A space-air-ground-sea integrated transmission method for maritime communication

Abstract

The application discloses a space-air-ground-sea integrated transmission method for maritime communication, which utilizes the cooperation of shore base stations, unmanned ships, unmanned aerial vehicles and satellites to provide services for maritime users in a wide sea area. According to the sea area position of the users, the application allocates appropriate communication links for the users, including base station communication links, unmanned ship relay links, unmanned aerial vehicle relay links and satellite communication links. After obtaining the channel information and position information of the users, the base station and the satellite utilize a joint optimization method of beam forming and running track to design corresponding transmission beams and unmanned ship and unmanned aerial vehicle track coordinates, then send the beam-formed signals to the maritime users, and the users obtain the transmitted information after decoding. The application provides a new generation of maritime communication with an integrated network architecture having good performance and strong dynamic adjustment capability.

Description

Technical Field

[0001] This invention belongs to the field of maritime wireless communication, and particularly relates to an integrated air-space-ground-sea transmission method for maritime communication. Background Technology

[0002] The ocean covers more than 70% of the Earth's surface and is closely related to ecological balance, economic development, and national defense. In recent years, human maritime activities have become increasingly frequent, leading to a continuous increase in demand for maritime communications; simultaneously, the rapid rise of the marine tertiary industry has created new demands for diversified maritime communication services. However, the existing maritime communication system architecture struggles to overcome the harsh marine environment and sparse user distribution, making the provision of reliable, high-speed maritime communication services a continued challenge. Therefore, establishing a next-generation maritime communication network architecture is becoming increasingly important.

[0003] To address the aforementioned issues, relevant research has employed various maritime wireless communication technologies. For example, shore-based base station communication technology is mature, but its service range is limited to nearshore areas. Maritime satellites offer wide coverage and play a crucial role in long-range maritime communication, but they are expensive and suffer from significant communication delays. Unmanned aerial vehicles (UAVs) and unmanned surface vessels (USVs) can leverage their high mobility and ease of deployment to act as mobile repeaters in wireless networks; however, UAVs are limited by sea winds and payload, while the communication performance of USVs fluctuates considerably with wave action.

[0004] In conclusion, each communication method has its own advantages, but its disadvantages are also obvious. It is difficult to truly establish a high-speed, low-cost, reliable, and widely covered maritime communication system by relying on only one method. Therefore, it is necessary to effectively integrate existing maritime communication systems and build a cross-domain collaborative maritime communication system based on four communication methods: space domain, air domain, land domain, and sea domain. Summary of the Invention

[0005] The purpose of this invention is to overcome the challenges of maritime communication, build an integrated maritime communication network, and provide an integrated air-space-sea transmission method for maritime communication.

[0006] To achieve the above-mentioned objectives, the present invention specifically adopts the following technical solution:

[0007] An integrated air-space-ground-sea transmission method for maritime communications includes the following steps:

[0008] S1. Construct an integrated air-space-ground-sea system for maritime communications, which includes shore-based base stations, unmanned vessels, drones, and satellites. The collaboration between shore-based base stations, unmanned vessels, drones, and satellites provides services to maritime users in a wide range of sea areas.

[0009] S2. The maritime user sends a communication request to the control center. After receiving the communication request, the control center obtains the user's location information and channel information in the current time slot, and allocates the corresponding communication device and communication resources to the maritime user who sent the communication request according to an integrated air-space-ground-sea communication link allocation method.

[0010] S3. Based on user location information and channel information, a beamforming and trajectory joint optimization method is used to calculate the optimal transmit beam and trajectory coordinates of the unmanned ship and drone in the current time slot;

[0011] S4. Based on the obtained optimal transmission beam and trajectory coordinates, the ground base station, unmanned ship, drone and satellite adjust the transmission beam and position coordinates accordingly, and after beamforming the transmitted data, broadcast the data on the downlink.

[0012] S5. After receiving the transmitted data, the maritime user decodes it to obtain the transmitted information;

[0013] S6. After the next time slot begins, reacquire user location information and channel information, repeat steps S3 to S5, complete the communication service for N time slots, and realize the information transmission of the integrated air-space-ground-sea system throughout the service time.

[0014] Based on the above scheme, each step can be implemented in the following preferred manner.

[0015] As a preferred embodiment, in step S2, a method for allocating integrated air-space-ground-sea communication links specifically involves: the integrated air-space-ground-sea system dividing the service sea area into coastal, near-shore, mid-sea, and offshore areas according to the distance from the shore, from near to far; and the control center allocating different communication links based on the sea area where the user is located. Specifically, shore-based base stations directly provide communication services to users located along the coast; satellites directly provide communication services to users located in the offshore area; unmanned vessels and drones depart from the starting point and move along a designed trajectory; unmanned vessels receive signals transmitted from ground base stations and forward them to users located near the shore; and drones receive signals transmitted from ground base stations and forward them to users located in the mid-sea area.

[0016] As a preferred embodiment, in step S3, a method for joint optimization of beamforming and trajectory is specifically as follows:

[0017] S31. Based on the position coordinates of shore-based base stations, unmanned surface vessels, drones, and satellites, the channel state information h of each communication link in the system within the current time slot is obtained using downlink channel estimation methods. b,i h b,v h b,a h v,i h a,i h s,i ; where h b,i hb,v h b,a These represent the channel state information from the base station to the user, the unmanned vessel, and the drone, respectively. v,i h a,i h s,i These represent the channel status information from unmanned ships, drones, and satellites to users, respectively.

[0018] S32. Initialize the iteration count l = 0 and the time slot number n, and set the initial values ​​for the transmit beam and trajectory coordinates respectively:

[0019]

[0020] Among them, w bj w bv w ba These represent the transmission beams from the base station to the user, unmanned surface vessel, and unmanned aerial vehicle, respectively; w vj w aj w sj These represent the transmission beams of unmanned ships, drones, and satellites, respectively; the superscript (0) indicates the 0th iteration. These represent the initial values ​​of the transmission beams from the base station to the user, the unmanned vessel, and the drone, respectively, given in the 0th iteration. These represent the initial values ​​of the transmission beams for the unmanned surface vessel, drone, and satellite, respectively, given in the 0th iteration. q represents the initial trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle given in the 0th iteration; v [n-1]、q a [n-1] represent the trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle within time slot n-1, respectively; P b P v P a P s These represent the maximum output power of the antennas for base stations, unmanned ships, drones, and satellites, respectively; N b N v N a N s These represent the number of antennas for base stations, unmanned ships, drones, and satellites, respectively; M b M v M a M s These represent the number of users for base stations, unmanned ships, drones, and satellite services, respectively. They represent lengths of N respectively. b N v N a N s The transpose of a row vector of all 1s, where T represents the transpose;

[0021] S33. In the l-th iteration, the following intermediate variable is introduced:

[0022]

[0023]

[0024] Among them, T ba and T bv The intermediate variables T and T' represent the signal reception rates of the UAV and unmanned surface vessel, respectively. bi T vi T ai T si The intermediate variable T represents the signal reception rate for base station users, unmanned surface vessel users, drone users, and satellite users, respectively. Let represent the user sets of base stations, unmanned surface vessels, drones, and satellites, respectively. Let bj, vj, aj, and sj represent the j-th base station user, unmanned surface vessel user, drone user, and satellite user, respectively. Let bi, vi, ai, and si represent the ith base station user, unmanned surface vessel user, drone user, and satellite user, respectively. All represent intermediate variables that depend on the transmitted beam and channel state information, and are used as relaxation variables in the optimization problem; Σ represents accumulation;

[0025] To maximize the minimum user signal reception rate To optimize the objective, in the formula, The representation is defined as follows: R bi R vi R ai R si These represent the signal reception rates of base station user bi, unmanned surface vessel user vi, unmanned aerial vehicle user ai, and satellite user si, respectively. Represents any symbol, based on a given set of transmitted beams in the l-th iteration. and the set of trajectory coordinates in the l-th iteration By optimizing the transmitted beam, a beamforming optimization problem is established:

[0026]

[0027] Among them, the optimization problem The symbol i can be replaced by any bi, vi, ai, si; the superscript (l) indicates the l-th iteration; r ai and r vi R respectively ai and R vi The corresponding slack variables; These represent the variances of additive Gaussian noise in the base station-to-user, unmanned vessel, and unmanned aerial vehicle links, respectively. These represent the variances of additive Gaussian noise in the unmanned ship, drone, and satellite-to-user links, respectively. These represent any base station user, unmanned surface vessel user, drone user, and satellite user, respectively; h b,bi h b,a h b,v h represents the channel state information from the base station to the base station user bi, the drone, and the unmanned vessel, respectively. v,bi h v,vi h v,ai h v,si These represent the channel state information for unmanned surface vessels (USVs) to base station users, USV users, drone users, and satellite users, respectively. These four categories can be summarized as h. v,i ;, h a,bi h a,vi h a,ai h a,si These represent the channel state information from drones to base station users, unmanned surface vessel users, drone users, and satellite users, respectively. These four categories can be summarized as h. a,i h s,bi h s,vi h s,ai h s,si These represent the channel state information for satellite-to-base station user bi, unmanned surface vessel user, unmanned aerial vehicle user, and satellite user, respectively. These four categories can be organized into h. s,i ;

[0028] The function expression for the l-th iteration is denoted as:

[0029]

[0030] Where h and w represent the channel state information parameter and the transmit beam parameter, respectively, h H w (l) and w (l)H Let Re represent the corresponding channel state information conjugate transpose, the transmit beam given in the l-th iteration, and its conjugate transpose, respectively; Re{·} represents taking the real part of the complex number;

[0031] The upper bound expression of the signal receiving rate expression Recorded as:

[0032]

[0033] Where Z∈{bi,ba,bv,ai,vi,si} indicates that the subscript Z can be replaced by one of the subscripts bi,ba,bv,ai,vi,si; e represents the natural constant; This represents the variance of the additive Gaussian noise corresponding to the subscript Z; This indicates that the intermediate variable T corresponding to the subscript Z will be...Z The transmitted beam {w} in the expression bi w bv w ba w vi w ai w si} should be replaced with The given transmit beam;

[0034] The beamforming optimization problem is solved using the interior-point method, and the transmitted beam after the l-th iteration optimization is obtained, denoted as .

[0035] S34. In the l-th iteration, the following intermediate variable is introduced:

[0036]

[0037]

[0038] in D ba and D bv D represents the intermediate variables representing the signal reception rates of UAVs and unmanned surface vessels, respectively; bi D vi D ai D si q represents the intermediate variables representing the signal reception rates of base station users, unmanned surface vessel users, drone users, and satellite users, respectively; b q i q bi q vi q ai q si These represent the trajectory coordinates of a base station, a user, a base station user, an unmanned surface vessel user, an unmanned aerial vehicle user, and a satellite user, respectively; h b h v h a h i H represents the antenna height of the base station, unmanned surface vessel, drone, and user, respectively; b,v H b,a H represents the conjugate transpose of the matrix independent of trajectory coordinates in the channel state information from the base station to the unmanned vessel and the unmanned aerial vehicle; v,bi H v,vi H v,ai H v,si These represent the conjugate transposes of matrices independent of trajectory coordinates in the channel state information of unmanned surface vessel (USV) users bi, vi, ai, and si, respectively. These four categories can be summarized as H. v,i H a,bi H a,vi H a,ai H a,siThese represent the conjugate transposes of matrices independent of trajectory coordinates in the channel state information from UAV to base station user bi, UAV user vi, UAV user ai, and satellite user si, respectively. These four categories can be summarized as H. a,i L B,a K b,v L a,ai K v,ai K v,vi L a,vi K v,si L a,si L a,bi K v,bi Both represent intermediate variables that depend on the running trajectory and are used as slack variables in the optimization problem;

[0039] With the optimization objective of maximizing the minimum user signal reception rate η, based on the transmit beam set given in the (l+1)th iteration... and the set of trajectory coordinates given in the lth round By optimizing the trajectory coordinates, a trajectory coordinate optimization problem is established:

[0040]

[0041] Among them, the optimization problem Δτ represents the time slot length; v c and v w These represent the measured wave speed and sea wind speed, respectively. and These represent the maximum speeds of the unmanned vessel and the drone, respectively. and q represents the maximum turning angle of the unmanned surface vessel and the unmanned aerial vehicle, respectively; v [n]、q a [n] represents the trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle within time slot n, respectively; q v [n-2]、q a [n-2] represent the trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle within time slot n-2, respectively; q v [1], q a [1] represents the trajectory coordinates of the unmanned ship and the unmanned aerial vehicle within time slot 1, respectively; x represents the x-axis unit vector; o k Indicates the coordinate position of the k-th obstacle; r sh and r ob,k q represents the safe distance between the unmanned vessel and the user at sea, and the k-th obstacle, respectively; v [0]、q a [0] represents the trajectory coordinates of the unmanned ship and the unmanned aerial vehicle within time slot 0, respectively;

[0042] The lower bound expression of the signal receiving rate expression Recorded as:

[0043]

[0044] in, and This indicates that the index Z corresponds to K. Z L Z D Z q in the expression Z Replace with the corresponding given trajectory coordinates

[0045] The interior point method is used to solve the trajectory coordinate optimization problem, and the optimized trajectory coordinates are obtained, denoted as .

[0046] S35. Transmit beam optimized based on the l-th iteration. and trajectory coordinates Let l = l + 1, and repeat steps S33 to S34 of a beamforming and trajectory joint optimization method until η is satisfied. (l) -η (l-1) Exit the iteration when ≤ε, and output the optimal transmit beam in the current time slot. and optimal trajectory coordinates Where, η (l) η (l-1) ε represents the objective function values ​​obtained from the trajectory coordinate optimization problem after the l-th and (l-1)-th iterations, respectively, and ε represents the convergence threshold.

[0047] Preferably, in step S3, the convergence threshold is set to 0.001.

[0048] Compared with the prior art, the present invention has the following advantages:

[0049] The method proposed in this invention utilizes the collaborative work of ground base stations, unmanned vessels, drones, and satellites to effectively expand the coverage of maritime communication systems. While leveraging the strengths of different communication devices, it also establishes an integrated air-ground-sea collaborative strategy. Furthermore, the beamforming and trajectory joint optimization method proposed in this invention effectively transforms a non-convex optimization problem that cannot be directly solved into a directly solvable optimization problem, exhibiting high efficiency and significant system performance improvement. Attached Figure Description

[0050] Figure 1 This is a flowchart of the steps of the method of the present invention;

[0051] Figure 2 This is a block diagram of the integrated air-space-ground-sea system of the present invention;

[0052] Figure 3This is a two-dimensional top view of the trajectory of the unmanned ship and unmanned aerial vehicle in the integrated air-space-ground-sea system of the present invention;

[0053] Figure 4 This figure shows the performance comparison results of the minimum user signal reception rate under different optimization schemes in an embodiment of the present invention. Detailed Implementation

[0054] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below. Technical features in the various embodiments of the present invention can be combined accordingly without mutual conflict.

[0055] The block diagram of the integrated air-space-ground-sea system of the present invention is as follows: Figure 2 As shown, this system uses ground base stations and satellites as transmitters, and unmanned surface vessels (USVs) and drones as repeaters for the ground base stations, working together to provide services to maritime users over a wide area. Ground base stations and satellites directly provide communication services to users located along the coast and in the open sea, respectively. Meanwhile, USVs and drones move along designed trajectories, receiving signals transmitted from the ground base stations and providing communication services to users in near-shore and mid-sea areas, respectively.

[0056] like Figure 1 As shown, in a preferred embodiment of the present invention, the above-mentioned integrated air-space-ground-sea transmission method for maritime communications includes the following steps S1 to S6. The specific implementation process of each step will be described in detail below.

[0057] S1. Construct an integrated air-space-ground-sea system for maritime communications, which includes shore-based base stations, unmanned vessels, drones, and satellites. The collaboration between shore-based base stations, unmanned vessels, drones, and satellites provides services to maritime users in a wide range of sea areas.

[0058] S2. The maritime user sends a communication request to the control center. After receiving the communication request, the control center obtains the user's location information and channel information in the current time slot, and allocates the corresponding communication device and communication resources to the maritime user who sent the communication request according to an integrated air-space-ground-sea communication link allocation method.

[0059] In step S2, a method for allocating integrated air-space-ground-sea communication links specifically involves the following: the integrated air-space-ground-sea system divides the service sea area into coastal, near-shore, mid-sea, and offshore areas according to the distance from the shore, from near to far. The control center allocates different communication links based on the sea area where the user is located. Among these, shore-based base stations directly provide communication services to users located in the coastal areas; satellites directly provide communication services to users located in the offshore areas; unmanned vessels and drones depart from the starting point and move along the designed trajectory. Unmanned vessels receive signals transmitted from ground base stations and forward them to users located in the near-shore areas, while drones receive signals transmitted from ground base stations and forward them to users located in the mid-sea areas.

[0060] S3. Based on user location information and channel information, a beamforming and trajectory joint optimization method is used to calculate the optimal transmit beam and trajectory coordinates of the unmanned ship and drone in the current time slot.

[0061] In step S3, a method for joint optimization of beamforming and trajectory is specifically as follows:

[0062] S31. Based on the position coordinates of shore-based base stations, unmanned surface vessels, drones, and satellites, the channel state information h of each communication link in the system within the current time slot is obtained using downlink channel estimation methods. b,i h b,v h b,a h v,i h a,i h s,i ; where h b,i h b,v h b,a These represent the channel state information from the base station to the user, the unmanned vessel, and the drone, respectively. v,i h a,i h s,i These represent the channel status information from unmanned ships, drones, and satellites to users, respectively.

[0063] S32. Initialize the iteration count l = 0 and the time slot number n, and set the initial values ​​for the transmit beam and trajectory coordinates respectively:

[0064]

[0065] Among them, w bj w bv w ba These represent the transmission beams from the base station to the user, unmanned surface vessel, and unmanned aerial vehicle, respectively; w vj w aj w sj These represent the transmission beams of unmanned ships, drones, and satellites, respectively; the superscript (0) indicates the 0th iteration. These represent the initial values ​​of the transmission beams from the base station to the user, the unmanned vessel, and the drone, respectively, given in the 0th iteration. These represent the initial values ​​of the transmission beams for the unmanned surface vessel, drone, and satellite, respectively, given in the 0th iteration. q represents the initial trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle given in the 0th iteration; v [n-1]、q a [n-1] represent the trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle within time slot n-1, respectively; P b P v P a P s These represent the maximum output power of the antennas for base stations, unmanned ships, drones, and satellites, respectively; N b N v N a N s These represent the number of antennas for base stations, unmanned ships, drones, and satellites, respectively; M b M v M a M s These represent the number of users for base stations, unmanned ships, drones, and satellite services, respectively. They represent lengths of N respectively. b N v N a N s The transpose of a row vector of all 1s, where T represents the transpose;

[0066] S33. In the l-th iteration, the following intermediate variable is introduced:

[0067]

[0068] Among them, T ba and T bv The intermediate variables T and T' represent the signal reception rates of the UAV and unmanned surface vessel, respectively. bi T vi T ai T si The intermediate variable T represents the signal reception rate for base station users, unmanned surface vessel users, drone users, and satellite users, respectively. Let represent the user sets of base stations, unmanned surface vessels, drones, and satellites, respectively. Let bj, vj, aj, and sj represent the j-th base station user, unmanned surface vessel user, drone user, and satellite user, respectively. Let bi, vi, ai, and si represent the ith base station user, unmanned surface vessel user, drone user, and satellite user, respectively. All represent intermediate variables that depend on the transmitted beam and channel state information, and are used as relaxation variables in the optimization problem; Σ represents accumulation;

[0069] To maximize the minimum user signal reception rate To optimize the objective, in the formula, The representation is defined as follows: R bi R vi R ai R si These represent the signal reception rates of base station user bi, unmanned surface vessel user vi, unmanned aerial vehicle user ai, and satellite user si, respectively. Represents any symbol, based on a given set of transmitted beams in the l-th iteration. and the set of trajectory coordinates in the l-th iteration By optimizing the transmitted beam, a beamforming optimization problem is established:

[0070]

[0071] Among them, the optimization problem The symbol i can be replaced by any bi, vi, ai, si; the superscript (l) indicates the l-th iteration; r ai and r vi R respectively ai and R vi The corresponding slack variables; These represent the variances of additive Gaussian noise in the base station-to-user, unmanned vessel, and unmanned aerial vehicle links, respectively. These represent the variances of additive Gaussian noise in the unmanned ship, drone, and satellite-to-user links, respectively. These represent any base station user, unmanned surface vessel user, drone user, and satellite user, respectively; h b,bi h b,a h b,v h represents the channel state information from the base station to the base station user bi, the drone, and the unmanned vessel, respectively. v,bi h v,vi h v,ai h v,si These represent the channel state information for unmanned surface vessels (USVs) to base station users, USV users, drone users, and satellite users, respectively. These four categories can be summarized as h. v,i ;, h a,bi h a,vi h a,ai h a,si These represent the channel state information from drones to base station users, unmanned surface vessel users, drone users, and satellite users, respectively. These four categories can be summarized as h. a,i h s,bi h s,vi h s,ai h s,siThese represent the channel state information for satellite-to-base station user bi, unmanned surface vessel user, unmanned aerial vehicle user, and satellite user, respectively. These four categories can be organized into h. s,i ;

[0072] The function expression for the l-th iteration is denoted as:

[0073]

[0074] Where h and w represent the channel state information parameter and the transmit beam parameter, respectively, h H w (l) and w (l)H Let Re represent the corresponding channel state information conjugate transpose, the transmit beam given in the l-th iteration, and its conjugate transpose, respectively; Re{·} represents taking the real part of the complex number;

[0075] The upper bound expression of the signal receiving rate expression Recorded as:

[0076]

[0077] Where Z∈{bi,ba,bv,ai,vi,si} indicates that the subscript Z can be replaced by one of the subscripts bi,ba,bv,ai,vi,si; e represents the natural constant; This represents the variance of the additive Gaussian noise corresponding to the subscript Z; This indicates that the intermediate variable T corresponding to the subscript Z will be... Z The transmitted beam {w} in the expression bi w bv w ba w vi w ai w si} should be replaced with The given transmit beam;

[0078] The beamforming optimization problem is solved using the interior-point method, and the transmitted beam after the l-th iteration optimization is obtained, denoted as .

[0079] S34. In the l-th iteration, the following intermediate variable is introduced:

[0080]

[0081] in D ba and D bv D represents the intermediate variables representing the signal reception rates of UAVs and unmanned surface vessels, respectively; bi D vi D ai D siq represents the intermediate variables representing the signal reception rates of base station users, unmanned surface vessel users, drone users, and satellite users, respectively; b q i q bi q vi q ai q si These represent the trajectory coordinates of a base station, a user, a base station user, an unmanned surface vessel user, an unmanned aerial vehicle user, and a satellite user, respectively; h b h v h a h i H represents the antenna height of the base station, unmanned surface vessel, drone, and user, respectively; b,v H b,a H represents the conjugate transpose of the matrix independent of trajectory coordinates in the channel state information from the base station to the unmanned vessel and the unmanned aerial vehicle; v,bi H v,vi H v,ai H v,si These represent the conjugate transposes of matrices independent of trajectory coordinates in the channel state information of unmanned surface vessel (USV) users bi, vi, ai, and si, respectively. These four categories can be summarized as H. v,i H a,bi H a,vi H a,ai H a,si These represent the conjugate transposes of matrices independent of trajectory coordinates in the channel state information from UAV to base station user bi, UAV user vi, UAV user ai, and satellite user si, respectively. These four categories can be summarized as H. a,i L B,a K b,v L a,ai K v,ai K v,vi L a,vi K v,si L a,si L a,bi K v,bi Both represent intermediate variables that depend on the running trajectory and are used as slack variables in the optimization problem;

[0082] With the optimization objective of maximizing the minimum user signal reception rate η, based on the transmit beam set given in the (l+1)th iteration... and the set of trajectory coordinates given in the lth round By optimizing the trajectory coordinates, a trajectory coordinate optimization problem is established:

[0083]

[0084] Among them, the optimization problem Δτ represents the time slot length; vc and v w These represent the measured wave speed and sea wind speed, respectively. and These represent the maximum speeds of the unmanned vessel and the drone, respectively. and q represents the maximum turning angle of the unmanned surface vessel and the unmanned aerial vehicle, respectively; v [n]、q a [n] represents the trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle within time slot n, respectively; q v [n-2]、q a [n-2] represent the trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle within time slot n-2, respectively; q v [1], q a [1] represents the trajectory coordinates of the unmanned ship and the unmanned aerial vehicle within time slot 1, respectively; x represents the x-axis unit vector; o k Indicates the coordinate position of the k-th obstacle; r sh and r ob,k q represents the safe distance between the unmanned vessel and the user at sea, and the k-th obstacle, respectively; v [0]、q a [0] represents the trajectory coordinates of the unmanned ship and the unmanned aerial vehicle within time slot 0, respectively;

[0085] The lower bound expression of the signal receiving rate expression Recorded as:

[0086]

[0087] in, and This indicates that the index Z corresponds to K. Z L Z D Z q in the expression Z Replace with the corresponding given trajectory coordinates

[0088] The interior point method is used to solve the trajectory coordinate optimization problem, and the optimized trajectory coordinates are obtained, denoted as .

[0089] S35. Transmit beam optimized based on the l-th iteration. and trajectory coordinates Let l = l + 1, and repeat steps S33 to S34 of a beamforming and trajectory joint optimization method until η is satisfied. (l) -η (l-1) Exit the iteration when ≤ε, and output the optimal transmit beam in the current time slot. and optimal trajectory coordinates Where, η (l) η(l-1) ε represents the objective function values ​​obtained from the trajectory coordinate optimization problem after the l-th and (l-1)-th iterations, respectively, and ε represents the convergence threshold.

[0090] It should be noted that in step S3, the convergence threshold is set to 0.001.

[0091] S4. Based on the obtained optimal transmission beam and trajectory coordinates, the ground base station, unmanned ship, drone and satellite adjust the transmission beam and position coordinates accordingly, and after beamforming the transmitted data, broadcast the data on the downlink.

[0092] S5. After receiving the transmitted data, the maritime user decodes it to obtain the transmitted information;

[0093] S6. After the next time slot begins, reacquire user location information and channel information, repeat steps S3 to S5, complete the communication service for N time slots, and realize the information transmission of the integrated air-space-ground-sea system throughout the service time.

[0094] Computer simulations show that, as Figure 3 As shown, the beamforming and trajectory joint optimization method proposed in this invention can effectively design the movement trajectories of unmanned surface vessels (USVs) and unmanned aerial vehicles (UAVs). It comprehensively considers maneuverability constraints, steering angle constraints, safe navigation constraints, and information causality constraints. While continuously reducing the distance between the USV / UAV and its target user, it can adjust the trajectory in real time according to the user's movement direction, exhibiting strong dynamic adjustment capabilities. Furthermore, Figure 4 The proposed beamforming and trajectory joint optimization method (Scheme 1) was compared with other optimization schemes, showing that the proposed joint optimization scheme achieved a stronger system performance improvement compared with other optimization schemes, demonstrating the feasibility and superiority of the method of the present invention.

[0095] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the invention. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention. Therefore, all technical solutions obtained through equivalent substitution or transformation fall within the protection scope of the present invention.

Claims

1. A method for integrated air-space-ground-sea transmission for maritime communications, characterized in that, Includes the following steps: S1. Construct an integrated air-space-ground-sea system for maritime communications, which includes shore-based base stations, unmanned vessels, drones, and satellites. The collaboration between shore-based base stations, unmanned vessels, drones, and satellites provides services to maritime users in a wide range of sea areas. S2. The maritime user sends a communication request to the control center. After receiving the communication request, the control center obtains the user's location information and channel information in the current time slot, and allocates the corresponding communication device and communication resources to the maritime user who sent the communication request according to an integrated air-space-ground-sea communication link allocation method. S3. Based on user location information and channel information, a beamforming and trajectory joint optimization method is used to calculate the optimal transmit beam and trajectory coordinates of the unmanned ship and drone in the current time slot; S4. Based on the obtained optimal transmission beam and trajectory coordinates, the ground base station, unmanned ship, drone and satellite adjust the transmission beam and position coordinates accordingly, and after beamforming the transmitted data, broadcast the data on the downlink. S5. After receiving the transmitted data, the maritime user decodes it to obtain the transmitted information; S6. After the next time slot begins, reacquire user location information and channel information, repeat steps S3 to S5, complete the communication service of N time slots, and realize the information transmission of the integrated air-space-ground-sea system throughout the service time. In S3, to maximize the minimum user signal reception rate To optimize the objective, in the formula, The representation is defined as follows: R bi R vi R ai R si These represent the signal reception rates of base station user bi, unmanned surface vessel user vi, unmanned aerial vehicle user ai, and satellite user si, respectively. Represents any symbol, based on a given set of transmitted beams in the l-th iteration. and the set of trajectory coordinates in the l-th iteration By optimizing the transmitted beam, a beamforming optimization problem is established: Among them, the optimization problem The symbol i can be replaced by any bi, vi, ai, si; the superscript (l) indicates the l-th iteration; r ai and r vi R respectively ai and R vi The corresponding slack variables; These represent the variances of additive Gaussian noise in the base station-to-user, unmanned vessel, and unmanned aerial vehicle links, respectively. These represent the variances of additive Gaussian noise in the unmanned ship, drone, and satellite-to-user links, respectively. These represent any base station user, unmanned surface vessel user, drone user, and satellite user, respectively; h b,bi h b,a h b,v These represent the channel state information from the base station to the base station user, the drone, and the unmanned vessel, respectively. v,bi h v,vi h v,ai h v,si These represent the channel state information for unmanned surface vessels (USVs) to base station users, USV users, drone users, and satellite users, respectively. These four categories can be summarized as h. v,i h a,bi h a,vi h a,ai h a,si These represent the channel state information from drones to base station users, unmanned surface vessel users, drone users, and satellite users, respectively. These four categories can be summarized as h. a,i h s,bi h s,vi h s,ai h s,si These represent the channel state information for satellite-to-base station user bi, unmanned surface vessel user, unmanned aerial vehicle user, and satellite user, respectively. These four categories can be organized into h. s,i ;F (l) (h,w) represents the function expression for the l-th iteration, where h and w represent the channel state information parameter and the transmit beam parameter, respectively. The expression for the signal reception rate represents the upper bound of the component, Z∈{bi,ba,bv,ai,vi,si}, indicating that the subscript Z can be replaced by one of the subscripts bi,ba,bv,ai,vi,si; h b,i h b,v h b,a These represent the channel state information from the base station to the user, the unmanned vessel, and the drone, respectively. v,i h a,i h s,i These represent the channel state information from unmanned surface vessels, unmanned aerial vehicles, and satellites to the user, respectively; w bj w bv w ba These represent the transmission beams from the base station to the user, unmanned surface vessel, and unmanned aerial vehicle, respectively; w vj w aj w sj These represent the transmission beams of unmanned ships, drones, and satellites, respectively; P b P v P a P s These represent the maximum output power of the antennas for base stations, unmanned ships, drones, and satellites, respectively; T ba and T bv The intermediate variables T and T' represent the signal reception rates of the UAV and unmanned surface vessel, respectively. bi T vi T ai T si The intermediate variable T represents the signal reception rate for base station users, unmanned surface vessel users, drone users, and satellite users, respectively. Let bj, vj, aj, and sj represent the user sets of base stations, unmanned ships, drones, and satellites, respectively. Let bi, vi, ai, and si represent the user sets of base stations, unmanned ships, drones, and satellites, respectively. All represent intermediate variables that depend on the transmitted beam and channel state information, and are used as relaxation variables in the optimization problem; Σ represents accumulation; T represents transpose; With the optimization objective of maximizing the minimum user signal reception rate η, based on the transmit beam set given in the (l+1)th iteration... and the set of trajectory coordinates given in the lth round By optimizing the trajectory coordinates, a trajectory coordinate optimization problem is established: Among them, the optimization problem Δτ represents the time slot length; v c and v w These represent the measured wave speed and sea wind speed, respectively. and These represent the maximum speeds of the unmanned vessel and the drone, respectively. and q represents the maximum turning angle of the unmanned surface vessel and the unmanned aerial vehicle, respectively; v [n]、q a [n] represents the trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle within time slot n, respectively; q v [n-2]、q a [n-2] represent the trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle within time slot n-2, respectively; q v [1], q a [1] represents the trajectory coordinates of the unmanned ship and the unmanned aerial vehicle within time slot 1, respectively; x represents the x-axis unit vector; o k Indicates the coordinate position of the k-th obstacle; r sh and r ob,k q represents the safe distance between the unmanned vessel and the user at sea, and the k-th obstacle, respectively; v [0]、q a [0] represents the trajectory coordinates of the unmanned ship and the unmanned aerial vehicle within time slot 0, respectively; q v [n-1]、q a [n-1] represent the trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle within time slot n-1, respectively; w bi Indicates the transmit beam from the base station to the user; w vi w ai w si These represent the transmission beams of unmanned ships, drones, and satellites, respectively; D ba and D bv D represents the intermediate variables representing the signal reception rates of UAVs and unmanned surface vessels, respectively; bi D vi D ai D si q represents the intermediate variables representing the signal reception rates of base station users, unmanned surface vessel users, drone users, and satellite users, respectively; b q i q bi q vi q ai q si These represent the trajectory coordinates of a base station, a user, a base station user, an unmanned surface vessel user, an unmanned aerial vehicle user, and a satellite user, respectively; H b,v H b,a H represents the conjugate transpose of the matrix independent of trajectory coordinates in the channel state information from the base station to the unmanned vessel and the unmanned aerial vehicle; v,bi H v,vi H v,ai H v,si These represent the conjugate transposes of matrices independent of trajectory coordinates in the channel state information of unmanned surface vessels (USVs) to base station users, USV users, UAV users, and satellite users, respectively. These four categories can be summarized as H... v,i H a,bi H a,vi H a,ai H a,si These represent the conjugate transposes of matrices independent of trajectory coordinates in the channel state information from UAV to base station user bi, unmanned surface vessel user, UAV user, and satellite user, respectively. These four categories can be summarized as H. a,i L B,a K b,v L a,ai K v,ai K v,vi L a,vi K v,si L a,si L a,bi K v,bi Both represent intermediate variables that depend on the running trajectory and are used as slack variables in the optimization problem; This represents the lower bound of the component in the expression for the signal reception rate; This indicates that the index Z corresponds to K. Z L Z q in the expression Z Replace with the corresponding given trajectory coordinates 2. The integrated air-space-ground-sea transmission method for maritime communications as described in claim 1, characterized in that, In step S2, a method for allocating integrated air-space-ground-sea communication links specifically involves the following: the integrated air-space-ground-sea system divides the service sea area into coastal, near-shore, mid-sea, and offshore areas according to the distance from the shore, from near to far. The control center allocates different communication links based on the sea area where the user is located. Among these, shore-based base stations directly provide communication services to users located in the coastal areas; satellites directly provide communication services to users located in the offshore areas; unmanned vessels and drones depart from the starting point and move along the designed trajectory. Unmanned vessels receive signals transmitted from ground base stations and forward them to users located in the near-shore areas, while drones receive signals transmitted from ground base stations and forward them to users located in the mid-sea areas.

3. The integrated air-space-ground-sea transmission method for maritime communications as described in claim 1, characterized in that, In step S3, a method for joint optimization of beamforming and trajectory is specifically as follows: S31. Based on the position coordinates of shore-based base stations, unmanned surface vessels, drones, and satellites, the channel state information h of each communication link in the system within the current time slot is obtained using downlink channel estimation methods. b,i h b,v h b,a h v,i h a,i h s,i ; S32. Initialize the iteration count l = 0 and the time slot number n, and set the initial values ​​for the transmit beam and trajectory coordinates respectively: Wherein, the superscript (0) indicates the 0th iteration; These represent the initial values ​​of the transmission beams from the base station to the user, the unmanned vessel, and the drone, respectively, given in the 0th iteration. These represent the initial values ​​of the transmission beams for the unmanned surface vessel, drone, and satellite, respectively, given in the 0th iteration. N represents the initial trajectory coordinates of the unmanned surface vessel and the unmanned aerial vehicle given in the 0th iteration; b N v N a N s These represent the number of antennas for base stations, unmanned ships, drones, and satellites, respectively; M b M v M a M s These represent the number of users for base stations, unmanned ships, drones, and satellite services, respectively. They represent lengths of N respectively. b N v N a N s The transpose of a row vector of all 1s; S33. In the l-th iteration, the following intermediate variable is introduced: After establishing the beamforming optimization problem, the functional expression for the l-th iteration is denoted as: Among them, h H w (l) and w (l)H Let Re represent the corresponding channel state information conjugate transpose, the transmit beam given in the l-th iteration, and its conjugate transpose, respectively; Re{·} represents taking the real part of the complex number; The upper bound expression of the signal receiving rate expression Recorded as: Where e represents the natural constant; This represents the variance of the additive Gaussian noise corresponding to the subscript Z; This indicates that the intermediate variable T corresponding to the subscript Z will be... Z The transmitted beam {w} in the expression bi w bv w ba w vi w ai w si } should be replaced with The given transmit beam; The beamforming optimization problem is solved using the interior-point method, and the transmitted beam after the l-th iteration optimization is obtained, denoted as . S34. In the l-th iteration, the following intermediate variable is introduced: in h b h v h a h i These represent the antenna heights of the base station, unmanned boat, drone, and user, respectively. After establishing the trajectory coordinate optimization problem, the lower bound expression of the signal receiving rate component is derived. Recorded as: in, This indicates that the D corresponding to the subscript Z is... Z q in the expression Z Replace with the corresponding given trajectory coordinates The interior point method is used to solve the trajectory coordinate optimization problem, and the optimized trajectory coordinates are obtained, denoted as . S35. Transmit beam optimized based on the l-th iteration. and trajectory coordinates Let l = l + 1, and repeat steps S33 to S34 of a beamforming and trajectory joint optimization method until η is satisfied. (l) -η (l-1) Exit the iteration when ≤ε, and output the optimal transmit beam in the current time slot. and optimal trajectory coordinates Where, η (l) η (l-1) ε represents the objective function values ​​obtained from the trajectory coordinate optimization problem after the l-th and (l-1)-th iterations, respectively, and ε represents the convergence threshold.

4. The integrated air-space-ground-sea transmission method for maritime communications as described in claim 3, characterized in that, In step S3, the convergence threshold is set to 0.001.

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