CN119788248A - Adaptive coding transmission method for deep space network links based on hop-by-hop redundant confirmation - Google Patents

Adaptive coding transmission method for deep space network links based on hop-by-hop redundant confirmation Download PDF

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CN119788248A
CN119788248A CN202510001880.2A CN202510001880A CN119788248A CN 119788248 A CN119788248 A CN 119788248A CN 202510001880 A CN202510001880 A CN 202510001880A CN 119788248 A CN119788248 A CN 119788248A
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node
hop
data packets
coded data
redundancy
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何华森
魏光远
万远龙
侯云鹏
姜晓枫
陈双武
杨坚
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University of Science and Technology of China USTC
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Abstract

The invention relates to the technical field of computer networks and discloses a deep space network link self-adaptive coding transmission method based on hop-by-hop redundancy confirmation, which comprises a data transmission architecture, wherein a link perception module dynamically estimates the link packet loss rate between nodes by periodically sending topology learning packets between nodes, a redundancy calculation module calculates optimal redundancy according to the estimated link packet loss rate at a source node, calculates the number of minimum coding data packets required by calculation, a coding module outputs the coding data packets according to the calculated optimal redundancy at the source node, a decoding module decodes the received coding data packets at a destination node and outputs original data, data is buffered at each node temporarily, a corresponding feedback packet is generated according to a checking result, a last hop node is informed to continue to transmit or clear the data buffer, and a receiving and transmitting queue comprises a receiving queue and a transmitting queue and is used for receiving and transmitting the data packets and the feedback packets at each node.

Description

Deep space network link self-adaptive coding transmission method based on hop-by-hop redundancy confirmation
Technical Field
The invention relates to the technical field of computer networks, in particular to a deep space network link self-adaptive coding transmission method based on hop-by-hop redundancy confirmation.
Background
With the rapid development of space exploration technology and the increasing demand for deep space network communication, the IP address in the traditional internet is designed for static network address and depends on the transmission control protocol of a fixed path from terminal to terminal, and is not suitable for the deep space network environment, and has great limitation in terms of resource efficiency, reliability, network performance and the like. In such a background, innovative deep space network transmission mechanism research has become a hotspot field of current global interest.
The traditional network architecture takes an IP address as a core, adopts a TCP/IP architecture designed according to an end-to-end principle, and is difficult to adapt to a deep space network environment. First, the conventional internet transmission control protocol is based on a fixed path from terminal to terminal, and is not applicable to deep space networks with large delay and topology change. And secondly, the channel conditions of the deep space network are dynamically changed, key indexes such as packet loss rate and the like are difficult to predict, the reliability of upper application service is destroyed, and the service quality of the network is influenced. Finally, the deep space network puts higher demands on the resource efficiency of data transmission, but the traditional coding transmission protocol cannot give consideration to higher channel utilization rate, high reliability and lower coding and decoding overhead, and cannot realize the high-efficiency and reliable transmission of data.
In view of the above problems, the existing solutions, such as linear network coding, propose a transmission mode for reliability, and improve the probability of successful data transmission by sending redundant coded data packets, so that the original data can be decoded from a certain number of coded data packets, and thus a certain degree of data packet loss can be tolerated. The transmission mode can solve the problem of reliability to a certain extent, but because the link quality of the deep space network changes dynamically at any time, the data transmission under the condition that the fixed number of redundant coded data packets cannot be qualified is realized, the successful delivery of the data cannot be ensured due to the too small redundancy, and the network resource waste is caused due to the too large redundancy. In addition, dynamic network topology and link disruption can also reduce transmission reliability. The existing end-to-end reliable transmission mechanism triggers retransmission when a link is disconnected, so that larger retransmission time delay and extra redundancy transmission are caused, and the transmission efficiency is reduced.
Aiming at the problems, the invention provides a novel deep space network transmission interaction mode to realize reliable transmission of data based on the requirements of the deep space network on resource efficiency, reliability and encoding and decoding overhead, and ensures higher resource utilization rate.
Disclosure of Invention
The invention provides a novel deep space network link self-adaptive coding transmission method based on hop-by-hop redundancy confirmation, which is characterized in that a deep space network node updates the coding redundancy rate in real time according to the dynamic link quality, reduces network transmission resource waste, and simultaneously utilizes a hop-by-hop feedback mechanism to reduce retransmission delay caused by link interruption. In addition, by designing a unique encoding mechanism based on the cauchy matrix, the destination node does not need to repeatedly attempt to calculate the decoding matrix in real time when preparing to decode, thereby reducing decoding overhead and calculation delay. This significantly improves the efficiency of data transmission and ensures reliability in the data transmission process.
In order to solve the technical problems, the invention adopts the following technical scheme:
a deep space network link self-adaptive coding transmission method based on hop-by-hop redundancy confirmation comprises the following steps:
the system comprises a data transmission architecture, a target node, a source node, a middle node, a destination node and a data transmission module, wherein the data transmission architecture is provided with a link perception module, a redundancy calculation module, a coding module, a decoding module, a data buffer and a receiving and transmitting queue, and each node of a deep space network uses the link perception module, the data buffer and the receiving and transmitting queue;
The link perception module dynamically estimates the link packet loss rate between nodes by periodically sending topology learning packets between the nodes;
the redundancy calculation module calculates optimal redundancy according to the estimated link packet loss rate at the source node, and calculates the required minimum coding data packet quantity according to the estimated link packet loss rate at the intermediate node;
The encoding module encodes the original data by using an encoding matrix based on a cauchy matrix at a source node according to the calculated optimal redundancy, and outputs an encoded data packet;
The decoding module decodes the received coded data packet at the destination node and outputs the original data;
Temporarily storing the coded data packet at each node, checking batches when the transmission is not completed, generating a corresponding feedback packet according to the checking result, and informing the last hop node to continue the transmission or clear the data buffer;
The receiving and transmitting queues comprise receiving queues and transmitting queues, and are used for receiving and transmitting data packets and feedback packets at each node;
The single-hop internal transmission flow of the coded data packet is as follows, the current node sends the coded data packet to the next hop node, the next hop node receives the coded data packet and temporarily stores the coded data packet in a data buffer, whether the coded data packet of the current batch meets the redundancy requirement of subsequent transmission or decoding is checked, and the current node is informed to continue transmission or stop transmission through a feedback packet according to the check result.
As a further preferable technical solution of the present invention, the checking whether the current batch of coded data packets meets the redundancy requirement of subsequent transmission or decoding, and notifying the current node to continue transmission or stop transmission through a feedback packet according to the checking result specifically includes:
If the number of the coded data packets received by the next-hop node does not meet the redundancy requirement, the next-hop node sends a feedback packet containing information of the coded data packets to be continuously transmitted to the current node, the current node continuously transmits the coded data packets of the current batch to the next-hop node after receiving the feedback packet, and if the number of the coded data packets received by the next-hop node meets the redundancy requirement of subsequent transmission or decoding, the next-hop node sends the feedback packet containing enough information of the number of the coded data packets to the current node, and the current node stops subsequent transmission of the coded data packets of the current batch after receiving the feedback packet and removes the coded data packets of the current batch from a data cache of the current node.
As a further preferable technical solution of the present invention, the link sensing module dynamically estimates a link packet loss rate between nodes by periodically sending topology learning packets between nodes, and specifically includes:
the packet loss rate of the link l i,j is denoted as p i,j, the packet loss rate of the link from the node U i to the destination node U D is denoted as p i→D, and the packet loss rate p i→D satisfies the following for the node U i and the next hop node U j of the node U i:
pi→D＝1-(1-pj→D)×(1-pi,j); (1)
When one node U i receives the topology learning packet generated by the destination node U d, calculating the link packet loss rate according to the formula (1), and continuously forwarding the updated topology learning packet to the neighbor node, if a plurality of topology learning packets generated by the same node are received, selecting the topology learning packet with the least forwarding hop count, thereby realizing the periodic update of the link packet loss rate.
As a further preferable technical solution of the present invention, the redundancy calculation module calculates, at a source node, an optimal redundancy according to an estimated link packet loss rate, and calculates, at an intermediate node, a required minimum number of encoded data packets according to the estimated link packet loss rate, including:
The number of the original data packets of one batch is recorded as N S, the number of the coded data packets generated by the source node is recorded as N C, and the coding redundancy is t, and the method comprises the following steps:
NC＝(t+1)×Ns;
The required successful decoding probability threshold is marked as gamma *, and the probability gamma L that the original data can be decoded is that the source node generates and transmits N C coded data packets, wherein the number of different coded data packets of which is not less than N S reach the destination node:
Where N C≥NS, then the smallest N C is obtained by solving the minimization problem as follows:
Wherein, the redundancy t is an optimization variable, if the minimum value of N C is The optimal redundancy t * is:
The redundancy calculation module of the source node uses the calculation result of the optimal redundancy to a subsequent coding module to generate a coded data packet for data transmission;
The redundancy calculation module of the intermediate node calculates through the link packet loss rate condition and the batch size of the subsequent path to determine the minimum coding data packet number Y i required to be obtained from the previous hop node, so that the destination node can receive enough coding data packets with the probability not lower than a preset threshold gamma *, and the probability gamma i that the intermediate node U i forwards Y i coding data packets can enable the destination node to finish original data decoding is as follows:
The minimum number of encoded packets Y i required by the intermediate node is obtained by solving the minimization problem as follows:
And the redundancy calculation module of the intermediate node compares the Y i with the different coded data packets in the current data cache, if the number of the coded data packets received currently is less than Y i, the generated feedback packet is returned to the last-hop node to request to continue transmitting the coded data packets until the number of the received different coded data packets exceeds Y i, the feedback packet is regenerated to the last-hop node, and the last-hop node is informed to stop the transmission of the subsequent coded data packets and clear the data cache.
As a further preferable technical solution of the present invention, the encoding module encodes, at a source node, original data by using a cauchy matrix-based encoding matrix according to the calculated optimal redundancy, and outputs an encoded data packet, and specifically includes:
let a batch of data contain n original data packets, and the coding redundancy is set to t, the coding module will generate k=c+n coded data packets, where c=t×n, and the coding matrix Φ k×n used is expressed as:
Wherein I n is an n-order identity matrix, E c×n is a c×n coding matrix, which is a submatrix of the following Cauchy matrix C n×n:
Where x i,yj∈GF(2q), i, j=1, 2,..n, and x i≠yj;GF(2q) represents a finite field, and after encoding using the cauchy matrix-based encoding matrix Φ k×n, the source node will obtain k encoded data packets for subsequent transmission.
Compared with the prior art, the invention has the beneficial technical effects that:
The invention has the advantages of ensuring the hop-by-hop redundancy reliability, reducing the network transmission resource waste, reducing the decoding overhead and the like. The limitation of the traditional network coding transmission end-to-end design is broken, the end-to-end reliability is guaranteed to be decomposed into hop-by-hop redundancy check through hop-by-hop redundancy, and each intermediate node on the transmission path can buffer the received coding data packet, so that the reliability is effectively improved. The hop-by-hop redundancy guarantee design also reduces a large number of full-path retransmissions under the end-to-end design, and the transmission of the redundancy coding data packet can be stopped in time through the transmission feedback design, so that the waste of network transmission resources is reduced. In addition, by designing a unique encoding and decoding mechanism based on the Cauchy matrix, the target node does not need to repeatedly attempt to calculate the decoding matrix in real time when preparing to decode, so that decoding cost and calculation delay are reduced, and the method is suitable for network data transmission with the requirements of energy delay cost control and reliable transmission, such as a deep space network.
Drawings
FIG. 1 is a diagram of a data transmission architecture of the present invention;
FIG. 2 is a timing diagram of a data single hop transceiver of the present invention;
FIG. 3 is a flow chart of a link aware module according to the present invention;
FIG. 4 is a flow chart of a redundant computing module of the present invention;
FIG. 5 is a flow chart of the encoding module of the present invention;
FIG. 6 is a flow chart of a decoding module according to the present invention;
FIG. 7 is a flow chart of a data buffering and transceiving module according to the present invention;
Fig. 8 is a schematic diagram of a hop-by-hop transmission and feedback process according to the present invention.
Detailed Description
A preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings.
The invention provides a deep space network link self-adaptive coding transmission method based on hop-by-hop redundancy confirmation. The data transmission architecture is shown in fig. 1, and the node mainly comprises a link sensing module, a redundancy calculation module, an encoding module, a decoding module, a data buffer, a receiving and transmitting queue and the like. Each node uses a link awareness module, a data cache, and a transmit-receive queue. The source node in the transmission architecture uses a redundancy calculation module and an encoding module, the intermediate node in the transmission architecture uses a redundancy calculation module, and the destination node in the transmission architecture uses a decoding module.
The link awareness module is responsible for dynamically acquiring link packet loss rate information between network nodes by periodically sending Topology Learning Packets (TLPs) between the nodes.
The redundancy calculation module is responsible for calculating the optimal redundancy of the subsequent coding according to the estimated link packet loss rate at the source node of the transmission, and calculating the minimum coding data packet quantity required by the subsequent transmission according to the estimated link packet loss rate at the intermediate node of the transmission.
The encoding module is responsible for encoding the original data by using the cauchy matrix according to the optimal redundancy at the source node of the transmission and outputting the encoded data packet.
The decoding module is responsible for decoding at the destination node of transmission according to the coded data packet information received by the buffer memory, and outputting the original data.
The data buffer is responsible for temporarily storing the coded data packet at each node, checking batches when the transmission is not completed, and generating a corresponding feedback packet according to the checking result to inform the last hop node to continue the transmission or clear the data buffer.
The transmit-receive queue is responsible for basic data packet and feedback packet transmit-receive operations at each node.
The single-hop intra-transmission flow of encoded data is shown in fig. 2. The current node sends the coded data packet to the next-hop node, the next-hop node receives the coded data packet, temporarily stores the coded data packet in a data buffer, and checks whether the coded data packet in the batch is enough to meet the redundancy requirement of subsequent transmission or decoding. If the number of the coded data packets received by the next-hop node does not meet the redundancy requirement, the next-hop node sends a feedback packet containing information of the coded data packets to be continuously transmitted to the current node, the current node continuously transmits the coded data packets of the batch to the next-hop node after receiving the feedback packet, and if the number of the coded data packets received by the next-hop node meets the redundancy requirement of subsequent transmission or decoding, the next-hop node sends the feedback packet containing enough information of the number of the coded data packets to the current node, and the current node stops subsequent transmission of the coded data packets of the batch after receiving the feedback packet and removes the coded data packets of the batch from a data cache of the current node.
The specific workflow of each main module is as follows.
1. Link sensing module
The link awareness module periodically transmits Topology Learning Packets (TLPs) between nodes, continuously updating the path loss rate. The packet loss rate of link l i,j is denoted as p i,j. The path packet loss rate from node U i to destination node U D is denoted as p i→D. For node U i and its next-hop node U j, the path packet loss rate satisfies:
pi→D＝1-(1-pj→D)×(1-pi,j); (1)
after a node U i receives the TLP generated by the destination node U d, the path packet loss rate is calculated according to formula (1), and the updated TLP is forwarded to the neighboring node. If a plurality of TLPs generated by the same node are received, a TLP with the least forwarding hop count is selected, so that the periodic update of the path packet loss rate is realized. The flow is shown in fig. 3.
2. Redundancy calculation module
The redundancy calculation module calculates the required redundancy and the number of coded data packets according to the link quality and the batch size. The goal of the redundancy calculation is to find the minimum number of encoded data packets to generate or forward so that the destination node can receive enough encoded data packets with a probability not below a preset threshold.
Considering a batch of original data packets, the number of which is denoted as N S, the number of encoded data packets generated by the source node is denoted as N C, and the encoding redundancy is denoted as t, there are:
NC＝(t+1)×NS; (2)
the required probability of successful decoding threshold is denoted Γ *.
For a source node, from N C coded data packets that it generates and transmits, no less than N L different coded data packets arrive at a destination node, so that the probability Γ L that the original data can be decoded is:
Wherein N C≥NS. The smallest N C can be obtained by solving the minimization problem as follows:
Where redundancy t is the optimization variable.
If the minimum value isThe optimal redundancy can be expressed as:
and the redundancy calculation module of the source node uses the result to a subsequent encoding module to generate an encoded data packet for data transmission.
For the intermediate node, the redundancy calculation module performs similar calculation through the packet loss rate condition and the batch size of the subsequent path to determine the minimum number Y i of coded data packets required to be acquired from the previous-hop node, so that the destination node can receive enough coded data packets with the probability not lower than a preset threshold gamma *. For intermediate node U i, the probability Γ i that its forwarding Y i encoded data packets can cause the destination node to complete the original data decoding is:
The minimum number of encoded packets Y i required by the intermediate node can be obtained by solving the minimization problem as follows:
And the redundancy calculation module of the intermediate node compares the number of the Y i with the number of different coded data packets in the current data cache, if the number of the coded data packets received currently is less than Y i, the generated feedback packet is returned to the previous-hop node to request the coded data packets to be continuously transmitted until the number of the received different coded data packets exceeds Y i, the generated feedback packet is regenerated to the previous-hop node to inform the previous-hop node to stop subsequent transmission and clear the data cache, and the flow of the redundancy calculation module is shown in fig. 4.
3. Coding module
The encoding module encodes a batch of original data packets at the source node and outputs encoded data packets. To avoid complex matrix operation overhead, the encoding module uses a cauchy-matrix-based encoding matrix. Assuming that a batch of data contains n original packets, the coding redundancy is set to t, k=c+n coded packets will be generated, where c=t×n. The coding matrix Φ k×n used can be expressed as:
Wherein I n is an n-order identity matrix. E c×n is a c n coding matrix, which is a submatrix of the following Cauchy matrix:
Where x i,yj∈GF(2q), i, j=1, 2,..n, and x i≠yj. One simple method of value is to let x i＝2i-1,yi = 2i, which depends on the line number i, and the range of values depends on the size of the finite field GF (2 q). After encoding using the cauchy matrix-based encoding matrix Φ k×n, the source node will obtain k encoded data packets for subsequent transmission. The flow of the encoding module is shown in fig. 5.
4. Decoding module
It can be demonstrated that the random selection of n rows from Φ k×n creates an n-th order matrix Φ n that is reversible. Therefore, the destination node can complete the decoding operation as long as receiving n different coded data packets of the batch, and finally outputs the complete original data of the batch. The unique cauchy matrix-based encoding matrix design is beneficial, and once the value function of the matrix elements is determined, the node can calculate all possible decoding matrices off-line and store them in memory space. If the node receives enough coded data packets, the corresponding decoding matrix can be directly selected from the memory, so that the original data recovery is completed quickly. The flow of the decoding module is shown in fig. 6.
5. Data storage and receiving-transmitting module
The data storage and transceiving module comprises a data buffer and a transceiving queue of the node, is responsible for temporarily storing coded data packets of which the batch is not completed, and executes basic bottom data transceiving operation. The flow is shown in fig. 7.
Examples
This embodiment is exemplified by a feedback-based retransmission procedure. The embodiment optimizes the data coding transmission protocol in the deep space network, and greatly improves the data transmission reliability and the utilization rate of the channel. The feedback-based hop-by-hop transmission mechanism employed in the present embodiment is described below.
As shown in the right diagram (2) of FIG. 8, ① node A forwards a batch of coded packets to node B, A being the sender and B being the receiver. ② The redundancy check module of the node B checks the number of different received coded data packets in the data cache, finds that the number of the coded data packets received currently does not meet the redundancy guarantee requirement, generates a feedback packet containing information of the coded data packets of the batch, and sends the feedback packet to the node A. ③ And after receiving the feedback packet, the node A continuously transmits the coded data packet of the batch from the data buffer. ④ The redundancy check module of the node B checks the number of different received coded data packets in the data cache, finds that the number of the coded data packets currently received meets the redundancy guarantee requirement, generates a feedback packet containing the information of stopping sending the batch of coded data packets and sends the feedback packet to the node A. And the node A receives and stops the forwarding of the batch of coded data packets and clears corresponding cache data from the data cache.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a single embodiment, and that this description is provided for clarity only, and that the disclosure is not limited to specific embodiments, and that the embodiments may be combined appropriately to form other embodiments that will be understood by those skilled in the art.

Claims (5)

1.一种基于逐跳冗余确认的深空网络链路自适应编码传输方法，其特征在于，包括：1. A deep space network link adaptive coding transmission method based on hop-by-hop redundant confirmation, characterized by comprising: 数据传输架构，具有链路感知模块、冗余计算模块、编码模块、解码模块、数据缓存及收发队列，其中，深空网络的每个节点均使用链路感知模块、数据缓存和收发队列；源节点使用冗余计算模块和编码模块；中间节点使用冗余计算模块；目的节点使用解码模块；The data transmission architecture has a link sensing module, a redundant computing module, an encoding module, a decoding module, a data cache and a transceiver queue, wherein each node of the deep space network uses the link sensing module, the data cache and the transceiver queue; the source node uses the redundant computing module and the encoding module; the intermediate node uses the redundant computing module; and the destination node uses the decoding module; 链路感知模块通过定期在节点间发送拓扑学习包来动态估计节点间的链路丢包率；The link awareness module dynamically estimates the packet loss rate of links between nodes by periodically sending topology learning packets between nodes; 冗余计算模块在源节点处根据估计的链路丢包率计算最优冗余度，并在中间节点处根据估计的链路丢包率计算所需的最小编码数据包数量；The redundancy calculation module calculates the optimal redundancy according to the estimated link packet loss rate at the source node, and calculates the minimum number of required coded data packets according to the estimated link packet loss rate at the intermediate node; 编码模块在源节点处根据计算得到的最优冗余度，使用基于柯西矩阵的编码矩阵对原始数据进行编码，输出编码数据包；The encoding module encodes the original data at the source node according to the calculated optimal redundancy using a coding matrix based on the Cauchy matrix and outputs a coded data packet; 解码模块在目的节点处对接收到的编码数据包进行解码，输出原始数据；The decoding module decodes the received coded data packet at the destination node and outputs the original data; 数据缓存在每个节点处暂存编码数据包，并在传输未完成时进行批次检查，根据检查结果生成相应的反馈包，通知上一跳节点继续传输或清理数据缓存；The data cache temporarily stores the encoded data packets at each node and performs batch checks when the transmission is not completed. According to the check results, the corresponding feedback packets are generated to notify the previous hop node to continue the transmission or clear the data cache; 收发队列包括接收队列和发送队列，用于在每个节点处进行数据包与反馈包的接收操作和发送操作；The transceiver queue includes a receiving queue and a sending queue, which are used to perform receiving operations and sending operations of data packets and feedback packets at each node; 其中，编码数据包的单跳内传输流程如下：当前节点向下一跳节点发送编码数据包，下一跳节点接收编码数据包后暂存于数据缓存内，检查当前批次编码数据包是否满足后续传输或解码的冗余要求，并根据检查结果通过反馈包通知当前节点继续传输或停止传输。Among them, the single-hop transmission process of the encoded data packet is as follows: the current node sends the encoded data packet to the next-hop node, and the next-hop node temporarily stores the encoded data packet in the data cache after receiving it, checks whether the current batch of encoded data packets meets the redundancy requirements of subsequent transmission or decoding, and notifies the current node to continue or stop transmission through the feedback packet based on the inspection results. 2.根据权利要求1所述的一种基于逐跳冗余确认的深空网络链路自适应编码传输方法，其特征在于，所述检查当前批次编码数据包是否满足后续传输或解码的冗余要求，并根据检查结果通过反馈包通知当前节点继续传输或停止传输，具体包括：2. According to claim 1, a deep space network link adaptive coding transmission method based on hop-by-hop redundancy confirmation is characterized in that the step of checking whether the current batch of coded data packets meets the redundancy requirements of subsequent transmission or decoding, and notifying the current node to continue transmission or stop transmission through a feedback packet according to the inspection result, specifically includes: 若下一跳节点已经收到的编码数据包数量尚未满足冗余要求，则下一跳节点将向当前节点发送包含需要继续传输编码数据包信息的反馈包，当前节点收到该反馈包后将继续向下一跳节点传输当前批次的编码数据包；若下一跳节点收到的编码数据包数量已经满足了后续传输或解码的冗余要求，则下一跳节点将向当前节点发送包含编码数据包数量已经足够信息的反馈包，当前节点收到该反馈包后将停止当前批次编码数据包的后续传输，并从当前节点的数据缓存中移除当前批次的编码数据包。If the number of coded data packets received by the next-hop node has not yet met the redundancy requirement, the next-hop node will send a feedback packet containing information about the need to continue transmitting the coded data packets to the current node. After receiving the feedback packet, the current node will continue to transmit the current batch of coded data packets to the next-hop node; if the number of coded data packets received by the next-hop node has met the redundancy requirement for subsequent transmission or decoding, the next-hop node will send a feedback packet containing information that the number of coded data packets is sufficient to the current node. After receiving the feedback packet, the current node will stop subsequent transmission of the current batch of coded data packets and remove the current batch of coded data packets from the data cache of the current node. 3.根据权利要求1所述的一种基于逐跳冗余确认的深空网络链路自适应编码传输方法，其特征在于，所述链路感知模块通过定期在节点间发送拓扑学习包来动态估计节点间的链路丢包率，具体包括：3. According to the method for adaptive coding and transmission of deep space network links based on hop-by-hop redundant confirmation in claim 1, it is characterized in that the link perception module dynamically estimates the link packet loss rate between nodes by regularly sending topology learning packets between nodes, specifically comprising: 链路li,j的丢包率表示为pi,j；从节点Ui到目的节点UD的链路丢包率表示为pi→D；对于节点Ui和节点Ui的下一跳节点Uj，链路丢包率pi→D满足：The packet loss rate of link l i,j is denoted as p i,j ; the packet loss rate of the link from node U i to destination node UD is denoted as p i→D ; for node U i and the next hop node U j of node U i , the link packet loss rate p i→D satisfies: pi→D＝1-(1-pj→D)×(1-pi,j)； (1)p i→D =1-(1-p j→D )×(1-p i,j ); (1) 当一个节点Ui接收到目的节点Ud生成的拓扑学习包后，根据式(1)计算链路丢包率，并将更新后的拓扑学习包继续转发给邻居节点；如果收到同一个节点生成的多个拓扑学习包，则选择转发跳数最少的拓扑学习包，从而实现链路丢包率的定期更新。When a node Ui receives a topology learning packet generated by the destination node Ud , it calculates the link packet loss rate according to formula (1) and continues to forward the updated topology learning packet to its neighboring nodes. If it receives multiple topology learning packets generated by the same node, it selects the topology learning packet with the least forwarding hops, thereby achieving regular update of the link packet loss rate. 4.根据权利要求1所述的一种基于逐跳冗余确认的深空网络链路自适应编码传输方法，其特征在于，所述冗余计算模块在源节点处根据估计的链路丢包率计算最优冗余度，并在中间节点处根据估计的链路丢包率计算所需的最小编码数据包数量，具体包括：4. According to claim 1, a deep space network link adaptive coding transmission method based on hop-by-hop redundant confirmation is characterized in that the redundancy calculation module calculates the optimal redundancy at the source node according to the estimated link packet loss rate, and calculates the minimum number of coded data packets required at the intermediate node according to the estimated link packet loss rate, specifically including: 将一个批次的原始数据包的数量记为NS，源节点生成的编码数据包数量记为NC，编码冗余度为t，则有：The number of original data packets in a batch is recorded as N S , the number of coded data packets generated by the source node is recorded as N C , and the coding redundancy is t, then: NC＝(t+1)×NS； NC = (t + 1) × NS ; 将要求的成功解码概率阈值记为Γ*；源节点生成并发送的NC个编码数据包中，有不少于NS个不同的编码数据包到达目的地节点，使得原始数据能够解码的概率ΓL为：The required successful decoding probability threshold is Γ * ; among the N C coded data packets generated and sent by the source node, there are no less than N S different coded data packets arriving at the destination node, so that the probability Γ L of the original data being decodable is: 其中NC≥NS；则最小的NC通过求解如下的最小化问题获得：Where N C ≥ N S ; the minimum N C is obtained by solving the following minimization problem: 其中，冗余度t为优化变量；若NC的最小值为则最优冗余度t*为：Among them, redundancy t is the optimization variable; if the minimum value of NC is Then the optimal redundancy t * is: 源节点的冗余计算模块将最优冗余度的计算结果用于后续编码模块生成编码数据包，进行数据传输；The redundancy calculation module of the source node uses the calculation result of the optimal redundancy to generate a coded data packet in the subsequent coding module for data transmission; 中间节点的冗余计算模块通过后续路径的链路丢包率情况和批次大小进行计算，以确定需要从上一跳节点获取的最小编码数据包数量Yi，使得目的节点能够以不低于预设阈值Γ*的概率收到足够的编码数据包；中间节点Ui转发Yi个编码数据包能够使得目的地节点完成原始数据解码的概率Γi为：The redundancy calculation module of the intermediate node calculates the link packet loss rate and batch size of the subsequent path to determine the minimum number of coded data packets Yi that need to be obtained from the previous hop node, so that the destination node can receive enough coded data packets with a probability not less than the preset threshold Γ * ; the probability Γ i that the intermediate node U i forwards Yi coded data packets so that the destination node can complete the decoding of the original data is : 中间节点需要的最小编码数据包数量Yi通过求解如下的最小化问题获得：The minimum number of encoded packets Yi required by the intermediate node is obtained by solving the following minimization problem: 中间节点的冗余计算模块将Yi与当前数据缓存中不同的编码数据包数量进行比较，若当前收到的编码数据包数量少于Yi，则将生成的反馈包回传至上一跳节点，要求继续传输编码数据包，直至收到的不同编码数据包数量超过Yi，再生成反馈包至上一跳节点，通知上一跳节点停止后续编码数据包的发送并清理数据缓存。The redundancy calculation module of the intermediate node compares Yi with the number of different coded data packets in the current data cache. If the number of coded data packets currently received is less than Yi , the generated feedback packet is sent back to the previous hop node, requesting to continue transmitting the coded data packets until the number of different coded data packets received exceeds Yi . Then, a feedback packet is generated to the previous hop node to notify the previous hop node to stop sending subsequent coded data packets and clean up the data cache. 5.根据权利要求4所述的一种基于逐跳冗余确认的深空网络链路自适应编码传输方法，其特征在于，所述编码模块在源节点处根据计算得到的最优冗余度，使用基于柯西矩阵的编码矩阵对原始数据进行编码，输出编码数据包，具体包括：5. According to the method for adaptive coding transmission of deep space network links based on hop-by-hop redundant confirmation of claim 4, it is characterized in that the coding module encodes the original data at the source node according to the calculated optimal redundancy using a coding matrix based on a Cauchy matrix and outputs a coded data packet, specifically comprising: 设一批数据包含n个原始数据包，编码冗余度设置为t*，则编码模块将生成k＝c+n个编码数据包，其中c＝t*×n，使用的编码矩阵Φk×n表示为：Assume that a batch of data contains n original data packets, and the coding redundancy is set to t*. Then the coding module will generate k=c+n coded data packets, where c=t*×n. The coding matrix Φ k×n used is expressed as: 其中In为n阶单位矩阵；Ec×n为c×n的编码矩阵，是如下柯西矩阵Cn×n的子矩阵：Where I n is the n-order identity matrix; E c×n is the c×n encoding matrix, which is a submatrix of the following Cauchy matrix C n×n : 其中，xi,yj∈GF(2q),i,j＝1,2,...,n,且xi≠yj；GF(2q)表示有限域；使用基于柯西矩阵的编码矩阵Φk×n进行编码后，源节点将获得k个编码数据包用于后续传输。Wherein, x i ,y j ∈GF(2 q ), i,j＝1,2,...,n, and x i ≠y j ; GF(2 q ) represents a finite field; after encoding using a coding matrix Φ k×n based on a Cauchy matrix, the source node will obtain k coded data packets for subsequent transmission.
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