Method and device for minimizing decoding error probability and storage medium

Abstract

The invention discloses a method and a device for minimizing a decoding error probability, and a storage medium. Comprising the following steps: determining a first coded stream and a second coded stream corresponding to a first terminal device, and determining a semantic coded stream corresponding to a second terminal device; according to the first coding stream, the second coding stream and the semantic coding stream, a decoding error probability minimization problem is determined, and the decoding error probability minimization problem comprises a transmitting power optimization problem, a bandwidth allocation optimization problem and a rate allocation factor optimization problem; solving a bandwidth allocation optimization problem and a rate allocation factor optimization problem based on a decoding error probability minimization problem; simplifying a decoding error probability minimization problem, and introducing an auxiliary variable so as to determine a problem equivalent to the decoding error probability minimization problem; solving a transmitting power optimization problem based on the determined problem; and minimizing the decoding error probability based on the optimal solution of the transmitting power optimization problem, the optimal solution of the bandwidth allocation optimization problem and the optimal solution of the rate allocation factor optimization problem.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a method, device and storage medium for minimizing decoding error probability. Background Art

[0002] With the growth of wireless applications and the increase in data traffic, wireless communications face the bottleneck of spectrum scarcity, which has prompted the transition from traditional communication to semantic communication. Semantic communication focuses on the meaning of the transmitted source information and shows great potential in reducing network traffic and alleviating spectrum shortage.

[0003] The basic idea of ​​rate splitting is to split the transmitted message into two parts at the transmitting end, namely the private part and the public part. The public part can be merged into a whole and transmitted in the same time-frequency resource as the private part. In addition to decoding the information consisting of two parts (i.e., public information and private information), the receiving end also needs to decode some interference. And as the number of terminal devices (i.e., transmitting ends) increases, the interference between different terminal devices increases. Therefore, how to minimize the overall decoding error probability is particularly important.

[0004] With respect to the technical problem existing in the above-mentioned prior art of how to minimize the probability of decoding errors during the communication process, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present disclosure provide a method, an apparatus, and a storage medium for minimizing the probability of decoding errors, so as to at least solve the technical problem existing in the prior art of how to minimize the probability of decoding errors in a communication process.

[0006] According to one aspect of an embodiment of the present disclosure, a method for minimizing decoding error probability is provided, including: determining a first coding stream and a second coding stream corresponding to a first terminal device, and determining a semantic coding stream corresponding to a second terminal device; determining a decoding error probability minimization problem based on the first coding stream, the second coding stream and the semantic coding stream, wherein the decoding error probability minimization problem includes a transmission power optimization problem, a bandwidth allocation optimization problem and a rate allocation factor optimization problem; solving the bandwidth allocation optimization problem and the rate allocation factor optimization problem based on the decoding error probability minimization problem; simplifying the decoding error probability minimization problem and introducing auxiliary variables to determine a problem equivalent to the decoding error probability minimization problem; solving the transmission power optimization problem based on the determined problem; and minimizing the decoding error probability based on the optimal solution of the transmission power optimization problem, the optimal solution of the bandwidth allocation optimization problem and the optimal solution of the rate allocation factor optimization problem.

[0007] According to another aspect of an embodiment of the present disclosure, a storage medium is further provided, the storage medium including a stored program, wherein when the program is running, a processor executes any one of the methods described above.

[0008] According to another aspect of an embodiment of the present disclosure, there is also provided an apparatus for minimizing the probability of decoding errors, comprising: a coding stream determination module, for determining a first coding stream and a second coding stream corresponding to a first terminal device, and determining a semantic coding stream corresponding to a second terminal device; a minimization problem determination module, for determining a decoding error probability minimization problem based on the first coding stream, the second coding stream and the semantic coding stream, wherein the decoding error probability minimization problem includes a transmission power optimization problem, a bandwidth allocation optimization problem and a rate allocation factor optimization problem; a first solving module, for solving a bandwidth allocation optimization problem and a rate allocation factor optimization problem based on the decoding error probability minimization problem; an equivalent problem determination module, for simplifying the decoding error probability minimization problem and introducing auxiliary variables, so as to determine a problem equivalent to the decoding error probability minimization problem; and a second solving module, for solving the transmission power optimization problem based on the determined problem.

[0009] According to another aspect of an embodiment of the present disclosure, there is also provided an apparatus for minimizing the probability of decoding errors, comprising: a processor; and a memory connected to the processor, for providing the processor with instructions for processing the following processing steps: determining a first coding stream and a second coding stream corresponding to a first terminal device, and determining a semantic coding stream corresponding to a second terminal device; determining a decoding error probability minimization problem according to the first coding stream, the second coding stream and the semantic coding stream, wherein the decoding error probability minimization problem includes a transmission power optimization problem, a bandwidth allocation optimization problem and a rate allocation factor optimization problem; solving a bandwidth allocation optimization problem and a rate allocation factor optimization problem based on the decoding error probability minimization problem; simplifying the decoding error probability minimization problem and introducing auxiliary variables to determine a problem equivalent to the decoding error probability minimization problem; solving a transmission power optimization problem based on the determined problem; and minimizing the decoding error probability based on the optimal solution of the transmission power optimization problem, the optimal solution of the bandwidth allocation optimization problem and the optimal solution of the rate allocation factor optimization problem.

[0010] The present application provides a method for minimizing the probability of decoding errors. First, the processor determines the first coding stream and the second coding stream corresponding to the first terminal device, and determines the semantic coding stream corresponding to the second terminal device. Then, the processor determines the problem of minimizing the probability of decoding errors based on the first coding stream, the second coding stream and the semantic coding stream. Then, the processor solves the bandwidth allocation optimization problem and the rate allocation factor optimization problem based on the problem of minimizing the probability of decoding errors. Then, the processor simplifies the problem of minimizing the probability of decoding errors and introduces auxiliary variables to determine a problem equivalent to the problem of minimizing the probability of decoding errors. Then, the processor solves the problem of optimizing the transmission power based on the determined problem. Finally, the processor minimizes the probability of decoding errors based on the optimal solution of the transmission power optimization problem, the optimal solution of the bandwidth allocation optimization problem and the optimal solution of the rate allocation factor optimization problem.

[0011] Since the decoding error probability minimization problem is related to the transmission power, bandwidth allocation and rate allocation factors, the decoding error probability can be minimized by determining the optimal solution corresponding to the transmission power optimization problem, the optimal solution corresponding to the bandwidth allocation optimization problem and the optimal solution corresponding to the rate allocation factor optimization problem.

[0012] Furthermore, since the decoding error probability minimization problem is simplified and an auxiliary variable is introduced, a minimization problem equivalent to the decoding error probability minimization problem is determined. Therefore, the transmission power optimization problem can be solved based on the determined equivalent problem.

[0013] Thus, the optimal solution corresponding to the transmission power optimization problem, the optimal solution corresponding to the bandwidth allocation optimization problem, and the optimal solution corresponding to the rate allocation factor optimization problem can be calculated, thereby minimizing the probability of decoding errors. This solves the technical problem of how to minimize the probability of decoding errors in the communication process in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The drawings described herein are used to provide a further understanding of the present disclosure and constitute a part of the present application. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure. In the drawings:

[0015] Figure 1 is a hardware structure block diagram of a computing device for implementing the method according to Embodiment 1 of the present disclosure;

[0016] Figure 2 is a schematic diagram of a system for minimizing decoding error probability according to Embodiment 1 of the present disclosure;

[0017] Figure 3is a flowchart of a method for minimizing decoding error probability according to the first aspect of Embodiment 1 of the present disclosure;

[0018] Figure 4 is a schematic diagram of a device for minimizing decoding error probability according to the first aspect of embodiment 2 of the present disclosure; and

[0019] Figure 5 It is a schematic diagram of the device for minimizing the probability of decoding errors according to the first aspect of Embodiment 3 of the present disclosure. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only embodiments of a part of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present disclosure.

[0021] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0022] Example 1

[0023] According to this embodiment, a method embodiment for minimizing the probability of decoding errors is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0024] The method embodiment provided in this embodiment can be executed in a mobile terminal, a computer terminal, a server or a similar computing device. Figure 1 FIG. 1 shows a hardware structure block diagram of a computing device for implementing a method for minimizing the probability of decoding errors. Figure 1As shown, the computing device may include one or more processors (the processor may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory for storing data, a transmission device for communication functions, and an input / output interface. The memory, the transmission device, and the input / output interface are connected to the processor via a bus. In addition, it may also include: a display, a keyboard, and a cursor control device connected to the input / output interface. A person skilled in the art can understand that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0025] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuitry may be a single independent processing module, or may be incorporated in whole or in part into any of the other components of the computing device. As involved in the embodiments of the present disclosure, the data processing circuitry acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0026] The memory can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the method for minimizing the probability of decoding errors in the embodiment of the present disclosure. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, the method for minimizing the probability of decoding errors of the above-mentioned application program is realized. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computing device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0027] The transmission device is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computing device. In one example, the transmission device includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device can be a radio frequency (Radio Frequency, RF) module, which is used to communicate with the Internet wirelessly.

[0028] The display may be, for example, a touch screen liquid crystal display (LCD) that may enable a user to interact with a user interface of the computing device.

[0029] It should be noted that, in some optional embodiments, the above Figure 1 The computing device shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware elements and software elements. Figure 1 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the computing devices described above.

[0030] Figure 2 is a schematic diagram of a system for minimizing the probability of decoding errors according to this embodiment. Figure 2 As shown, the system includes: a first terminal device corresponding to a first user, a second terminal device corresponding to a second user, and a base station.

[0031] The first terminal device receives a bit data stream corresponding to the first user, and splits and encodes the bit data stream to generate a first coded stream and a second coded stream.

[0032] The second terminal device receives the semantic data stream corresponding to the second user, and encodes the semantic data stream to generate a semantic coding stream.

[0033] The first terminal device sends the first coding stream and the second coding stream to the base station, and the second terminal device sends the semantic coding stream to the base station.

[0034] For example, the base station decodes the first coding stream, the second coding stream and the semantic coding stream respectively in a fixed decoding order, thereby generating a first decoded stream corresponding to the first coding stream, a second decoded stream corresponding to the second coding stream and a semantic decoded stream corresponding to the semantic coding stream.

[0035] It should be noted that the first terminal device, the second terminal device and the base station in the system can all be applicable to the hardware structure described above.

[0036] Under the above operating environment, according to a first aspect of this embodiment, a method for minimizing decoding error probability is provided. The method comprises: Figure 1 The processor implementation shown in . Figure 3 A schematic diagram showing the process of the method is shown in FIG. Figure 3 As shown, the method includes:

[0037] S302: Determine a first coded stream and a second coded stream corresponding to the first terminal device, and determine a semantic coded stream corresponding to the second terminal device;

[0038] S304: determining a decoding error probability minimization problem according to the first coded stream, the second coded stream and the semantic coded stream, wherein the decoding error probability minimization problem includes a transmission power optimization problem, a bandwidth allocation optimization problem and a rate allocation factor optimization problem;

[0039] S306: Solving the bandwidth allocation optimization problem and the rate allocation factor optimization problem based on the decoding error probability minimization problem;

[0040] S308: simplifying the decoding error probability minimization problem and introducing auxiliary variables, thereby determining a problem equivalent to the decoding error probability minimization problem;

[0041] S310: Solving a transmit power optimization problem based on the determined minimization problem; and

[0042] S312: Based on the optimal solution of the transmit power optimization problem, the optimal solution of the bandwidth allocation optimization problem, and the optimal solution of the rate allocation factor optimization problem, the decoding error probability is minimized.

[0043] Specifically, first, the processor determines a first coded stream and a second coded stream corresponding to the first terminal device, and determines a semantic coded stream corresponding to the second terminal device (S302). Figure 2 As shown, when the first terminal device receives the bit data stream corresponding to the first user, the bit data stream is split and encoded to generate a first encoded stream and a second encoded stream. The first encoded stream and the second encoded stream can be recorded as x b,k , k∈(1,2).

[0044] When the second terminal device receives the semantic data stream corresponding to the second user, it encodes the semantic data stream to generate a semantic encoding stream x s The first user may be, for example, a bit communication user, and the second user may be, for example, a semantic communication user.

[0045] Then, the first terminal device sends the first coding stream and the second coding stream to the base station, and the second terminal device sends the semantic coding stream to the base station.

[0046] In addition, suppose p b,k is the transmission power of the first terminal device, so the signal received by the base station can be expressed as:

[0047]

[0048] Among them, p s is the transmission power of the second terminal device, h b is the channel coefficient from the base station to the first terminal device, h sis the channel coefficient from the base station to the second terminal device, and n is the additive white Gaussian noise emitted by the base station.

[0049] Then, the processor determines the decoding error probability minimization problem (S304) based on the first coding stream, the second coding stream and the semantic coding stream. Specifically, for example, in this embodiment, rate splitting multiple access is used to implement the decoding of the first coding stream, the second coding stream and the semantic coding stream, and the decoding order of the first coding stream, the second coding stream and the semantic coding stream cannot be determined by the channel conditions. In addition, in this embodiment, for example, DeepSC is used as the semantic communication model, so the sending end (i.e., the first terminal device and the second terminal device) and the receiving end (i.e., the base station) of the semantic transmission are pre-trained. It is therefore assumed that a fixed decoding order is used to decode the first coding stream, the second coding stream and the semantic coding stream, respectively. That is, the decoding order is x b,1 →x b,2 →x s .

[0050] Since decoding errors may occur during the decoding process, based on the decoding order adopted, the causes of decoding errors are as follows: (1) x b,1 Decoding error. (2)x b,1 is decoded correctly, but x b,2 is decoded incorrectly. Therefore, in the case of overall error, the probability of obtaining the first user is:

[0051] ∈ b =∈ b,1 +(1-∈ b,1 )∈ b,2 (Formula 2)

[0052] In order to enable ultra-reliable low-latency communication to transmit the first encoded stream x b,1 and the second encoded stream x b,2 Our goal is to optimize the transmission power, bandwidth allocation, and rate allocation factor under the performance requirements of semantic communication to minimize the overall decoding error probability. The formula for minimizing the decoding error probability is as follows:

[0053]

[0054]

[0055]

[0056]

[0057]

[0058] W b +Ws =W (Formula 3f)

[0059] 0≤α≤1 (Formula 3g)

[0060] Among them, formula 3b means that the sum of the first transmission power corresponding to the first coding stream and the second transmission power corresponding to the second coding stream does not exceed the maximum transmission power for transmitting the bit data stream. Formula 3c means that the third transmission power corresponding to the semantic coding stream does not exceed the maximum transmission power for transmitting the semantic data stream. Formula 3d means that the semantic rate corresponding to the semantic coding stream is greater than or equal to the target semantic rate. Formula 3e means that the effective semantic communication corresponding to the semantic coding stream is greater than or equal to the minimum semantic similarity. Formula 3f means that the sum of the first bandwidth corresponding to the first coding stream, the second bandwidth corresponding to the second coding stream and the third bandwidth corresponding to the semantic coding stream is equal to the total bandwidth. Formula 3g represents the constraint on the rate allocation factor. The above content will be described in detail later, so it will not be repeated here.

[0061] There are two challenges for the proposed decoding error probability minimization problem. First, the above formula 3d and formula 3e are non-convex, so it is necessary to convexify the non-convex function. Second, the combination of message error probabilities. Therefore, in order to solve the above problems, this embodiment proposes a low-complexity iterative algorithm based on an inner approximation framework to obtain a stable point.

[0062] Thus, the processor solves the bandwidth allocation optimization problem and the rate allocation factor optimization problem based on the decoding error probability minimization problem (S306). Specifically, for a given third bandwidth W s The above formula 3a is further approximated by the case of the rate allocation factor α, so that the third bandwidth W s The above content will be described in detail later, so it will not be repeated here.

[0063] The processor then simplifies the decoding error probability minimization problem and introduces auxiliary variables to determine a problem equivalent to the decoding error probability minimization problem (S308). Specifically, according to the above formula 3f and the total bandwidth W, W can be calculated. b According to the value of K and γ s The generalized similarity function of (i.e., the following formula 19), and the bandwidth W allocated to the semantic coding stream s , so that formula 3d can be rewritten as:

[0064]

[0065] Among them, σ 2 represents the covariance of the additive Gaussian white noise from a single antenna access point, p srepresents the transmission power of the semantic coding stream, h s represents the channel coefficient from the single-antenna access point to the second terminal device, W s represents the feasible bandwidth corresponding to the semantic coding stream, and the other parameters are fitting parameters. The above formula 4 is a convex constraint, which gives the feasible bandwidth W of the semantic coding stream. s and rate allocation factor α. Thus, the above formula 3a can be simplified to:

[0066]

[0067] Then, we introduce auxiliary variables t,η b,1 ,η b,2 ,ρ b,1 ,ρ b,2 , then the above formula 5 can be equivalent to:

[0068]

[0069] η b,1 +η b,2 ≤η b,1 η b,2 +t (Formula 5b)

[0070] η b,1 ≤Q(s(ρ b,1 )) (Formula 5c)

[0071] η b,2 ≤Q(s(ρ b,2 )) (Formula 5d)

[0072]

[0073]

[0074] in,

[0075] Further, the processor solves the transmit power optimization problem based on the determined problem (S310). In order to solve the above formula 5a, given a reference point n is the iteration index. b,1 ,η b,2 The first-order Taylor approximation of , the right side of the above formula 5b can be expressed as:

[0076]

[0077] In order to obtain Q(s(ρ b,1 )) is convex, for ρ b,1 and s(ρ b,1 )have:

[0078] s(ρb,1 )≥0 (Formula 7)

[0079] Then according to the above formula 7, it can be calculated:

[0080]

[0081] For Equation 7 and Equation 8, the first-order Taylor approximation point is Nearby approximation Q(s(ρ b,1 )), we can get formula 9:

[0082]

[0083] Similarly, by convexifying the right side of the above formula 5d, we can get:

[0084]

[0085]

[0086] Similarly, for the above formula 5e and the above formula 5f, the first-order Taylor approximation points are respectively and Approximately, we can get the following formula:

[0087]

[0088]

[0089] Among them, the above formula 5e corresponds to formula 12, and formula 5f corresponds to formula 13.

[0090] Then, using the above formula 6 and formula 13, given the reference point So we can get the formula:

[0091]

[0092] η b,1 ≤Φ [n] (ρ b,1 ) (Formula 14b)

[0093] η b,2 ≤Φ [n] (ρ b,2 ) (Formula 14c)

[0094] The above formula 14a can be solved by a ready-made CVX solver, and the optimal solution corresponding to the transmission power optimization problem can be obtained.

[0095] Finally, the processor minimizes the decoding error probability based on the optimal solution to the transmit power optimization problem, the optimal solution to the bandwidth allocation optimization problem, and the optimal solution to the rate allocation factor optimization problem (S312).

[0096] As described in the background technology, the basic idea of ​​rate splitting is to split the transmitted message into two parts at the transmitting end, namely the proprietary part and the public part. The public part can be merged into a whole and transmitted in the same time-frequency resource as the proprietary part. In addition to decoding the information consisting of two parts (i.e., public information and proprietary information), the receiving end also decodes some interference. And as the number of terminal devices (i.e., transmitting end) increases, the interference between different terminal devices intensifies. Therefore, how to minimize the overall decoding error probability is particularly important.

[0097] In view of this, the present application provides a method for minimizing the probability of decoding errors. Since the problem of minimizing the probability of decoding errors is related to the transmission power, bandwidth allocation and rate allocation factor, the probability of decoding errors can be minimized when the optimal solution corresponding to the transmission power optimization problem, the optimal solution corresponding to the bandwidth allocation optimization problem and the optimal solution corresponding to the rate allocation factor optimization problem are determined.

[0098] Furthermore, since the decoding error probability minimization problem is simplified and an auxiliary variable is introduced, a minimization problem equivalent to the decoding error probability minimization problem is determined. Therefore, the transmission power optimization problem can be solved based on the determined equivalent problem.

[0099] Optionally, the operations of determining a first coding stream and a second coding stream corresponding to a first terminal device, and determining a semantic coding stream corresponding to a second terminal device, include: determining a bit data stream corresponding to the first terminal device and a semantic data stream corresponding to the second terminal device; using the first terminal device to split and encode the bit data stream to generate a first coding stream and a second coding stream corresponding to the first terminal device; and using the second terminal device to encode the semantic data stream to generate a semantic coding stream corresponding to the second terminal device.

[0100] Specifically, when the first terminal device receives the bit data stream corresponding to the first user, the bit data stream is split and encoded to generate a first encoded stream and a second encoded stream. The first encoded stream and the second encoded stream can be recorded as x b,k , k∈(1,2).

[0101] When the second terminal device receives the semantic data stream corresponding to the second user, it encodes the semantic data stream to generate a semantic encoding stream x s The first user may be, for example, a bit communication user, and the second user may be, for example, a semantic communication user.

[0102] Optionally, the operation of determining the decoding error probability minimization problem according to the first coding stream, the second coding stream and the semantic coding stream includes: determining the decoding error probability problem according to the first coding stream, the second coding stream and the semantic coding stream; determining the constraints corresponding to the decoding error probability; and determining the decoding error probability minimization problem based on the decoding error probability problem and the constraints. Further optionally, the operation of determining the decoding error probability problem according to the first coding stream, the second coding stream and the semantic coding stream includes: determining a first signal-to-noise ratio corresponding to the first coding stream and a second signal-to-noise ratio corresponding to the second coding stream; determining a first target rate corresponding to the first coding stream and a second target rate corresponding to the second coding stream; determining a first bandwidth allocated to the first coding stream and a second bandwidth allocated to the second coding stream; and determining the decoding error probability problem according to the first signal-to-noise ratio, the second signal-to-noise ratio, the first target rate, the second target rate, the first bandwidth, and the second bandwidth. Further optionally, the operation of determining the constraint conditions corresponding to the decoding error probability includes: determining a first transmission power of a first coding stream and a second transmission power of a second coding stream, and making the sum of the first transmission power and the second transmission power not exceed a first maximum transmission power, wherein the first maximum transmission power is the maximum transmission power for transmitting a coding stream corresponding to a bit data stream; determining a third transmission power of a semantic coding stream, and making the third transmission power less than the second maximum transmission power, wherein the second maximum transmission power is the maximum transmission power for transmitting the semantic coding stream; determining a semantic rate corresponding to the semantic coding stream, and making the semantic rate not less than a target semantic rate; determining effective semantic communication corresponding to the semantic coding stream, and making the effective semantic communication not less than a minimum semantic similarity; determining a third bandwidth corresponding to the semantic coding stream, and making the sum of the first bandwidth, the second bandwidth and the third bandwidth equal to the total bandwidth; and determining a rate allocation factor, and making the rate allocation factor less than 1.

[0103] Specifically, the first coded stream x b,1 The signal-to-noise ratio can be expressed as:

[0104]

[0105] Among them, p b,1 represents the transmission power of the first coded stream, p b,2 represents the transmission power of the second coded stream, p s represents the transmission power of the semantic coding stream, h b represents the channel coefficient from the single-antenna access point to the first terminal device, h s Represents the channel coefficient from the single-antenna access point to the second terminal device. 2 Represents the covariance of the additive white Gaussian noise emitted by a single-antenna access point.

[0106] The second coded stream x b,2 The signal-to-noise ratio can be expressed as:

[0107]

[0108] Semantic encoding stream x s The signal-to-noise ratio can be expressed as:

[0109]

[0110] In addition, after performing serial interference removal SIC, the semantic rate is:

[0111]

[0112] Among them, L represents the average number of words to be transmitted for each sentence text, and W s represents the feasible bandwidth corresponding to the semantic encoding stream, K represents the average number of mapped semantic symbols transmitted by DeepSC for each word, I represents the average amount of semantic information contained in the transmitted sentence, ε(K,γ s ) represents the semantic similarity function relative to K and γs.

[0113] For a given K and γ s , which is approximately expressed by the generalized logic function:

[0114]

[0115] Among them, A K,1 >0 and A K,2 >0 indicates the lower left asymptote and the upper right asymptote respectively. C K,1 >0 and C K,2 >0 represents the logistics growth rate and logistics midpoint respectively.

[0116] Based on the above formula, the achieved semantic rate is approximately:

[0117]

[0118] The target rate index of the first terminal device is r b Therefore, the target rate of the first coding stream can be expressed by the following formula:

[0119] r b,1 =αr b (Formula 21)

[0120] The target rate of the second coded stream can be expressed as follows:

[0121] r b,2 =(1-α)r b (Formula 22)

[0122] Where α is the ratio allocation factor.

[0123] Given a finite block length transmission rate, the error probability can be expressed as:

[0124]

[0125] in, represents channel dispersion, Q(·) represents Gaussian Q function, γ represents the signal-to-noise ratio of the data stream, N represents the block length, r represents the target rate of the data stream, and W represents the bandwidth allocated to the data stream.

[0126] For example, when the error probability corresponding to the first coded stream needs to be calculated, the parameters corresponding to the first coded stream need to be substituted into the above formula. That is, the signal-to-noise ratio γ of the first coded stream is b,1 , the target rate r of the first coded stream b,1 , and the bandwidth W allocated to the first coded stream b,1 .

[0127] When the error probability corresponding to the second coded stream needs to be calculated, the parameters corresponding to the second coded stream need to be substituted into the above formula. That is, the signal-to-noise ratio γ of the second coded stream is b,2 , the target rate r of the second coded stream b,2 , and the bandwidth W allocated to the second coded stream b,2 .

[0128] Then, the processor determines the constraint condition corresponding to the decoding error probability. Specifically, the first coded stream x b,1 The first transmission power p b,1 and the second encoded stream x b,2 The second transmission power p b,2 The sum cannot exceed the maximum transmit power used to transmit the coded stream corresponding to the bit data stream

[0129] The third transmission power p of the semantic coding stream s The maximum transmit power used to transmit the semantic coding stream cannot be exceeded

[0130] The semantic rate S of the semantic coding stream is not less than the target semantic rate

[0131] Efficient semantic communication corresponding to the semantic encoding stream Cannot be less than the minimum semantic similarity

[0132] With the first encoded stream x b,1 The corresponding first bandwidth W b,1 , and the second coded stream x b,2 The corresponding second bandwidth Wb,2 and the third encoded stream x s The corresponding third bandwidth W s The sum is equal to the total bandwidth W.

[0133] The rate allocation factor a is greater than 0 and less than 1.

[0134] Optionally, based on the problem of minimizing the probability of decoding errors, the operation of solving the bandwidth allocation optimization problem and the rate allocation factor optimization problem includes: determining a bound corresponding to the third bandwidth, and optimizing through a fast two-dimensional grid search, thereby calculating a value corresponding to the third bandwidth and a value corresponding to the rate allocation factor; and based on the total bandwidth and the third bandwidth, calculating a value corresponding to the first bandwidth and a value corresponding to the second bandwidth.

[0135] Specifically, since the third bandwidth W in the above formula 12d is s and the signal-to-noise ratio γ of the semantic coding stream s is coupled, so a decomposition solution is needed. Therefore, the third bandwidth W s The boundary of is:

[0136]

[0137] Thus, for the third bandwidth W s and rate allocation factor α are respectively The third bandwidth W can be obtained by optimizing through fast two-dimensional grid search on and α∈[0,1] s and the value of the rate allocation factor α.

[0138] Therefore, according to the second aspect of this embodiment, the technical effect of minimizing the probability of decoding errors is achieved.

[0139] In addition, reference Figure 1 As shown, according to the second aspect of this embodiment, a storage medium is provided, wherein the storage medium includes a stored program, wherein when the program is run, a processor executes any one of the above methods.

[0140] Therefore, according to this embodiment, the technical effect of minimizing the probability of decoding errors is achieved.

[0141] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0142] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0143] Example 2

[0144] Figure 4 The apparatus 400 for minimizing the decoding error probability according to the first aspect of this embodiment is shown, and the apparatus 400 corresponds to the method according to the first aspect of embodiment 1. Figure 4 As shown, the device 400 includes: a coding stream determination module 410, which is used to determine the first coding stream and the second coding stream corresponding to the first terminal device, and determine the semantic coding stream corresponding to the second terminal device; a minimization problem determination module 420, which is used to determine the decoding error probability minimization problem according to the first coding stream, the second coding stream and the semantic coding stream, wherein the decoding error probability minimization problem includes a transmission power optimization problem, a bandwidth allocation optimization problem and a rate allocation factor optimization problem; a first solution module 430, which is used to solve the bandwidth allocation optimization problem and the rate allocation factor optimization problem based on the decoding error probability minimization problem; an equivalent problem determination module 440, which is used to simplify the decoding error probability minimization problem and introduce auxiliary variables to determine a problem equivalent to the decoding error probability minimization problem; a second solution module 450, which is used to solve the transmission power optimization problem based on the determined problem; and a minimization module 460, which is used to minimize the decoding error probability based on the optimal solution of the transmission power optimization problem, the optimal solution of the bandwidth allocation optimization problem and the optimal solution of the rate allocation factor optimization problem.

[0145] Optionally, the coding stream determination module 410 includes: a first coding stream determination submodule, used to determine the bit data stream corresponding to the first terminal device and the semantic data stream corresponding to the second terminal device; a first coding stream generation module, used to split and encode the bit data stream using the first terminal device, thereby generating a first coding stream and a second coding stream corresponding to the first terminal device; a second coding stream generation module, used to encode the semantic data stream using the second terminal device, thereby generating a semantic coding stream corresponding to the second terminal device.

[0146] Optionally, the minimization problem determination module 420 includes: a problem determination module, used to determine the decoding error probability problem based on the first coding stream, the second coding stream and the semantic coding stream; a constraint determination module, used to determine the constraints corresponding to the decoding error probability; and a minimization problem determination sub-module, used to determine the decoding error probability minimization problem based on the decoding error probability problem and the constraints.

[0147] Optionally, problem determination includes: a signal-to-noise ratio determination module, used to determine a first signal-to-noise ratio corresponding to a first coding stream and a second signal-to-noise ratio corresponding to a second coding stream; a target rate determination module, used to determine a first target rate corresponding to the first coding stream and a second target rate corresponding to the second coding stream; a bandwidth determination module, used to determine a first bandwidth allocated to the first coding stream and a second bandwidth allocated to the second coding stream; and a problem determination submodule, used to determine a decoding error probability problem based on the first signal-to-noise ratio, the second signal-to-noise ratio, the first target rate, the second target rate, the first bandwidth, and the second bandwidth.

[0148] Optionally, the constraint determination module includes: a first constraint determination submodule, used to determine a first transmission power of a first coding stream and a second transmission power of a second coding stream, and make the sum of the first transmission power and the second transmission power not exceed a first maximum transmission power, wherein the first maximum transmission power is the maximum transmission power for transmitting a coding stream corresponding to a bit data stream; a second constraint determination submodule, used to determine a third transmission power of a semantic coding stream, and make the third transmission power less than the second maximum transmission power, wherein the second maximum transmission power is the maximum transmission power for transmitting a semantic coding stream; a third constraint determination submodule, used to determine a semantic rate corresponding to the semantic coding stream, and make the semantic rate not less than a target semantic rate; a fourth constraint determination submodule, used to determine effective semantic communication corresponding to the semantic coding stream, and make the effective semantic communication not less than a minimum semantic similarity; a fifth constraint determination submodule, used to determine a third bandwidth corresponding to the semantic coding stream, and make the sum of the first bandwidth, the second bandwidth and the third bandwidth equal to the total bandwidth; and a sixth constraint determination submodule, used to determine a rate allocation factor, and make the rate allocation factor less than 1.

[0149] Optionally, the first solution module 430 includes: a first calculation module, used to determine the boundary corresponding to the third bandwidth, and optimize through a fast two-dimensional grid search, so as to calculate the value corresponding to the third bandwidth and the value corresponding to the rate allocation factor; and a second calculation module, used to calculate the value corresponding to the first bandwidth and the value corresponding to the second bandwidth based on the total bandwidth and the third bandwidth.

[0150] Therefore, according to this embodiment, the technical effect of minimizing the probability of decoding errors is achieved.

[0151] Example 3

[0152] Figure 5 The apparatus 500 for minimizing the decoding error probability according to the first aspect of this embodiment is shown, and the apparatus 500 corresponds to the method according to the first aspect of embodiment 1. Figure 5 As shown, the device 500 includes: a processor 510; and a memory 520, which is connected to the processor 510 and is used to provide the processor 510 with instructions for processing the following processing steps: determining a first coding stream and a second coding stream corresponding to a first terminal device, and determining a semantic coding stream corresponding to a second terminal device; determining a decoding error probability minimization problem based on the first coding stream, the second coding stream and the semantic coding stream, wherein the decoding error probability minimization problem includes a transmission power optimization problem, a bandwidth allocation optimization problem and a rate allocation factor optimization problem; solving the bandwidth allocation optimization problem and the rate allocation factor optimization problem based on the decoding error probability minimization problem; simplifying the decoding error probability minimization problem and introducing auxiliary variables to determine a problem equivalent to the decoding error probability minimization problem; solving the transmission power optimization problem based on the determined problem; and minimizing the decoding error probability based on the optimal solution of the transmission power optimization problem, the optimal solution of the bandwidth allocation optimization problem and the optimal solution of the rate allocation factor optimization problem.

[0153] Optionally, the operations of determining a first coding stream and a second coding stream corresponding to a first terminal device, and determining a semantic coding stream corresponding to a second terminal device, include: determining a bit data stream corresponding to the first terminal device and a semantic data stream corresponding to the second terminal device; using the first terminal device to split and encode the bit data stream to generate a first coding stream and a second coding stream corresponding to the first terminal device; and using the second terminal device to encode the semantic data stream to generate a semantic coding stream corresponding to the second terminal device.

[0154] Optionally, the operation of determining a decoding error probability minimization problem based on the first coding stream, the second coding stream and the semantic coding stream includes: determining the decoding error probability problem based on the first coding stream, the second coding stream and the semantic coding stream; determining constraints corresponding to the decoding error probability; and determining the decoding error probability minimization problem based on the decoding error probability problem and the constraints.

[0155] Optionally, the operation of determining a decoding error probability problem based on the first coding stream, the second coding stream and the semantic coding stream includes: determining a first signal-to-noise ratio corresponding to the first coding stream and a second signal-to-noise ratio corresponding to the second coding stream; determining a first target rate corresponding to the first coding stream and a second target rate corresponding to the second coding stream; determining a first bandwidth allocated to the first coding stream and a second bandwidth allocated to the second coding stream; and determining the decoding error probability problem based on the first signal-to-noise ratio, the second signal-to-noise ratio, the first target rate, the second target rate, the first bandwidth and the second bandwidth.

[0156] Optionally, the operation of determining the constraint conditions corresponding to the decoding error probability includes: determining a first transmission power of a first coding stream and a second transmission power of a second coding stream, and making the sum of the first transmission power and the second transmission power not exceed a first maximum transmission power, wherein the first maximum transmission power is the maximum transmission power for transmitting a coding stream corresponding to a bit data stream; determining a third transmission power of a semantic coding stream, and making the third transmission power less than the second maximum transmission power, wherein the second maximum transmission power is the maximum transmission power for transmitting the semantic coding stream; determining a semantic rate corresponding to the semantic coding stream, and making the semantic rate not less than a target semantic rate; determining effective semantic communication corresponding to the semantic coding stream, and making the effective semantic communication not less than a minimum semantic similarity; determining a third bandwidth corresponding to the semantic coding stream, and making the sum of the first bandwidth, the second bandwidth and the third bandwidth equal to the total bandwidth; and determining a rate allocation factor, and making the rate allocation factor less than 1.

[0157] Optionally, based on the problem of minimizing the probability of decoding errors, the operation of solving the bandwidth allocation optimization problem and the rate allocation factor optimization problem includes: determining a bound corresponding to the third bandwidth, and optimizing through a fast two-dimensional grid search, thereby calculating a value corresponding to the third bandwidth and a value corresponding to the rate allocation factor; and based on the total bandwidth and the third bandwidth, calculating a value corresponding to the first bandwidth and a value corresponding to the second bandwidth.

[0158] Therefore, according to this embodiment, the technical effect of minimizing the probability of decoding errors is achieved.

[0159] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0160] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0161] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0162] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0163] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0164] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0165] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for minimizing the probability of decoding errors, characterized in that: include: Determine a first coded stream and a second coded stream corresponding to the first terminal device, and determine a semantic coded stream corresponding to the second terminal device; Determine a decoding error probability minimization problem according to the first coded stream, the second coded stream and the semantic coded stream, wherein the decoding error probability minimization problem includes a transmission power optimization problem, a bandwidth allocation optimization problem and a rate allocation factor optimization problem; Based on the decoding error probability minimization problem, solving the bandwidth allocation optimization problem and the rate allocation factor optimization problem; Simplifying the decoding error probability minimization problem and introducing auxiliary variables, thereby determining a problem equivalent to the decoding error probability minimization problem; Solving the transmit power optimization problem based on the determined problem; as well as Based on the optimal solution of the transmit power optimization problem, the optimal solution of the bandwidth allocation optimization problem and the optimal solution of the rate allocation factor optimization problem, the decoding error probability is minimized.

2. The method according to claim 1, characterized in that The operation of determining a first coded stream and a second coded stream corresponding to a first terminal device, and determining a semantic coded stream corresponding to a second terminal device includes: Determine a bit data stream corresponding to the first terminal device and a semantic data stream corresponding to the second terminal device; Using the first terminal device to split and encode the bit data stream, thereby generating a first coded stream and a second coded stream corresponding to the first terminal device; and The semantic data stream is encoded using the second terminal device, thereby generating a semantically encoded stream corresponding to the second terminal device.

3. The method according to claim 1, characterized in that The operation of determining a decoding error probability minimization problem according to the first coded stream, the second coded stream, and the semantic coded stream comprises: Determining the decoding error probability problem according to the first coding stream, the second coding stream and the semantic coding stream; determining a constraint condition corresponding to the decoding error probability; and Based on the decoding error probability problem and the constraint condition, the decoding error probability minimization problem is determined.

4. The method according to claim 3, characterized in that: The operation of determining the decoding error probability problem according to the first coding stream, the second coding stream and the semantic coding stream includes: Determining a first signal-to-noise ratio corresponding to the first coded stream and a second signal-to-noise ratio corresponding to the second coded stream; Determine a first target rate corresponding to the first coded stream and a second target rate corresponding to the second coded stream; Determining a first bandwidth allocated to the first encoded stream and a second bandwidth allocated to the second encoded stream; and The decoding error probability problem is determined according to the first signal-to-noise ratio, the second signal-to-noise ratio, the first target rate, the second target rate, the first bandwidth, and the second bandwidth.

5. The method according to claim 4, characterized in that The operation of determining a constraint condition corresponding to the decoding error probability comprises: Determine a first transmit power of the first coded stream and a second transmit power of the second coded stream, and make the sum of the first transmit power and the second transmit power not exceed a first maximum transmit power, wherein the first maximum transmit power is a maximum transmit power for transmitting a coded stream corresponding to a bit data stream; Determine a third transmit power of the semantic coding stream, and make the third transmit power less than a second maximum transmit power, wherein the second maximum transmit power is a maximum transmit power for transmitting the semantic coding stream; Determining a semantic rate corresponding to the semantic coding stream, and making the semantic rate not less than a target semantic rate; Determine the effective semantic communication corresponding to the semantic coding stream, and make the effective semantic communication not less than the minimum semantic similarity; determining a third bandwidth corresponding to the semantic coding stream, and making the sum of the first bandwidth, the second bandwidth and the third bandwidth equal to the total bandwidth; and A rate allocation factor is determined, and the rate allocation factor is made smaller than 1.

6. The method according to claim 5, characterized in that The operation of solving the bandwidth allocation optimization problem and the rate allocation factor optimization problem based on the decoding error probability minimization problem includes: Determining a bound corresponding to the third bandwidth, and optimizing by fast two-dimensional grid search, thereby calculating a value corresponding to the third bandwidth and a value corresponding to the rate allocation factor; and Based on the total bandwidth and the third bandwidth, a value corresponding to the first bandwidth and a value corresponding to the second bandwidth are calculated.

7. A storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is run, the processor executes the method according to any one of claims 1 to 6.

8. A device for minimizing the probability of decoding errors, characterized in that include: A coding stream determination module, used to determine a first coding stream and a second coding stream corresponding to a first terminal device, and to determine a semantic coding stream corresponding to a second terminal device; a minimization problem determination module, configured to determine a decoding error probability minimization problem according to the first coding stream, the second coding stream and the semantic coding stream, wherein the decoding error probability minimization problem includes a transmission power optimization problem, a bandwidth allocation optimization problem and a rate allocation factor optimization problem; A first solving module, used for solving the bandwidth allocation optimization problem and the rate allocation factor optimization problem based on the decoding error probability minimization problem; An equivalent problem determination module, used to simplify the decoding error probability minimization problem and introduce auxiliary variables to determine a problem equivalent to the decoding error probability minimization problem; A second solving module, configured to solve the transmit power optimization problem based on the determined problem; The minimization module is used to minimize the decoding error probability based on the optimal solution of the transmission power optimization problem, the optimal solution of the bandwidth allocation optimization problem and the optimal solution of the rate allocation factor optimization problem.

9. A device for minimizing the probability of decoding errors, characterized in that include: processor; as well as A memory, connected to the processor, configured to provide the processor with instructions for processing the following processing steps: Determine a first coded stream and a second coded stream corresponding to the first terminal device, and determine a semantic coded stream corresponding to the second terminal device; Determine a decoding error probability minimization problem according to the first coded stream, the second coded stream and the semantic coded stream, wherein the decoding error probability minimization problem includes a transmission power optimization problem, a bandwidth allocation optimization problem and a rate allocation factor optimization problem; Based on the decoding error probability minimization problem, solving the bandwidth allocation optimization problem and the rate allocation factor optimization problem; Simplifying the decoding error probability minimization problem and introducing auxiliary variables, thereby determining a problem equivalent to the decoding error probability minimization problem; Solving the transmit power optimization problem based on the determined problem; as well as Based on the optimal solution of the transmit power optimization problem, the optimal solution of the bandwidth allocation optimization problem and the optimal solution of the rate allocation factor optimization problem, the decoding error probability is minimized.

Images