A RA-IDNC network coding method based on partial blind transmission

Abstract

The present invention provides a RA‑IDNC network coding method based on partial blind transmission, comprising: (1) obtaining a forward link packet loss rate and a feedback link packet loss rate of a user node and a channel capacity of the user; (2) the target user feeds back a receiving state to a base station through a feedback link, performs ML judgment on lost feedback, processes nodes according to the judgment result, and updates a feedback matrix; (3) constructs a RA‑IDNC coding relationship graph; (4) determines whether an active node set in the RA‑IDNC coding relationship graph is empty; if the active node set is empty but there are hidden nodes, resets all the hidden nodes to active nodes; (5) if the active node set is not empty, constructs a maximum weight group; (6) performs RA‑IDNC according to data packets corresponding to nodes in the maximum weight group, and goes to (2) for iterative operation until all node sets in the RA‑IDNC coding relationship graph are empty.

Description

Technical Field

[0001] The present invention relates to the field of physical layer network coding, and in particular to a RA-IDNC (Rate Aware Instantaneous Coding Network Coding) network coding method for partial blind transmission in a lossy feedback environment. Background Art

[0002] Most of the previous works, optimizing different parameters in systems based on on-the-fly network coding IDNC, consider a high-level view of the network and abstract its physical layer conditions, such as fading, shadowing, etc. into a simple erasure channel model. Furthermore, all coded combinations coming from the base station are assumed to be sent at the same physical layer rate and therefore occupy a fixed duration. Such an assumption undoubtedly simplifies the modeling of IDNC scenarios at the expense of an unrealistic channel model. In fact, it is well known that different users in a cellular network experience different channel conditions and will therefore be served by the base station at different rates. This difference in possible service rates does affect the decision on which two signals are combined in each transmission, as well as the rate at which they are sent. This rate adaptation not only affects the ability of different users to successfully receive each transmission, but also determines the duration required to deliver each message or combination.

[0003] The algorithms proposed in most other opportunistic network coding works assume perfect feedback (i.e., feedback from all receivers always reaches the sender and is not affected by losses). This assumption is not always feasible in wireless networks, since it is common to have similar wireless channel imperfections on both forward and feedback links. Therefore, even if a high level of protection is applied to feedback packets in some network settings, such as cellular, WiFi, and WiMAX systems, the inevitable deep fading conditions on the wireless channel still expose them to loss events. In other network settings, it may not be possible to guarantee that every feedback packet reaches the sender due to transmission power limitations and possible interference to other transmissions. Summary of the invention

[0004] In response to the above problem, how to select a network coding method that takes into account the physical layer channel conditions in a lossy feedback environment to reduce network transmission delay and improve system throughput. The present invention provides a RA-IDNC network coding method based on partial blind transmission, which is combined with lossy feedback to solve the problem of physical layer network coding under interference of feedback.

[0005] In a first aspect, the present invention provides a RA-IDNC network coding method based on partial blind transmission, comprising:

[0006] Step (1): obtaining the forward link packet loss rate and feedback link packet loss rate of each user node in the area covered by the base station transmission signal and the channel capacity of the corresponding user;

[0007] Step (2): In response to the base station sending a data packet to the target user, the target user feeds back the receiving status to the base station through the feedback link, uses the maximum likelihood criterion ML decision rule to judge the lost feedback, processes the node according to the judgment result, updates the feedback matrix, and determines the data packet information that the user node needs to receive;

[0008] Step (3): constructing a RA-IDNC coding relationship graph according to the forward link packet loss rate of the user node, the feedback link packet loss rate, the channel capacity of the corresponding user, and the data packet information that the user node needs to receive;

[0009] Step (4): determine whether the set of active nodes in the RA-IDNC coding relationship graph is empty. If the set of active nodes in the RA-IDNC coding relationship graph is empty but there are hidden nodes, reset all the hidden nodes to active nodes.

[0010] Step (5): If the set of active nodes in the RA-IDNC coding relationship graph is not empty, construct a maximum weighted clique based on the data packet information that all user nodes in the area covered by the base station transmission signal need to receive;

[0011] Step (6): Perform rate-aware real-time coding network coding RA-IDNC according to the data packets corresponding to the nodes in the maximum weight group, and then go to step (2) and iterate until all node sets in the RA-IDNC coding relationship graph are empty.

[0012] In some embodiments, step (2) comprises:

[0013] In the transmission under lossy feedback environment, if the base station does not receive feedback from the target user i, it means one of the following two events: the user does not receive the data packet and does not send feedback; the user receives the data packet and sends a feedback packet, but the feedback packet does not reach the base station;

[0014] Assuming channel reciprocity, the forward link packet loss rate of user i is p i Equal to the feedback link packet loss rate q i , that is, p i =q i , t i is the time slot when the base station receives the last feedback from user i, θ ij Expressed as: i Since then, the base station sends data packet P j To user i, but user i does not send feedback information to the base station. is the uncertain data packet P of user i at this time j The probability of having been lost is The expression is: In short:

[0015] pass Estimate user i for data packet P j The receiving state of the feedback matrix should satisfy: , it is estimated that the data packet is lost at user i, that is, the node corresponding to the data packet is retained, then x = 1; if When , it is estimated that the data packet is successfully received at user i, that is, the node corresponding to the hidden data packet, then x=0.

[0016] In some embodiments, in step (3), constructing a RA-IDNC coding relationship diagram includes:

[0017] Step 301: RA-IDNC encoding relationship diagram node v ijr Indicates that user i within the coverage area of ​​the base station needs to receive data packet P j , and only when the transmission rate r is less than or equal to the channel capacity R of user i i It is possible to be accepted only when

[0018] Step 302: RA-IDNC encoding relationship diagram node v ijr and node v i′j′r′ The condition for the existence of a coded connection edge between them is:

[0019] (1) The transmission rate is equal, that is, r = r';

[0020] (2) User i and user i′ request the same message or combined message It is immediately decodable for both user i and user i'.

[0021] In some embodiments, step (5) constructs a maximum weighted group according to the data packet information that all user nodes in the area covered by the base station transmission signal need to receive, including:

[0022] Step 501: At a given coded data packet sending time slot t, the expected lower limits of completion time for all users are calculated, the channel capacity of the user with the largest expected lower limit of completion time is used as the transmission rate r, and the expected lower limits of completion time for these users are arranged in descending order;

[0023] Step 502: In the subgraph of the RA-IDNC coding relationship graph corresponding to the transmission rate r, calculate the weights of all nodes under each user, and select the nodes with the largest weights from each user that meets the conditions according to the order of step 501 and add them to the maximum weight group.

[0024] In some embodiments, in step 501, at a given encoded data packet transmission time slot t, the lower limit F of the expected completion time of user i is calculated. i(t), including:

[0025]

[0026] Where B is the packet size, |W i (t)| is the size of the data packet set required by user i in the current time slot t, R i (t) is the channel capacity of user i, H i (t-1) is the time taken by user i from the end of the initial transmission phase to the transmission of the data packet in the previous time slot t-1, p i is the forward link packet loss rate of user i.

[0027] Furthermore, in some embodiments, the lower limit F of the expected completion time of user i is i (t) The method for obtaining the calculation formula includes:

[0028] The completion time H of user i i It is the sum of the time taken for instant decodable transmission, the time taken for receiving non-instant decodable data packets, and the transmission time of the sent data packets without receiving feedback. The expression is:

[0029]

[0030] Where B is the packet size, |W i (0)| represents the size of the data packet set required after the ML decision is completed at the end of the initial transmission phase of user i. is the harmonic mean of all transmission rates that the ith user in the transmission schedule S successfully receives and can decode immediately, This means that the receiving transmission rate of the i-th user in the transmission schedule S is R(t k ) is the time taken for the non-immediately decodable data packet, p i is the forward link packet loss rate of user i, and the overall completion time is: H = max i∈I {H i}, then the problem of minimizing the completion time of RA-IDNC with partial blind transmission is transformed into finding the optimal schedule S * , expressed as:

[0031]

[0032] In some embodiments, the optimal solution to the completion time minimization problem is transformed into the problem of finding the maximum weight group in the RA-IDNC coding relationship graph of partial blind transmission. The initial node weight w(v ijr )for:

[0033]

[0034] Among them, r is the transmission rate and B is the data packet size.

[0035] Furthermore, during the iteration process, the updated node weights for:

[0036]

[0037] Where A(v ijr ) is the node v ijr The set of adjacent nodes, the algorithm selects the node with the highest weight w(v ijr ), and has a strong adjacency relationship with other high-weight nodes in the RA-IDNC coding relationship graph.

[0038] In a second aspect, the present invention provides a RA-IDNC network coding device based on partial blind transmission, comprising a processor and a storage medium;

[0039] The storage medium is used to store instructions;

[0040] The processor is used to operate according to the instructions to execute the steps of the method according to the first aspect.

[0041] In a third aspect, the present invention provides a storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in the first aspect.

[0042] Beneficial technical effects achieved by the present invention:

[0043] The present invention fully considers the interference suffered by the user when feeding back information to the base station, provides a RA-IDNC network coding method based on partial blind transmission, performs ML judgment on lossy feedback information packets, and constructs a RA-IDNC coding relationship diagram based on node weights. According to the diagram, the RA-IDNC coding method is selected at the base station end, which can reduce the completion time of network transmission data while expanding the applicable scenarios of network coding to lossy feedback, which has strong practical significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a flow chart of a method according to an embodiment of the present invention;

[0045] Figure 2 This is the RA-IDNC diagram after the example data packet is broadcast;

[0046] Figure 3 It is a feedback matrix state diagram and ML decision situation under lossy feedback in an embodiment of the present invention;

[0047] Figure 4 This is a comparison chart of system completion time of different encoding methods in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and specific embodiments:

[0049] In the description of the present invention, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0050] Example 1

[0051] A RA-IDNC network coding method based on partial blind transmission, comprising:

[0052] Step (1): obtaining the forward link packet loss rate and feedback link packet loss rate of each user node in the area covered by the base station transmission signal and the channel capacity of the corresponding user;

[0053] Step (2): In response to the base station sending a data packet to the target user, the target user feeds back the receiving status to the base station through the feedback link, uses the maximum likelihood criterion ML decision rule to judge the lost feedback, processes the node according to the judgment result, updates the feedback matrix, and determines the data packet information that the user node needs to receive;

[0054] Step (3): constructing a RA-IDNC coding relationship graph according to the forward link packet loss rate of the user node, the feedback link packet loss rate, the channel capacity of the corresponding user, and the data packet information that the user node needs to receive;

[0055] Step (4): determine whether the set of active nodes in the RA-IDNC coding relationship graph is empty. If the set of active nodes in the RA-IDNC coding relationship graph is empty but there are hidden nodes, reset all the hidden nodes to active nodes.

[0056] Step (5): If the set of active nodes in the RA-IDNC coding relationship graph is not empty, construct a maximum weighted clique based on the data packet information that all user nodes in the area covered by the base station transmission signal need to receive;

[0057] Step (6): Perform rate-aware real-time coding network coding RA-IDNC according to the data packets corresponding to the nodes in the maximum weight group, and then go to step (2) and iterate until all node sets in the RA-IDNC coding relationship graph are empty.

[0058] In some embodiments, a RA-IDNC network coding method based on partial blind transmission, such as Figure 1 The specific steps are as follows:

[0059] Step (1): The base station estimates the forward link packet loss rate and feedback link packet loss rate of each user node within the area covered by the transmitted signal and the corresponding channel capacity;

[0060] Step (2): The target user feeds back the receiving status to the base station through the feedback link. The base station judges the lost feedback according to the ML judgment rule. When the judgment is received, the node is hidden, and when the judgment is lost, the node is retained. The specific method is as follows:

[0061] In transmission under lossy feedback environment, the base station does not receive feedback from target user i (the feedback information is x in this case), which may mean one of the following two events: the user did not receive the information packet and therefore did not send feedback; the user received the information packet and sent a feedback information packet, but the feedback information packet did not reach the base station;

[0062] Assuming channel reciprocity, the forward link packet loss rate of user i is p i Equal to the feedback link packet loss rate q i (i.e. p i =q i ), t i is the time slot when the base station receives the last feedback from user i, θ ij Expressed as: i Since then, the base station sends data packet P j To user i, but user i does not send feedback information to the base station. is the uncertain data packet P of user i at this time j The probability of having been lost is The expression is: In short:

[0063] Calculate by formula Estimate user i for data packet P j The receiving state of the feedback matrix should satisfy: , it is estimated that the data packet is lost at user i, that is, the node corresponding to the data packet is retained, then x = 1; if When , it is estimated that the data packet is successfully received at user i, that is, the node corresponding to the hidden data packet, then x=0.

[0064] Step (3): Each user constructs a corresponding RA-IDNC coding relationship diagram according to its forward link packet loss rate, feedback link packet loss rate, corresponding channel capacity, data packet information that the user node needs to receive, and RA-IDNC network coding conditions;

[0065] The method for constructing the user's corresponding RA-IDNC coding relationship diagram is:

[0066] Determine the node, v ijr Indicates that user i within the coverage area of ​​the base station needs to receive data packet P j And only when the transmission rate r is less than or equal to the channel capacity R of user i i It is possible to be accepted only when

[0067] Determine the encoding connection edge between nodes, node v ijr and v i′j′r′ The condition for the existence of a coded connection edge between them is:

[0068] (1) The transmission rate is equal, that is, r = r';

[0069] (2) Users i and i′ request the same message or combined message It is immediately decodable for both users i and i'.

[0070] Step (4): If there are no active nodes (non-hidden nodes) in the RA-IDNC coding relationship graph, but there are still hidden nodes (nodes that are not considered for transmission temporarily), then all these hidden nodes are reset to active nodes; if the node set in the RA-IDNC coding relationship graph is a non-empty subset, then run downward until the node set in the RA-IDNC coding relationship graph is empty;

[0071] Step (5): The base station constructs a maximum weight group according to the data packet information that all user nodes in the area covered by its own transmission signal need to receive and the RA-IDNC coding relationship diagram; the specific method is:

[0072] (501). User i completes time H i It is the sum of the time taken for instant decodable transmission, the time taken for receiving non-instant decodable data packets, and the transmission time of the sent data packets without receiving feedback. The expression is:

[0073]

[0074] Where B is the packet size, |W i (0)| represents the size of the data packet set required after the ML decision is completed at the end of the initial transmission phase of user i. is the harmonic mean of all transmission rates that the ith user in the transmission schedule S successfully receives and can decode immediately, This means that the receiving transmission rate of the i-th user in the transmission schedule S is R(t k ) of the non-immediately decodable data packets, the overall completion time is: H = max i∈I {H i}, then the problem of minimizing the completion time of RA-IDNC with partial blind transmission can be transformed into finding the optimal schedule S * , expressed as:

[0075]

[0076] (502) At a given coded data packet sending time slot t, the lower limit of the expected completion time of user i is F i (t) is expressed as:

[0077]

[0078] Among them, |W i (t)| is the size of the data packet set required by user i in the current time slot t, R i (t) is the channel capacity of user i, H i (t-1) is the time taken by user i from the end of the initial transmission phase to the data packet transmission process of the previous time slot (t-1);

[0079] (503) Take the channel capacity of the user with the largest lower limit of expected completion time as the transmission rate r, and arrange the lower limits of expected completion time of these users in order from large to small;

[0080] (504). The optimal solution to the problem of minimizing the completion time is transformed into the problem of finding the maximum weight group in the RA-IDNC graph with partial blind transmission. The initial node weight w(v ijr )for:

[0081]

[0082] Among them, r is the transmission rate, B is the data packet size;

[0083] (505). During the iteration process, the node weights are updated for:

[0084]

[0085] Where A(v ijr ) is the node v ijr The set of adjacent nodes, the algorithm selects the node with the highest weight w(v ijr ), and has a strong adjacency relationship with other high-weight nodes in the RA-IDNC coding relationship graph.

[0086] (506). In the subgraph of the RA-IDNC coding relationship graph corresponding to r, the weights of all nodes under each user are calculated, and the nodes with the largest weights are selected from each user who meets the conditions in turn according to the previous order and added to the maximum weight group.

[0087] Step (506): The base station performs RA-IDNC encoding according to the data packet corresponding to the node in the maximum weight group, and then goes to step (502) for iterative operation.

[0088] Assume that the base station broadcasts 4 data packets P1, P2, P3, and P4 to 3 users C1, C2, and C3. After the initial transmission phase, there is no feedback loss, user C1 loses data packets P1 and P3, user C2 loses data packets P2, P3, and P4, and user C3 loses data packet P3. Assume that the channel capacity from the base station to the user is: R1 = 5 bit / s, R2 = 8 bit / s, and R3 = 10 bit / s, then the rate sets of users C1, C2, and C3 are: The data packet size is B=10 bits, and the forward link packet loss rates of each user are: p1=0.0753, p2=0.2764, p3=0.1188.

[0089] Based on the above method, the corresponding RA-IDNC diagram is constructed according to the feedback information packet. Figure 2 As shown, the nodes in the graph are: v 11R1 、v 13R1 、v 22R1 、v 23R1 、v 24R1 、v 33R1 、v 22R2 、v 23R2 、v 24R2 、v 33R2 、v 33R3 , according to formula F i (t) The lower limit of the expected completion time for each user is calculated as: F1 = 4.3257 seconds, F2 = 5.1824 seconds, F3 = 1.1348 seconds. The channel capacity R2 corresponding to user C2 is used as the transmission rate r. The node weight formula is The calculated node weight is: Select the node v under each user in the order of users C2 and C3. 23R2 、v 33R2 Add to the maximum weight group, that is, the maximum weight group κ = {v 23R2 ,v 33R2}, then the network coding method corresponding to this transmission (κ, r) is that the base station sends the coded data packet 3, and the transmission rate is 8bit / s. If users C2 and C3 can correctly receive the coded packet, then users C2 and C3 can obtain data packet P3 through decoding. In this case, the time used by users C2 and C3 in this data packet transmission is 10 / 8=1.25seconds, and user C1 cannot receive the data packet because the channel capacity is less than the transmission rate, so its transmission time does not increase.

[0090] When the feedback from users C2 and C3 is lost, the possible states of the feedback matrix are a, b, c, and d. At this time, θ 23 =1,θ 33 =1, that is and Both are greater than 0.5, indicating that both packets are judged to be lost. The ML judgment result is state b. The specific situation is as follows Figure 3 shown.

[0091] Figure 4 It is a simulation diagram comparing the performance of the traditional IDNC coding method (IDNC-PF), the RA-IDNC coding method (RA-IDNC-PF), the RA-IDNC coding method with partial blind transmission (RA-IDNC-ML) and the RA-IDNC coding method with partial blind non-estimation state transmission (RA-IDNC-NVE), which mainly compares the completion time achieved by different numbers of users. In this system, the physical model of the present invention is: the base station is located at the center of the cell, the users are evenly distributed in the cell, only large-scale fading is considered when estimating the user channel capacity, and the physical parameters used are: the cell diameter is 500m, ideal channel estimation, Rayleigh fading channel model, and the path loss model is 148+40log 10(distance [km]), the transmission power is -45dBm / Hz, the noise power is -174dBm / Hz, the link channel bandwidth is 1MHz, and the forward link packet loss rate and feedback link packet loss rate of the users in the system are set to be equal and in the range of 0.05 to 0.30. The number of fixed data packets is 20, the data packet size is 1Mb, and the Matlab simulation results are the average of multiple experiments. It can be seen that the completion time of the four schemes is constantly increasing with the increase in the number of users. Moreover, the RA-IDNC coding method proposed by the present invention is superior to the traditional IDNC coding method because it proposes a new coding graph concept and considers the lower limit of the expected completion time and the dynamic transmission rate of each user in the decision-making. However, the traditional IDNC coding method blindly uses the minimum channel capacity of the target user as the transmission rate, and cannot jointly consider the coding data packet selection and the transmission rate selection. In addition, in the RA-IDNC coding method of lossy feedback transmission, the transmission performance when estimating the feedback state is better than the transmission performance when not estimating the state, which shows that the reasonable estimation of the state can well optimize the transmission performance. In addition, it can be found that when the number of users reaches a certain level, the RA-IDNC coding method with lossy feedback transmission is better than the traditional IDNC coding method, which well illustrates that the present invention has a good performance advantage.

[0092] The present invention provides a RA-IDNC network coding method based on partial blind transmission, performs ML judgment on lossy feedback information packets, and constructs a RA-IDNC graph based on node weights. According to the graph, the RA-IDNC coding method is selected at the base station end, which can reduce the completion time of network transmission data while expanding the applicable scenarios of network coding to lossy feedback, which has strong practical significance.

[0093] Example 2

[0094] In a second aspect, this embodiment provides a RA-IDNC network coding device based on partial blind transmission, including a processor and a storage medium;

[0095] The storage medium is used to store instructions;

[0096] The processor is used to operate according to the instructions to execute the steps of the method according to embodiment 1.

[0097] Example 3

[0098] In a third aspect, this embodiment provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in Example 1 are implemented.

[0099] Example 4

[0100] In a fourth aspect, the present invention provides a computing device, comprising:

[0101] One or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and are configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the methods described in Example 1.

[0102] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0103] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0104] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0105] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0106] It should be pointed out that the description of the above embodiments is only used to help understand the method of the present application and its core idea. For ordinary technicians in this technical field, several improvements and modifications can be made to the present application without departing from the principles of the present application. These improvements and modifications are also within the scope of protection of the claims of the present application.

Claims

1. A RA-IDNC network coding method based on partial blind transmission, characterized in that: include: Step (1): obtaining the forward link packet loss rate and feedback link packet loss rate of each user node in the area covered by the base station transmission signal and the channel capacity of the corresponding user; Step (2): In response to the base station sending a data packet to the target user, the target user feeds back the receiving status to the base station through the feedback link, uses the maximum likelihood criterion ML decision rule to judge the lost feedback, processes the node according to the judgment result, updates the feedback matrix, and determines the data packet information that the user node needs to receive; Step (3): constructing a RA-IDNC coding relationship diagram according to the forward link packet loss rate of the user node, the feedback link packet loss rate, the channel capacity of the corresponding user, and the data packet information that the user node needs to receive, specifically including: Step 301: RA-IDNC encoding relationship diagram node v ijr Indicates that user i within the coverage area of ​​the base station needs to receive data packet P j , and only when the transmission rate r is less than or equal to the channel capacity R of user i i It is possible to be accepted only when Step 302: RA-IDNC encoding relationship diagram node v ijr and node v i′j′r′ The condition for the existence of a coded connection edge between them is: (1) The transmission rate is equal, that is, r = r'; (2) User i and user i′ request the same message or combined message It is immediately decodable for both user i and user i′; Step (4): determine whether the set of active nodes in the RA-IDNC coding relationship graph is empty. If the set of active nodes in the RA-IDNC coding relationship graph is empty but there are hidden nodes, reset all the hidden nodes to active nodes. Step (5): If the active node set in the RA-IDNC coding relationship graph is not empty, construct a maximum weight group according to the data packet information that all user nodes in the area covered by the base station transmission signal need to receive, specifically including: Step 501: At a given coded data packet transmission time slot t, calculate the expected completion time lower limit of all users, and use the channel capacity of the user with the largest expected completion time lower limit as the transmission rate r , and rank the expected lower limits of completion time for these users in descending order; Step 502: In the subgraph of the RA-IDNC coding relationship graph corresponding to the transmission rate r, the weights of all nodes under each user are calculated, and the nodes with the largest weights are selected from the users that meet the conditions in sequence according to step 501 and added to the maximum weight group; Step (6): Perform rate-aware real-time coding network coding RA-IDNC according to the data packets corresponding to the nodes in the maximum weight group, and then go to step (2) and iterate until all node sets in the RA-IDNC coding relationship graph are empty.

2. The RA-IDNC network coding method based on partial blind transmission according to claim 1, characterized in that: The step (2) comprises: In the transmission under lossy feedback environment, if the base station does not receive feedback from the target user i, it means one of the following two events: the user does not receive the data packet and does not send feedback; the user receives the data packet and sends a feedback packet, but the feedback packet does not reach the base station; Assuming channel reciprocity, the forward link packet loss rate of user i is p i Equal to the feedback link packet loss rate q i , that is, pi = qi, t i is the time slot when the base station receives the last feedback from user i, θ ij Expressed as: i Since then, the base station sends data packet P j To user i, but user i does not send feedback information to the base station. is the uncertain data packet P of user i at this time j The probability of having been lost is The expression is: In short: pass Estimate user i for data packet P j The receiving state of the feedback matrix should satisfy: , it is estimated that the data packet is lost at user i, that is, the node corresponding to the data packet is retained, then x = 1; if When , it is estimated that the data packet is successfully received at user i, that is, the node corresponding to the hidden data packet, then x=0.

3. The RA-IDNC network coding method based on partial blind transmission according to claim 1, characterized in that: In step 501, at a given coded data packet transmission time slot t, the lower limit of the expected completion time of user i is calculated. i (t), including: Where B is the packet size, |W i (t)| is the size of the data packet set required by user i in the current time slot t, R i (t) is the channel capacity of user i, H i (t-1) is the time taken by user i from the end of the initial transmission phase to the transmission of the data packet in the previous time slot t-1, p i is the forward link packet loss rate of user i.

4. The RA-IDNC network coding method based on partial blind transmission according to claim 3 is characterized in that: The lower bound F of the expected completion time of user i i (t) The method for obtaining the calculation formula includes: The completion time H of user i i It is the sum of the time taken for instant decodable transmission, the time taken for receiving non-instant decodable data packets, and the transmission time of the sent data packets without receiving feedback. The expression is: Where B is the packet size, |W i (0) represents the size of the data packet set required after the ML decision is completed at the end of the initial transmission phase of user i. is the harmonic mean of all transmission rates that the ith user in the transmission schedule S successfully receives and can decode immediately, This means that the receiving transmission rate of the i-th user in the transmission schedule S is R(t k ) is the time taken for the non-immediately decodable data packet, p i is the forward link packet loss rate of user i, and the overall completion time is: H = max i∈I {H i }, then the problem of minimizing the completion time of RA-IDNC with partial blind transmission is transformed into finding the optimal schedule S * , expressed as:

5. The RA-IDNC network coding method based on partial blind transmission according to claim 1, characterized in that: The optimal solution to the completion time minimization problem is transformed into the problem of finding the maximum weight group in the RA-IDNC coding relationship graph of partial blind transmission. The initial node weight w(v ijr )for: Among them, r is the transmission rate and B is the data packet size.

6. The RA-IDNC network coding method based on partial blind transmission according to claim 5, characterized in that: During the iteration process, the updated node weights for: Where A(v ijr ) is the node v ijr The set of adjacent nodes, the node selected in each iteration not only has the highest weight w(v ijr ), and has a strong adjacency relationship with other high-weight nodes in the RA-IDNC coding relationship graph.

7. A RA-IDNC network coding device based on partial blind transmission, characterized in that: including processor and storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 6.

8. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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