Ocean buoy selective access method under satellite communication network

Abstract

The invention discloses an ocean buoy selection access method under a satellite communication network, which comprises the following steps: based on a time slot framework, sensing the link state of a coverage satellite in real time through buoy equipment at the beginning of each time slot, fusing multi-dimensional parameters such as signal strength, bandwidth and time delay, and quantifying the link quality by using a channel estimation algorithm; an optimal satellite link is dynamically selected through a deep reinforcement learning intelligent decision algorithm, and multi-target collaborative optimization of throughput maximization, inter-satellite load balance and access delay minimization is realized; in the execution stage, reliable access is completed by adopting a standardized four-way handshake mechanism, and meanwhile, invalid links are actively avoided through an elevation coverage model. The method has the advantages that the communication efficiency and reliability of a dense buoy area are improved, the computing power requirement of a miniaturized buoy terminal is reduced, and a core support of a self-adaptive dynamic environment is provided for a global ocean monitoring network.

Description

Technical Field

[0001] This invention relates to the field of satellite communication technology, and in particular to a method for selecting and accessing marine buoys in a satellite communication network. Background Technology

[0002] In marine environmental monitoring, buoys play a crucial role, collecting key data such as temperature, salinity, and current velocity in real time and transmitting them to land-based data centers via communication links. Because marine areas are far from land-based base stations, buoys must rely on satellite networks for remote connectivity. However, buoys are typically designed with miniaturized structures and only equipped with a single antenna interface, making it impossible to connect to multiple satellites simultaneously. Furthermore, the random distribution and dynamic drift of marine environmental buoys pose significant challenges to the stability of communication links. With the continuous expansion of global marine monitoring and the increasing number of buoys, the demands for reliability and real-time performance of communication systems are becoming increasingly urgent, and existing access mechanisms are struggling to efficiently handle large-scale deployment scenarios.

[0003] Low-Earth orbit (LEO) satellite networks, with their wide coverage, are ideal for maritime communications. Multiple satellites often overlap in coverage during operation, providing buoys with multiple potential connection opportunities. However, satellite orbital motion causes dynamic changes in coverage areas, and whether a buoy can connect to a specific satellite depends on the elevation angle between them—when the elevation angle is not lower than the minimum communication threshold, the satellite can cover the buoy; otherwise, a connection cannot be established. Simultaneously, communication channels in the marine environment exhibit significant time-varying characteristics. Signal propagation is affected by a combination of Doppler shift, multipath interference, and atmospheric attenuation, causing drastic fluctuations in channel quality and further increasing the complexity of link selection.

[0004] Existing access methods suffer from multiple bottlenecks. When multiple buoys simultaneously compete for high-quality satellite links, the limited communication channels are prone to congestion. Some studies alleviate congestion by delaying the buoy access time and distributing requests across different time slots, but this strategy sacrifices system throughput, leading to decreased data transmission efficiency. Uneven load distribution among satellites is a significant problem, with some satellites experiencing performance degradation due to overload, while other satellite resources remain idle and wasted. Access latency cannot be effectively controlled, especially when retransmission mechanisms are triggered, where the cumulative effect of latency is significant, affecting the real-time performance of monitoring data. Traditional decision-making mechanisms rely on static rules (such as prioritizing the strongest signal link) and lack the ability to dynamically fuse multi-dimensional parameters (such as bandwidth, latency, and congestion status), making it unable to adapt to the rapid changes in channel state under block fading channels. While the four-way handshake mechanism improves connection reliability, the interaction process is prolonged under high load conditions, and frequent retransmission operations exacerbate latency issues, making it difficult to balance efficiency and stability.

[0005] To address the aforementioned technological gaps, this invention was developed. Existing methods cannot simultaneously optimize system throughput, satellite load balancing, and minimum access latency, especially in densely populated buoy areas. Therefore, there is an urgent need for an intelligent access mechanism capable of real-time sensing of environmental changes, dynamic fusion of multi-dimensional parameters, and achieving multi-objective balance through adaptive decision-making. This invention innovatively introduces a deep reinforcement learning algorithm to drive buoys to intelligently select the optimal link in each time slot, aiming to overcome the limitations of traditional static strategies and provide highly reliable, low-latency communication support for global ocean monitoring applications, serving key areas such as climate research and disaster early warning. Summary of the Invention

[0006] This invention addresses the shortcomings of existing technologies by providing a method for selecting and accessing marine buoys within a satellite communication network.

[0007] To achieve the above-mentioned objectives, the technical solution adopted by the present invention is as follows:

[0008] A method for selecting and accessing marine buoys in a satellite communication network includes the following steps:

[0009] S1: At the beginning of each transmission time slot, the buoy device senses the link status information of multiple available satellite communication links, including channel quality, link congestion status and signal-to-noise ratio;

[0010] S2: The sensed link status information is fused, and the fused parameters include signal strength, bandwidth and latency from different satellites;

[0011] S3: Based on the information fusion results, a link state assessment layer is used to estimate the channel quality of each available link.

[0012] S4: Input the sensing parameters and channel quality assessment results into the intelligent decision layer, and use the intelligent decision-making algorithm based on deep reinforcement learning to select the optimal satellite communication link for access;

[0013] S5: By executing the access layer, perform access or link switching operations based on the decision results.

[0014] Furthermore, the sensing is performed at the beginning of each time slot, and the sensed link status information includes real-time monitoring of satellite coverage, buoy's own position and availability information; the sensing process is based on the time slot structure of opportunistic access to satellite communication links, where the duration of a single time slot is τ, and the time slot structure includes channel detection and decision-making phases.

[0015] Furthermore, the information fusion includes integrating parameters from multiple heterogeneous satellite systems, specifically by weighting and synthesizing the signal strength, bandwidth, and latency of different satellites to generate a unified link quality index.

[0016] Furthermore, the link state assessment layer employs a channel estimation algorithm to perform channel estimation and quantify the channel quality g. i (t)=|h i (t)| 2 , where h i (t) represents the channel gain of the i-th channel, and the channel model is expressed as:

[0017]

[0018] Where c is the speed of light, f c Let D(s) be the carrier frequency, and D(s) be the atmospheric attenuation component. For Ricean fading, s is the transmission distance between the satellite and the buoy. (x,y) represents the buoy position, (L) x ,L y () indicates the position directly below the satellite.

[0019] Furthermore, the intelligent decision-making layer is based on deep reinforcement learning and dynamically selects access links in each time slot. The decision objective is to maximize system throughput, balance inter-satellite load, and minimize access latency. The decision input includes sensing parameters and channel quality assessment results, and the output is the access identifier of the optimal link.

[0020] Furthermore, the execution access is based on a four-way handshake mechanism, including:

[0021] The buoy device sends an access request Msg1 to the target satellite;

[0022] After satellite verification, an access response Msg2 is returned, which includes uplink timing advance and resource allocation information;

[0023] The buoy sends a contention resolution request Msg3 based on Msg2, which includes the terminal's unique identifier;

[0024] After satellite verification, a contention resolution message Msg4 is sent back to complete the access process; if it fails, a retransmission mechanism is initiated.

[0025] Furthermore, the sensing determines whether the buoy is covered by satellites using a satellite beam coverage model, with the coverage conditions being:

[0026] θ U,M (t)≥θ0

[0027] in, d U,M (t) represents the Euclidean distance. θ0 is the minimum beacon angle.

[0028] Furthermore, the communication connection between the buoy device and the satellite is determined by the binary variable z.U,M (t) represents: when buoy U connects to satellite M, z U,M (t) = 1, otherwise it is 0; the buoy device only connects to one link in a single time slot, and when multiple buoys compete, congestion is avoided by delaying access scheduling.

[0029] Furthermore, the atmospheric attenuation component Where σ is the atmospheric attenuation coefficient, with units of dB / km, and h is the satellite orbital altitude.

[0030] Furthermore, the four-way handshake mechanism involves the physical transport layer, the medium access control layer, and the radio link control layer, where Msg1 is the physical layer preamble, Msg2 contains the access identifier and resource allocation, Msg3 is sent on the physical uplink shared channel, and Msg4 allocates the network temporary identifier.

[0031] Furthermore, this method is applicable to low-Earth orbit satellite networks, where buoy devices are randomly distributed on the sea surface and access is achieved through a single antenna communication interface, ensuring that the load is balanced among satellites and the access latency is minimized while maximizing system throughput.

[0032] Compared with the prior art, the advantages of the present invention are as follows:

[0033] 1. Significantly improve the overall performance of marine buoy communication systems

[0034] This invention, through a deep reinforcement learning-driven dynamic decision-making mechanism, completely resolves the core contradiction in traditional satellite access methods where throughput, load balancing, and access latency cannot be simultaneously balanced. The buoy device senses multi-dimensional link parameters in real time within each time slot, and the intelligent decision-making algorithm simultaneously optimizes three objectives: maximizing data transmission throughput, balancing communication load among multiple satellites, and minimizing buoy access latency. Compared to static scheduling strategies, the system significantly improves data transmission efficiency in densely populated buoy areas while avoiding the risk of communication interruptions due to localized satellite overload, providing highly robust support for large-scale marine monitoring networks.

[0035] 2. Enhance communication reliability in complex marine environments

[0036] To address the challenges of time-varying ocean satellite channels and numerous interference factors (such as Doppler shift and atmospheric attenuation), this invention establishes a precise channel quality assessment and coverage determination model. The buoy device actively filters available satellite links by calculating elevation angle and quantifies the combined effects of Ricean fading and atmospheric attenuation using a channel estimation algorithm, ensuring that only links with stable communication conditions are selected for connection. This mechanism significantly reduces the probability of link interruptions caused by sudden changes in signal quality, enabling the buoy to maintain reliable connections even under adverse weather conditions, thus guaranteeing the continuity and integrity of monitoring data.

[0037] 3. Achieve global optimized scheduling of satellite resources

[0038] By dynamically managing the connection relationship between buoys and satellites using binary variables, a load-adaptive resource allocation system is constructed. When multiple buoys compete for high-quality links, the intelligent decision-making algorithm automatically diverts some access requests to satellites with lower loads, eliminating the contradiction between resource idleness and local congestion in traditional solutions. The overall utilization rate of the satellite network approaches equilibrium, avoiding systemic bottlenecks caused by the overload of a single satellite, and providing elastic scaling capabilities for high-concurrency buoy access scenarios.

[0039] 4. Simplify buoy terminal design and reduce deployment costs

[0040] This invention relates to a buoy device compatible with a single-antenna communication architecture, which replaces complex multi-link parallel processing modules with a time-slotted sensing and decision-making process. The buoy only needs to perform lightweight calculations (such as elevation angle determination and parameter fusion) within a fixed time slot, significantly reducing the computing power requirements and energy consumption of the terminal processor. The standardized process of the four-way handshake mechanism further reduces the customized development cost of protocol interaction, making it possible to deploy miniaturized, low-power buoys on a large scale in the ocean.

[0041] 5. Promote the intelligent upgrading of marine monitoring technologies

[0042] By introducing deep reinforcement learning into the satellite access decision-making layer, the system is endowed with the ability to autonomously adapt to dynamic environments. Buoy devices can learn online about channel variation patterns and satellite trajectories, continuously optimizing link selection strategies and forming a closed-loop learning framework of "perception-evaluation-decision-execution." This technological breakthrough provides unmanned marine monitoring networks with continuous evolution capabilities, supporting the data acquisition needs of key applications such as long-term climate research and disaster early warning. Attached Figure Description

[0043] Figure 1 This is a time slot diagram of opportunistic access to satellite communication links according to an embodiment of the present invention.

[0044] Figure 2 This is a flowchart of the satellite link access process according to an embodiment of the present invention. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and examples.

[0046] This invention provides a method for selecting and accessing marine buoys under a satellite communication network, comprising the following steps:

[0047] At the start of each transmission time slot, the buoy device senses the link status information of multiple available satellite communication links, including channel quality, link congestion status, and signal-to-noise ratio;

[0048] The sensed link status information is fused, and the fused parameters include signal strength, bandwidth and latency from different satellites;

[0049] Based on the information fusion results, a link state assessment layer is used to estimate the channel quality of each available link.

[0050] The sensing parameters and channel quality assessment results are input into the intelligent decision-making layer, and an intelligent decision-making algorithm based on deep reinforcement learning is used to select the optimal satellite communication link for access.

[0051] By executing the access layer, operations such as accessing or switching links are performed based on the decision results.

[0052] The specific implementation of this embodiment is as follows:

[0053] The satellite communication system environment considers ground-orbiting satellites. The satellite network set can be represented as M = {1, 2, ..., m}, where 1 ≤ m ≤ M represents LEO satellites. The set of buoy devices can be represented as U = {1, 2, ..., U}, where 1 ≤ u ≤ U represents surface buoy devices, randomly distributed across a certain area of ​​the sea surface. When a buoy device needs to connect to a satellite link to transmit data, it first senses the satellite communication environment, monitoring in real time the coverage of multiple heterogeneous satellites, their position relative to the buoy itself, and their availability. Then, it fuses the sensed information, including parameters such as signal strength, bandwidth, and latency from different satellite systems. Next, it passes through a link state evaluation layer, using the channel estimation algorithm from Chapter 3 to estimate the channel quality of each available link in each time slot. Then, it sends the sensed parameters and evaluation results to an intelligent decision layer, using a deep reinforcement learning-based intelligent decision-making algorithm to make an access decision for the optimal link in each time slot. Finally, the execution access layer performs the access or link switching operation according to the decision selection.

[0054] Figure 1 For the time slot diagram of the satellite communication link access opportunity, the buoy device needs to sense the status of the communication link at the beginning of each time slot, including information such as channel quality, link congestion, and signal-to-noise ratio. Within each time slot, the decision algorithm selects the optimal communication link to access based on the sensed link status.

[0055] Satellite channel model

[0056] Satellite communication systems in marine environments exhibit significant time-varying characteristics, and their transmission quality is constrained by multiple factors, including but not limited to: Doppler shift caused by orbital motion, multipath interference during signal propagation, and atmospheric absorption effects caused by the ionosphere and troposphere. Based on the characteristics of physical layer propagation, this section constructs a communication channel model suitable for near-Earth orbit satellites in marine environments. This model consists of three components: free-space path loss, Ricean distribution small-scale fading, and signal attenuation caused by atmospheric absorption. The atmospheric attenuation component can be mathematically represented by equation (1):

[0057]

[0058] Where s is the transmission distance between the satellite and the sea surface buoy, h is the satellite's orbital altitude, and σ is the attenuation after passing through the atmosphere, with units of dB / km. The formula for calculating s is shown in equation (2):

[0059]

[0060] Where (x,y) represents the position of the buoy on the sea surface, (L x ,L y () indicates the position directly below the satellite.

[0061] The expression for the satellite channel model is (3):

[0062]

[0063] Where c is the speed of light, f c For carrier frequency, This led to the decline of Rice.

[0064] This embodiment analyzes a satellite communication system based on a time-slot structure. This system employs a fixed-time-slot frame structure, with each time slot lasting for a duration of τ. At the initial stage of each transmission time slot, the buoy device performs channel detection, evaluating the current channel's transmission quality indicators and occupancy status, and dynamically deciding whether to establish an inter-satellite communication connection using an intelligent decision-making algorithm.

[0065] Assuming the buoy chooses the i-th channel for communication, the expression for the transmitted signal after passing through the channel is equation (4):

[0066] y i (t)=x(t)h i (t)+n i (t)+I i (t) (4)

[0067] Where x(t) represents the transmitted signal at time t, h i(t) represents the estimated channel gain of the i-th channel, and n i (t) represents Gaussian white noise, I i (t) represents interference from the environment during transmission. Define g i (t)=|h i (t)| 2 This represents channel quality.

[0068] Suppose a communication link with channel number k has channel quality parameters that follow a probability density function. The channel exhibits a random distribution. It also exhibits block fading characteristics, meaning that the channel state information (CSI) remains constant within a single transmission slot ΔT.

[0069] Satellite beam coverage model

[0070] Because low-Earth orbit (LEO) satellites have a limited beam coverage range, not all LEO satellites can cover a single sea surface buoy. Whether a user is covered can be determined by the relationship between the elevation angle between the buoy and the satellite and a specific minimum communication angle. Assume buoy U is located at {x... U (t),y U (t), 0}, satellite M is located at {x M (t),y M The elevation angle between them is calculated using equation (5): (t), 0}

[0071]

[0072] Where, d U,M (t) represents the Euclidean distance between user U and satellite M, as shown in equation (6):

[0073]

[0074] The coverage relationship between each satellite and the user can be expressed as equation (7):

[0075]

[0076] At any given time t, a single buoy device may detect multiple available satellite communication links, but its single-input, single-output communication interface only supports access to one link. Therefore, using a binary variable z... U,M Let z(t) represent the communication connection between the U-th buoy and the M-th satellite. If buoy U connects to the communication link of satellite M in time slot t, then z(t) U,M (t) = 1, if buoy U fails to connect to the communication link of satellite M in time slot t, then z U,M (t) = 0.

[0077] Access Selection Process

[0078] In the current satellite access selection mechanism, the system adopts a layered protocol architecture to establish and manage links, which mainly includes the following three core protocol layers: physical transport layer, media access control layer, and radio link control layer.

[0079] In satellite communication systems, to improve the reliability of link establishment, an access selection mechanism based on a four-way handshake is designed. This mechanism achieves end-to-end connection verification through multi-round signaling interactions between terminal equipment and satellite nodes. The specific access process is as follows: Figure 2 As shown:

[0080] 1. Terminal initiates access request: In the initial stage of the access selection process, the user terminal device first sends a physical layer preamble signal (Msg1) to the target satellite node to start the connection establishment procedure and initiate an access request.

[0081] 2. The satellite performs verification and returns an access response: After successfully receiving the preamble sequence, the satellite sends back an access response (Msg2) for each access request. This response includes uplink timing advance, backoff parameters, access identifier, and time-frequency domain resources required for subsequent transmission.

[0082] 3. Terminal initiates contention resolution request: After successfully receiving the access response (Msg2) sent by the satellite node, the terminal device extracts the precise timing advance from Msg2 to compensate for the propagation delay, and sends the terminal's unique identifier on the physical uplink shared channel.

[0083] 4. Satellite Response Contention Resolution: After receiving Msg3 from the terminal, the satellite performs multi-user detection and authentication. The system decodes and compares the messages, assigns a unique temporary network identifier to the verified device, and returns a contention resolution message (Msg4) via the downlink channel. If the terminal device correctly decodes Msg4, the access process is considered complete; if no response is received or decoding fails, the terminal will initiate a retransmission mechanism according to a preset strategy, re-initiating the access request within the maximum number of attempts set by the system.

[0084] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the implementation methods of the present invention, and should be understood that the scope of protection of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of the present invention.

Claims

1. A method for selecting and accessing marine buoys under a satellite communication network, characterized in that, Includes the following steps: S1: At the beginning of each transmission time slot, the buoy device senses the link status information of multiple available satellite communication links, including channel quality, link congestion status and signal-to-noise ratio; S2: The sensed link status information is fused, and the fused parameters include signal strength, bandwidth and latency from different satellites; S3: Based on the information fusion results, a link state assessment layer is used to estimate the channel quality of each available link. S4: Input the sensing parameters and channel quality assessment results into the intelligent decision layer, and use the intelligent decision-making algorithm based on deep reinforcement learning to select the optimal satellite communication link for access; S5: By executing the access layer, perform access or link switching operations based on the decision results.

2. The method for selecting and accessing marine buoys according to claim 1, characterized in that, The sensing is performed at the beginning of each time slot, and the sensed link status information includes real-time monitoring of satellite coverage, buoy position and availability information; the sensing process is based on the time slot structure of opportunistic access to satellite communication links, where the duration of a single time slot is τ, and the time slot structure includes channel detection and decision-making phases.

3. The method for selecting and accessing marine buoys according to claim 1, characterized in that, The information fusion includes integrating parameters from multiple heterogeneous satellite systems, specifically by weighting and synthesizing the signal strength, bandwidth, and latency of different satellites to generate a unified link quality index.

4. The method for selecting and accessing marine buoys according to claim 1, characterized in that, The link state assessment layer uses a channel estimation algorithm to perform channel estimation and quantize the channel quality g. i (t)=|h i (t)| 2 , where h i (t) represents the channel gain of the i-th channel, and the channel model is expressed as: Where c is the speed of light, f c Let D(s) be the carrier frequency, and D(s) be the atmospheric attenuation component. For Ricean fading, s is the transmission distance between the satellite and the buoy. (x,y) represents the buoy position, (L) x ,L y () indicates the position directly below the satellite.

5. The method for selecting and accessing marine buoys according to claim 1, characterized in that, The intelligent decision-making layer is based on deep reinforcement learning and dynamically selects access links in each time slot. The decision objective is to maximize system throughput, balance inter-satellite load, and minimize access latency. The decision input includes sensing parameters and channel quality assessment results, and the output is the access identifier of the optimal link.

6. The method for selecting and accessing marine buoys according to claim 1, characterized in that, The execution access is based on a four-way handshake mechanism, including: The buoy device sends an access request Msg1 to the target satellite; After satellite verification, an access response Msg2 is returned, which includes uplink timing advance and resource allocation information; The buoy sends a contention resolution request Msg3 based on Msg2, which includes the terminal's unique identifier; After satellite verification, a contention resolution message Msg4 is sent back to complete the access process; if it fails, a retransmission mechanism is initiated.

7. The method according to claim 1, characterized in that, The sensing method determines whether the buoy is covered by satellites using a satellite beam coverage model, with the coverage conditions being: i U,M (t)≥θ0 in, d U,M (t) represents the Euclidean distance. θ0 is the minimum beacon angle.

8. The method according to claim 1, characterized in that, The communication connection between the buoy device and the satellite is determined by the binary variable z. U,M (t) represents: when buoy U connects to satellite M, z U,M (t) = 1, otherwise it is 0; the buoy device only connects to one link in a single time slot, and when multiple buoys compete, congestion is avoided by delaying access scheduling.

9. The method according to claim 4, characterized in that, The atmospheric attenuation component Where σ is the atmospheric attenuation coefficient, with units of dB / km, and h is the satellite orbital altitude.

10. The method according to claim 6, characterized in that, The four-way handshake mechanism involves the physical transport layer, the medium access control layer, and the radio link control layer. Msg1 is the physical layer preamble, Msg2 contains the access identifier and resource allocation, Msg3 is sent on the physical uplink shared channel, and Msg4 allocates the network temporary identifier.

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