A scheduling method for physical layer network coding coordination applied to linear multi-dive underwater acoustic networks

Abstract

This invention relates to a physical layer network coding coordination scheduling method for linear multi-hop underwater acoustic networks. This method introduces PNC (Physical Number Coordination) technology into the link access strategy design of linear multi-hop underwater acoustic networks, overcoming the inherent inter-hop interference limitations of such networks. The method includes the following steps: all sensor nodes transmit local data packets in time slot 1; all sensor nodes except the upstream and downstream nodes simultaneously receive data packets from upstream and downstream neighbor nodes in even-numbered time slots, obtaining coded data packets after PNC mapping; the downstream sensor node receives data packets from upstream neighbor nodes in even-numbered time slots; all sensor nodes transmit data packets received in the previous time slot in odd-numbered time slots; and the sink node completes data packet reception in even-numbered time slots. Compared with existing technologies, this invention exhibits better performance in channel utilization, throughput, and end-to-end latency, especially in channel utilization, which can reach half of the theoretical upper limit.

Description

Technical Field

[0001] This invention relates to the fields of underwater acoustic communication, underwater acoustic networks, and media access control (MAC) protocol design, and in particular to a scheduling mechanism for physical layer network coding coordination applied to linear multi-hop underwater acoustic networks. Background Technology

[0002] With the rapid development of the marine economy, the increasing human activities in the ocean, and the growing awareness of marine protection and security, marine science and technology have received unprecedented attention from countries around the world. In order to respond to the needs of marine strategy and improve my country's marine development, utilization, and management capabilities, the construction of the "Smart Ocean" project is urgently needed. It aims to rely on the development of information technology to improve the marine information collection and transmission system and to establish a sound underwater communication network.

[0003] The "Smart Ocean" project encompasses important industrial production and public safety sectors such as marine shipping, oil and gas and mineral resource exploration and extraction, marine environmental monitoring, marine fisheries, offshore wind power, and emergency rescue. Among these, the specific application requirements for transmitting underwater information have garnered significant attention. For example, oil and gas exploration requires underwater communication while drilling to monitor the status of underwater equipment; submarine earthquake monitoring requires real-time transmission of seismic wave information via underwater communication; and underwater target detection requires submersible buoys to remain silent on the seabed and report anomalies in real time using underwater communication technology. All these applications require comprehensive, balanced, and real-time monitoring of the marine environment over a wide linear area. An underwater network with a linear multi-hop topology, where sensor nodes are evenly deployed over a wide area, collects information through multi-hop relays before reaching buoy nodes and interacts with the internet in real time via satellite links. This effectively meets these business needs and represents a relatively economical and efficient networking form for underwater information transmission. As the most widely used underwater transmission method, acoustic communication has inherent characteristics such as long propagation delay, large transmission loss, and narrow available bandwidth, which pose great challenges to how to build an efficient, real-time, and reliable linear multi-dip underwater acoustic network. Among these challenges, the link access strategy that coordinates the sharing of limited channel resources among various sensor nodes in the network is of paramount importance in improving the performance of the underwater acoustic network.

[0004] Existing link access strategies for linear multi-drop underwater acoustic networks include end-to-end continuous link scheduling and dynamic programming-based scheduling methods. These methods have relatively low channel utilization and throughput. Summary of the Invention

[0005] To address the problems existing in the prior art, the present invention aims to provide a scheduling method for physical layer network coding coordination applied to linear multi-dip underwater acoustic networks, which improves the channel utilization and throughput of linear multi-dip underwater acoustic networks while ensuring local load balancing.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A scheduling method for physical layer network coding coordination applied to a linear multi-dive underwater acoustic network, wherein the linear multi-dive underwater acoustic network consists of K sensor nodes and N k The network consists of a sensor node (k = 1, 2, ..., K) and a sink node. Sensor nodes farther from the sink node are called upstream nodes, and sensor nodes closer to the sink node are called downstream nodes. Data packets flow from upstream nodes to downstream nodes. PNC (Positioning Control) technology is introduced into the linear multi-dive underwater acoustic network. The scheduling method first determines the number of sensor nodes K in the network. When the number of sensor nodes K is less than or equal to A, a direct PNC scheduling mechanism is adopted. The sink node needs to be configured with a buffer, while the sensor nodes do not. The data scheduling process is as follows:

[0008] (1) Sensor node N k (k = 1, 2, ..., K) sends local data packet x in time slot 1. k ;

[0009] (2) Sensor node N k (k=2,3,…,K-1) In the even time slot 2m (0<m<k), data packets from upstream and downstream neighbor nodes are received simultaneously, and encoded data packets are obtained after PNC mapping;

[0010] (3) Sensor node N K Receive data packets from upstream neighbor nodes in even-numbered time slots 2m (0 < m < K);

[0011] (4) Sensor node N k (k=1,2,…K) In the odd-numbered time slot 2m+1 (0<m<k), the data packets received in the previous time slot are sent;

[0012] (5) The sink node completes the reception of data packets in an even time slot of 2m (0<m≤K);

[0013] All packets x k The data packets arrive at the sink node in time slot 2 (K-k+1) in the form of ordinary data packets or PNC-encoded data packets combined with downstream data packets. The sink node maintains a buffer that stores all successfully received target data packets.

[0014] When the number of sensor nodes K is greater than A, a code-assisted PNC scheduling mechanism is adopted. All sensor nodes in the network (except N1) need to be configured with buffers, while the sink node does not need to be configured with buffers. The data scheduling process is as follows:

[0015] (1) Sensor node Nk (k = 1, 2, ..., K) sends local data packet x in time slot 1. k And store the data packet in the node's own buffer (except for N1);

[0016] (2) Sensor node N k (k=2,3,…,K-1) In the even time slot 2m (0<m<K), data packets from upstream and downstream neighbor nodes are received simultaneously, and encoded data packets are obtained after PNC mapping;

[0017] (3) Sensor node N K Receive data packets from upstream neighbor nodes in even-numbered time slots 2m (0 < m < K);

[0018] (4) Sensor node N k (k=1,2,…K) In odd time slot 3, the data packet received in the previous time slot is sent and the data packet is stored in the node’s own buffer;

[0019] Sensor node N k (k=1,2,…K) In the odd-numbered time slot 2m+1 (1<m<k) which is not time slot 1 and not time slot 3, the data packets sent before the previous time slot are encoded to obtain the target data packet. Then the data packet is sent and stored in the node's own buffer.

[0020] (5) The sink node directly receives the target data packet x from the upstream neighbor node in an even time slot of 2m (0 < m ≤ K). K-m+1 .

[0021] By adopting the above solution, the present invention has the following beneficial effects: Compared with the prior art, the present invention has the following outstanding advantages and effects:

[0022] 1) The present invention has better performance in terms of channel utilization, throughput and end-to-end latency, especially the channel utilization can reach 1 / 2 of the theoretical upper limit;

[0023] 2) The advantages of the direct PNC scheduling mechanism are that it is simple to implement, has low hardware requirements, and all sensor nodes operate exactly the same as the nodes in the traditional two-way relay communication system, and no buffer configuration is required.

[0024] 3) The advantage of the coding-assisted PNC scheduling mechanism is that it can optimize the end-to-end bit error rate performance by using coding to block error propagation, which is more friendly to large-scale networks. Attached Figure Description

[0025] Figure 1 This is a deployment diagram of a linear multi-dive acoustic network.

[0026] Figure 2 This is a schematic diagram illustrating the principle of physical layer network coding technology.

[0027] Figure 3 This is a schematic diagram of the direct PNC scheduling mechanism.

[0028] Figure 4 This is a schematic diagram of a coding-assisted PNC scheduling mechanism.

[0029] Figure 5 This is a schematic diagram comparing the channel utilization of the present invention and existing inventions under ideal channel conditions.

[0030] Figure 6 This is a schematic diagram comparing the throughput of the present invention and existing inventions under ideal channel conditions.

[0031] Figure 7 This is a schematic diagram comparing the end-to-end delay performance of the present invention and existing inventions under ideal channel conditions.

[0032] Figure 8 This is a BER analysis diagram of a linear multi-dive underwater acoustic network under a direct PNC scheduling mechanism.

[0033] Figure 9 This is a schematic diagram of the average end-to-end BER of the direct PNC scheduling mechanism under different network sizes.

[0034] Figure 10 This is a diagram illustrating the channel utilization of the direct PNC scheduling mechanism under different network sizes.

[0035] Figure 11 This is a BER analysis diagram of a linear multi-dive underwater acoustic network under a coding-assisted PNC scheduling mechanism.

[0036] Figure 12 This is a schematic diagram of the average end-to-end BER of the coding-assisted PNC scheduling mechanism under different network sizes.

[0037] Figure 13 This is a diagram illustrating the channel utilization of the coding-assisted PNC scheduling mechanism under different network sizes. Detailed Implementation

[0038] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be more thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art.

[0039] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0040] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0041] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0042] This invention applies, for example Figure 1 The linear multi-dive underwater acoustic network shown consists of K sensor nodes N k The system consists of a group of nodes (k = 1, 2, ..., K) and a sink node. These nodes are evenly arranged in a straight line, with a distance of d between adjacent nodes. Each node is equipped with a sensor module and an acoustic module. The sensor module is responsible for collecting marine environmental information, while the acoustic module converts the collected data into acoustic signals and continuously transmits them to the next hop node in the form of data packets, eventually converging at the sink node.

[0043] Sensor nodes farther from the sink node are called upstream nodes, and those closer to the sink are called downstream nodes. Data packets flow from upstream to downstream nodes. Therefore, the load of each node consists of two parts: the local load generated by the data collected by the node's own sensors, and the relay load received from neighboring nodes. To ensure local load balancing, each sensor node collects the same amount of data within the same time period. For ease of analysis, the duration of a time slot is set to the one-hop propagation delay when the distance between nodes is , while the duration of a data packet is set slightly shorter than the time slot duration. Thus, a data packet transmitted by a node at the beginning of one time slot will arrive at its destination node at the beginning of the next time slot. Based on the analysis of interference range in underwater acoustic networks, the transmission range of each node can be reasonably set to one hop, and the interference range to two hops.

[0044] Furthermore, this invention introduces PNC (Physical Layer Network Coding) technology into a linear multi-dive underwater acoustic network. PNC technology is relatively mature, such as... Figure 2 As shown, two source nodes A and B transmit data packet x through relay node R. A and x B The exchange can simultaneously receive x using the PNC relay node R. A and x B And map to obtain encoded data packets ( (This represents the XOR operation), then R will x NC The broadcast is sent to nodes A and B; after receiving the encoded data packet, node A... The decoding operation yields the target data packet x. B Node B then... The decoding operation yields x A .

[0045] The scheduling method of the present invention specifically includes the following:

[0046] Determine the number of sensor nodes K in the network, and decide whether to use a direct PNC scheduling mechanism or a coding-assisted PNC scheduling mechanism.

[0047] When the number of sensor nodes K is less than or equal to A (the value of A depends on the network end-to-end BER threshold and signal-to-noise ratio for specific communication requirements; in this embodiment, K can be 6), the network is a small-scale linear multi-dip underwater acoustic network, employing a direct PNC scheduling mechanism. The sink node in the network needs to be configured with a buffer, while the sensor nodes do not. When the number of sensor nodes K is greater than A, the network is a large-scale linear multi-dip underwater acoustic network, employing an encoding-assisted PNC scheduling mechanism. All sensor nodes in the network (except N1) need to be configured with a buffer, while the sink node does not.

[0048] When a linear multi-dive underwater acoustic network adopts a direct PNC scheduling mechanism, the data scheduling process is as follows:

[0049] (1) Sensor node N k (k = 1, 2, ..., K) sends local data packet x in time slot 1. k .

[0050] (2) Sensor node N k (k = 2, 3, ..., K-1) In even time slot 2m (0 < m < k), data packets are simultaneously received from upstream and downstream neighbor nodes, and encoded data packets are obtained after PNC mapping. For example... Figure 3As shown, dark gray represents data packet transmission, and white represents data packet reception. Relay N3 simultaneously receives data packets from nodes N2 and N4 in time slot 2, and obtains the encoded data packets after PNC mapping.

[0051] (3) Sensor node N K (At this time K=6) Receive data packets from upstream neighbor nodes in even time slot 2m (0<m<K).

[0052] (4) Sensor node N k (k=1,2,…K) In the odd-numbered time slot 2m+1 (0<m<k), the data packets received in the previous time slot are sent.

[0053] (5) The sink node completes the reception of data packets in an even time slot of 2m (0<m≤K).

[0054] All packets x k All data packets can arrive at the sink node in time slot 2 (K-k+1) as ordinary data packets or PNC-encoded data packets combined with downstream data packets. The sink node maintains a buffer that stores all successfully received target data packets. Figure 3 As shown, since the data packets from downstream nodes arrive at the Sink earlier, the sink node can predict the data packet format in advance and use the data packets stored in the buffer to decode and extract the required data packets.

[0055] When a linear multi-dive underwater acoustic network employs a code-assisted PNC scheduling mechanism, the data scheduling process is as follows:

[0056] (1) Sensor node N k (k = 1, 2, ..., K) sends local data packet x in time slot 1. k The data packet is then stored in the node's own buffer (except for N1).

[0057] (2) Sensor node N k (k = 2, 3, ..., K-1) In even time slot 2m (0 < m < K), data packets are simultaneously received from upstream and downstream neighbor nodes, and encoded data packets are obtained after PNC mapping. For example... Figure 4 As shown, dark gray represents data packet transmission, and white represents data packet reception. Relay N3 simultaneously receives data packets in time slot 4. and Encoded data packets obtained through PNC mapping

[0058] (3) Sensor node N K Data packets from upstream neighbor nodes are received in even time slots of 2m (0 < m < K).

[0059] (4) Sensor node N k (k=1,2,…K) In odd time slot 3, the data packet received in the previous time slot is sent and the data packet is stored in the node’s own buffer.

[0060] Sensor node N k (k = 1, 2, ..., K) In an odd-numbered time slot 2m+1 (1 < m < k) that is not in time slot 1 or time slot 3, the data packets sent before the previous time slot are encoded (XOR operation) to obtain the target data packet. This target data packet is then sent and stored in the node's own buffer. For example... Figure 4 As shown, relay N3 sends 3 packets of data that were previously stored in the node buffer four times before time slot 5, and receives the packets. Encoding

[0061] (5) The sink node directly receives the target data packet x from the upstream neighbor node in an even time slot of 2m (0 < m ≤ K). K-m+1 .

[0062] To illustrate the effectiveness of the scheduling method of the present invention, it is compared with existing methods below.

[0063] Figure 5-7 This chart compares the performance of the method of this invention with existing end-to-end continuous link scheduling methods and dynamic programming-based scheduling strategies under ideal channel conditions and error-free transmission, as the network size varies. Figure 5 This is a comparison chart of network utilization. Figure 6 This is a throughput comparison chart. Figure 7 A comparison chart of end-to-end latency, from Figure 5-7 As can be seen, compared with existing methods, the present invention has better performance in terms of channel utilization, throughput and end-to-end latency, and its advantages become more obvious as the network scale increases, especially the channel utilization can reach half of the theoretical upper limit.

[0064] Figure 8This is a bit error rate (BER) analysis diagram of the method of this invention using a direct PNC scheduling mechanism. In this invention, since all data packets propagate simultaneously to upstream and downstream nodes and are superimposed with other data packets that generate single-hop interference to form encoded data packets, error propagation occurs in linear multi-hop networks. Error propagation refers to the fact that the decoding error of downstream node data packets propagates to upstream node data packets, resulting in a high end-to-end BER. Because data packets are continuously PNC encoded by nodes two hops away, the decoding error of node N6 for data packet x5 in time slot 2 will propagate to data packets generated by all odd-numbered upstream nodes. Therefore, when an odd (even) numbered data packet has an estimation error on the link, it will affect the estimation error of all subsequent odd (even) numbered data packets, that is, data packet x... k The end-to-end error will affect the next (Kk) / 2 data packets.

[0065] Figure 9 and 10 This describes the performance of the method of the present invention under different network sizes when using a direct PNC scheduling mechanism. Figure 9 It is the average end-to-end BER under additive white Gaussian noise channel; Figure 10 This refers to channel utilization under additive white Gaussian noise (AWGN) conditions. Due to error propagation, the end-to-end BER increases exponentially with network size, leading to a significant decrease in channel utilization. Improving the signal-to-noise ratio (SNR) can improve both end-to-end BER and channel utilization to some extent, and the improvement is more significant in larger networks.

[0066] Figure 11 This is a BER analysis diagram under the PNC scheduling mechanism with encoding assistance used in this invention. Since each node needs to re-encode the received data packet with the previously sent data packet, any erroneous symbols caused by reception errors will appear simultaneously in both the received data packet and the required buffer data packet. Encoding these two packets cancels out the erroneous symbols, thus preventing error propagation. When node N6 estimates an error in data packet x5 in time slot 2, it only affects the data packet in the gray shaded area of ​​the diagram. When node N6 receives data packet x3 in time slot 2, it needs to encode it with x5 in the buffer. Since both data packets have errors in the same symbol, the errors cancel each other out. Similarly, other data packets received by the Sink afterward will not be affected by the error in x5.

[0067] Figure 12-13 This describes the performance of the coding-assisted PNC scheduling mechanism employed in this invention under different network sizes. Figure 12 It is the average end-to-end BER under additive white Gaussian noise channel; Figure 13This refers to channel utilization under additive white Gaussian noise (AGO) channel conditions. Compared to the direct PNC scheduling mechanism, the end-to-end BER and channel utilization of the network are significantly improved. Although the end-to-end BER increases with the network size due to the increase in the number of transmission hops, the increase is linear and the magnitude is small, and the channel utilization only decreases slightly. Similarly, improving the signal-to-noise ratio (SNR) will improve the end-to-end BER and channel utilization to some extent, and the improvement is more significant in larger networks.

[0068] In summary, the direct PNC scheduling mechanism has the advantages of simple operation and low hardware requirements; while the code-assisted PNC scheduling mechanism solves the error propagation problem of PNC in multi-hop networks, has better end-to-end BER, and is more friendly to large-scale networks.

[0069] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein.

[0070] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A scheduling method for physical layer network coding coordination applied to a linear multi-dive underwater acoustic network, wherein the linear multi-dive underwater acoustic network consists of... sensor nodes and a convergence node Composition, in which, ; away from the convergence node The sensor node is called the upstream node, which is close to The sensor nodes are called downstream nodes, and data packets flow from upstream nodes to downstream nodes; the feature is that PNC technology is introduced into the linear multi-dive underwater acoustic network, and the scheduling method first determines the number of sensor nodes in the network. The number of sensor nodes When the number of sensor nodes K is less than or equal to A, the network is a small-scale linear multi-dip underwater acoustic network, employing a direct PNC scheduling mechanism. The sink node in the network needs to be configured with a buffer, while the sensor nodes do not require buffer configuration. When the number of sensor nodes K is greater than A, the network is a large-scale linear multi-dip underwater acoustic network, employing a code-assisted PNC scheduling mechanism. Except for the sensor nodes K, the network requires buffer configuration. All external nodes require a buffer to be configured, while the sink node does not require a buffer to be configured. When a linear multi-dive underwater acoustic network adopts a direct PNC scheduling mechanism, the data scheduling process is as follows: (1) Sensor Node Send local data packets in time slot 1 ,in, ; (2) Sensor Node In even time slots Simultaneously, data packets are received from both upstream and downstream neighbor nodes. After PNC mapping, encoded data packets are obtained, where... , ; (3) Sensor Node In even time slots Receive data packets from upstream neighboring nodes; (4) Sensor Node In odd time slots Send the data packets received in the previous time slot, where, ; (5) Convergence Node In even time slots Complete the reception of data packets; All data packets In the time slot, either as a regular data packet or as a PNC-encoded data packet combined with downstream data packets. Reaching the convergence node And the convergence node The maintained buffer stores all successfully received target data packets.

2. The scheduling method for physical layer network coding coordination applied to linear multi-dive underwater acoustic networks according to claim 1, characterized in that: When a linear multi-dive underwater acoustic network employs a code-assisted PNC scheduling mechanism, the data scheduling process is as follows: (1) Sensor Node Send local data packets in time slot 1 And store the data packet except In the buffer of the external node itself, where, ; (2) Sensor Node In even time slots Simultaneously, data packets are received from upstream and downstream neighboring nodes, and encoded data packets are obtained after PNC mapping. ; (3) Sensor Node In even time slots Receive data packets from upstream neighboring nodes; (4) Sensor Node In odd-numbered time slot 3, the data packet received in the previous time slot is transmitted, and the data packet is stored in the node's own buffer. ; sensor nodes In odd-numbered time slots that are not time slot 1 or time slot 3 The target data packet is obtained by encoding the data packets received in the previous time slot using the data packets sent four time slots ago stored in the buffer. Then the data packet is sent and stored in the node's own buffer. (5) Convergence Node In even time slots Directly receive target data packets from upstream neighbor nodes .

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