Satellite communication resource optimization method and device for power business in remote areas

Abstract

The invention provides a satellite communication resource optimization method and a satellite communication resource optimization device for electric power services in remote areas, and relates to the technical field of communication of electric power services. Determining the minimum total information transmission rate of each power receiving end based on the transmitting beam forming vectors of all the public signals, the transmitting beam forming vectors of all the private signals, the reflection beam forming vector set and the actual public signal transmission rate; and obtaining a maximum value of the minimum total information transmission rate of each power receiving end to determine an optimized resource set. By solving the maximum value of the minimum total information transmission rate of each power receiving end, optimization of transmission beamforming vectors of all public signals, optimization of transmission beamforming vectors of all private signals, optimization of a reflection beamforming vector set and optimization of actual public signal transmission rates of all power receiving ends are realized. The optimal distribution of the transmission resources of the satellite communication system of the power business is realized.

Description

Technical Field

[0001] The present invention relates to the field of communication technology for electric power services, and in particular to a satellite communication resource optimization method and device for electric power services in remote areas. Background Art

[0002] In satellite communications for power services in remote areas, there are still problems such as insufficient security, insufficient number of connections, insufficient delay, and insufficient reliability, which require further research and improvement by the industry. In addition, since the Internet of Things uses short packet transmission, it will have a higher bit error rate than traditional satellite communications. In research, it is necessary to improve the system's achievable rate while ensuring reliability.

[0003] In existing satellite communications for power services in remote areas, the communication efficiency is low due to unreasonable allocation of transmission resources. Summary of the invention

[0004] The present invention provides a satellite communication resource optimization method and device for electric power business in remote areas, so as to solve the defect of unreasonable allocation of transmission resources in satellite communication for electric power business in remote areas in the prior art, and realize reasonable allocation of transmission resources in satellite communication for electric power business in remote areas.

[0005] The present invention provides a satellite communication resource optimization method for electric power business in remote areas, comprising: in a satellite communication system for electric power business, based on the transmission beamforming vectors of all public signals of the transmitting end, the transmission beamforming vectors of all private signals of the transmitting end to all electric power receiving ends, the reflection beamforming vector set of multiple intelligent reflection arrays and the actual public signal transmission rate of the electric power receiving end, determining the minimum total information transmission rate of each electric power receiving end; obtaining the maximum value of the minimum total information transmission rate of each electric power receiving end to determine an optimized resource set, and allocating transmission resources of the satellite communication system for electric power business based on the optimized resource set, wherein the optimized resource set includes the optimized transmission beamforming vectors of all public signals, the optimized transmission beamforming vectors of all private signals, the optimized reflection beamforming vector set and the optimized actual public signal transmission rate of all electric power receiving ends.

[0006] According to the satellite communication resource optimization method for electric power services in remote areas provided by the present invention, it is characterized in that the maximum value of the minimum total information transmission rate of each electric power receiving end is obtained to determine the optimized resource set, including: a fixed reflection beamforming vector set, a first target constraint condition set for obtaining the minimum total information transmission rate of each electric power receiving end, the first target constraint condition set including a first constraint condition, a second constraint condition, a third constraint condition and a fourth constraint condition, the first constraint condition including that the transmission power of each transmitting end is less than or equal to the maximum transmission power of the transmitting end, the second constraint condition including that the sum of the actual public signal transmission rates of all electric power receiving ends is less than or equal to the transmission threshold, the third constraint condition including that the actual public signal transmission rate of each electric power receiving end is greater than or equal to 0, the fourth constraint condition including that the theoretical private signal transmission rate of each electric power receiving end is greater than or equal to 0, the theoretical private signal transmission rate of the electric power receiving end is determined based on the transmit beamforming vectors of all private signals and the fixed reflection beamforming vector set, and the transmission threshold is determined based on the theoretical public signal transmission rate of each electric power receiving end; the theoretical public signal transmission rate of all electric power receiving ends is determined based on the transmit beamforming vectors of all public signals and the fixed reflection The invention relates to a method for determining a minimum total information transmission rate of each power receiving end by fixing the transmission beamforming vectors of all public signals, the transmission beamforming vectors of all private signals and the actual public signal transmission rate of the power receiving end, and obtaining a second target constraint condition set for the minimum total information transmission rate of each power receiving end. The second target constraint condition set includes a second set of constraints, wherein the maximum value of the minimum total information transmission rate of each power receiving end is calculated based on the first target constraint condition set in combination with the path tracking method and the penalty function method, so as to simultaneously optimize the transmission beamforming vectors of all public signals, the transmission beamforming vectors of all private signals and the actual public signal transmission rate of the power receiving end. The second target constraint condition set includes a second set of constraints, wherein the maximum value of the minimum total information transmission rate of each power receiving end is calculated based on the first target constraint condition set. The method comprises the following steps: a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition and a fifth constraint condition, wherein the fifth constraint condition includes that the modulus of the reflection beamforming vector set is equal to a set value; a path tracking method and a penalty function method are combined to calculate the maximum value of the minimum total information transmission rate of each power receiving end based on the second target constraint condition set to optimize the reflection beamforming vector set; and an iterative optimization is performed on the transmit beamforming vectors of all public signals, the transmit beamforming vectors of all private signals, the actual public signal transmission rates of all power receiving ends and the reflection beamforming vector set until the minimum total information transmission rate of the power receiving end no longer increases, thereby obtaining an optimized resource set.

[0007] According to the satellite communication resource optimization method for electric power services in remote areas provided by the present invention, the transmission beamforming vectors of all private signals of the transmitter to all electric power receiving terminals include the transmission beamforming vectors of the target private signals of the transmitter to the target electric power receiving terminal and the transmission beamforming vectors of other private signals of the transmitter to other electric power receiving terminals, the target electric power receiving terminal is any electric power receiving terminal, and the other electric power receiving terminals are electric power receiving terminals other than the target electric power receiving terminal. Based on the transmission beamforming vectors of all public signals of the transmitter, the transmission beamforming vectors of all private signals of the transmitter to all electric power receiving terminals, the reflection beamforming vector sets of multiple intelligent reflection arrays and the actual public signal transmission rate of the power receiving terminal, the minimum total information transmission rate of each electric power receiving terminal is determined, including: based on the target electric power receiving terminal, the transmission beamforming vectors of all public signals of the transmitter, the transmission beamforming vectors of all private signals of the transmitter to all electric power receiving terminals, the reflection beamforming vector sets of multiple intelligent reflection arrays and the actual public signal transmission rate of the power receiving terminal, the minimum total information transmission rate of each electric power receiving terminal is determined. The invention discloses a method for determining the first useful information of the target power receiving end based on the target channel vector set of the target power receiving end and the transmit beamforming vector of the target private signal; determining the first useless information of the target power receiving end based on the target channel vector set, the transmit beamforming vector of each other private signal and the noise of the target power receiving end; determining the first target signal-to-noise ratio of the target power receiving end based on the ratio of the first useful information to the first useless information, and determining the target theoretical private signal transmission rate of the target power receiving end based on the first target signal-to-noise ratio; obtaining the target actual public signal transmission rate of the target power receiving end, and obtaining the total information transmission rate of the target power receiving end based on the sum of the target actual public signal transmission rate and the target theoretical private signal transmission rate; when the total information transmission rate reaches the minimum value, obtaining the target minimum total information transmission rate of the target power receiving end.

[0008] According to the satellite communication resource optimization method for power services in remote areas provided by the present invention, the target channel vector set is determined based on the following steps: obtaining the direct channel vector set between all transmitting ends and the target power receiving end, obtaining the incident channel vector matrix between all transmitting ends and all intelligent reflection arrays, and obtaining the reflection channel vector matrix between all intelligent reflection arrays and the target power receiving end; based on the incident channel vector matrix, the reflection channel vector matrix and the reflection beamforming vector set, obtaining the indirect channel vector set between all transmitting ends and the target power receiving end; based on the sum of the direct channel vector set and the indirect channel vector set, obtaining the target channel vector set.

[0009] According to the satellite communication resource optimization method for electric power services in remote areas provided by the present invention, each intelligent reflector array includes multiple reflector units, and a reflection beamforming vector set is determined based on the following steps: determining a reflection beamforming vector based on a phase shift angle of a reflector unit and a reflection coefficient of a reflector unit; and obtaining a reflection beamforming vector set based on the reflection beamforming vectors of all intelligent reflector arrays.

[0010] According to the satellite communication resource optimization method for electric power services in remote areas provided by the present invention, the theoretical public signal transmission rate of each power receiving end is determined based on the following steps: based on the target channel vector set of the target power receiving end and the transmit beamforming vectors of all public signals, the second useful information of the target power receiving end is determined; based on the target channel vector set, the transmit beamforming vectors of all private signals and the noise of the target power receiving end, the second useless information of the target power receiving end is determined; based on the ratio of the second useful information to the second useless information, the second target signal-to-noise ratio of the target power receiving end is determined, and the target theoretical public signal transmission rate is determined based on the second target signal-to-noise ratio.

[0011] According to the satellite communication resource optimization method for electric power services in remote areas provided by the present invention, the transmission power of the transmitting end is determined based on the following steps: determining the public signal transmission power of the transmitting end based on the transmission beamforming vectors of all public signals and a preset unit diagonal matrix; determining the transmission power of the private signal of each electric power receiving end based on the transmission beamforming vector of each private signal and a preset unit diagonal matrix, summing the transmission powers of the private signals of all electric power receiving ends to obtain the total transmission power of the private signals; and obtaining the transmission power of the transmitting end based on the public signal transmission power and the total transmission power of the private signals.

[0012] The present invention also provides a satellite communication resource optimization device for electric power services in remote areas, comprising: a determination module, used to determine the minimum total information transmission rate of each power receiving end in the satellite communication system of the electric power service based on the transmission beamforming vector of all public signals of the transmitting end, the transmission beamforming vector of all private signals of the transmitting end to all power receiving ends, the reflection beamforming vector set of multiple intelligent reflection arrays and the actual public signal transmission rate of the power receiving end; an optimization module, used to obtain the maximum value of the minimum total information transmission rate of each power receiving end to determine an optimized resource set, and allocate transmission resources of the satellite communication system of the electric power service based on the optimized resource set, the optimized resource set including the optimized transmission beamforming vector of all public signals, the optimized transmission beamforming vector of all private signals, the optimized reflection beamforming vector set and the optimized actual public signal transmission rate of all power receiving ends.

[0013] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-mentioned satellite communication resource optimization methods for electric power services in remote areas.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned satellite communication resource optimization methods for electric power services in remote areas.

[0015] The present invention provides a satellite communication resource optimization method and device for electric power services in remote areas. In the satellite communication system for electric power services, based on the transmission beamforming vectors of all public signals of the transmitter, the transmission beamforming vectors of all private signals of the transmitter to all electric power receiving ends, the reflection beamforming vector set of multiple intelligent reflection arrays and the actual public signal transmission rate of the electric power receiving end, the minimum total information transmission rate of each electric power receiving end is determined; the maximum value of the minimum total information transmission rate of each electric power receiving end is obtained to determine the optimized resource set, and the transmission resources of the satellite communication system for electric power services are allocated based on the optimized resource set, wherein the optimized resource set includes the optimized transmission beamforming vectors of all public signals, the optimized transmission beamforming vectors of all private signals, the optimized reflection beamforming vector set and the optimized actual public signal transmission rate of all electric power receiving ends. The present invention optimizes the transmission beamforming vectors of all public signals, optimizes the transmission beamforming vectors of all private signals, optimizes the reflection beamforming vector set and optimizes the actual public signal transmission rate of all power receiving ends by obtaining the maximum value of the minimum total information transmission rate of each power receiving end, thereby achieving the optimal allocation of transmission resources for the satellite communication system of the power business. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a flow chart of a satellite communication resource optimization method for electric power business in remote areas provided by the present invention.

[0018] Figure 2 It is a structural schematic diagram of a satellite communication system for electric power business provided by the present invention.

[0019] Figure 3 It is a curve showing the maximum value of the minimum total information transmission rate of the power receiving end provided by the present invention changing with the transmission packet length.

[0020] Figure 4 It is a curve showing the maximum value of the minimum total information transmission rate of the power receiving end provided by the present invention changing with the packet error rate.

[0021] Figure 5 It is a curve showing the maximum value of the minimum total information transmission rate of the power receiving end provided by the present invention changing with the maximum transmission power of the transmitting end.

[0022] Figure 6 It is a structural schematic diagram of a satellite communication resource optimization device for electric power services in remote areas provided by the present invention.

[0023] Figure 7 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] In satellite communication systems, Multiple-Input Multiple-Output (MIMO) technology is to equip the transmitter and receiver with multiple antennas, use appropriate signal processing technology, and use the multipath propagation and spatial diversity of multiple independent channels to reduce the impact of multipath effects. It also uses beamforming technology to form directional beams to further reduce interference and improve channel quality and transmission rate. With the development and evolution of technology, the number of antennas at the transmitter has reached 8, 64, or even larger antenna arrays, which has developed into large-scale MIMO technology. Large-scale MIMO not only gives full play to the advantages of MIMO technology itself, but also improves the directivity of beamforming through a large number of antennas, forming narrow beam directional transmission with relatively concentrated energy.

[0026] As an important form of massive MIMO technology, the advantages of non-cellular massive MIMO system are simplicity, flexibility, low cost, etc. It has broad application prospects in the future 5G and subsequent communication networks.

[0027] In order to further improve the rate of short packet communication systems in the Internet of Things, a new network architecture can be considered at the network level. Cell-free massive MIMO is a shift from centralization to distribution that fits the vision of 6G network architecture. Compared with traditional massive MIMO, it has a higher coverage area and macro gain, and can avoid the problem of handover in multi-cell systems, bringing better system performance. In addition, the use of rate-splitting multiple access (RSMA) technology to replace traditional multiple access technology can not only break through the resource limitations of frequency domain, time domain and code domain, but also manage interference more scientifically and effectively, achieve a compromise between space division multiple access (SDMA) and non-orthogonal multiple access (NOMA) in the power domain, and reduce the impact of inter-user interference on the system. At the same time, the reconfigurable intelligent surface (RIS) realizes active control of the wireless channel. With low cost, flexible deployment, low complexity and changeable shapes, RIS has opened up new ideas for future wireless communication scenarios and brought new solutions to improve system performance at low cost. Therefore, the present invention adds RSMA technology and RIS technology to the non-cellular massive MIMO of short packet communication to improve the satellite communication system for power services in remote areas, and studies the resource allocation problem of the satellite communication system for remote power services.

[0028] Combine the following Figure 1-Figure 7 The invention describes a satellite communication resource optimization method, device and electronic equipment for power services in remote areas.

[0029] Figure 1 FIG. 1 is a flow chart of a satellite communication resource optimization method for power services in remote areas provided by the present invention. Figure 1 As shown, the satellite communication resource optimization method for electric power services in remote areas includes steps S100 to S200, and each step is specifically as follows.

[0030] S100: In a satellite communication system for electric power business, the minimum total information transmission rate of each electric power receiving end is determined based on the transmit beamforming vectors of all public signals of the transmitter, the transmit beamforming vectors of all private signals of the transmitter to all electric power receiving ends, the reflection beamforming vector set of multiple intelligent reflection arrays and the actual public signal transmission rate of the electric power receiving end.

[0031] like Figure 2As shown, a satellite communication system for electric power business is constructed. The satellite communication system for electric power business of the present invention is a RIS-assisted satellite-ground fusion non-cellular massive MIMO-RSMA system. The satellite communication system includes a low-orbit satellite, multiple transmitting terminals (Access Point, AP), multiple intelligent reflection (RIS) arrays and multiple power receiving terminals.

[0032] For example, Figure 2 As shown in the figure, the satellite communication system for the power business includes N transmitters (APs) with M antennas and L intelligent reflect arrays (RIS). Each RIS contains U reflection units, represented by , and there are K single-antenna power receiving ends (UEs) randomly distributed in the area. In the satellite communication system for the power business, all APs are connected to the same low-orbit satellite. At the same time, the RIS can receive the incident signal from the AP and transmit it to the UE through its reflection unit to enhance the UE's receiving signal.

[0033] Based on the above embodiment, the target channel vector set is determined based on the following steps.

[0034] Obtain a set of direct channel vectors between all transmitters and target power receiving ends, obtain incident channel vector matrices between all transmitters and all smart reflective arrays, and obtain reflected channel vector matrices between all smart reflective arrays and target power receiving ends.

[0035] Based on the incident channel vector matrix, the reflected channel vector matrix and the reflected beamforming vector set, an indirect channel vector set between all transmitters and the target power receiving end is obtained.

[0036] Based on the sum of the direct channel vector set and the indirect channel vector set, a target channel vector set is obtained.

[0037] Based on the above embodiment, each smart reflect array includes multiple reflective units, and the reflection beamforming vector set is determined based on the following steps: determining a reflection beamforming vector based on a phase shift angle of a reflective unit and a reflection coefficient of a reflective unit; and obtaining the reflection beamforming vector set based on the reflection beamforming vectors of all smart reflect arrays.

[0038] The direct channel from the nth AP to the kth UE (target power receiving end) is , the incident channel from the nth AP to the lth RIS is , and the reflection channel from the lth RIS to the kth UE is Assuming that all APs in the area serve each UE, for the kth UE, there are N direct channels from the AP to it, and the direct channel vector set is expressed as There are NL incoming channels from AP to RIS, and the incoming channel matrix from all (N) APs to the lth RIS can be expressed as , then the incident channel vector matrix from all (N) APs to all (L) RISs is written as In addition, there are L reflection channel vector matrices from all RIS to the kth UE, expressed as .

[0039] The reflection unit of the lth RIS is represented as a set of phase-shifted diagonal matrices , then the phase shift matrix of L RIS is as follows.

[0040] ; in Indicates the first RIS The phase shift angle of each reflector unit, Indicates the first RIS The reflection coefficient of the reflection unit is assumed to be , , , is the phase shift diagonal matrix of all (L) RIS, is the set of reflection beamforming vectors for all RIS, is the reflection beamforming vector of the first reflection unit of the Lth smart reflection array, is the number of smart reflective arrays, is the number of power receiving terminals.

[0041] Then the expression formula of the target channel vector set from all transmitters (APs) to the target power receiving end (kth UE) is as follows.

[0042] ; in, is the target channel vector set of the target power receiving end, is the conjugate transpose, is the direct channel vector set, For the The phase-shifted diagonal matrix of RIS, For the sender to The incident channel matrix of each RIS end, is the reflection channel vector matrix from all RIS to the target power receiving end (kth UE), is the phase shift diagonal matrix of all RIS, is the incident channel vector matrix between all transmitters and all smart reflector arrays, For A reflection channel matrix from a smart reflective array (RIS) to the target power receiving end, is the reflection beamforming vector set of L RIS, is the middle diagonal matrix of the target power receiving end, is the number of RIS, is the number of reflective units in a smart reflective array, is the number of senders, is the indirect channel vector set, is the number of antennas at each power receiving end, For the The first intelligent reflective array The reflection beamforming vector of the reflection unit, is a diagonal matrix.

[0043] Based on the above embodiment, the transmit beamforming vector of all private signals of the transmitting end to all power receiving ends includes the transmit beamforming vector of the target private signal of the transmitting end to the target power receiving end and the transmit beamforming vector of other private signals of the transmitting end to other power receiving ends, the target power receiving end is any power receiving end, and the other power receiving ends are power receiving ends other than the target power receiving end. Based on the transmit beamforming vector of all public signals of the transmitting end, the transmit beamforming vector of all private signals of the transmitting end to all power receiving ends, the reflection beamforming vector set of multiple intelligent reflection arrays and the actual public signal transmission rate of the power receiving end, the minimum total information transmission rate of each power receiving end is determined, including the following steps.

[0044] Based on a target channel vector set of the target power receiving end and a transmit beamforming vector of a target private signal, first useful information of the target power receiving end is determined.

[0045] First useless information of the target power receiving end is determined based on the target channel vector set, the transmit beamforming vector of each other private signal, and the noise of the target power receiving end.

[0046] A first target signal-to-noise ratio of the target power receiving end is determined based on the ratio of the first useful information to the first useless information, and a target theoretical private signal transmission rate of the target power receiving end is determined based on the first target signal-to-noise ratio.

[0047] The target actual public signal transmission rate of the target power receiving end is obtained, and the total information transmission rate of the target power receiving end is obtained based on the sum of the target actual public signal transmission rate and the target theoretical private signal transmission rate.

[0048] When the total information transmission rate reaches the minimum value, the target minimum total information transmission rate of the target power receiving end is obtained.

[0049] like Figure 2 As shown in the figure, according to the RSMA transmission scheme, at the transmitting end, the CPU first splits the user information into two parts: public signal and private signal, and synthesizes the public signals of all power receiving ends, and then encodes them together. The CPU encodes the private signal independently, and then transmits it to the AP through the fronthaul link, and then the AP sends it out after beamforming. Therefore, the expression formula of the total transmitted information at the transmitting end is as follows.

[0050] ; in, is the total information sent by the sender, is the transmit beamforming vector of all common signals at the transmitter, is the transmit beamforming vector of the first common signal, is the common signal for all power receiving ends, is the transmit beamforming vector of the private signal from the transmitter to all power receivers, For the A private signal of the power receiving end, is the number of power receiving terminals, is the transmit beamforming vector of the private signal of the transmitter to the first power receiving end.

[0051] Based on the above embodiments, the theoretical common signal transmission rate of each power receiving end is determined based on the following steps.

[0052] Based on the target channel vector set of the target power receiving end and the transmit beamforming vectors of all common signals, second useful information of the target power receiving end is determined.

[0053] Based on the target channel vector set, the transmit beamforming vectors of all private signals, and the noise of the target power receiving end, second useless information of the target power receiving end is determined.

[0054] A second target signal-to-noise ratio of the target power receiving end is determined based on the ratio of the second useful information to the second useless information, and a target theoretical common signal transmission rate is determined based on the second target signal-to-noise ratio.

[0055] After receiving the data signal, the power receiving end decodes the data signal and splits the information to obtain the received information.

[0056] Therefore, the The expression formula of the receiving information of a power receiving end (target receiving end) is as follows.

[0057] ; in, is the target channel vector set of the target power receiving end, Send information to the total is the transmit beamforming vector of all common signals, For public signals, is the transmit beamforming vector of the private signal of the target power receiving end, is the private signal of the target power receiving end, is the transmit beamforming vector of the private signal of other power receiving end, It is a private signal of other power receiving terminals. is the noise at the target receiving end, Receive information at the target receiving end.

[0058] Assuming that the public and private signals sent are independent of each other and both carry unit energy, we have , The target received power of the target power receiving end, the first target signal-to-noise ratio, the second target signal-to-noise ratio, the target theoretical private signal transmission rate, the target theoretical public signal transmission rate, and the target minimum total information transmission rate are calculated using the following formulas.

[0059] ; in, is the target received power at the target power receiving end, is the second target signal-to-noise ratio, The second useful information is is the second useless information, For the first useful information, The first useless information is is the target theoretical public signal transmission rate, is the target theoretical private signal transmission rate, is the channel dispersion of the common signal, is the channel dispersion of the private signal at the target power receiving end, is the first target signal-to-noise ratio, The first useless information is is the second target signal-to-noise ratio, For noise, is a Gaussian function, is the packet length for transmitting public signals (set value), The packet length for transmitting private signals (set value), is the total information transmission rate at the target power receiving end, is the target actual common signal transmission rate of the target power receiving end.

[0060] Based on the above steps, the total information transmission rate of any target power receiving end is calculated. When the total information transmission rate of the target power receiving end reaches the minimum value, the target minimum total information transmission rate of the target power receiving end is obtained.

[0061] S200: Obtain the maximum value of the minimum total information transmission rate of each power receiving end to determine an optimized resource set, and allocate transmission resources of the satellite communication system for the power service based on the optimized resource set. The optimized resource set includes the optimized transmit beamforming vectors of all public signals, the optimized transmit beamforming vectors of all private signals, the optimized reflection beamforming vector set and the optimized actual public signal transmission rates of all power receiving ends.

[0062] Obtain the total constraint condition set of the minimum total information transmission rate of each power receiving end. In order to ensure that all power receiving ends in the satellite communication system of the power business can accurately recover the signal of the public information, it is required that the maximum transmission rate of the public information cannot exceed the theoretical public signal transmission rate of any power receiving end. At the same time, it is required that the transmission power of each transmitting end is less than or equal to the maximum transmission power of the transmitting end. In summary, the minimum total information transmission rate and the total constraint condition set of the power receiving end are as follows.

[0063] ; (1) in, is the minimum total information transmission rate at the power receiving end, For the The transmit power of the transmitter, For the The maximum transmission power of the transmitter, is the sum of the actual common signal transmission rates of all power receiving ends, For the The target theoretical common signal transmission rate of each power receiving end is For the The target theoretical private signal transmission rate of each power receiving end is For the The target actual common signal transmission rate of each power receiving end, is the number of RIS, is the number of reflective units in a smart reflective array, is the number of senders, is the number of power receiving terminals, is the set of reflection beamforming vectors for all RIS, is a first preset unit diagonal matrix.

[0064] The embodiment of the present invention provides a satellite communication resource optimization method for electric power services in remote areas. In the satellite communication system for electric power services, based on the transmit beamforming vectors of all public signals of the transmitter, the transmit beamforming vectors of all private signals of the transmitter to all electric power receiving ends, the reflection beamforming vector set of multiple intelligent reflection arrays and the actual public signal transmission rate of the electric power receiving end, the minimum total information transmission rate of each electric power receiving end is determined; the maximum value of the minimum total information transmission rate of each electric power receiving end is obtained to determine an optimized resource set, and the transmission resources of the satellite communication system for electric power services are allocated based on the optimized resource set, wherein the optimized resource set includes the optimized transmit beamforming vectors of all public signals, the optimized transmit beamforming vectors of all private signals, the optimized reflection beamforming vector set and the optimized actual public signal transmission rate of all electric power receiving ends. The present invention optimizes the transmission beamforming vectors of all public signals, optimizes the transmission beamforming vectors of all private signals, optimizes the reflection beamforming vector set and optimizes the actual public signal transmission rate of all power receiving ends by obtaining the maximum value of the minimum total information transmission rate of each power receiving end, thereby achieving the optimal allocation of transmission resources for the satellite communication system of the power business.

[0065] Based on the above embodiment, obtaining the maximum value of the minimum total information transmission rate of each power receiving end to determine the optimized resource set includes the following steps.

[0066] A fixed reflection beamforming vector set is used to obtain a first target constraint set for the minimum total information transmission rate of each power receiving end. The first target constraint set includes a first constraint, a second constraint, a third constraint and a fourth constraint. The first constraint includes that the transmission power of each transmitting end is less than or equal to the maximum transmission power of the transmitting end, the second constraint includes that the sum of the actual public signal transmission rates of all power receiving ends is less than or equal to the transmission threshold, the third constraint includes that the actual public signal transmission rate of each power receiving end is greater than or equal to 0, and the fourth constraint includes that the theoretical private signal transmission rate of each power receiving end is greater than or equal to 0. The theoretical private signal transmission rate of the power receiving end is determined based on the transmit beamforming vectors of all private signals and the fixed reflection beamforming vector set, and the transmission threshold is determined based on the theoretical public signal transmission rate of each power receiving end; the theoretical public signal transmission rate of all power receiving ends is determined based on the transmit beamforming vectors of all public signals and the fixed reflection beamforming vector set.

[0067] Combining the path tracking method and the penalty function method, the maximum value of the minimum total information transmission rate of each power receiving end is calculated based on the first target constraint set to simultaneously optimize the transmit beamforming vectors of all public signals, the transmit beamforming vectors of all private signals and the actual public signal transmission rate of the power receiving end.

[0068] Fix the transmit beamforming vectors of all public signals, the transmit beamforming vectors of all private signals and the actual public signal transmission rate of the power receiving end, and obtain the second target constraint condition set of the minimum total information transmission rate of each power receiving end. The second target constraint condition set includes the second constraint condition, the third constraint condition, the fourth constraint condition and the fifth constraint condition. The fifth constraint condition includes that the modulus length of the reflection beamforming vector set is equal to the set value.

[0069] Combining the path tracking method and the penalty function method, the maximum value of the minimum total information transmission rate of each power receiving end is calculated based on the second objective constraint condition set to optimize the reflection beamforming vector set.

[0070] Iteratively optimize the transmit beamforming vectors of all public signals, the transmit beamforming vectors of all private signals, the actual public signal transmission rates of all power receiving ends, and the reflection beamforming vector set until the minimum total information transmission rate of the power receiving end no longer increases, and obtain the optimized resource set.

[0071] Calculating the maximum value of the minimum total information transmission rate for each power receiving end is a complex non-convex problem with multivariable coupling. Obtaining the global optimal solution will face two technical challenges. First, the minimum sign in the objective function (1) and the theoretical public information transmission rate makes the problem non-smooth, which makes it difficult to accurately determine the actual public information transmission rate and the private signal transmission rate of the worst power receiving end, increasing the difficulty of precoding design. Second, the coupling of active and passive beamforming vectors in the total constraint set makes the solution of the objective function (1) non-convex and difficult to solve directly. In addition, due to the unknown dual difference, the non-convex problem is also difficult to solve in the dual domain. In summary, it is extremely difficult to obtain the global optimal solution of the objective function (1).

[0072] In order to address these challenges, the present invention proposes an alternating optimization algorithm for multivariable coupling problems, which decomposes the solution of objective function (1) into two sub-problems. The first sub-problem is the active beamforming sub-problem at the transmitting (AP) end, that is, the set of reflection beamforming vectors is fixed, and the transmit beamforming vectors of public signals, the transmit beamforming vectors of private signals, and the actual public signal transmission rate of the power receiving end are optimized. The second sub-problem is the passive beamforming sub-problem at the intelligent reflect array (RIS) end, that is, the transmit beamforming vectors of all public signals, the transmit beamforming vectors of all private signals, and the actual public signal transmission rate of the power receiving end are fixed, and the set of reflection beamforming vectors is optimized.

[0073] Solve the first subproblem. Assume that all reflected beamforming vector sets are known. Obtain the minimum total information transmission rate and the first objective constraint set for each power receiving end.

[0074] ; (2) in, is the minimum total information transmission rate of the power receiving end corresponding to the first sub-problem, For the The transmit power of the transmitter, For the The maximum transmission power of the transmitter, is the sum of the actual common signal transmission rates of all power receiving ends, The first sub-problem corresponds to The target theoretical common signal transmission rate of each power receiving end is The first sub-problem corresponds to The target theoretical private signal transmission rate of each power receiving end is For the The target actual common signal transmission rate of each power receiving end, is the number of RIS, is the number of reflective units in a smart reflective array, is the number of senders, is the number of power receiving terminals, is the first constraint, is the second constraint, is the third constraint, is the fourth constraint.

[0075] It is not difficult to see that the first problem is non-convex and non-smooth, and it is difficult to solve directly. The present invention proposes to convert the first sub-problem into a convex problem based on the path tracking method. Specifically, the minimum total information transmission rate of the non-smooth power receiving end is first smoothly approximated, and then the actual public signal transmission rate of the complex non-convex power receiving end and the theoretical private signal transmission rate expression of the power receiving end are approximated by the lower bound concave function, and the problem simplified to a convex problem is iteratively calculated to obtain the optimal solution to the first sub-problem. Finally, the first sub-problem can be obtained using the convex optimization tool (Convex Optimization, CVX), and then the transmit beamforming vectors of all public signals, the transmit beamforming vectors of all private signals, and the actual public signal transmission rate of the power receiving end are simultaneously optimized.

[0076] Solve the second sub-problem. Assume that the transmit beamforming vectors of all public signals, the transmit beamforming vectors of all private signals, and the actual public signal transmission rate of the power receiving end are known. Obtain the minimum total information transmission rate and the second target constraint set of each power receiving end.

[0077] ; (3) in, is the minimum total information transmission rate at the power receiving end corresponding to the second sub-problem, is the sum of the actual common signal transmission rates of all power receiving ends, The second sub-problem corresponds to The target theoretical common signal transmission rate of each power receiving end is The second sub-problem corresponds to The target theoretical private signal transmission rate of each power receiving end is For the The target actual common signal transmission rate of each power receiving end, is the number of RIS, is the number of reflective units in a smart reflective array, is the number of power receiving terminals, is the first preset unit diagonal matrix, is the set of reflection beamforming vectors for all RIS, is the fifth constraint.

[0078] The second sub-problem is also non-convex and non-smooth, and is difficult to solve directly. The present invention combines the path tracking method with the penalty function method to transform the solution of the second sub-problem into a convex problem. Finally, the convex optimization tool CVX can be used to solve the second sub-problem and then optimize the reflection beamforming vector set.

[0079] Finally, by solving the first subproblem and the second subproblem through multiple alternating iterations, the maximum value of the minimum total information transmission rate and the optimized resource set of the power receiving end can be obtained.

[0080] Figure 3 The maximum value of the minimum total information transmission rate at the power receiving end varies with the transmission packet length in the systems with and without RIS assistance using the RSMA scheme. It can be seen that as the packet length increases, the maximum value of the minimum total information transmission rate at the power receiving end of the system also increases and gradually tends to a constant value. This is because as the packet length continues to increase, the short packet rate of the system will gradually approach the Shannon capacity. At the same time, the system rate after adding RIS is improved overall compared to the system rate without RIS, because RIS can perform secondary reflection on the beam transmitted by the AP, and can reflect the beam to the corresponding user after optimizing the reflected beamforming. Therefore, the user end is equivalent to having an additional receiving channel, thereby obtaining a higher receiving rate, which improves the system throughput.

[0081] Figure 4 The maximum value of the minimum total information transmission rate at the power receiving end varies with the packet error rate in the RSMA scheme with and without RIS assistance. Figure 4 It can be seen that with the increase in the requirements for the packet error rate, the maximum value of the minimum total information transmission rate of the power receiving end of the system will be reduced. In addition, the addition of RIS also improves the reliability of the system to a certain extent, so that the system can still obtain a better maximum value of the minimum total information transmission rate of the power receiving end under a lower bit error rate.

[0082] Figure 5 This is the curve of the maximum value of the minimum total information transmission rate at the power receiving end of the RIS-assisted system changing with the maximum transmission power of the transmitting end. It can be seen that with the increase of the maximum transmission power, the maximum value of the minimum total information transmission rate at the power receiving end of the system gradually increases. At the same time, the achievable rate of the RIS-assisted RSMA scheme is higher than that of the SDMA scheme. This is because RSMA encodes the common part of the transmitted information together and sends it, and uses SIC decoding at the power receiving end. Compared with SDMA, it can better handle inter-user interference, so it can obtain a higher system rate.

[0083] The present invention solves the first subproblem and the second subproblem by alternate iteration until convergence, thereby realizing the calculation of the maximum value of the minimum total information transmission rate of each power receiving end and the corresponding optimized resource set.

[0084] Based on the above embodiment, the transmission power of the transmitting end is determined based on the following steps.

[0085] The common signal transmission power of the transmitting end is determined based on the transmit beamforming vectors of all common signals and a preset unit diagonal matrix.

[0086] The transmission power of the private signal of each power receiving end is determined based on the transmit beamforming vector of each private signal and a preset unit diagonal matrix, and the transmission powers of the private signals of all power receiving ends are summed to obtain the total transmission power of the private signal.

[0087] The transmission power of the transmitting end is obtained based on the total transmission power of the public signal and the private signal.

[0088] Assuming that the public and private signals sent are independent of each other and both carry unit energy, we have , The preset unit diagonal matrix includes a first preset unit diagonal matrix and a second preset unit diagonal matrix. The calculation formula of the transmission power of each transmitting end (AP) is as follows.

[0089] ; in, For the The transmit power of the transmitter, is the second preset unit diagonal matrix, is the first preset unit diagonal matrix, is the transmit beamforming vector of all common signals at the transmitter, is the transmit beamforming vector of the private signal from the transmitter to all power receivers, is the number of RIS, is the number of reflective units in a smart reflective array, is the number of senders, is the number of antennas at each power receiving end, is the number of power receiving terminals.

[0090] The present invention realizes the uniform passing through by presetting the unit diagonal matrix and Calculating the transmission power at the transmitting end achieves the unification of variables, which is beneficial to the subsequent unification of the variables of the minimum total information transmission rate at the power receiving end.

[0091] The satellite communication resource optimization device for electric power services in remote areas provided by the present invention is described below. The satellite communication resource optimization device for electric power services in remote areas described below and the satellite communication resource optimization method for electric power services in remote areas described above can be referenced to each other.

[0092] like Figure 6 As shown, a satellite communication resource optimization device for electric power business in remote areas is characterized in that it includes: a determination module 601, which is used to determine the minimum total information transmission rate of each power receiving end in the satellite communication system of the electric power business based on the transmission beamforming vector of all public signals of the transmitting end, the transmission beamforming vector of all private signals of the transmitting end to all power receiving ends, the reflection beamforming vector set of multiple intelligent reflection arrays and the actual public signal transmission rate of the power receiving end.

[0093] The optimization module 602 is used to obtain the maximum value of the minimum total information transmission rate of each of the power receiving ends to determine an optimized resource set, and allocate transmission resources of the satellite communication system of the power business based on the optimized resource set, wherein the optimized resource set includes the optimized transmit beamforming vectors of all public signals, the optimized transmit beamforming vectors of all private signals, the optimized reflection beamforming vector set and the optimized actual public signal transmission rates of all power receiving ends.

[0094] The satellite communication resource optimization device for electric power services in remote areas provided by an embodiment of the present invention determines the minimum total information transmission rate of each electric power receiving end in the satellite communication system for electric power services based on the transmission beamforming vector of all public signals of the transmitting end, the transmission beamforming vector of all private signals of the transmitting end to all electric power receiving ends, the reflection beamforming vector set of multiple intelligent reflection arrays and the actual public signal transmission rate of the electric power receiving end; obtains the maximum value of the minimum total information transmission rate of each electric power receiving end to determine the optimized resource set, and allocates transmission resources of the satellite communication system for electric power services based on the optimized resource set, wherein the optimized resource set includes the optimized transmission beamforming vector of all public signals, the optimized transmission beamforming vector of all private signals, the optimized reflection beamforming vector set and the optimized actual public signal transmission rate of all electric power receiving ends. The present invention optimizes the transmission beamforming vectors of all public signals, optimizes the transmission beamforming vectors of all private signals, optimizes the reflection beamforming vector set and optimizes the actual public signal transmission rate of all power receiving ends by obtaining the maximum value of the minimum total information transmission rate of each power receiving end, thereby achieving the optimal allocation of transmission resources for the satellite communication system of the power business.

[0095] In one embodiment, the optimization module 602 is used to: fix the reflection beamforming vector set, obtain the first target constraint set of the minimum total information transmission rate of each power receiving end, the first target constraint set includes a first constraint, a second constraint, a third constraint and a fourth constraint, the first constraint includes that the transmission power of each transmitting end is less than or equal to the maximum transmission power of the transmitting end, the second constraint includes that the sum of the actual public signal transmission rates of all power receiving ends is less than or equal to the transmission threshold, the third constraint includes that the actual public signal transmission rate of each power receiving end is greater than or equal to 0, the fourth constraint includes that the theoretical private signal transmission rate of each power receiving end is greater than or equal to 0, the theoretical private signal transmission rate of the power receiving end is determined based on the transmit beamforming vectors of all private signals and the fixed reflection beamforming vector set, and the transmission threshold is determined based on the theoretical public signal transmission rate of each power receiving end; the theoretical public signal transmission rate of all power receiving ends is determined based on the transmit beamforming vectors of all public signals and the fixed reflection beamforming vector set; combined with the path tracking method and the penalty function method, based on The first target constraint condition set calculates the maximum value of the minimum total information transmission rate of each power receiving end to simultaneously optimize the transmit beamforming vectors of all public signals, the transmit beamforming vectors of all private signals and the actual public signal transmission rate of the power receiving end; the transmit beamforming vectors of all public signals, the transmit beamforming vectors of all private signals and the actual public signal transmission rate of the power receiving end are fixed to obtain the second target constraint condition set of the minimum total information transmission rate of each power receiving end, the second target constraint condition set includes the second constraint condition, the third constraint condition, the fourth constraint condition and the fifth constraint condition, and the fifth constraint condition includes that the modulus length of the reflection beamforming vector set is equal to the set value; combining the path tracking method and the penalty function method, the maximum value of the minimum total information transmission rate of each power receiving end is calculated based on the second target constraint condition set to optimize the reflection beamforming vector set; iteratively optimize the transmit beamforming vectors of all public signals, the transmit beamforming vectors of all private signals, the actual public signal transmission rates of all power receiving ends and the reflection beamforming vector set until the minimum total information transmission rate of the power receiving end no longer increases, and the optimized resource set is obtained.

[0096] In one embodiment, the transmit beamforming vectors of all private signals of all power receiving ends from the transmitting end include the transmit beamforming vectors of the target private signal of the target power receiving end from the transmitting end and the transmit beamforming vectors of other private signals of other power receiving ends from the transmitting end, the target power receiving end is any power receiving end, and the other power receiving ends are power receiving ends other than the target power receiving end, and the determination module 601 is used to: determine the first useful information of the target power receiving end based on the target channel vector set of the target power receiving end and the transmit beamforming vector of the target private signal; determine the first useful information of the target power receiving end based on the target channel vector set, each other private signal The method comprises the following steps: determining a first useless information of the target power receiving end based on the transmit beamforming vector of the target power receiving end and the noise of the target power receiving end; determining a first target signal-to-noise ratio of the target power receiving end based on the ratio of the first useful information to the first useless information, and determining a target theoretical private signal transmission rate of the target power receiving end based on the first target signal-to-noise ratio; obtaining a target actual public signal transmission rate of the target power receiving end, and obtaining a total information transmission rate of the target power receiving end based on the sum of the target actual public signal transmission rate and the target theoretical private signal transmission rate; and obtaining a target minimum total information transmission rate of the target power receiving end when the total information transmission rate reaches a minimum value.

[0097] In one embodiment, the determination module 601 is also used to: obtain a direct channel vector set between all transmitting ends and the target power receiving end, obtain an incident channel vector matrix between all transmitting ends and all smart reflection arrays, and obtain a reflection channel vector matrix between all smart reflection arrays and the target power receiving end; based on the incident channel vector matrix, the reflection channel vector matrix and the reflection beamforming vector set, obtain an indirect channel vector set between all transmitting ends and the target power receiving end; based on the sum of the direct channel vector set and the indirect channel vector set, obtain the target channel vector set.

[0098] In one embodiment, the determination module 601 is further used to: determine a reflection beamforming vector based on a phase shift angle of a reflection unit and a reflection coefficient of a reflection unit; and obtain a reflection beamforming vector set based on the reflection beamforming vectors of all smart reflect arrays.

[0099] In one embodiment, the determination module 601 is also used to: determine the second useful information of the target power receiving end based on the target channel vector set of the target power receiving end and the transmit beamforming vectors of all public signals; determine the second useless information of the target power receiving end based on the target channel vector set, the transmit beamforming vectors of all private signals and the noise of the target power receiving end; determine the second target signal-to-noise ratio of the target power receiving end based on the ratio of the second useful information to the second useless information, and determine the target theoretical public signal transmission rate based on the second target signal-to-noise ratio.

[0100] In one embodiment, the optimization module 602 is also used to: determine the public signal transmission power of the transmitting end based on the transmission beamforming vector of all public signals and a preset unit diagonal matrix; determine the transmission power of the private signal of each power receiving end based on the transmission beamforming vector of each private signal and a preset unit diagonal matrix, sum the transmission powers of the private signals of all power receiving ends to obtain the total transmission power of the private signals; obtain the transmission power of the transmitting end based on the public signal transmission power and the total transmission power of the private signals.

[0101] Figure 7 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 7 As shown, the electronic device may include: a processor (processor) 710 , a communication interface (Communications Interface) 720 , a memory (memory) 730 and a communication bus 740 , wherein the processor 710 , the communication interface 720 , and the memory 730 communicate with each other through the communication bus 740 . The processor 710 can call the logic instructions in the memory 730 to execute a satellite communication resource optimization method for electric power services in remote areas, the method comprising: in a satellite communication system for electric power services, based on the transmit beamforming vectors of all public signals of the transmitter, the transmit beamforming vectors of all private signals of the transmitter to all electric power receiving ends, the reflection beamforming vector set of multiple intelligent reflection arrays and the actual public signal transmission rate of the electric power receiving end, determine the minimum total information transmission rate of each electric power receiving end; obtain the maximum value of the minimum total information transmission rate of each electric power receiving end to determine an optimized resource set, and allocate transmission resources of the satellite communication system for electric power services based on the optimized resource set, the optimized resource set including the optimized transmit beamforming vectors of all public signals, the optimized transmit beamforming vectors of all private signals, the optimized reflection beamforming vector set and the optimized actual public signal transmission rate of all electric power receiving ends.

[0102] In addition, the logic instructions in the above-mentioned memory 730 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0103] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the satellite communication resource optimization method for electric power services in remote areas provided by the above-mentioned methods, the method comprising: in a satellite communication system for electric power services, based on the transmit beamforming vectors of all public signals of the transmitting end, the transmit beamforming vectors of all private signals of the transmitting end to all electric power receiving ends, the reflection beamforming vector set of multiple intelligent reflection arrays and the actual public signal transmission rate of the electric power receiving end, determining the minimum total information transmission rate of each electric power receiving end; obtaining the maximum value of the minimum total information transmission rate of each electric power receiving end to determine an optimized resource set, and allocating transmission resources of the satellite communication system for electric power services based on the optimized resource set, the optimized resource set comprising the optimized transmit beamforming vectors of all public signals, the optimized transmit beamforming vectors of all private signals, the optimized reflection beamforming vector set and the optimized actual public signal transmission rate of all electric power receiving ends.

[0104] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0105] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A satellite communication resource optimization method for power services in remote areas, characterized in that: include: In a satellite communication system for electric power services, a minimum total information transmission rate for each electric power receiving end is determined based on a transmit beamforming vector of all public signals of a transmitting end, a transmit beamforming vector of all private signals of a transmitting end to all electric power receiving ends, a set of reflection beamforming vectors of a plurality of smart reflection arrays, and an actual public signal transmission rate of the electric power receiving end; The maximum value of the minimum total information transmission rate of each of the power receiving ends is obtained to determine an optimized resource set, and the transmission resources of the satellite communication system of the power service are allocated based on the optimized resource set, wherein the optimized resource set includes the optimized transmit beamforming vectors of all public signals, the optimized transmit beamforming vectors of all private signals, the optimized reflection beamforming vector set and the optimized actual public signal transmission rates of all power receiving ends.

2. The satellite communication resource optimization method for power services in remote areas according to claim 1, characterized in that: The obtaining the maximum value of the minimum total information transmission rate of each of the power receiving terminals to determine the optimized resource set includes: The reflection beamforming vector set is fixed, and a first target constraint set of a minimum total information transmission rate of each of the power receiving ends is obtained, wherein the first target constraint set includes a first constraint, a second constraint, a third constraint and a fourth constraint, wherein the first constraint includes that the transmission power of each transmitting end is less than or equal to the maximum transmission power of the transmitting end, the second constraint includes that the sum of the actual public signal transmission rates of all the power receiving ends is less than or equal to the transmission threshold, the third constraint includes that the actual public signal transmission rate of each of the power receiving ends is greater than or equal to 0, and the fourth constraint includes that the theoretical private signal transmission rate of each power receiving end is greater than or equal to 0, and the theoretical private signal transmission rate of the power receiving end is determined based on the transmit beamforming vectors of all the private signals and the fixed reflection beamforming vector set, and the transmission threshold is determined based on the theoretical public signal transmission rate of each power receiving end; the theoretical public signal transmission rates of all the power receiving ends are determined based on the transmit beamforming vectors of all the public signals and the fixed reflection beamforming vector set; Combining a path tracking method and a penalty function method, calculating the maximum value of the minimum total information transmission rate of each of the power receiving ends based on the first target constraint condition set, so as to simultaneously optimize the transmit beamforming vectors of all the public signals, the transmit beamforming vectors of all the private signals, and the actual public signal transmission rate of the power receiving end; Fixing the transmit beamforming vectors of all the public signals, the transmit beamforming vectors of all the private signals, and the actual public signal transmission rate of the power receiving end, and obtaining a second target constraint condition set of the minimum total information transmission rate of each of the power receiving ends, wherein the second target constraint condition set includes the second constraint condition, the third constraint condition, the fourth constraint condition, and the fifth constraint condition, and the fifth constraint condition includes that the modulus length of the reflection beamforming vector set is equal to a set value; Combining the path tracking method and the penalty function method, calculating the maximum value of the minimum total information transmission rate of each of the power receiving ends based on the second target constraint condition set to optimize the reflection beamforming vector set; Iteratively optimize the transmit beamforming vectors of all the public signals, the transmit beamforming vectors of all the private signals, the actual public signal transmission rates of all the power receiving ends, and the reflection beamforming vector set until the minimum total information transmission rate of the power receiving end no longer increases, thereby obtaining the optimized resource set.

3. The satellite communication resource optimization method for power services in remote areas according to claim 2, characterized in that: The transmit beamforming vector of all private signals of the transmitting end to all power receiving ends includes the transmit beamforming vector of the target private signal of the target power receiving end and the transmit beamforming vector of other private signals of the transmitting end to other power receiving ends, the target power receiving end is any of the power receiving ends, and the other power receiving ends are power receiving ends other than the target power receiving end, and the minimum total information transmission rate of each power receiving end is determined based on the transmit beamforming vector of all public signals of the transmitting end, the transmit beamforming vector of all private signals of the transmitting end to all power receiving ends, the reflection beamforming vector set of multiple smart reflection arrays and the actual public signal transmission rate of the power receiving end, including: Determining first useful information of the target power receiving end based on a target channel vector set of the target power receiving end and a transmit beamforming vector of the target private signal; Determine first useless information of the target power receiving end based on the target channel vector set, the transmit beamforming vector of each of the other private signals, and the noise of the target power receiving end; Determine a first target signal-to-noise ratio of the target power receiving end based on a ratio of the first useful information to the first useless information, and determine a target theoretical private signal transmission rate of the target power receiving end based on the first target signal-to-noise ratio; Acquire a target actual public signal transmission rate of the target power receiving end, and obtain a total information transmission rate of the target power receiving end based on a sum of the target actual public signal transmission rate and the target theoretical private signal transmission rate; When the total information transmission rate reaches the minimum value, the target minimum total information transmission rate of the target power receiving end is obtained.

4. The satellite communication resource optimization method for power services in remote areas according to claim 3, characterized in that: The target channel vector set is determined based on the following steps: Obtaining a direct channel vector set between all the transmitting ends and the target power receiving end, obtaining an incident channel vector matrix between all the transmitting ends and all the smart reflective arrays, and obtaining a reflected channel vector matrix between all the smart reflective arrays and the target power receiving end; Based on the incident channel vector matrix, the reflected channel vector matrix and the reflected beamforming vector set, acquiring an indirect channel vector set between all the transmitting ends and the target power receiving end; The target channel vector set is obtained based on the sum of the direct channel vector set and the indirect channel vector set.

5. The satellite communication resource optimization method for power services in remote areas according to claim 1, characterized in that: Each of the smart reflective arrays includes a plurality of reflective units, and the reflective beamforming vector set is determined based on the following steps: Determining a reflection beamforming vector based on a phase shift angle of the reflection unit and a reflection coefficient of the reflection unit; The reflection beamforming vector set is obtained based on the reflection beamforming vectors of all the smart reflect arrays.

6. The satellite communication resource optimization method for power services in remote areas according to claim 3, characterized in that: The theoretical common signal transmission rate of each of the power receiving ends is determined based on the following steps: Determining second useful information of the target power receiving end based on the target channel vector set of the target power receiving end and the transmit beamforming vectors of all the common signals; Determining second useless information of the target power receiving end based on the target channel vector set, the transmit beamforming vectors of all the private signals, and the noise of the target power receiving end; A second target signal-to-noise ratio of the target power receiving end is determined based on the ratio of the second useful information to the second useless information, and a target theoretical common signal transmission rate is determined based on the second target signal-to-noise ratio.

7. The satellite communication resource optimization method for power services in remote areas according to claim 2, characterized in that: The transmit power of the transmitting end is determined based on the following steps: Determine the common signal transmission power of the transmitting end based on the transmit beamforming vectors of all the common signals and a preset unit diagonal matrix; Determine the transmit power of the private signal of each power receiving end based on the transmit beamforming vector of each private signal and the preset unit diagonal matrix, and sum the transmit powers of the private signals of all the power receiving ends to obtain the total transmit power of the private signal; The transmission power of the transmitting end is obtained based on the total transmission power of the public signal and the private signal.

8. A satellite communication resource optimization device for power services in remote areas, characterized in that: include: A determination module is used to determine, in a satellite communication system for electric power services, a minimum total information transmission rate of each electric power receiving end based on a transmit beamforming vector of all public signals of a transmitting end, a transmit beamforming vector of all private signals of a transmitting end to all electric power receiving ends, a set of reflection beamforming vectors of a plurality of smart reflection arrays, and an actual public signal transmission rate of the electric power receiving end; An optimization module is used to obtain the maximum value of the minimum total information transmission rate of each of the power receiving ends to determine an optimized resource set, and allocate transmission resources of the satellite communication system of the power business based on the optimized resource set, wherein the optimized resource set includes optimized transmit beamforming vectors of all public signals, optimized transmit beamforming vectors of all private signals, an optimized reflection beamforming vector set, and optimized actual public signal transmission rates of all power receiving ends.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the method for optimizing satellite communication resources for electric power services in remote areas as described in any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the satellite communication resource optimization method for power services in remote areas as described in any one of claims 1 to 7 is implemented.

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