CN113726374B - Long-short period complementary multi-beam satellite bandwidth allocation method - Google Patents
Long-short period complementary multi-beam satellite bandwidth allocation method Download PDFInfo
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Abstract
The invention discloses a long-period and short-period complementary multi-beam satellite bandwidth allocation method, which utilizes the self-similarity of satellite network flow in a long period and the increase and decrease retentivity of the satellite network flow in a short period, namely the characteristic that the satellite network flow keeps continuous increase or decrease in a shorter time scale, and designs a new long-period and short-period cooperative resource allocation method. Therefore, the communication quality of the satellite in long service time is effectively ensured, the utilization rate of the limited bandwidth resource of the satellite is improved, and the communication experience of a user is increased. Compared with the existing scheme of fixed pre-allocation, dynamic allocation and the combination of fixed pre-allocation and dynamic allocation, the scheme can more effectively reduce the blocking rate, improve the supply-demand ratio of the system and improve the communication experience of users. Meanwhile, the scheme is low in complexity, less in consumed computing resources, and after historical traffic information and the current service request are known, long-period requirements and requirements at the current moment can be quickly balanced to form a bandwidth allocation scheme.
Description
Technical Field
The invention relates to a bandwidth allocation scheme of a multi-beam satellite multi-user space-ground communication system, belonging to the technical field of wireless resource allocation in wireless communication.
Background
With the continuous advancement of global informatization and the continuous expansion of human activity range, the existing ground base station communication cannot completely meet the current communication demand. Thus, satellite communication is becoming an important means of communication in mountainous areas, oceans, and emergency relief. In order to further improve the satellite communication quality, guarantee the communication experience of users in special environments and improve the utilization rate of limited satellite resources, improvement of the bandwidth allocation scheme of the existing multi-beam satellite is urgently needed. The existing satellite bandwidth allocation scheme mainly focuses on allocation for the current situation, and the short-term situation exists in the allocation scheme, so that the communication quality of the satellite in the service time in a long period is difficult to guarantee.
The traffic change of the satellite network has own regularity, and the existing bandwidth allocation scheme does not fully utilize the change law of the satellite network traffic, so that the self-similarity of the satellite network traffic on a long period, namely the average change level of the satellite network traffic on the long period is similar to the average change level in a short period, and the increase and decrease retentivity of the satellite network traffic on a short period, namely the characteristic that the satellite network traffic keeps continuous increase or decrease on a short time scale can be utilized. As shown in fig. 1, in a space-earth communication network formed by a multi-beam satellite, network traffic of the satellite has self-similarity in a long period, and keeps increasing or decreasing in a short period.
With the use of satellite communication being more and more, the communication quality of satellite communication is more and more important, and the requirement of users on the bandwidth provided by the satellite system and the blocking rate of service access is higher and higher, which is in serious conflict with the limited bandwidth resource of the satellite system. Therefore, it becomes important how to fully utilize the limited resources of the satellite system, how to guarantee the communication quality in a long period, and how to make a better distribution scheme by using the existing software and hardware conditions.
For the scheme of allocating bandwidth for the satellite system, the conventional scheme is a fixed pre-allocation scheme, that is, the same bandwidth is fixedly allocated to each beam, and then the unused bandwidth is recovered according to the actual requirement. However, this scheme lacks flexibility and does not match user requests well. Liu et al, moreover, in the article "Research on satellite communication resource allocation algorithm Learning" based on Reinforcement Learning[1]The dynamic allocation scheme is proposed, namely, a reinforced learning algorithm is used according to the actual service request conditionDifferent sizes of bandwidth are allocated to the beams, but the scheme only considers the current time and does not consider the influence on the future. Fei Zheng et al, Leo Satellite Channel Allocation Scheme Based on Reinforcement Learning[2]The method proposes a scheme combining fixed pre-allocation and dynamic allocation, namely allocating a fixed bandwidth to each beam first, and then adjusting the bandwidth of each beam according to actual requirements. But this scheme does not take into account the effect of fixed pre-allocation pairing dynamic allocation.
Therefore, these schemes can only obtain a locally optimal solution, resulting in degradation of communication quality over a long period. Therefore, the method and the device utilize the historical records of satellite network flow to predict in a long period, and utilize the short-term change trend of satellite beam flow to distribute and adjust the bandwidth, thereby improving the supply-demand ratio (bandwidth supply and actual demand ratio) of the system, reducing the blocking rate of request service, enabling a bandwidth distribution algorithm to be more matched with the actual demand, and being capable of taking into account the influence on future service requests.
Disclosure of Invention
The invention aims to provide a bandwidth allocation method suitable for a multi-beam satellite multi-user space-ground communication system, which aims to predict a long period by using a historical record of satellite network flow and allocate and adjust bandwidth by using a short-term change trend of the satellite beam flow so as to ensure the communication quality of a satellite in the long period, improve the bandwidth supply-demand ratio of a satellite system and reduce the blocking rate of user service requests.
Suppose a satellite system has a number of beams of K (numbered 1,2, …, K), a number of communication resource blocks of N (numbered 1,2, …, N) (the total bandwidth is divided into small blocks of fixed size and constitutes a communication resource block with other on-board satellite resources), and a size of a communication resource block of Bch. The number of communication resource blocks needed by the kth wave beam at the time t is
Has a power of
Has an antenna gain of
Having a common frequency interference of
Having a Gaussian white noise of δ2The long period duration is 10ms, and the short-term scheduling duration is 1 ms.
S1 performs long-period bandwidth prediction on the kth beam using a heler moving average with a moving period T. Predicted long period bandwidth demand of kth beam at time t
The calculation method of (c) is as follows:
s2 pre-allocates the communication resource blocks to the beams using the predicted number of communication resource blocks for a long period. The communication resource blocks required for the beam are calculated as follows:
the pre-allocation method using the predicted value of the number of communication resource blocks in a long period is as follows: when available communication resource blocks still exist, distributing the communication resource blocks according to the predicted values, otherwise, finishing distribution;
the method for responding to the user request by the S3 multi-beam satellite is as follows:
and when the allocated bandwidth meets the bandwidth required by the user request, accessing the user request and recording the number of the worked communication resource blocks and the number of the non-worked communication resource blocks, otherwise, accessing the user request according to the number of the allocated communication resource blocks and recording the number of the communication resource blocks required by the non-accessed user request.
S4 schedules unused communication resource blocks of each beam using short term traffic trends. Flow trend factor of kth beam at time t
The calculation is as follows:
the bandwidth priority assignment of the kth beam at time t is calculated as:
s5 for short-term scheduling of unused communication resource blocks, we use a modified Q-learning algorithm for decision making. The state of the Q learning algorithm is (the number of unused communication resource blocks of the beam, the number of communication resource blocks required for a beam-unaccessed user request, and the bandwidth priority assignment of the beam), and the Q learning algorithm acts to schedule an unused communication resource block of a certain beam.
The method of S6 for scheduling unused bandwidth according to short-term traffic trends is as follows:
initializing a Q table, wherein the number of times of initialization training epicode is 10000, the initialization random probability is 0.1, the learning rate is 0.01, and the discount rate is 0.99;
when the system has unaccessed users and unused communication resource blocks exist in each wave beam, randomly selecting actions or selecting actions according to a Q table; if the actions are selected randomly, when the training times are less than half, counting the times of each action, wherein the larger the times, the smaller the probability of selection, and otherwise, selecting the action by using the same probability; if the action is selected according to the Q table, the action with the maximum Q value is selected; allocating the unused communication resource blocks of the beam represented by the action to the beam with the maximum priority; updating the Q value of the state of the Q table; when no unaccessed user exists in the system or no unused communication resource block exists in each wave beam, adding one to the value of the epsilon; if the epicode is 10000, ending the training;
s7 scheduling unused communication resource blocks according to the trained Q table
The key points of the invention are as follows: by utilizing the self-similarity of the satellite network traffic on a long period and utilizing the short-term increase and decrease retentivity of the satellite network traffic, namely the characteristic that the satellite network traffic keeps continuously increasing or decreasing on a short time scale, a new resource allocation method with long-term and short-term coordination is designed. Therefore, the communication quality of the satellite in long-term service time is effectively guaranteed, the utilization rate of the satellite priority bandwidth resource is improved, and the communication experience of users is increased.
The invention has the following effects:
compared with the existing scheme of fixed pre-allocation, dynamic allocation and the combination of fixed pre-allocation and dynamic allocation, the scheme can more effectively reduce the blocking rate, improve the supply-demand ratio of the system and improve the communication experience of users. Meanwhile, the scheme is low in complexity, less in consumed computing resources, and after historical traffic information and the current service request are known, long-period requirements and requirements at the current moment can be quickly balanced to form a bandwidth allocation scheme.
Drawings
Figure 1 is a diagram of a multi-beam satellite earth-ground communications network and its traffic variation.
Figure 2 algorithm flow chart.
Fig. 3 is a graph comparing the blocking rates of different schemes.
FIG. 4 is a comparison graph of the supply-demand ratio of different schemes.
Detailed Description
The scheme is applied to the space-ground communication system shown in figure 1, the multi-beam satellite height is 500km, the maximum transmission rate of the satellite is 1000Mbps, and the satellite beams are 10. The simulation process randomly generates the number of users according to the poisson process, the total service requests of the users are increased along with time, and the load of the simulated satellite gradually exceeds the load of the system from the load of the system along with the time.
Under the simulation conditions, the example simulates the satellite system to obtain the supply-demand ratio and the blocking rate of the system under different loads, and compares the performance of the scheme with the scheme of dynamic allocation, fixed pre-allocation and combination of the fixed pre-allocation and the dynamic allocation. Fig. 3 and 4 are comparison between the present patent and other embodiments. Fig. 3 shows a comparison of blocking rates of the present patent and other solutions, which shows that the present patent can avoid the situation of traffic blocking when the total traffic request does not exceed the maximum load of the system, and can effectively reduce the situation of traffic blocking when the total user request exceeds the maximum load of the system. Fig. 4 shows the comparison between the supply and demand ratios of the present patent and other patents, and it can be seen that the present patent can maintain the higher supply and demand ratio than other schemes.
Reference documents:
[1]Z.Liu.Research on satellite communication resource allocation algorithm based on Reinforcement Learning[J].Mobile Communication,2019,2019.
[2]Zheng F,Pi Z,Zhou Z,et al.LEO Satellite Channel Allocation Scheme Based on Reinforcement Learning[J].Mobile Information Systems,2020,2020.
Claims (1)
1. a multi-beam satellite bandwidth allocation method with complementary long and short periods is characterized in that: assume that the satellite system has a number of beams K, numbered 1,2, …, K, a number of communication resource blocks N, and a size of the communication resource blocks BchThe number of communication resource blocks needed by the kth wave beam at the time t is
Has a power of
Has an antenna gain of
Having a common frequency interference of
Having a white Gaussian noise of δ2The duration of the long period is 10ms, the duration of the short-term scheduling is 1ms,
s1 using the moving period T of the Hell moving average to make long period bandwidth prediction for the kth beam, the predicted long period bandwidth demand of the kth beam at the time T
The calculation of (c) is as follows:
s2 pre-allocates communication resource blocks to the beam using the predicted number of communication resource blocks with a long period, where the communication resource blocks required by the beam are calculated as follows:
the pre-allocation method using the predicted value of the number of communication resource blocks in a long period is as follows: when available communication resource blocks still exist, distributing the communication resource blocks according to the predicted values, otherwise, finishing distribution;
the method for responding to the user request by the S3 multi-beam satellite is as follows:
when the allocated bandwidth meets the bandwidth required by the user request, accessing the user request and recording the number of the working communication resource blocks and the number of the non-working communication resource blocks, otherwise accessing the user request according to the number of the allocated communication resource blocks and recording the number of the communication resource blocks required by the non-access user request,
s4 scheduling unused communication resource blocks of each beam using short-term traffic trends, the traffic trend factor of the kth beam at time t
The calculation is as follows:
the bandwidth priority assignment of the kth beam at time t is calculated as:
s5, for scheduling short-term unused communication resource blocks, we use the modified Q learning algorithm to make a decision, wherein the Q learning algorithm is in the state of scheduling unused communication resource blocks of a certain beam, the number of communication resource blocks required for a beam unaccessed user request, the bandwidth priority allocation of the beam, the Q learning algorithm acts to schedule unused communication resource blocks of a certain beam,
s6 the method for scheduling unused bandwidth according to short-term traffic trends is as follows:
initializing a Q table, wherein the number of times of initialization training epicode is 10000, the initialization random probability is 0.1, the learning rate is 0.01, and the discount rate is 0.99;
when the system has the non-access user and each wave beam has the non-use communication resource block, randomly selecting the action or selecting the action according to the Q table; if the actions are selected randomly, when the training times are less than half, counting the times of each action, wherein the larger the times, the smaller the probability of selection, and otherwise, selecting the action by using the same probability; if the action is selected according to the Q table, the action with the maximum Q value is selected; allocating the unused communication resource blocks of the beam represented by the action to the beam with the maximum priority; updating the Q value of the state of the Q table; when no unaccessed user exists in the system or no unused communication resource block exists in each wave beam, adding one to the value of the epsilon; if the epicode is 10000, ending the training;
s7 scheduling unused communication resource blocks according to the trained Q table
By utilizing the self-similarity of the satellite network flow in a long period and the increase and decrease retentivity of the satellite network flow in a short period, namely the characteristic that the satellite network flow keeps continuously increasing or decreasing in a short time scale, a new resource allocation method with long-term and short-term cooperation is designed, the communication quality of the satellite in long-term service time is ensured, the utilization rate of satellite priority bandwidth resources is improved, and the communication experience of users is improved.
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