A low-latency hop-beam resource allocation method in a low earth orbit satellite

Abstract

The application relates to a low-latency hop-beam resource allocation method, which comprises the following steps: step 1, selecting users to be served according to a maximum delay criterion and a serial mode; step 2, considering the interference between adjacent cells, selecting a user with the maximum delay based on the user delay maximum and the serial user selection method; and step 3, balancing the delay values between different users by adopting a two-stage power allocation method to minimize the maximum delay between all users. The low-latency hop-beam resource allocation method has the following main superior technical effects: the constraint of total transmission power is fully considered in resource allocation, the maximum cumulative delay between all users in a low-orbit satellite scene is minimized under the condition of considering the inter-beam interference, and the fairness between different users is ensured.

Description

Technical Field

[0001] This invention relates to a method for allocating low-latency hopping beam resources in satellites, and more specifically to a method for allocating low-latency hopping beam resources in low-Earth orbit satellites. Background Technology

[0002] With the continuous growth of internet application demands, the future goal of mobile communication is to provide seamless coverage, improve service reliability, and enhance network scalability. Satellite communication systems, with their wide coverage, large capacity, long transmission distance, high spectrum utilization, and unrestricted geographical environment, effectively address the problems existing in current terrestrial communication systems and have become an important component of the construction and development of integrated space-ground networks. Satellite communication systems can provide communication services such as prediction, prevention, and recovery between remote terminals within a beam for natural disaster communication, as well as satellite multimedia services such as satellite internet, remote learning, and telemedicine. They can also provide broadband connectivity to sparsely populated remote areas and broadcast telecommunications services to a wider geographical area. Based on satellite orbital altitude, satellites are classified into Very Low Earth Orbit (VLEO), Low Earth Orbit (LEO), Medium Earth Orbit (MEO), Geostationary / Geosynchronous Earth Orbit (GEO / GSO), and Highly Elliptical Orbit (HEO). This invention aims to provide a low-latency beam-hopping resource allocation method in LEO satellite scenarios.

[0003] The time-fragmentation mechanism of beam hopping technology changes the fixed resource allocation on satellites in traditional multi-beam systems. Driven by the demand for on-demand services, it meets the diversity of service types and the spatiotemporal unevenness of distribution, increasing system capacity and improving overall system performance, thus becoming a key technology for satellite communication systems. A beam hopping system consists of a network control center, gateways, beam hopping satellites, and various ground user terminals. Utilizing time slicing can effectively improve the utilization efficiency of scarce satellite resources such as bandwidth and power, better meeting the dynamic service needs of users. Simultaneously, beam hopping features spatial isolation and frequency reuse, short beam operating time slots, and flexible system resource scheduling, effectively solving the problem of limited satellite resources.

[0004] Satellite communication systems face significant challenges due to high latency, large Doppler shift, limited satellite platform power, and difficulties in capacity analysis. Furthermore, managing resources such as time, frequency, and power is challenging. Beam hopping technology can flexibly allocate system resources, enabling on-demand coverage for satellite communication systems. However, most current research focuses on improving system capacity while neglecting user latency and quality of service optimization. Therefore, a comprehensive resource allocation scheme that improves both system transmission rate and user latency to enhance user experience requires further investigation. Secondly, inter-beam interference in satellite communication severely impacts communication quality and power allocation. Optimization methods that directly ignore interference are impractical for real-world engineering applications. Therefore, a high-performance, low-complexity, and highly feasible power allocation algorithm is urgently needed. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention proposes a low-latency beam hopping resource allocation method for low-Earth orbit satellites.

[0006] The low-delay beam hopping resource allocation method includes the following steps:

[0007] Step 1. Select the users to be served based on the maximum latency criterion and the serial method;

[0008] Step 2. Considering the possibility of interference between adjacent cells, select the user with the largest delay based on the user with the largest delay and the serial user selection method;

[0009] Step 3. Use a two-stage power allocation method to balance the latency values ​​between different users in order to minimize the maximum latency among all users.

[0010] Further, in step 1, the step of selecting the user to provide services based on the maximum latency criterion and the serial method specifically involves:

[0011] To minimize the maximum delay for each beam hopping period, users are sorted based on the maximum delay criterion. The delay of the nth user at the end of the i-th time slot is expressed as follows (1):

[0012]

[0013] In the above formula, T s The length of each time slot, This represents the remaining traffic volume of the nth user at the end of the (i-1)th time slot, B represents the system beam bandwidth, and N0 represents the noise power spectral density. This indicates the beam allocation situation. If the k-th beam is allocated to the n-th user in the i-th time slot, let... otherwise h nk and These represent channel gain and transmit power, respectively.

[0014] To reduce the latency caused by service transmission in previous time slots, K users with the largest current latency values ​​are selected from all users in each time slot, as shown in the following formula (2):

[0015]

[0016] In equation (2) above, k (K) This refers to the selected user ID.

[0017] Furthermore, in step 2, considering the possibility of interference between adjacent cells, the user with the largest delay is selected based on the user selection method of maximum user delay and serial selection, including the following steps:

[0018] Step 2.1 Select the user with the longest latency among all users;

[0019] Step 2.2 Select user 2 with the largest delay from among the other non-adjacent users;

[0020] Step 2.3 Select user 3 with the longest delay from the other users who are not adjacent to users 1 and 2, and continue until all K users have been selected;

[0021] Step 2.4 Select up to K non-adjacent users, and continue this process until only two adjacent users remain. Serve each user one by one until all users have completed their service or the hop cycle ends, thus concluding this hop beam resource allocation.

[0022] Furthermore, in step 3, the method of balancing the latency values ​​between different users using a two-stage power allocation approach to minimize the maximum latency among all users includes the following steps:

[0023] Step 3.1 Employ the Total Rate Maximization (TRM) algorithm:

[0024] To maximize the total rate of the selected users at each time step, the power allocation is as shown in equation (3):

[0025]

[0026]

[0027]

[0028]

[0029] In equation (3) above: This represents the set of users selected in the current time slot. When the constraints of single-beam power and actual remaining traffic are ignored, the power allocation can be directly solved according to the water-filling theorem (adaptively allocate power; allocate more power when the channel condition is good and less power when the channel condition is poor, in order to maximize the transmission rate). That is, the power allocation is as follows (4):

[0030]

[0031] The constraints of the actual remaining business are transformed into After considering the constraints of single-beam power and actual remaining traffic, the final TRM power allocation is as follows (5):

[0032]

[0033] In equation (5) above:

[0034] Step 3.2 To minimize the maximum queuing delay for all users, the results of the binary power allocation are given through the following steps:

[0035] Step 3.2.1 Initialization: Error threshold ε, power change value Δp, number of users U, current remaining traffic volume under equal power allocation for selected users. and cumulative delay Total power constraint P T Single-beam power constraint P M ;

[0036] Step 3.2.2 Find the set of users whose power allocation is not 0.

[0037] Step 3.2.3 Order

[0038] Step 3.2.4

[0039] Step 3.2.5 Calculate the user latency at this time. and

[0040] Step 3.2.6 If or make And Δp = Δp / 2;

[0041] Step 3.2.7 If Δp > ε, continue with step 3.2.2; otherwise, calculate the remaining traffic under the current power allocation. Continue with step 3.2.8;

[0042] Step 3.2.8 Iterate through the selected users, if Then calculate the power required by the user according to the channel capacity formula. And make

[0043] Step 3.2.9 Iterate through the selected users, if and Then let If P = 0; and Then let

[0044] Step 3.3 Combining user sorting and user selection, the accumulated delay-aware (ADA) power allocation algorithm is used to calculate the accumulated delay of all users after the beam hopping period ends, following these steps:

[0045] Step 3.3.1 Initialization: User business requirements Number of time slots I, maximum number of beams K, user set Total power constraint P T Single-beam power constraint P M , i = 1;

[0046] Step 3.3.2 If i < I+1 and Then, based on the user ranking method based on the maximum delay criterion and the user selection scheme based on serial selection, from the set... Select K users and put them into a set Calculate the remaining traffic under the current power allocation. Continue to step 3.3.3; otherwise, continue to step 3.3.5.

[0047] Step 3.3.3 If Then remove the user from the set Delete the first one and continue to step b); otherwise, let i = i + 1 and continue to step 3.3.4.

[0048] Step 3.3.4 Obtain the power allocation result according to the TRM algorithm. Continue with step 3.3.2;

[0049] Step 3.3.5 If i < I+1 and Then, based on the serial user selection scheme and the user ranking criterion based on the maximum delay criterion, from the set... Select K users and put them into a set Continue to step 3.3.6; otherwise, end this algorithm step.

[0050] Step 3.3.6 uses the binary power allocation algorithm to obtain the following steps: and

[0051] Step 3.3.7 Calculate the remaining traffic volume under the current power allocation. And let i = i + 1, then continue with step 3.3.5.

[0052] The cumulative delay of the nth user after the beam hopping period ends is given by the following formula (6):

[0053]

[0054] In the above formula (6): This represents the initial service requirements of the nth user at the start of the beam hopping cycle.

[0055] Furthermore, in step 3, the two-stage power allocation is cumulative delay-aware power allocation (ADA power allocation), that is, the first stage uses TRM power allocation and the second stage uses binary power allocation.

[0056] The low-delay beam hopping resource allocation method for low-Earth orbit satellites described in this invention has the following superior technical effects:

[0057] 1. The low-latency hopping beam resource allocation method for low-orbit satellites described in this invention uses user queuing delay as the target for power allocation and schedules overall resources, thereby jointly optimizing the consumption of communication resources and the quality of user service.

[0058] 2. The low-latency hopping beam resource allocation method for low-Earth orbit satellites described in this invention fully considers the constraint of total transmission power. Under the consideration of inter-beam interference, it minimizes the maximum cumulative delay among all users in the low-Earth orbit satellite scenario, ensuring fairness among different users.

[0059] 3. Compared with traditional algorithms, the low-latency hopping beam resource allocation method for low-orbit satellites described in this invention can significantly reduce the maximum latency among all users in each hopping beam period, improving user service quality while also ensuring fairness among different users.

[0060] 4. The algorithm proposed in this invention for low-latency hopping beam resource allocation in low-orbit satellites has good performance regardless of the number of cells, the maximum number of working beams, or the total transmission power, and the algorithm has good stability. Attached Figure Description

[0061] Figure 1 This is a graph showing the relationship between maximum user delay and total transmit power under the low-delay beam hopping resource allocation method for low-Earth orbit satellites described in this invention and a control method. Detailed Implementation

[0062] The following is in conjunction with the instruction manual appendix. Figure 1 The specific implementation of the low-delay beam hopping resource allocation method in low-Earth orbit satellites described in this invention is described in detail.

[0063] Example:

[0064] The method for allocating low-latency hopping beam resources in low-Earth orbit satellites includes:

[0065] Step 1. Select the users to be served based on the maximum latency criterion and the serial method;

[0066] To minimize the maximum delay for each beam hopping period, users are sorted based on the maximum delay criterion. The delay of the nth user at the end of the i-th time slot is expressed as follows (1):

[0067]

[0068] In the above formula, T s The length of each time slot, This represents the remaining traffic volume of the nth user at the end of the (i-1)th time slot, B represents the system beam bandwidth, and N0 represents the noise power spectral density. This indicates the beam allocation situation. If the k-th beam is allocated to the n-th user in the i-th time slot, let... otherwise h nk and These represent channel gain and transmit power, respectively.

[0069] To reduce the latency caused by service transmission in previous time slots, K users with the largest current latency values ​​are selected from all users in each time slot, as shown in the following formula (2):

[0070]

[0071] In equation (2) above, k (K) That is, the selected user ID;

[0072] Step 2. Considering the possibility of interference between adjacent cells, select the user with the largest delay based on the user selection method that uses the maximum user delay and the serial user selection method:

[0073] Step 2.1 Select the user with the longest latency among all users;

[0074] Step 2.2 Select user 2 with the largest delay from among the other non-adjacent users;

[0075] Step 2.3 Select user 3 with the longest delay from the other users who are not adjacent to users 1 and 2, and continue until all K users have been selected;

[0076] Step 2.4 Select up to K non-adjacent users until only two adjacent users remain. Serve them one by one until all users have completed service or the hop cycle ends, then end this hop beam resource allocation.

[0077] Step 3. Employ a two-stage power allocation method to balance the latency values ​​among different users, in order to minimize the maximum latency among all users:

[0078] Step 3.1 Employ the Total Rate Maximization (TRM) algorithm:

[0079] To maximize the total rate of the selected users at each time step, the power allocation is as shown in equation (3):

[0080]

[0081]

[0082]

[0083]

[0084] In equation (3) above: This represents the set of users selected in the current time slot. When the constraints of single-beam power and actual remaining traffic are ignored, the power allocation can be directly solved according to the water-filling theorem, i.e., the power allocation is as follows (4):

[0085]

[0086] The constraints of the actual remaining business are transformed into After considering the constraints of single-beam power and actual remaining traffic, the final TRM power allocation is as follows (5):

[0087]

[0088] In equation (5) above:

[0089] Step 3.2 To minimize the maximum queuing delay for all users, the results of the binary power allocation are given through the following steps:

[0090] Step 3.2.1 Initialization: Error threshold ε, power change value Δp, number of users U, current remaining traffic volume under equal power allocation for selected users. and cumulative delay Total power constraint P T Single-beam power constraint P M ;

[0091] Step 3.2.2 Find the set of users whose power allocation is not 0.

[0092] Step 3.2.3 Order

[0093] Step 3.2.4

[0094] Step 3.2.5 Calculate the user latency at this time. and

[0095] Step 3.2.6 If or make And Δp = Δp / 2;

[0096] Step 3.2.7 If Δp > ε, continue with step 3.2.2; otherwise, calculate the remaining traffic under the current power allocation. Continue with step 3.2.8;

[0097] Step 3.2.8 Iterate through the selected users, if Then calculate the power required by the user according to the channel capacity formula. And make

[0098] Step 3.2.9 Iterate through the selected users, if and Then let If P = 0; and Then let

[0099] Step 3.3 Combining user sorting and user selection, the accumulated delay-aware (ADA) power allocation algorithm is used to calculate the accumulated delay of all users after the beam hopping period ends, following these steps:

[0100] Step 3.3.1 Initialization: User business requirements Number of time slots I, maximum number of beams K, user set Total power constraint P T Single-beam power constraint P M , i = 1;

[0101] Step 3.3.2 If i < I+1 and Then, based on the user ranking method based on the maximum delay criterion and the user selection scheme based on serial selection, from the set... Select K users and put them into a set Calculate the remaining traffic under the current power allocation. Continue to step 3.3.3; otherwise, continue to step 3.3.5.

[0102] Step 3.3.3 If Then remove the user from the set Delete the first one and continue to step b); otherwise, let i = i + 1 and continue to step 3.3.4.

[0103] Step 3.3.4 Obtain the power allocation result according to the TRM algorithm. Continue with step 3.3.2;

[0104] Step 3.3.5 If i < I+1 and Then, based on the serial user selection scheme and the user ranking criterion based on the maximum delay criterion, from the set... Select K users and put them into a set Continue to step 3.3.6; otherwise, end this algorithm step.

[0105] Step 3.3.6 uses the binary power allocation algorithm to obtain the following steps: and

[0106] Step 3.3.7 Calculate the remaining traffic volume under the current power allocation. And let i = i + 1, continue with step 3.3.5, then the cumulative delay of the nth user after the beam hopping period ends is given by the following formula (6):

[0107]

[0108] In the above formula (6): This represents the initial service requirements of the nth user at the start of the beam hopping cycle.

[0109] Furthermore, in step 3, the two-stage power allocation is cumulative delay-aware power allocation (ADA power allocation), that is, the first stage uses TRM power allocation and the second stage uses binary power allocation.

[0110] refer to Figure 1 , Figure 1 This paper illustrates the relationship between the maximum user delay and total transmit power under the low-latency beam-hopping resource allocation method for low-Earth orbit satellites described in this invention and a comparative scheme. In comparative scheme 1, inter-beam interference is ignored, the maximum delay criterion is directly used when selecting users, and interference is not considered in the simulation. In comparative scheme 2, inter-beam interference is included in the simulation without considering system inter-beam interference. It can be seen that, given the number of cells and the maximum number of beams, the maximum user delay gradually decreases as the total transmit power of the satellite increases; on the other hand, according to... Figure 1 It can be seen that the low-latency hopping beam resource allocation method in low-orbit satellites described in this invention, through beam combination scheduling or user selection and power allocation, greatly avoids interference and significantly reduces the maximum latency for users.

[0111] This invention is not limited to the above-described embodiments. Any modifications, improvements, or substitutions that can be conceived by those skilled in the art without departing from the essential content of this invention fall within the protection scope of this invention.

Claims

1. A low-delay beam hopping resource allocation method, characterized in that, Includes the following steps: Step 1. Select the users to be served based on the maximum latency criterion and the serial method: To minimize the maximum delay for each hop beam cycle, users are sorted based on the maximum delay criterion. The delay of the nth user at the end of the i-th time slot is expressed as follows (1): ......(1), In the above formula, T s The length of each time slot, This represents the remaining traffic volume of the nth user at the end of the (i-1)th time slot, B represents the system beam bandwidth, and N0 represents the noise power spectral density. This indicates the beam allocation situation. If the k-th beam is allocated to the n-th user in the i-th time slot, let... ,otherwise ; and These represent channel gain and transmit power, respectively. To reduce the latency caused by service transmission in previous time slots, K users with the largest current latency values ​​are selected from all users in each time slot, as shown in the following formula (2): .......（2）, In the above formula (2), That is, the selected user ID; Step 2. Considering the possibility of interference between adjacent cells, select the user with the largest delay based on the user selection method that uses the maximum user delay and the serial user selection method: Step 2.1 Select the user with the longest latency among all users; Step 2.2 Select user 2 with the largest delay from among the other non-adjacent users; Step 2.3 Select user 3 with the longest delay from the other users who are not adjacent to users 1 and 2, and continue until all K users have been selected; Step 2.4 Select no more than K non-adjacent users until only two adjacent users remain. Serve them one by one until all users have completed service or the hop cycle ends, then end this hop beam resource allocation. Step 3. Use a two-stage power allocation method to balance the latency values ​​between different users in order to minimize the maximum latency among all users.

2. The low-delay beam hopping resource allocation method according to claim 1, characterized in that, Step 3 The method of balancing latency values ​​among different users using a two-stage power allocation approach to minimize the maximum latency among all users includes the following steps: Step 3.1 Employ the total transmission rate maximization algorithm: To maximize the total rate of the selected users at each time step, the power allocation is as shown in equation (3): ......(3)， In the above formula (3): This represents the set of users selected in the current time slot. When the constraints of single-beam power and actual remaining traffic are ignored, the power allocation can be directly solved according to the water-filling theorem, i.e., the power allocation is as follows (4): ......(4)， The constraints of the actual remaining business are transformed into Considering the constraints of single-beam power and actual remaining service, the final TRM power allocation is as follows (5): ......(5)， In the above formula (5): ; Step 3.2 To minimize the maximum queuing delay for all users, the results of the binary power allocation are given through the following steps: Step 3.2.1 Initialization: Error threshold ε, power change value Δp, number of users U, current remaining traffic volume under equal power allocation for selected users. and cumulative delay Total power constraint Single-beam power constraint ; Step 3.2.2 Find the set of users whose power allocation is not zero. ; Step 3.2.3 Let , ; Step 3.2.4 , ; Step 3.2.5 Calculate the user latency at this time. and ; Step 3.2.6 If or ,make , and ; Step 3.2.7 If Continue to step 3.2.2; otherwise, calculate the remaining traffic under the current power allocation. Continue with step 3.2.8; Step 3.2.8 Iterate through the selected users, if Then, the power required by the user is calculated according to the channel capacity formula. And make , ; Step 3.2.9 Iterate through the selected users, if and Then let , ;like and Then let , ; Step 3.3 Combining user sorting and user selection, the cumulative delay-aware power allocation algorithm is used to calculate the cumulative delay of all users after the beam hopping period ends, following these steps: Step 3.3.1 Initialization: User business requirements Number of time slots I, maximum number of beams K, user set Total power constraint Single-beam power constraint , , , ; Step 3.3.2 If and Then, based on the user ranking method based on the maximum delay criterion and the user selection scheme based on serial selection, from the set... Select K users and put them into a set Calculate the remaining traffic volume under the current power allocation. If yes, proceed to step 3.3.3; otherwise, proceed to step 3.3.

5. Step 3.3.3 If Then remove the user from the set. Delete it and continue to step 3.3.2; otherwise, let Proceed to step 3.3.4; Step 3.3.4 Obtain the power allocation result based on the TRM algorithm. Continue with step 3.3.2; Step 3.3.5 If and Then, based on the user selection scheme based on serial selection and the user ranking criterion based on the maximum delay criterion, the user is selected from the set. Select K users and put them into a set If not, continue to step 3.3.6; otherwise, end this algorithm step. Step 3.3.6 Obtain the power allocation using the bisection algorithm. and ; Step 3.3.7 Calculate the remaining traffic volume under the current power allocation. And make Continue with step 3.3.

5. The cumulative delay of the nth user after the beam hopping period ends is given by the following formula (6): ......(6）， In the above formula (6): This represents the initial service requirements of the nth user at the start of the beam hopping cycle.

3. The low-delay beam hopping resource allocation method according to claim 1, characterized in that, In step 3, the two-stage power allocation is that the first stage uses TRM power allocation and the second stage uses binary power allocation.

Images