream data stream, the target antennas are grouped according to the number of data streams to generate an antenna set corresponding to each target data stream.

[0057] The number of data streams refers to the total number of target data streams that need to be transmitted simultaneously in the current communication system.

[0058] Specifically, the number of data streams is obtained by the business scheduling unit on the aggregation core side. The scheduling unit counts the independent data streams currently waiting to be transmitted, and determines the total number of target data streams that can be transmitted in parallel, based on the system's maximum concurrent transmission capacity and business priority strategy. This number is denoted as the data stream count.

[0059] In this scheme, when the target data stream is a multi-stream data stream, the target antennas can be grouped equally according to the number of data streams to generate an antenna set corresponding to each target data stream.

[0060] In this embodiment, data streams can also be dynamically grouped based on the number of data streams and the transmission quality score corresponding to the target data streams, generating antenna sets for each target data stream. For example, for target data streams with low transmission quality scores and poor channel conditions, more antennas can be allocated to improve diversity gain; for target data streams with high transmission quality scores, the antenna configuration can be appropriately reduced to achieve dynamic optimization allocation of antenna resources.

[0061] Optionally, the target antennas are grouped according to the number of data streams to generate an antenna set corresponding to each target data stream, including: The target antennas are grouped equally according to the number of data streams to generate an antenna set corresponding to each target data stream.

[0062] In this solution, when the core converges... When transmitting multiple data streams simultaneously, assuming the number of antennas configured at the transmitter in the MIMO system is... The number of antennas configured at the receiver is The number of data streams is When target antennas are evenly distributed according to the number of data streams, each target data stream will receive a fixed number of antennas for data transmission. Since both the total number of antennas and the number of data streams are integer powers of 2, the number of antennas must be divisible by the number of data streams, and there is no remainder during the even distribution process. Without loss of generality, assume a convergence core... The number of antennas is greater than that of satellite earth stations The number of antennas, the number of antennas corresponding to each target data stream is .

[0063] Furthermore, regarding satellite earth stations The antennas are numbered sequentially as follows The set of antennas allocated to the l-th data stream is defined as follows: The total number of antennas is After performing singular value decomposition on the channel matrix corresponding to each antenna set, the resulting diagonal matrix is ​​sorted in descending order of singular values ​​as follows: Under these conditions, the optimization problem aimed at achieving fairness in the transmission of all data streams can be formulated as follows: The goal of optimization is to adjust the antenna grouping method. Maximize the minimum of the worst channel gain among all data streams: ; For each data stream Calculate the antenna set it is assigned to. The sum of all singular values ​​in the set represents the total channel gain of that data stream. The minimum gain of all data streams (i.e., the worst-performing stream) is then selected. By adjusting the antenna grouping, this worst-performing gain is maximized to ensure that the transmission performance of all data streams is not severely hampered, thus achieving fairness.

[0064] The size of the antenna set allocated to each data stream must be equal to Q, that is: Where Q is a pre-set single-stream antenna quota, ensuring that each data stream receives the same number of antenna resources.

[0065] The antenna sets of any two data streams cannot intersect, that is: , This ensures that each antenna can only be assigned to one data stream, eliminating resource conflicts.

[0066] The union of the antenna sets of all data streams must equal the total antenna set A, that is: This ensures that all available antennas in the system are allocated, with no resources wasted.

[0067] Limited by Given the unordered combination characteristics of the data streams, the optimal antenna allocation problem is an NP-hard problem with no closed-form solution. Using an exhaustive search method to find the optimal solution would consume extremely high computational resources. This scheme fully utilizes the key characteristic that the number of antennas is always an integer power of 2, proposing a low-complexity solution method: based on this exponential property, a divide-and-conquer strategy can be adopted. First, the optimal allocation for pairwise combinations is solved, then the optimal allocation for four-by-four combinations is solved based on the result, and so on iteratively until the optimal solution is obtained. The optimal allocation scheme for combining data streams.

[0068] Specifically, the algorithm is as follows: Step 1: Initialization Let the iteration parameter q = 1. q represents the number of singular values ​​contained in each current assignment group. Initially, each group contains only 1 singular value.

[0069] Step 2: Outer loop (paired iteration) Loop condition: 2q ≠ Q, where Q = / , is the number of antennas ultimately allocated to a single data stream (and also the number of singular values ​​it contains). The iteration continues as long as twice the current group size q has not yet reached the target group size Q.

[0070] Step 2.1: Sort the diagonal matrix Reorder the singular values ​​in the diagonal matrix from largest to smallest, that is: ; This represents the number of valid singular values ​​in the current iteration.

[0071] Step 2.2: Initialize the antenna set ; Initialize the antenna set for each index i: At this point, each set contains only one singular value. .

[0072] Step 2.3: Pairing and Merging ; Pair and merge the largest singular value with the smallest singular value: ; ; ; The purpose of this step is to add the maximum and minimum singular values ​​and store them in... This achieves "strong-weak complementarity"; the original smallest singular value is set to zero to avoid reuse; and the antenna channels corresponding to the two singular values ​​are added to the same set. .

[0073] Step 2.4: Update iteration parameters Let q = 2q, the group size doubles, and the cycle continues.

[0074] Step 3: End the loop and output the result. When 2q = Q, the outer loop ends, and at this point, the antenna set for each data stream is... The system has been built.

[0075] Final output: Antenna set evenly distributed across the target antenna Each data stream contains Q singular values, and the total gain of each stream has been maximized to ensure fairness through strong-weak pairing.

[0076] By employing a low-complexity iterative strategy of divide-and-conquer pairing and strong-weak complementarity, and with a computational overhead far lower than exhaustive search, antenna resource sharing and channel gain fair allocation for multiple data streams are achieved. This ensures that each data stream receives a fixed number of antenna resources, while significantly improving the overall transmission fairness and resource utilization efficiency of the system by maximizing the channel gain of the worst data stream.

[0077] Optionally, grouping the target antennas according to the number of data streams to generate an antenna set corresponding to each target data stream further includes: Based on the number of data streams, the target antenna is divided into a first antenna and a second antenna; wherein the number of first antennas is equal to the number of data streams; and the second antenna consists of the remaining antennas in the target antenna group excluding the first antenna. The first antenna is assigned to each target data stream; Calculate the transmission quality score of each target data stream, and allocate the second antenna in sequence according to the transmission quality score to generate the antenna set corresponding to each target data stream.

[0078] In this scheme, the system needs to maintain similar information rates for each data stream as much as possible. This is both a basic requirement of the data synchronization module and a key to ensuring the robustness of joint transmission of multiple data streams. However, due to differences in the channel gain of each antenna, simply allocating antennas equally according to the number of data streams often fails to achieve the system's steady-state optimal solution, i.e., a state where the information rates of each data stream are as close as possible and the overall transmission efficiency is high. In contrast, adopting a flexible antenna allocation method can further improve the system's transmission quality: for antennas with good channel conditions, they can transmit independently or form an array with fewer antennas to transmit data; for antennas with poor channel conditions, multiple antennas can work together to transmit information with a configuration exceeding the average number of antennas per stream, thereby reducing the information rate differences among the data streams and achieving steady-state optimality.

[0079] The transmission quality score is calculated by taking the square of the second norm of the vector formed by all singular values ​​in the target data stream antenna set.

[0080] Specifically, based on the number of target data streams, the target antennas are divided into a first antenna set and a second antenna set. The antennas in the first antenna set are assigned to each target data stream, providing initial transmission resources for each data stream. The transmission quality score of each target data stream is calculated. Then, a single antenna is selected from the second antenna set and assigned to the target data stream with the lowest current transmission quality score. After updating the transmission quality score of this data stream, the above assignment steps are repeated, continuously assigning antennas in the second antenna set to the target data stream with the lowest transmission quality score, until all antennas in the second antenna set are assigned.

[0081] At this point, in order to make the transmission rates of all data streams tend to be consistent, the following optimization problem is constructed: The core objective of optimization is to adjust the antenna grouping scheme. Under the premise of satisfying constraints, maximize the minimum value of the worst channel gain among all data streams: ; For each data stream Calculate the antenna set it is assigned to. The sum of all singular values ​​in the set represents the total channel gain of that data stream. The minimum gain of all data streams (i.e., the worst-performing stream) is then selected. By adjusting the antenna grouping, this worst-performing gain is maximized to ensure that the transmission performance of all data streams is not severely hampered, thus achieving fairness.

[0082] Each data stream must be allocated at least one antenna, that is: To ensure that each data stream can obtain basic transmission resources and avoid situations where no antenna is available.

[0083] The antenna sets of any two data streams cannot intersect, that is: , This ensures that each antenna can only be assigned to one data stream, eliminating resource conflicts.

[0084] The union of the antenna sets of all data streams must equal the total antenna set A, that is: This ensures that all available antennas in the system are allocated, with no resources wasted.

[0085] Specifically, the algorithm is as follows: Step 1: Initialize the basic antenna set for each data stream : Initialize the antenna set for each data stream i, and then... The largest singular value (corresponding to the antenna with the best channel conditions) is assigned to each data stream as the basic configuration: At this point, each data stream has been equipped with a base antenna, ensuring that all data streams have the ability to transmit.

[0086] Step 2: Iteratively allocate remaining antennas ; For the remaining Root antenna (corresponding to the remaining singular values) Dynamic allocation is performed: Step 2.1: Calculate the current transmission quality of each data stream. For each data stream l, calculate its antenna set. The square of the L2 norm of the vector formed by all singular values ​​in the vector is used as the transmission quality score: ; Sort all data stream transmission quality scores from highest to lowest and renumber them as 1: Find the data stream with the lowest current rating (numbered as follows) That route).

[0087] Step 2.2: Assign the current antenna to the data stream with the lowest score. The remaining singular values The data stream assigned to the lowest transmission quality score: ; The core logic of this step is to address the shortcomings: by allocating additional antennas to the worst-performing data stream, its channel gain is improved, thereby reducing the rate difference between the various data streams.

[0088] Step 3: End the loop and output the result. Once all remaining antennas have been allocated, the algorithm terminates, ultimately outputting the antenna allocation strategies for each data stream. .

[0089] By using the squared L2 norm of the singular value vector of the target data stream antenna set as the transmission quality score, a precise quantitative assessment of the channel conditions of each data stream is achieved, providing an objective basis for subsequent dynamic antenna allocation. Based on this, the remaining antennas are preferentially allocated to the data stream with the lowest score, which not only ensures the basic transmission capability of each data stream, but also efficiently smooths out the differences in channel gain among the streams. This achieves rate convergence of multi-stream transmission and maximizes the overall system utility with low complexity, significantly improving transmission fairness and robustness, while effectively avoiding the performance shortcomings of simple equal-allocation strategies.

[0090] S420. Based on the channel state information of the antenna set, determine a first vector and a second vector; wherein, the first vector is the transmission direction vector of the transmitting end signal; and the second vector is the reception direction vector of the receiving end signal.

[0091] S430. Determine the number of resource blocks corresponding to the target data stream.

[0092] S440. Based on the first vector, the second vector, and the number of resource blocks, transmit the target data stream.

[0093] The technical solution of this invention, when the target data stream is a multi-stream data stream, groups the target antennas according to the number of data streams to generate an antenna set corresponding to each target data stream; determines a first vector and a second vector based on the channel state information of the antenna sets; determines the number of resource blocks corresponding to the target data stream; and transmits the target data stream based on the first vector, the second vector, and the number of resource blocks. By implementing this technical solution, in a multi-stream data stream scenario, by grouping the target antennas according to the number of data streams, a dedicated antenna set is constructed for each target data stream; then, based on the channel state information of each group of antennas, the transmit and receive vectors are determined, and the number of resource blocks is accurately allocated in combination with transmission requirements, achieving coordinated optimization of antenna resources, signal processing, and time-frequency resources. This not only fully exploits the diversity gain of multiple antennas through differentiated antenna grouping and transmit / receive vector matching, improving link transmission performance and anti-interference capability, but also avoids resource waste through on-demand allocation of resource blocks. While ensuring the fairness and stability of parallel transmission of multiple data streams, it significantly improves the overall transmission efficiency and resource utilization efficiency of the system.

[0094] In this embodiment, the algorithm performance is verified through simulation. This scheme is a data transmission algorithm customized for "East Data West Computation," therefore, the algorithm performance comparison must be based on the premise of equivalent construction costs. This scheme selects two benchmark algorithms for comparison: Algorithm 1 is the traditional configuration scheme, and Algorithm 2 is the antenna equalization algorithm; both adopt MIMO-MMSE reception technology.

[0095] Furthermore, Figure 5 The system and rate variation with transmission power provided in Embodiment 3 of this application are shown in the following figure. Figure 5 As shown in the simulation results, both Algorithm 1 and Algorithm 2 of the proposed scheme significantly outperform the comparative Algorithms 1 and 2, with Algorithm 2 showing particularly outstanding performance gains. This fully verifies the effectiveness of the adaptive antenna allocation method described in this proposal: this method can rationally allocate antenna resources for different services based on the channel quality strength among the antennas.

[0096] in, Figure 6 The minimum service rate versus transmission power diagram provided in Embodiment 3 of this application is shown below. Figure 6 As shown, the proposed algorithm also outperforms the two comparison algorithms. This advantage stems from the fact that the proposed algorithm fully considers the transmission directionality of the east-to-west data processing scenario and achieves resource optimization through adaptive antenna selection, further demonstrating the effectiveness and robustness of the proposed algorithm in real-world scenarios.

[0097] Example 4 Figure 7 This is a schematic diagram of a data transmission device provided in Embodiment 4 of the present invention. Figure 7 As shown, the device includes: Antenna set acquisition module 710 is used to acquire the antenna set corresponding to the target data stream; wherein, the antenna set is obtained by grouping the target antennas; the target antennas include transmitting antennas and receiving antennas; The vector determination module 720 is used to determine a first vector and a second vector based on the channel state information of the antenna set; wherein the first vector is the transmission direction vector of the transmitting end signal; and the second vector is the reception direction vector of the receiving end signal. Resource block quantity determination module 730 is used to determine the number of resource blocks corresponding to the target data stream; The transmission module 740 is used to transmit the target data stream based on the first vector, the second vector, and the number of resource blocks.

[0098] Optionally, the antenna collection acquisition module 710 includes: The antenna set partitioning submodule is used to partition the target antenna into antenna sets corresponding to the target data stream when the target data stream is a single data stream.

[0099] Optionally, the antenna collection acquisition module 710 includes: The antenna set determination submodule is used to group the target antennas according to the number of data streams when the target data stream is a multi-stream data stream, and generate an antenna set corresponding to each target data stream.

[0100] Optional, the antenna set determination submodule is specifically used for: The target antennas are grouped equally according to the number of data streams to generate an antenna set corresponding to each target data stream.

[0101] Optionally, the antenna set determination submodule is also used for: Based on the number of data streams, the target antenna is divided into a first antenna and a second antenna; wherein the number of first antennas is equal to the number of data streams; and the second antenna consists of the remaining antennas in the target antenna group excluding the first antenna. The first antenna is assigned to each target data stream; Calculate the transmission quality score of each target data stream, and allocate the second antenna in sequence according to the transmission quality score to generate the antenna set corresponding to each target data stream.

[0102] Optionally, the vector determination module 720 is specifically used for: Singular value decomposition is performed on the channel state information of the antenna set to obtain the target matrix; Based on the elements in the target matrix, determine the first vector and the second vector.

[0103] Optional, the resource block quantity determination module 730 is specifically used for: Obtain the size of the data packets corresponding to the target data stream; The number of resource blocks corresponding to the target data stream is calculated based on the data packet size and the pre-set number of information bits for the resource blocks.

[0104] The data transmission device provided in this embodiment of the invention can execute a data transmission method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0105] Example 5 Figure 8 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0106] like Figure 8 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0107] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0108] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a data transfer method.

[0109] In some embodiments, a data transfer method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the data transfer method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform a data transfer method by any other suitable means (e.g., by means of firmware).

[0110] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transferring data and instructions to the storage system, the at least one input device, and the at least one output device.

[0111] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0112] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0113] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0114] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0115] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0116] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of the embodiments of the present invention.

[0117] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0118] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A data transmission method, characterized in that, include: Obtain the antenna set corresponding to the target data stream; wherein, the antenna set is obtained by grouping the target antennas; the target antennas include transmitting antennas and receiving antennas; Based on the channel state information of the antenna set, a first vector and a second vector are determined; wherein, the first vector is the transmission direction vector of the transmitting end signal; and the second vector is the reception direction vector of the receiving end signal. Determine the number of resource blocks corresponding to the target data stream; The target data stream is transmitted based on the first vector, the second vector, and the number of resource blocks.

2. The method according to claim 1, characterized in that, Obtain the antenna set corresponding to the target data stream, including: When the target data stream is a single data stream, the target antenna is divided into an antenna set corresponding to the target data stream.

3. The method according to claim 1, characterized in that, Obtain the antenna set corresponding to the target data stream, including: When the target data stream is a multi-stream data stream, the target antennas are grouped according to the number of data streams to generate an antenna set corresponding to each target data stream.

4. The method according to claim 3, characterized in that, The target antennas are grouped according to the number of data streams to generate an antenna set corresponding to each target data stream, including: The target antennas are grouped equally according to the number of data streams to generate an antenna set corresponding to each target data stream.

5. The method according to claim 3, characterized in that, The target antennas are grouped according to the number of data streams to generate an antenna set corresponding to each target data stream, and the method further includes: Based on the number of data streams, the target antenna is divided into a first antenna and a second antenna; wherein the number of first antennas is equal to the number of data streams; and the second antenna consists of the remaining antennas in the target antenna group excluding the first antenna. The first antenna is assigned to each target data stream; Calculate the transmission quality score of each target data stream, and allocate the second antenna in sequence according to the transmission quality score to generate the antenna set corresponding to each target data stream.

6. The method according to claim 1, characterized in that, Based on the channel state information of the antenna set, the first vector and the second vector are determined, including: Singular value decomposition is performed on the channel state information of the antenna set to obtain the target matrix; Based on the elements in the target matrix, determine the first vector and the second vector.

7. The method according to claim 1, characterized in that, Determining the number of resource blocks corresponding to the target data stream includes: Obtain the size of the data packets corresponding to the target data stream; The number of resource blocks corresponding to the target data stream is calculated based on the data packet size and the pre-set number of information bits for the resource blocks.

8. A data transmission device, characterized in that, include: An antenna set acquisition module is used to acquire the antenna set corresponding to the target data stream; wherein, the antenna set is obtained by grouping the target antennas; the target antennas include transmitting antennas and receiving antennas; The vector determination module is used to determine a first vector and a second vector based on the channel state information of the antenna set; wherein the first vector is the transmission direction vector of the transmitting end signal; and the second vector is the reception direction vector of the receiving end signal. The resource block quantity determination module is used to determine the number of resource blocks corresponding to the target data stream; The transmission module is used to transmit the target data stream based on the first vector, the second vector, and the number of resource blocks.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform a data transmission method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that are used to cause a processor to execute a data transmission method according to any one of claims 1-7.

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