Resource allocation method and device, equipment, medium and program product

Abstract

Provided are a resource allocation method, apparatus, device, medium and program product, applied to the technical field of communications, the method comprising: acquiring channel information of a target system, the target system comprising M sub-channels, each of which has a long packet service and K short packet services; based on the channel information, determining a first decoding sequence of K sub-services corresponding to the long packet service and the K short packet services; based on the channel information and the first decoding sequence, determining a target resource allocation mode of the target system under the condition that the transmitting power of transmitting the long packet service and the K short packet services is minimum; and performing resource allocation on the sub-channel of the target system based on the target resource allocation mode. The target resource allocation mode is obtained through the method, so that the target system after resource allocation can complete data packet transmission of the long packet service and the K short packet services at the transmission rate as high as possible.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a resource allocation method, apparatus, device, medium, and program product. Background Technology

[0002] Current multiple access technologies are broadly divided into orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA). OMA allocates an independent subcarrier to each transmitted service, preventing interference between services and ensuring transmission reliability. However, as the number of connected devices in the network gradually increases, spectrum resources become insufficient, making it impossible to provide an independent subcarrier for each access device. Non-orthogonal multiple access can increase the number of connected devices and has gradually become the mainstream communication technology.

[0003] 5G has proposed the Ultra Reliable Low Latency Communications (URLLC) scenario. However, if the decoding order is determined based on channel conditions in the traditional NOMA, the following impact will occur: Since long packet services wait for an entire resource block (RB) to be transmitted before being decoded, if URLLC services need to wait for long packet services to be decoded before they can be decoded, then more time will be required, which may result in a large latency that cannot meet the low latency requirements. Summary of the Invention

[0004] This application provides a resource allocation method, apparatus, device, medium, and program product that can solve the problem of large latency that may occur in existing non-orthogonal multiple access systems.

[0005] In a first aspect, embodiments of this application provide a resource allocation method, the method comprising:

[0006] Obtain the channel information of the target system, which includes M sub-channels, each of which has long packet services and K short packet services, where M and K are integers greater than 1;

[0007] Based on the channel information, a first decoding order is determined for the K sub-services corresponding to the long packet service and the K short packet services. The K sub-services are services split from the long packet service. The packet length of the data packets of the K sub-services corresponds one-to-one with the packet length of the data packets of the K short packet services. The sub-services and the data packets of the corresponding short packet services with the same packet length are simultaneously transmitted through the same time-frequency resource block corresponding to the same sub-channel. Under the first decoding order, the transmission rate of the target system is maximized.

[0008] Based on the channel information and the first decoding order, a target resource allocation method is determined when the transmission power of the target system for transmitting the long packet service and the K short packet services is minimized. The target resource allocation method is used to indicate the transmission power and packet length of the long packet service and the transmission power and packet length of the short packet service.

[0009] Resource allocation is performed on the sub-channels of the target system based on the target resource allocation method.

[0010] Secondly, embodiments of this application also provide a resource allocation device, the device comprising:

[0011] The first acquisition module is used to acquire the channel information of the target system, wherein the target system includes M sub-channels, each of which has long packet services and K short packet services, where M and K are integers greater than 1;

[0012] The first determining module is used to determine, based on the channel information, a first decoding order of the K sub-services corresponding to the long packet service and the K short packet services. The K sub-services are services split from the long packet service. The packet lengths of the data packets of the K sub-services correspond one-to-one with the packet lengths of the data packets of the K short packet services. The sub-services and the data packets of the corresponding short packet services with the same packet length are simultaneously transmitted through the same time-frequency resource block corresponding to the same sub-channel. Under the first decoding order, the transmission rate of the target system is maximized.

[0013] The second determining module is used to determine, based on the channel information and the first decoding order, the target resource allocation method when the transmission power of the target system for transmitting the long packet service and the K short packet services is minimized. The target resource allocation method is used to indicate the transmission power and data packet length of the long packet service and the transmission power and data packet length of the short packet service.

[0014] The allocation module is used to allocate resources to the sub-channels of the target system based on the target resource allocation method.

[0015] Thirdly, embodiments of this application also provide an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the resource allocation method as described in the first aspect.

[0016] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the resource allocation method as described in the first aspect.

[0017] Fifthly, a computer program product is provided, including computer instructions that, when executed by a processor, implement the steps of the resource allocation method as described in the first aspect.

[0018] In this embodiment of the application, the resource allocation method involves splitting a long packet service into K sub-services of equal length, each corresponding to a short packet service. The transmission process of each sub-service and its corresponding short packet service can then be considered a NOMA transmission process of equal packet length. By analyzing this NOMA transmission process using channel information, the decoding order with the highest transmission rate for each sub-service and its corresponding short packet service can be determined. This determines the first decoding order with the highest transmission rate for the K sub-services and the K short packet services. Furthermore, under the first decoding order, the data packet transmission process of the K sub-services and the K short packet services is further analyzed using channel information to obtain the target resource allocation method. This allows the target system, after resource allocation, to complete the data packet transmission of the long packet service and the K short packet services at the highest possible transmission rate, thereby reducing latency. Furthermore, by splitting the transmission of long packet services and short packet services into K sub-services and K equal-length NOMA transmission processes corresponding to K short packet services, the situation in the prior art where long packet services wait for the entire RB to be transmitted before unified decoding can be avoided, which can reduce the waiting time required for decoding and thus reduce latency. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is one of the flowcharts illustrating the resource allocation method provided in the embodiments of this application;

[0021] Figure 2 This is a schematic diagram of the structure of the target system provided in the embodiments of this application;

[0022] Figure 3 This is a second flowchart illustrating the resource allocation method provided in the embodiments of this application;

[0023] Figure 4 This is a schematic diagram of the structure of the resource allocation device provided in the embodiments of this application;

[0024] Figure 5 This is a structural diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] This application provides a resource allocation method for NOMA resource allocation, where the resources can be power or the packet length of the transmitted data packets. NOMA is mainly divided into two categories: Power Domain Non-Orthogonal Multiple Access (PD-NOMA) and Code Domain Non-Orthogonal Multiple Access. PD-NOMA has attracted much attention from researchers due to its simple design and significant capabilities. PD-NOMA technology provides communication services to multiple users simultaneously through power domain multiplexing. The base station determines the power coefficient based on the channel quality between it and the user, and can simultaneously provide services to a nearby user and a distant user. To achieve higher system utility, traditional NOMA allocates more power to users with weak channels, directly decoding them upon reception. For users with strong channels, Successive Interference Cancellation (SIC) technology must be used to first decode and recover the data of the user with weak channels, then subtract the data of the user with weak channels from the received signal before recovering its own information. The uplink system is completely opposite to the downlink system, allocating more power to nearby users and less power to distant users. Non-orthogonal multiple access can simultaneously meet the communication needs of two or more users on the same frequency band, significantly increasing the number of IoT connections.

[0027] See Figure 1 , Figure 1 This is a flowchart illustrating the resource allocation method provided in an embodiment of this application. The method includes the following steps:

[0028] Step 101: Obtain the channel information of the target system. The target system includes M sub-channels, each of which has long packet services and K short packet services, where M and K are integers greater than 1.

[0029] In this step, the channel information includes the channel conditions of the data packet, the bit error rate tolerance of the data packet, the signal-to-dryness ratio of the data packet, and the minimum rate requirement of the data packet. The channel conditions include the channel coefficient, commonly represented by h, |h|. 2 It can be understood as the attenuation ratio of signal power (including the superposition of all effects such as distance, fading, and shadow).

[0030] Figure 2The diagram below shows the model of the target system. The target system has M independent sub-channels. Each sub-channel has one long packet service and K short packet services multiplexed using PD-NOMA technology. The different short packet services do not overlap in the time domain.

[0031] In the description of this application, a Resource Element (RE) refers to a time-frequency resource block consisting of one subcarrier in the frequency domain and one Orthogonal Frequency Division Multiplexing (OFDM) symbol in the time domain. An RB refers to a time-frequency resource block consisting of one subcarrier in the frequency domain and multiple OFDM symbols in the time domain; the specific number of symbols depends on the uplink / downlink time slot ratio in a Time Division Duplex (TDD) system or the length of one transmission cycle in a Frequency Division Duplex (FDD) downlink system.

[0032] Defineable sets This represents the set of time-frequency resource blocks available for service transmission. This represents the set of all short-packet devices that need to provide services. Assume each time-frequency resource block... If the number of short packet users requiring service from the base station is K, then MK = U. The data packets sent by the base station to the K short packet users are denoted as data packet m1, data packet m2, data packet m3, and so on, where the length of the kth data packet is... The rate is Define a set In any time-frequency resource block m, the central base station provides services to short packet users sequentially according to their short packet sequence numbers, with different short packet services not overlapping in the time domain. Assume the system allocates power P to the m-th sub-channel. m The long packet service transmission power is Long-term contract service speed is The transmission power of the short packet service is Obviously there is Established.

[0033] Step 102: Based on the channel information, determine the first decoding order of the K sub-services corresponding to the long packet service and the K short packet services. The K sub-services are services split from the long packet service. The packet length of the data packets of the K sub-services corresponds one-to-one with the packet length of the data packets of the K short packet services. The sub-services and the data packets of the corresponding short packet services with the same packet length are sent simultaneously through the same time-frequency resource block corresponding to the same sub-channel. Under the first decoding order, the transmission rate of the target system is maximized.

[0034] In this step, for long packet services, since they are reused in different time periods and with different short packet services, the long packet service can be simulated as "split". In the m-th time-frequency resource block, the long data packet is regarded as K sub-data packets, and the packet length of the k-th data sub-packet is equal to the packet length of the k-th short packet service. After the "split" process, the rate of the long packet service will be represented by the equivalent rate.

[0035] Since the packet length of the sub-services in the long packet service is equal to the packet length of the corresponding short packet service, the weight of the equivalent rate of the long packet service is also the same as that of the corresponding short packet service, which can be expressed as α. m，k This is explained by the concept of "splitting." After "splitting," the data packets of any sub-service and a corresponding short-packet service can be considered as a single NOMA transmission process of equal packet length. Therefore, based on channel information, this single NOMA transmission process of equal packet length can be analyzed to obtain the first decoding order of the two equal-packet-length data packets (the transmission rate of the two equal-packet-length data packets is maximized under the first decoding order). This allows us to obtain the first decoding order of K sub-services and K short-packet services, i.e., the first decoding order of long-packet services and K short-packet services.

[0036] It should be noted that by splitting the transmission of long packet services and short packet services into K sub-services and K equal-length NOMA transmission processes corresponding to K short packet services, the situation in the prior art where long packet services wait for the entire RB to be transmitted before unified decoding can be avoided. This can reduce the waiting time required for decoding, thereby reducing latency.

[0037] Step 103: Based on the channel information and the first decoding order, determine the target resource allocation method when the transmission power of the target system for transmitting the long packet service and the K short packet services is minimized. The target resource allocation method is used to indicate the transmission power and data packet length of the long packet service and the transmission power and data packet length of the short packet service.

[0038] In this step, under the condition that the long packet service and K short packet services are decoded in the first decoding order, the transmission power and data packet length of the target system transmitting the long packet service and short packet service respectively are analyzed by integrating channel information to obtain the transmission power and data packet length corresponding to the long packet service and short packet service when the transmission power is minimized.

[0039] Solving the problem of how to allocate the target resources can be equivalent to the following problem:

[0040] In the target system, a time-frequency resource block (RB) is the smallest unit of resource allocation. Within the same RB, the transmission power of long-packet and short-packet services remains constant. Matching of short-packet services with sub-channels on m sub-channels has been completed, and services with similar reliability requirements and channel quality are allocated to the same sub-channel. This paper proposes an optimization problem aiming to maximize the system sum and rate (the sum of the transmission rates of long-packet and short-packet services). as follows:

[0041]

[0042] in, N represents the rate weight for short-package services in calculation and rate calculation. l This indicates the length of a long packet service, and is also the maximum transmission packet length on an RB. P represents the maximum transmission power of the base station. This represents the lower limit of the rate for the k-th short packet service on the m-th RB (e.g., the first minimum rate requirement and the second minimum rate requirement in subsequent embodiments). Indicates bit error rate, This indicates the tolerance for bit error rate. Typically, short packet services (such as URLLC) have high reliability requirements. Therefore, this application considers the bit error rate tolerance of short packet services to be... Far less than the error rate tolerance of long-term packet services

[0043] Step 104: Allocate resources to the sub-channels of the target system based on the target resource allocation method.

[0044] In this step, the resources of the sub-channels of the target system are allocated according to the target resource allocation method, so that the target system after resource allocation can complete the data packet transmission of long packet service and K short packet service at the highest possible transmission rate, thereby reducing latency.

[0045] In the resource allocation method of this application embodiment, after simulating the splitting of long packet services into K sub-services of equal packet length corresponding one-to-one with K short packet services, the transmission process of the sub-services and their corresponding short packet services can be regarded as a NOMA transmission process of equal packet length. By analyzing the NOMA transmission process of equal packet length in combination with channel information, the decoding order with the highest transmission rate of the sub-services and their corresponding short packet services can be determined, thereby determining the first decoding order with the highest transmission rate of the K sub-services and the K short packet services. Then, under the condition of the first decoding order, the data packet transmission process of the K sub-services and the K short packet services is further analyzed in combination with channel information to obtain the target resource allocation method. This enables the target system after resource allocation to complete the data packet transmission of long packet services and K short packet services at the highest possible transmission rate, thereby reducing latency.

[0046] Optionally, determining the first decoding order of the K sub-services corresponding to the long packet service and the K short packet services based on the channel information includes:

[0047] Obtain a first service and a second service, wherein the first service is any one of the K sub-services, and the second service is a service among the K short packet services whose data packet length is equal to that of the first service;

[0048] Obtain from the channel information the first channel condition, the first bit error rate tolerance, and the first minimum rate requirement corresponding to the first service, and obtain the second channel condition, the second bit error rate tolerance, and the second minimum rate requirement corresponding to the second service;

[0049] Based on the first channel conditions, the first bit error rate tolerance, the first minimum rate requirement, the second channel conditions, the second bit error rate tolerance, and the second minimum rate requirement, determine the first decoding order of the first service and the second service;

[0050] Based on the first decoding order of each of the first service and the second service, the first decoding order of the K sub-services and the K short packet services is determined.

[0051] Since users have different levels of reliability, the decoding order becomes a critical issue. In this embodiment, by determining the first decoding order with the highest transmission rate between the first service and the second service, it can be extended to K sub-services and K short packet services.

[0052] For any NOMA transmission process of equal packet length, the two services are labeled as service 1 and service 2, respectively. The corresponding two data packets and receiving devices are labeled as data packet 1 and data packet 2, device 1 and device 2, respectively. The power allocated by the base station to the two services is P. iThe channel conditions from the base station to the two service receiving devices are h i Both services have a data packet length of N and a bit error rate tolerance of θ. i The signal-to-interference-plus-noise ratio is Γ i The speed is R i Since the packet lengths of both services are finite, their rate expressions are as follows:

[0053]

[0054] Among them, Q -1 (·) is the inverse function of the right-tail function of the standard normal distribution. The rates of the first service and the second service can be determined by the first channel conditions, the first bit error rate tolerance, the first minimum rate requirement, the second channel conditions, the second bit error rate tolerance, and the second minimum rate requirement, thereby determining the first decoding method.

[0055] In this embodiment, the rates of the first service and the second service are analyzed by relevant content in the channel information to determine the first decoding method.

[0056] Furthermore, since the first decoding method maximizes the sum of the two service rates, an optimization problem can be proposed with the objective of maximizing the sum of the two service rates as follows:

[0057]

[0058] Record as a problem Where, r i This indicates the minimum rate requirement.

[0059] Optionally, determining the first decoding order of the first service and the second service based on the first channel conditions, the first bit error rate tolerance, the first minimum rate requirement, the second channel conditions, the second bit error rate tolerance, and the second minimum rate requirement includes:

[0060] Obtain a second decoding order, wherein the second decoding order is either to decode the data packet of the second service first and then decode the data packet of the first service, or to decode the data packet of the first service first and then decode the data packet of the second service.

[0061] Based on the first minimum rate requirement and the second minimum rate requirement, a first condition is determined, which is used to indicate that the data packet sending rate of the first service is less than or equal to the first minimum rate requirement, and to indicate that the data packet sending rate of the second service is less than or equal to the second minimum rate requirement.

[0062] Based on the first channel condition, the second channel condition, and the channel noise power of the target system obtained in advance, the first condition is equivalent to the second condition under the second decoding order. The second condition is used to indicate that the signal-to-dryness ratio of the service decoded first is greater than or equal to the first preset threshold, and to indicate that the signal-to-dryness ratio of the service decoded later is greater than or equal to the second preset threshold.

[0063] Based on the second condition and the third condition corresponding to the second decoding order, a fourth condition is determined. The third condition is used to indicate that the bit error rate of the later decoded service is the sum of the first bit error rate and the second bit error rate. The first bit error rate is the bit error rate of the earlier decoded service under the influence of channel noise and the interference of the later decoded service. The second bit error rate is the bit error rate of the later decoded service under the influence of channel noise. The fourth condition is used to indicate that the decoding reliability requirement of the earlier decoded service is greater than the decoding reliability requirement of the later decoded service. The decoding reliability requirement is related to the first bit error rate tolerance or the second bit error rate tolerance.

[0064] Based on the second condition, the fourth condition, and the second decoding order, the first decoding order is determined, wherein the first decoding order is either the second decoding order or the decoding order opposite to the second decoding order.

[0065] It should be noted that, because the target system uses non-orthogonal transmission, the problem... The optimization objective is a non-convex function of power. Furthermore, service equipment detecting the required signal using SIC technology can be interfered with by other services, especially when the later-decoded signal has high reliability requirements; this interference can severely impact decoding reliability. In this embodiment, analyzing the impact of earlier-decoded services on later-decoded services can improve the reliability of the determined first decoding order.

[0066] The NOMA decoding order for the two services includes two possibilities, as shown in Table 1:

[0067] Table 1: NOMA Decoding Order

[0068]

[0069] The following uses decoding method 1 in Table 1 (where the service decoded first is the second service and the service decoded later is the first service) as an example to illustrate the method of this embodiment:

[0070] In this embodiment, the first condition is associated with the first minimum rate requirement and the second minimum rate requirement. The first condition can be expressed as follows:

[0071] R i ≥r i i = 1, 2;

[0072] In this application, the transmission rates of the first and second services are finite block length (FBL) rates. Based on the FBL rate, proposition 1 can be proposed: In the FBL rate, for short data packets with a signal-to-interference-plus-noise ratio (SINR), under the given constraints of data packet length and block error rate, the FBL rate is a concave function of SINR and also a monotonically increasing function of SINR.

[0073] Therefore, the first condition R i ≥r i It can be based on the first channel condition, the second channel condition, and the channel noise power. (The channel noise is additive white Gaussian noise), which can be equivalently represented by the second condition:

[0074]

[0075] Wherein, γ1 and γ2 are the first preset threshold and the second preset threshold, respectively.

[0076] In non-orthogonal multiple access (NOMA), the reliability of post-decoding services depends not only on the signal-to-interference-plus-noise ratio (SIRR) but also on the reliability of pre-decoding services.

[0077] For the device requiring SIC technology detection, let's assume this device is designated as Device 1. Device 1 must first recover the first data packet, then the second data packet, and the decoding reliability of the first data packet is affected by the decoding reliability of the second data packet. At the receiving end of Device 1, define ε... 2，1+n ε represents the bit error rate of the second data packet under the interference of the first data packet and the influence of channel noise. 1，n Let represent the bit error rate of data packet A under the influence of channel noise. Based on this, the equivalent third condition can be obtained:

[0078] ε1=ε 2，1+n +(1-ε 2，1+n )ε 1，n ;

[0079] Since ε1>ε 2，1+n Therefore, to ensure the decoding reliability of the later-decoded data packets, a higher reliability requirement must be imposed on the earlier-decoded data packets than on the later-decoded data packets. This leads to the fourth condition:

[0080]

[0081] in, θ1 / δ represents the bit error rate of the second service decoding at device A. ε，1 To ensure the reliability of the first service, a higher constraint is imposed on the bit error rate tolerance of the second service, δε，1 The preset parameter is greater than 1.

[0082] After obtaining the second and fourth conditions mentioned above, the second decoding order can be analyzed to determine the first decoding order.

[0083] Optionally, determining the first decoding order based on the second condition, the fourth condition, and the second decoding order includes:

[0084] Based on the second condition, the fourth condition is equivalent to the fifth condition, which is used to indicate that the information-to-dryness ratio of the service being decoded first is greater than or equal to the first parameter. The first parameter is determined based on the first preset threshold and is greater than the first preset threshold.

[0085] The second parameter is determined based on the ratio of the channel noise corresponding to the first channel condition to the channel noise corresponding to the second channel condition;

[0086] The third parameter is determined based on the fifth condition, the first preset threshold, and the second preset threshold;

[0087] If the value of the second parameter is less than the value of the third parameter, the second decoding order is determined as the first decoding order; or, if the value of the second parameter is greater than the value of the third parameter, the decoding order opposite to the second decoding order is determined as the first decoding order.

[0088] In this embodiment, based on the characteristics of FBL, Proposition 2 can be proposed: In FBL, when the data packet rate and packet length are fixed, a sufficient condition for the bit error rate to not exceed the tolerance is that the signal-to-interference-plus-noise ratio exceeds a certain threshold. That is...

[0089] Based on Proposition 2, the sufficient condition (i.e., the fifth condition) for the formula corresponding to the fourth condition can be obtained as follows:

[0090]

[0091] in, The first parameter represents the signal-to-interference-plus-noise ratio constraint threshold in the formula corresponding to the fourth condition, based on the equivalent transformation of Proposition 2. To be with δ ε，1 The corresponding preset parameters.

[0092] Regarding the aforementioned problem The corresponding power minimization problem can be given. as follows:

[0093]

[0094] Regarding the question Proposition 3 can be proposed: The optimal decoding order of a two-user NOMA system is related to the channel conditions. If the channel conditions satisfy:

[0095]

[0096] The target system then uses decoding method 2 (the decoding order opposite to the second decoding order); otherwise, it uses decoding method 1 (the second decoding order). For the second parameter, This is the third parameter.

[0097] It should be noted that, for ease of description, the first service is assumed to be enhanced mobile broadband (eMBB) with long packets, and the second service is URLLC with short packets. Their reliability requirements are shown in Table 2.

[0098] Table 2 Reliability Indicators for Different Business Types

[0099] Business type Reliability requirements eMBB 99.9％ URLLC 99.9999％

[0100] Based on Table 2, Proposition 4 can be proposed: For the 2-user NOMA problem With users randomly distributed, reliability metrics conforming to Table 2, and path loss of [value missing], Under the premise that Prob{X h With a sum of ≥J}≈0.9, there is a 90% probability that prioritizing the decoding of services with high reliability requirements (decoding method 2) will result in a higher sum rate.

[0101] Based on Proposition 4, Proposition 5 can be proposed: the problem given by Proposition 4. The optimal decoding order and discrimination threshold of the system also apply to maximizing the sum and rate objectives, that is, they also apply to the problem. Solve for it.

[0102] Due to Prob{X h Since ≥J}≈0.9, in other words, there is only a 10% probability that choosing decoding method 1 will achieve higher system efficiency. For the transmission scenario where K short packet services are multiplexed with long packet services on the same time-frequency resource block RB, it is necessary to ensure that the power of long and short packet services transmitted within that time slot remains constant. Similarly, the NOMA decoding order within that time slot should also remain unchanged. Therefore, from the perspective of the overall system, choosing to decode services with high reliability requirements first (decoding method 2) can achieve higher system efficiency and speed.

[0103] This embodiment determines the first decoding order corresponding to the case where the sum of the data packets of the first and second services reaches the maximum rate. This allows the subsequent target system to allocate resources according to the target resource allocation method determined by the first decoding order, thereby reducing latency. This embodiment enables the joint transmission of long and short packets. In this process, the short packet service with higher reliability is decoded first, and a higher reliability requirement is set for the first-decoded service than for the later-decoded service, ensuring the reliability of the short packet service transmission. Furthermore, multiple short packet services are allowed to share the same Resource Block (RB), and from the perspective of adapting to the existing network, the total frame length of the short packet services is required not to exceed the maximum frame length of one RB, ensuring compatibility. In addition, due to the use of non-orthogonal multiple access technology, more devices can be connected within a limited frequency band.

[0104] Optionally, determining the target resource allocation method for the target system under the condition of minimum transmit power based on the channel information and the first decoding order includes:

[0105] Obtain a first power allocation factor corresponding to the first service and a second power allocation factor corresponding to the second service from the channel information, wherein the sum of the first power allocation factor and the second power allocation factor is 1;

[0106] Based on the first power allocation factor, the first channel condition, and the channel noise power, the first rate of the first service is determined.

[0107] Based on the second power allocation factor, the second channel conditions, the channel noise power, and the second bit error rate tolerance, the second rate of the second service is determined.

[0108] The correction terms of the first rate and the second rate are subjected to continuous convex approximation processing to obtain the sum rate function of the sum of the first rate and the second rate. The Hessian matrix of the sum rate function with respect to the sum of the power of the first service and the second service is a negative definite matrix, and the sum rate function is a joint concave function with respect to the sum of the power of the first service and the second service.

[0109] Based on the sum rate function and the first decoding order, the target resource allocation method corresponding to the first service and the second service is determined;

[0110] The target resource allocation method is determined based on the target resource allocation method for each of the first service and the second service.

[0111] In this embodiment, given the first decoding order, the optimal sum rate and optimal power allocation are:

[0112]

[0113] Having derived the optimal power allocation design function for the two-user NOMA above, we only need to assume the sum of the power of any long packet data sub-packet and its corresponding short packet to calculate the optimal transmission power for both long and short packet services.

[0114] Back to the question Assume the total transmission power of the m-th sub-channel is P. m Therefore, the total transmit power P can be calculated based on the optimal power allocation design function for the two-user NOMA. m The transmission power of each long packet service and short packet service on the m-th sub-channel can be denoted as follows: and Take β m Let be the power allocation factor. Therefore, the optimal power allocation for long-packet and short-packet services transmitted on the m-th RB is:

[0115]

[0116] Where, β m For the first power allocation factor, 1-β m Let be the second power allocation factor; take and This represents the minimum transmission power for long-packet and short-packet services on the i-th RB, provided that the constraints are satisfied. Therefore:

[0117]

[0118] The rates (first rate) and short packet rates (second rate) of the k-th data sub-packet in the m-th time-frequency resource block are respectively:

[0119]

[0120] Consider using Successive Convex Approximation (SCA) to approximate the correction term in the FBL rate formula for services with high reliability requirements. An approximate solution to the original problem is obtained through multiple iterations, as follows:

[0121] definition:

[0122] P = [P1 P2 … P] M-1 P M ] T ;

[0123]

[0124]

[0125] After approximation by convexity, we can obtain:

[0126]

[0127] Due to the function g (n) (P) is an M-variable linear function after first-order Taylor expansion approximation, taking:

[0128]

[0129] in, n represents the number of iterations. Based on the above, the sum rate function can be obtained as:

[0130]

[0131] R all Regarding P m The Hessian matrix is ​​a negative definite matrix, R all It's about P m Joint concave functions:

[0132]

[0133] Therefore, the problem is addressed through this embodiment. This becomes a convex optimization problem, based on the sum rate function and the first decoding order pair problem. Further analysis can determine the target resource allocation methods for the first and second business segments.

[0134] Optionally, determining the target resource allocation method corresponding to the first service and the second service based on the sum rate function and the first decoding order includes:

[0135] Based on the sum-rate function, determine the optimal power allocation function for the first service and the second service;

[0136] Based on the first rate and the second rate, a packet length function is constructed, wherein the Hessian matrix of the packet length function with respect to the packet length of the second service is a positive definite matrix.

[0137] Based on the preset service instruction QoS conditions, the constraints for determining the packet length of the second service are determined;

[0138] Based on the packet length function and the constraints of the packet length of the second service, the optimal packet length function of the second service is determined;

[0139] The optimal packet length function and the optimal allocation function are iterated to determine the sum of the minimum transmission power of the first service and the second service, and to determine the packet length of the second service;

[0140] The minimum transmission power of the first service and the minimum transmission power of the second service are determined based on the sum of the minimum transmission powers, the first power allocation factor, and the second power allocation factor.

[0141] In this embodiment, the problem is solved by using the sum and rate function. As a convex optimization problem, its optimal power allocation function is:

[0142]

[0143] in, Representation function The inverse function of . According to Proposition 1, yes and P m A one-to-one mapping between them. Finally, find the appropriate... satisfy That's all.

[0144] Based on the first rate and the second rate, a packet length function can be constructed:

[0145]

[0146] because The equivalent rate weight is affected by the packet length of short-packet services, therefore, α v，k It can no longer be considered a constant. Calculations show that... about The Hessian matrix is ​​a positive definite matrix. For QoS conditions, there are also equivalent constraints (constraints on the packet length of the second service) as follows:

[0147]

[0148] in, The optimal packet length function is:

[0149]

[0150] in,

[0151] After determining the optimal packet length function and the optimal power allocation function, P is iterated alternately. m and Until convergence, the problem is obtained. The optimal solution is the sum of the minimum transmission powers of the first service and the second service, and the packet length of the second service is determined. The packet lengths of the first service and the second service are the same, and the minimum transmission powers of the first service and the second service are the product of the sum of the minimum transmission powers and the first power allocation factor, and the product of the sum of the minimum transmission powers and the second power allocation factor, respectively.

[0152] like Figure 3 As shown, the target resource allocation method for long-package transactions and K short-package transactions can be summarized into the following steps:

[0153] Obtain channel conditions; group short packet services; split long packet services into K sub-services; analyze the transmission process of the sub-services and their corresponding short packet services (which can be regarded as two user NOMA processes) to determine the first decoding order (the decoding order of the two user NOMA processes); after the first decoding order, perform power allocation for the first and second services (power allocation of the two user NOMA processes); determine the optimal packet length function and the optimal power allocation function; after iterating the optimal packet length function and the optimal power allocation function, obtain the target resource allocation method.

[0154] Furthermore, Propositions 1-5 in the above embodiments are proved by the following:

[0155] Proposition 1:

[0156] Proof: Constructor:

[0157]

[0158] Pick Since the transmission rate is non-negative in a physical sense, f must hold. r (Γ)≥0, therefore b satisfies:

[0159]

[0160] Where ln(·) denotes the logarithmic function with the natural constant e as the base, and the logarithmic function f r (Γ), the first derivative of Γ is:

[0161]

[0162] The second derivative with respect to Γ is:

[0163]

[0164] When the second derivative is not positive, f r (Γ) is a concave function of Γ, and f r The first derivative of (Γ) is monotonically decreasing with respect to Γ, and the corresponding range of b is:

[0165]

[0166] if The range of values ​​for Γ is specified in the text. The subset of the range of values ​​for Γ is defined in the standard, namely:

[0167] b≤g r (Γ)≤h r (Γ).

[0168] For any physically existing data packet transmission process, its transmission rate f r (Γ) must be a concave function of Γ. According to g r (Γ)≤h r (Γ), solving for Γ gives Γ ≥ 0.6905. At this point, g r (Γ) is a monotonically increasing function of Γ, therefore b ≤ min{g r (Γ)}=g r (0.6905) = 0.6512, at this time, the function f r The first derivative of (Γ) with respect to Γ is always positive, therefore, f r (Γ) is an increasing function of Γ. Proof complete.

[0169] Proposition 2:

[0170] prove:

[0171] Define a function:

[0172]

[0173] For f er Differentiating (Γ) with respect to Γ, we get:

[0174]

[0175] Since the signal-to-interference-plus-noise ratio Γ≥ and Γ≥log(1+Γ) always holds true, therefore:

[0176]

[0177] f er (Γ) is a monotonically decreasing function of Γ. Therefore, for any θ0, there must exist a suitable Γ0 such that when Γ≥Γ0, the bit error rate ε corresponding to Γ always satisfies ε≤θ0. Proof complete.

[0178] Proposition 3:

[0179] Proof: Define the function:

[0180]

[0181] If max{v1, v2} > max{v3, v4}, then decoding method 2 requires less power, and the system should use decoding method 2. Define a set. This indicates that v satisfies i >v j Channel conditions X h From the set of possible values, we can derive:

[0182]

[0183] Define a set This represents the channel ratio X of two users when decoding method i is selected. h Given the set of values, we get Φ2={Φ 13 ∪Φ 14}∩{Φ 23 ∪Φ 24}∩{Φ 13 ∪Φ 24}∩{Φ 14 ∪Φ 23}, given δ γ，2 ≥0, δ γ，1 ≥0, γ1>γ2>0, therefore Simplifying, we get:

[0184] Φ2={X h |X h >min{J3, max{J1, J2}}};

[0185] Since it is assumed that the reliability of the first service is much higher than that of the second service, in decoding method 2, it can be basically assumed that the reliability impact caused by the first decoded signal A when device B recovers the signal is negligible. That is, δ γ，2 =0, therefore J2 < J1 < J3

[0186]

[0187] Pick Represents the set of positive real numbers, since Then we have:

[0188]

[0189] The proof is complete.

[0190] Proposition 4:

[0191] Proof: The optimal decoding order and discrimination threshold for a system with the goal of minimizing power consumption given in Proposition 3 also apply to the goal of maximizing sum and rate. Therefore, as shown in Table 3, there are the following three transmission scenarios.

[0192] Table 3 Comparison of Different Channel Conditions and Decoding Methods

[0193] Transmission status Channel conditions Decoding method at the receiving end 1 <![CDATA[0<X h ≤J]]> Decoding method 1 2 <![CDATA[1<X h ]]> Decoding method 2 3 <![CDATA[J<X h ≤1]]> Decoding method 2

[0194] Since J is given in the form of an expression, we can consider obtaining a rough range of values ​​for J by providing specific reliability values. For δ... γ，1Generally, when the signal-to-interference-plus-noise ratio (SNR) of the first decoded signal is more than 5 dB better than that of the second decoded signal, their bit error rates are on the same order of magnitude. Therefore, it can be considered that the first decoded signal has little impact on the anti-interference performance of the second decoded signal. Based on the reliability requirements in Table 2, J≈0.05. According to the path loss formula given in the literature... Assuming two users are uniformly distributed within a circular cell with a radius of 500m, then Prob{X} h ≥J}≈0.9, in other words, there is only a 10% probability that choosing decoding method 1 will result in higher system utility.

[0195] Considering that K short packet services are multiplexed with long packets on the same time-frequency resource block (RB), it is necessary to ensure that the power of long packet services and short packet services transmitted within this time slot remains constant. Similarly, the NOMA decoding order within this time slot should also remain unchanged. Since for each equal-length transmission packet, Prob{X} h Since ≥J}≥0.9, from the perspective of the overall system, choosing to decode services with high reliability requirements first can achieve higher system performance and speed. The data rate corresponding to decoding method 2 is:

[0196]

[0197] Observation shows that, for a given P2, R1 is a monotonically increasing function of P1. Therefore, to maximize the sum rate, P1 must be increased as much as possible to achieve a higher sum rate. Thus, we must have:

[0198] P1 + P2 = P;

[0199] QoS can be equivalent to:

[0200]

[0201] Define R sum =R1+R2, because the FBL correction term contains roots and fractions, obtaining an analytical solution is extremely difficult. Consider mathematical approximation. have:

[0202]

[0203] in, Considering that long packet traffic is not sensitive to bit error rate, the bit error rate correction term for long packet traffic can be basically ignored. sum Taking the derivative with respect to P2, we get:

[0204]

[0205] Since the channel strength relationship between the two services affects the optimal power allocation of the system, we consider conducting research from different channel conditions.

[0206] When the channel for the first service is weaker than the channel for the second service, the corresponding transmission condition is 2, where 1 < X. h If |h2| > |h1|, then we have:

[0207]

[0208] Therefore, the system and rate are monotonically increasing with respect to P2. The optimal transmission power for the second service is the upper bound of the QoS value, and the range of P2 is:

[0209]

[0210] The optimal power allocation for the system is:

[0211]

[0212] When the channel strength of the first service is greater than that of the second service, this corresponds to transmission scenario 3. At this point, the optimal sum and rate of the system are:

[0213]

[0214] The optimal transmission power for the second service is:

[0215]

[0216] because The optimal power allocation given still needs to compare the sum rate of the two ends of P2. Therefore, we will continue to explore the optimal transmission power under high signal-to-noise ratio conditions. Comparing the two items, we have:

[0217]

[0218] Therefore, at high signal-to-noise ratios, achievable When the channel strength of the first service is greater than that of the second service, the optimal transmission power of the second service is also the upper bound of the QoS requirement. Proof complete.

[0219] Proposition 5:

[0220] Proof: For a two-user downlink non-orthogonal multiple access system, without loss of generality, assume that user 1 directly decodes, and user 2 first decodes to recover user 1's signal, then recovers user 2's signal. For the optimization problem... Assume the optimal objective value of the problem, the transmission power, data rate, and signal-to-interference-plus-noise ratio (SINNR) for user i to reach the optimal solution are respectively... and and It can be known It's a problem A set of feasible solutions. Assume the problem... The optimal target value, the transmission power, rate, and signal-to-interference-plus-noise ratio when user i reaches the optimal solution are P′, P. i ′, R i ′ and Γ i If P' ≤ P, then:

[0221]

[0222] Take Δ P =PP′, then for a set of power allocations:

[0223]

[0224] On the issue Verifying the constraints, it is clear that:

[0225]

[0226] That is, this power allocation satisfies the problem. All constraints can be considered as a problem. A feasible solution is given. Assume the relationship between the signal-to-interference-plus-noise ratio (SIR) and the data rate for user i is... At this point, the system and its rate, as well as the optimal rate, are... The difference is:

[0227]

[0228] Whether using the Shannon rate formula or the FBL formula, the rate is an increasing function of the signal-to-interference-plus-noise ratio (SINR), therefore:

[0229]

[0230] However, the previous assumption It's a problem The optimal solution achieves the maximum sum and speed of the system when the total power consumption is P. Therefore:

[0231]

[0232] comprehensive and Δ R =0, and thus Δ P=0, that is, P = P′. Since this proposition does not specify the channel, this conclusion always holds for any channel. Considering the arbitrariness of the channel, in order to satisfy Δ at all times... P =0, there must be:

[0233]

[0234] Therefore, in the problem The optimal Γ i yes At that time, the problem and the problem They have the same optimal solution. For any two-user NOMA system, suppose the optimal decoding order obtained from Proposition 4 is m. Without loss of generality, assume that this decoding order is that user 1 decodes directly, and user 2 decodes first to recover user 1's signal, and then recovers user 2's signal.

[0235] For a decoding order n (n≠m) that is different from the decoding order m, assume the maximum transmission power is P. n It is certain that the problem can be solved. To obtain the optimal signal-to-interference-plus-noise ratio User Power and system and rate This inevitably leads to an equivalent optimization problem. Correspondingly.

[0236] According to Proposition 4, when the decoding order is m, less power consumption P can be used. m To reach the same Γ i That is, to achieve a decoding order n with a power consumption of P n The system's maximum sum rate R at that time * Let the power of user 1 and user 2 at this time be respectively and Δ P ′=P n -P m This represents the remaining power. When the decoding order is [order] and User 1's power is [power], [this indicates that the remaining power is not specified]. User 2's power is At this time, the system and the rate R m Maximum sum rate when using decoding order n The difference is:

[0237]

[0238] If and only if |h e | 2 =J|h u | 2Equality holds. Therefore, in the problem of maximizing the system sum and rate of two-user downlink non-orthogonal multiple access given a total transmit power, the optimal decoding order always achieves a higher system sum and rate under the same power consumption and constraints compared to a non-optimal decoding order. Proof complete.

[0239] Based on the resource allocation method of this embodiment, the following algorithm can be designed:

[0240] Input: Channel noise power Maximum transmit power P, channel conditions and Error rate constraints for short packet services Rate constraints and Total contract length N l Power accuracy δ P ;

[0241] Output: Optimal transmit power P m , and Optimal packet length

[0242]

[0243]

[0244] See Figure 4 , Figure 4 This is a structural diagram of a resource allocation apparatus provided in an embodiment of this application. The apparatus 400 includes:

[0245] The first acquisition module 401 is used to acquire the channel information of the target system, wherein the target system includes M sub-channels, each of which has long packet services and K short packet services, and M and K are integers greater than 1;

[0246] The first determining module 402 is used to determine, based on the channel information, a first decoding order of K sub-services corresponding to the long packet service and K short packet services, wherein the K sub-services are services split from the long packet service, the packet length of the data packets of the K sub-services corresponds one-to-one with the packet length of the data packets of the K short packet services, and the sub-services and the data packets of the corresponding short packet services with the same packet length are simultaneously transmitted through the same time-frequency resource block corresponding to the same sub-channel, and the transmission rate of the target system is maximized under the first decoding order;

[0247] The second determining module 403 is used to determine, based on the channel information and the first decoding order, the target resource allocation method when the transmission power of the target system for transmitting the long packet service and the K short packet services is minimized. The target resource allocation method is used to indicate the transmission power and data packet length of the long packet service and the transmission power and data packet length of the short packet service.

[0248] The allocation module 404 is used to allocate resources to the sub-channels of the target system based on the target resource allocation method.

[0249] Optionally, the first determining module 402 is further configured to:

[0250] Obtain a first service and a second service, wherein the first service is any one of the K sub-services, and the second service is a service among the K short packet services whose data packet length is equal to that of the first service;

[0251] Obtain from the channel information the first channel condition, the first bit error rate tolerance, and the first minimum rate requirement corresponding to the first service, and obtain the second channel condition, the second bit error rate tolerance, and the second minimum rate requirement corresponding to the second service;

[0252] Based on the first channel conditions, the first bit error rate tolerance, the first minimum rate requirement, the second channel conditions, the second bit error rate tolerance, and the second minimum rate requirement, determine the first decoding order of the first service and the second service;

[0253] Based on the first decoding order of each of the first service and the second service, the first decoding order of the K sub-services and the K short packet services is determined.

[0254] Optionally, the first determining module 402 is further configured to:

[0255] Obtain a second decoding order, wherein the second decoding order is either to decode the data packet of the second service first and then decode the data packet of the first service, or to decode the data packet of the first service first and then decode the data packet of the second service.

[0256] Based on the first minimum rate requirement and the second minimum rate requirement, a first condition is determined, which is used to indicate that the data packet sending rate of the first service is less than or equal to the first minimum rate requirement, and to indicate that the data packet sending rate of the second service is less than or equal to the second minimum rate requirement.

[0257] Based on the first channel condition, the second channel condition, and the channel noise power of the target system obtained in advance, the first condition is equivalent to the second condition under the second decoding order. The second condition is used to indicate that the signal-to-dryness ratio of the service decoded first is greater than or equal to the first preset threshold, and to indicate that the signal-to-dryness ratio of the service decoded later is greater than or equal to the second preset threshold.

[0258] Based on the second condition and the third condition corresponding to the second decoding order, a fourth condition is determined. The third condition is used to indicate that the bit error rate of the later decoded service is the sum of the first bit error rate and the second bit error rate. The first bit error rate is the bit error rate of the earlier decoded service under the influence of channel noise and the interference of the later decoded service. The second bit error rate is the bit error rate of the later decoded service under the influence of channel noise. The fourth condition is used to indicate that the decoding reliability requirement of the earlier decoded service is greater than the decoding reliability requirement of the later decoded service. The decoding reliability requirement is related to the first bit error rate tolerance or the second bit error rate tolerance.

[0259] Based on the second condition, the fourth condition, and the second decoding order, the first decoding order is determined, wherein the first decoding order is either the second decoding order or the decoding order opposite to the second decoding order.

[0260] Optionally, the first determining module 402 is further configured to:

[0261] Based on the second condition and the fourth condition, a fifth condition is determined. The fifth condition is used to indicate that the information-to-dryness ratio of the service being decoded first is greater than or equal to a first parameter. The first parameter is determined based on the first preset threshold and is greater than the first preset threshold.

[0262] The second parameter is determined based on the ratio of the channel noise corresponding to the first channel condition to the channel noise corresponding to the second channel condition;

[0263] Based on the fifth condition, the first preset threshold, and the second preset threshold, the third parameter is determined;

[0264] If the value of the second parameter is less than the value of the third parameter, the second decoding order is determined as the first decoding order; or, if the value of the second parameter is greater than the value of the third parameter, the decoding order opposite to the second decoding order is determined as the first decoding order.

[0265] Optionally, the second determining module 403 is further configured to:

[0266] Obtain a first power allocation factor corresponding to the first service and a second power allocation factor corresponding to the second service from the channel information, wherein the sum of the first power allocation factor and the second power allocation factor is 1;

[0267] Based on the first power allocation factor, the first channel condition, and the channel noise power, the first rate of the first service is determined.

[0268] Based on the second power allocation factor, the second channel conditions, the channel noise power, and the second bit error rate tolerance, the second rate of the second service is determined.

[0269] The correction terms of the first rate and the second rate are subjected to continuous convex approximation processing to obtain the sum rate function of the sum of the first rate and the second rate. The Hessian matrix of the sum rate function with respect to the sum of the power of the first service and the second service is a negative definite matrix, and the sum rate function is a joint concave function with respect to the sum of the power of the first service and the second service.

[0270] Based on the sum rate function and the first decoding order, the target resource allocation method corresponding to the first service and the second service is determined;

[0271] The target resource allocation method is determined based on the target resource allocation method for each of the first service and the second service.

[0272] Optionally, the second determining module 403 is further configured to:

[0273] Based on the sum-rate function, determine the optimal power allocation function for the first service and the second service;

[0274] Based on the first rate and the second rate, a packet length function is constructed, wherein the Hessian matrix of the packet length function with respect to the packet length of the second service is a positive definite matrix.

[0275] Based on the preset service instruction QoS conditions, the constraints for determining the packet length of the second service are determined;

[0276] Based on the packet length function and the constraints of the packet length of the second service, the optimal packet length function of the second service is determined;

[0277] The optimal packet length function and the optimal allocation function are iterated to determine the sum of the minimum transmission power of the first service and the second service, and to determine the packet length of the second service;

[0278] The minimum transmission power of the first service and the minimum transmission power of the second service are determined based on the sum of the minimum transmission powers, the first power allocation factor, and the second power allocation factor.

[0279] The resource allocation device 400 provided in this application embodiment is capable of implementing... Figure 1 The entire technical process of the resource allocation method shown is to achieve the same technical effect, and will not be described again here to avoid repetition.

[0280] The resource allocation device 400 in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. Non-mobile electronic devices can also be servers, network attached storage (NAS), personal computers (PCs), televisions (TVs), ATMs, or self-service machines, etc. This application embodiment does not specifically limit the specific type of electronic device.

[0281] Optionally, such as Figure 5 As shown, this application embodiment also provides an electronic device 500, including a processor 501 and a memory 502. The memory 502 stores a program or instructions that can run on the processor 501. When the program or instructions are executed by the processor 501, they implement the various steps of the above-described resource allocation method embodiment and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0282] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0283] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the various processes of the resource allocation method embodiments described above and achieves the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0284] This application also provides a computer program product, including computer instructions. When executed by a processor, these computer instructions implement the various processes of the above-described resource allocation method embodiments and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0285] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0286] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0287] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A resource allocation method, characterized in that, The method includes: Obtain the channel information of the target system, which includes M sub-channels, each of which has long packet services and K short packet services, where M and K are integers greater than 1; Based on the channel information, a first decoding order is determined for the K sub-services corresponding to the long packet service and the K short packet services. The K sub-services are services split from the long packet service. The packet length of the data packets of the K sub-services corresponds one-to-one with the packet length of the data packets of the K short packet services. The sub-services and the data packets of the corresponding short packet services with the same packet length are simultaneously transmitted through the same time-frequency resource block corresponding to the same sub-channel. Under the first decoding order, the transmission rate of the target system is maximized. Based on the channel information and the first decoding order, a target resource allocation method is determined when the transmission power of the target system for transmitting the long packet service and the K short packet services is minimized. The target resource allocation method is used to indicate the transmission power and packet length of the long packet service and the transmission power and packet length of the short packet service. Resource allocation is performed on the sub-channels of the target system based on the target resource allocation method.

2. The method according to claim 1, characterized in that, The step of determining the first decoding order of the K sub-services corresponding to the long packet service and the K short packet services based on the channel information includes: Obtain a first service and a second service, wherein the first service is any one of the K sub-services, and the second service is a service among the K short packet services whose data packet length is equal to that of the first service; Obtain from the channel information the first channel condition, the first bit error rate tolerance, and the first minimum rate requirement corresponding to the first service, and obtain the second channel condition, the second bit error rate tolerance, and the second minimum rate requirement corresponding to the second service; Based on the first channel conditions, the first bit error rate tolerance, the first minimum rate requirement, the second channel conditions, the second bit error rate tolerance, and the second minimum rate requirement, determine the first decoding order of the first service and the second service; Based on the first decoding order of each of the first service and the second service, the first decoding order of the K sub-services and the K short packet services is determined.

3. The method according to claim 2, characterized in that, The step of determining the first decoding order of the first service and the second service based on the first channel conditions, the first bit error rate tolerance, the first minimum rate requirement, the second channel conditions, the second bit error rate tolerance, and the second minimum rate requirement includes: Obtain a second decoding order, wherein the second decoding order is either to decode the data packet of the second service first and then decode the data packet of the first service, or to decode the data packet of the first service first and then decode the data packet of the second service. Based on the first minimum rate requirement and the second minimum rate requirement, a first condition is determined, which is used to indicate that the data packet sending rate of the first service is less than or equal to the first minimum rate requirement, and to indicate that the data packet sending rate of the second service is less than or equal to the second minimum rate requirement. Based on the first channel condition, the second channel condition, and the channel noise power of the target system obtained in advance, the first condition is equivalent to the second condition under the second decoding order. The second condition is used to indicate that the signal-to-dryness ratio of the service decoded first is greater than or equal to the first preset threshold, and to indicate that the signal-to-dryness ratio of the service decoded later is greater than or equal to the second preset threshold. Based on the second condition and the third condition corresponding to the second decoding order, a fourth condition is determined. The third condition is used to indicate that the bit error rate of the later decoded service is the sum of the first bit error rate and the second bit error rate. The first bit error rate is the bit error rate of the earlier decoded service under the influence of channel noise and the interference of the later decoded service. The second bit error rate is the bit error rate of the later decoded service under the influence of channel noise. The fourth condition is used to indicate that the decoding reliability requirement of the earlier decoded service is greater than the decoding reliability requirement of the later decoded service. The decoding reliability requirement is related to the first bit error rate tolerance or the second bit error rate tolerance. Based on the second condition, the fourth condition, and the second decoding order, the first decoding order is determined, wherein the first decoding order is either the second decoding order or the decoding order opposite to the second decoding order.

4. The method according to claim 3, characterized in that, Determining the first decoding order based on the second condition, the fourth condition, and the second decoding order includes: Based on the second condition and the fourth condition, a fifth condition is determined. The fifth condition is used to indicate that the information-to-dryness ratio of the service being decoded first is greater than or equal to a first parameter. The first parameter is determined based on the first preset threshold and is greater than the first preset threshold. The second parameter is determined based on the ratio of the channel noise corresponding to the first channel condition to the channel noise corresponding to the second channel condition. Based on the fifth condition, the first preset threshold, and the second preset threshold, the third parameter is determined; If the value of the second parameter is less than the value of the third parameter, the second decoding order is determined as the first decoding order; or, if the value of the second parameter is greater than the value of the third parameter, the decoding order opposite to the second decoding order is determined as the first decoding order.

5. The method according to claim 3, characterized in that, The step of determining the target resource allocation method for the target system under the condition of minimum transmission power based on the channel information and the first decoding order includes: Obtain a first power allocation factor corresponding to the first service and a second power allocation factor corresponding to the second service from the channel information, wherein the sum of the first power allocation factor and the second power allocation factor is 1; Based on the first power allocation factor, the first channel condition, and the channel noise power, the first rate of the first service is determined. Based on the second power allocation factor, the second channel conditions, the channel noise power, and the second bit error rate tolerance, the second rate of the second service is determined. The correction terms of the first rate and the second rate are subjected to continuous convex approximation processing to obtain the sum rate function of the sum of the first rate and the second rate. The Hessian matrix of the sum rate function with respect to the sum of the power of the first service and the second service is a negative definite matrix, and the sum rate function is a joint concave function with respect to the sum of the power of the first service and the second service. Based on the sum rate function and the first decoding order, the target resource allocation method corresponding to the first service and the second service is determined; The target resource allocation method is determined based on the target resource allocation method for each of the first service and the second service.

6. The method according to claim 5, characterized in that, The step of determining the target resource allocation method corresponding to the first service and the second service based on the sum rate function and the first decoding order includes: Based on the sum-rate function, determine the optimal power allocation function for the first service and the second service; Based on the first rate and the second rate, a packet length function is constructed, wherein the Hessian matrix of the packet length function with respect to the packet length of the second service is a positive definite matrix. Based on the preset service instruction QoS conditions, the constraints for determining the packet length of the second service are determined; Based on the packet length function and the constraints of the packet length of the second service, the optimal packet length function of the second service is determined; The optimal packet length function and the optimal allocation function are iterated to determine the sum of the minimum transmission power of the first service and the second service, and to determine the packet length of the second service; The minimum transmission power of the first service and the minimum transmission power of the second service are determined based on the sum of the minimum transmission powers, the first power allocation factor, and the second power allocation factor.

7. A resource allocation device, characterized in that, The device includes: The first acquisition module is used to acquire the channel information of the target system, wherein the target system includes M sub-channels, each of which has long packet services and K short packet services, where M and K are integers greater than 1; The first determining module is used to determine, based on the channel information, a first decoding order of the K sub-services corresponding to the long packet service and the K short packet services, wherein the K sub-services are services split from the long packet service, the packet length of the data packets of the K sub-services corresponds one-to-one with the packet length of the data packets of the K short packet services, and the sub-services and the data packets of the corresponding short packet services with the same packet length are simultaneously transmitted through the same time-frequency resource block corresponding to the same sub-channel, and the transmission rate of the target system is maximized under the first decoding order; The second determining module is used to determine, based on the channel information and the first decoding order, the target resource allocation method when the transmission power of the target system for transmitting the long packet service and the K short packet services is minimized. The target resource allocation method is used to indicate the transmission power and data packet length of the long packet service and the transmission power and data packet length of the short packet service. The allocation module is used to allocate resources to the sub-channels of the target system based on the target resource allocation method.

8. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the resource allocation method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the resource allocation method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, It includes computer instructions that, when executed by a processor, implement the steps of the resource allocation method as described in any one of claims 1 to 6.

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