Transmission link selection method and system based on statistical QoS (Quality of Service)

Abstract

The invention discloses a statistical QoS (Quality of Service)-based transmission link selection method and system, and the method comprises the following steps: constructing a multi-service transmission link selection scene, constructing communication terminal services with different service quality requirements in the scene, and supporting different types of network resources; the maximum reachable rate is calculated according to different service types, and then the effective capacity of the service is obtained; according to the current service type, a network transmission link j with the maximum effective capacity ECi is selected for transmission; the system comprises a high-orbit satellite, a low-orbit satellite and a plurality of communication terminals, and a single communication terminal sends a plurality of traffic flows. According to the method, the statistical QoS requirements of different services can be considered, different application scenes are adapted by adjusting the statistical QoS constraints of different service types, the requirements of various services are flexibly met, and environmental changes are dynamically adapted.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a transmission link selection method based on statistical QoS and a system thereof. Background Art

[0002] With the rapid development of communication technology, communication systems have gradually shown high data demand and diversified application scenarios. In particular, with the support of multiple network environments such as 5G, satellite communications and Wi-Fi, the performance and coverage of communication networks have been significantly improved. However, due to the significant differences in the demand for transmission resources for different business types, achieving efficient resource allocation has become a key problem in the optimization design of communication systems.

[0003] With the development of new communication systems, the demand for flexible, efficient and random access of multiple subjects is becoming increasingly urgent. The current mainstream ground-based communication methods (such as optical fiber communication networks, wireless public networks, wireless private networks, etc.) have problems such as large line operation and maintenance workload, fixed communication that cannot be flexibly switched, and susceptibility to damage by natural disasters such as earthquakes. It is also difficult to achieve full coverage, especially for services in blind areas of communication network coverage. Due to the long-term inability to access the network, business data cannot be transmitted in time. At this time, satellite communication technology, which is less affected by disasters and can achieve wide-area coverage, will become an important supplement. However, due to the diversity of business types, the time-varying nature of wireless communication environments, and the complexity of satellite communication technology, the traditional single indicator adaptation method is no longer applicable. Summary of the invention

[0004] Purpose of the invention: The purpose of the present invention is to provide a transmission link selection method and system based on statistical QoS.

[0005] Technical solution: The transmission link selection method based on statistical QoS described in the present invention comprises the following steps:

[0006] (1) constructing a multi-service transmission link selection scenario, constructing communication terminal services with different service quality requirements in the scenario, and supporting different types of network resources;

[0007] (2) Calculate the maximum achievable rate based on different service types, and then derive the effective capacity of the service;

[0008] (3) Select the effective capacity EC according to the current business type i The largest network transmission link j is used for transmission.

[0009] Furthermore, the network resources in step (1) include satellite network, 5G network and Wi-Fi network.

[0010] Furthermore, the step (1) comprises:

[0011] (1.1) Define the service flow i∈{1, 2, ..., I} transmitted by the current communication terminal, and the network transmission link j∈{1, 2, ..., J}; define the binary variable λ ij ={0,1},λ ij =1 means that network resource j is selected for transmission for service i, two service types are defined, and the bandwidth of network transmission link j is defined as B j , power is P j ;

[0012] (1.2) When λ ij =1, the channel gain is Z ij , the signal-to-noise ratio γ of the communication terminal transmission service flow i on the network transmission link j ij , which can be expressed as:

[0013]

[0014] Among them, B ij and P ij They represent the bandwidth and power allocated to service flow i by network transmission link j at this time, represents the noise of network transmission link j.

[0015] Furthermore, the two types of services in step (1.1) include Q1 type services and Q2 type services, and the Q1 type services only have a delay constraint θ i and rate constraint R i , Q2 type of business also has a delay constraint θ i , reliability constraint, i.e. bit error rate ε i and rate constraint R i .

[0016] Furthermore, the step (2) calculates the maximum achievable rates of two types of services, including Q1 type services and Q2 type services, and then obtains the effective capacity of the services.

[0017] Furthermore, the step (2) comprises:

[0018] (2.1) The maximum achievable rate of service i belonging to type Q1 is defined as:

[0019]

[0020] The effective capacity of service i of type Q1 can be calculated as:

[0021]

[0022] Effective capacity is defined as the maximum constant arrival rate that a service can support while meeting given quality of service requirements; Represents the random variable γ ij expectations;

[0023] (2.2) The maximum achievable rate of service i belonging to type Q2 is defined as:

[0024]

[0025] Among them, l represents the code length of the short packet, C(γ ij ) and V(γ ij ) are respectively expressed as channel capacity and channel dispersion, which are defined as:

[0026]

[0027] The effective capacity of service i of type Q2 is calculated as:

[0028]

[0029] Furthermore, the step (3) comprises:

[0030] (3.1) The optimization problem is defined as service i selects the effective capacity EC while meeting the statistical QoS requirements. ij The largest network j is used for transmission, and the optimization goal is to maximize the effective capacity of all services of the current terminal, which is defined as:

[0031]

[0032] Among them, R i，th is the rate threshold, C(γ ij ) and V(γ ij ) are respectively represented as channel capacity and channel dispersion;

[0033] (3.2) Use heuristic algorithms or reinforcement learning to solve the optimization problem, which is a mixed integer programming problem.

[0034] Furthermore, the heuristic algorithm in step (3.2) adopts a genetic algorithm.

[0035] Furthermore, the constraints of step (3.1) include: rate constraints, where R i，th The constraints are rate threshold, total transmission power constraint of each access network, total bandwidth constraint of different network transmission links, and restriction on selecting one network transmission link for each service flow.

[0036] Furthermore, the transmission link system based on statistical QoS includes a high-orbit satellite, a low-orbit satellite and multiple communication terminals. A single communication terminal sends multiple service flows. Through the transmission link selection method, each service flow is selectively allocated to multiple network resources of high-orbit satellites and low-orbit satellites, and corresponding power and bandwidth are allocated to each service flow to maximize the total effective capacity of the terminal.

[0037] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages:

[0038] The communication terminal of the present invention can access multiple network transmission links such as 5G, Wi-Fi, satellite, etc., providing extensive and stable communication support for the communication system. It allows flexible switching between different network transmission links to adapt to the specific requirements of different services for power, bandwidth, latency and reliability, which not only helps to improve the reliability and security of multiple service access networks, but also can effectively avoid the waste of resources and insufficient coverage of communication blind spots.

[0039] The present invention uses effective capacity to measure the maximum constant packet arrival rate that a service flow can achieve when the transmission service meets the statistical QoS requirements. It can take into account the statistical QoS requirements of different services, and adapt to different application scenarios by adjusting the statistical QoS constraints of different service types, such as delay default probability, bit error rate, etc., to flexibly meet the needs of various services and dynamically adapt to environmental changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of a multi-service transmission link system of the present invention;

[0041] Figure 2 It is a curve diagram showing the change of total effective capacity of communication terminals along with the change of service quality index. DETAILED DESCRIPTION

[0042] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0043] The transmission link selection method based on statistical QoS of the present invention comprises the following steps:

[0044] (1) Construct a multi-service transmission link selection scenario, in which communication terminal services with different service quality requirements are constructed and different types of network resources are supported; the network resources include satellite networks, 5G networks, and Wi-Fi networks.

[0045] (1.1) Define the service flow i∈{1, 2, ..., I} transmitted by the current communication terminal, and the network transmission link j∈{1, 2, ..., J}; define the binary variable λ ij ={0,1},λ ij=1 means that network resource j is selected for transmission for service i, two service types are defined, and the bandwidth of network transmission link j is defined as B j , power is P j ; The two types of services include Q1 type services and Q2 type services. The Q1 type service has only the delay constraint θ i and rate constraint R i , Q2 type of business also has a delay constraint θ i , reliability constraint, i.e. bit error rate ε i and rate constraint R i .

[0046] (1.2) When λ ij =1, the channel gain is Z ij , the signal-to-noise ratio γ of the communication terminal transmission service flow i on the network transmission link j ij , which can be expressed as:

[0047]

[0048] Among them, B ij and P ij They represent the bandwidth and power allocated to service flow i by network transmission link j at this time, represents the noise of network transmission link j.

[0049] (2.1) The maximum achievable rate of service i belonging to type Q1 is defined as:

[0050]

[0051] The effective capacity of service i of type Q1 can be calculated as:

[0052]

[0053] Effective capacity is defined as the maximum constant arrival rate that a service can support while meeting given quality of service requirements; Represents the random variable γ ij expectations;

[0054] (2.2) The maximum achievable rate of service i belonging to type Q2 is defined as:

[0055]

[0056] Among them, l represents the code length of the short packet, C(γ ij ) and V(γ ij ) are respectively expressed as channel capacity and channel dispersion, which are defined as:

[0057]

[0058] The effective capacity of service i of type Q2 is calculated as:

[0059]

[0060] (3.1) The optimization problem is defined as service i selects the effective capacity EC while meeting the statistical QoS requirements. ij The largest network j is used for transmission, and the constraints include: rate constraint, where R i，th is the rate threshold; the total transmission power constraint of each access network; the total bandwidth constraint of different network transmission links; and the restriction that each service flow selects a network transmission link. The optimization goal is to maximize the effective capacity of all services of the current terminal, which is defined as:

[0061]

[0062] Among them, R i，th is the rate threshold, C(γ ij ) and V(γ ij ) are respectively represented as channel capacity and channel dispersion;

[0063] (3.2) Use heuristic algorithms or reinforcement learning to solve the optimization problem, which is a mixed integer programming problem, and the heuristic algorithm uses a genetic algorithm.

[0064] like Figure 1 As shown, the transmission link system based on statistical QoS described in the present invention includes a high-orbit satellite, a low-orbit satellite and multiple communication terminals. A single communication terminal sends multiple service flows. Through the transmission link selection method, each service flow is selectively allocated to a variety of network resources of the high-orbit satellite and the low-orbit satellite, and corresponding power and bandwidth are allocated to each service flow to maximize the total effective capacity of the terminal.

[0065] The communication terminal can send multiple service flows with different statistical QoS requirements, and support simultaneous access to high-orbit satellites, low-orbit satellites, 5G networks and Wi-Fi networks. Based on the service quality requirements, the communication terminal can flexibly allocate different service flows to different networks for transmission, thereby improving the total effective capacity of the communication terminal.

[0066] like Figure 2 The figure shows the change of the total effective capacity of the communication terminal in the example of the present invention under different QoS indicators. The scheme proposed by the present invention adopts a genetic algorithm to solve the optimization problem, and the random network access scheme and the fixed network access scheme are used as comparison schemes. In the random network access scheme, the terminal service is randomly selected as follows Figure 1 Any of the networks shown is used for transmission; in the fixed network access solution, services of type choose 5G network for transmission, while services of type use Wi-Fi network for transmission.

[0067] In the transmission link system, the Q1 type and Q2 type services are both set to 4. The maximum allocated power of high-orbit satellites, low-orbit satellites, 5G networks, and Wi-Fi networks are 20W, 10W, 1W, and 0.5W, respectively, and the maximum allocatable bandwidths are 200MHz, 100MHz, 100MHz, and 40MHz, respectively. th Both are set to 0.1Mbits / sec, and the bit error rate∈ is required to be 0.001.

[0068] like Figure 2 As shown, it can be observed that as the service quality index requirements become more stringent, the total effective capacity of the three solutions all show a downward trend. This trend is consistent with the calculation principle of effective capacity. In addition, the multi-network access solution proposed in the present invention shows a significant advantage in total effective capacity compared with the comparative solution, reflecting its superiority in optimizing the utilization rate of communication terminal network resources.

Claims

1. A transmission link selection method based on statistical QoS, characterized in that: The method comprises the following steps: (1) constructing a multi-service transmission link selection scenario, constructing communication terminal services with different service quality requirements in the scenario, and supporting different types of network resources; (2) Calculate the maximum achievable rate based on different service types, and then derive the effective capacity of the service; (3) Select the effective capacity EC according to the current business type i The largest network transmission link j is used for transmission.

2. The transmission link selection method based on statistical QoS according to claim 1, characterized in that: The network resources in step (1) include satellite network, 5G network and Wi-Fi network.

3. The transmission link selection method based on statistical QoS according to claim 1, characterized in that: The step (1) comprises: (1.1) Define the service flow i∈{1, 2, ..., I} transmitted by the current communication terminal, and the network transmission link j∈{1, 2, ..., J}; define the binary variable λ ij ={0,1},λ ij =1 means that network resource j is selected for transmission for service i, two service types are defined, and the bandwidth of network transmission link j is defined as B j , power is P j ; (1.2) When λ ij =1, the channel gain is Z ij , the signal-to-noise ratio γ of the communication terminal transmission service flow i on the network transmission link j ij , which can be expressed as: Among them, B ij and P ij They represent the bandwidth and power allocated to service flow i by network transmission link j at this time, represents the noise of network transmission link j.

4. The transmission link selection method based on statistical QoS according to claim 1, characterized in that: The two types of services in step (1.1) include Q1 type services and Q2 type services. The Q1 type services only have a delay constraint θ i and rate constraint R i , Q2 type of business also has a delay constraint θ i , reliability constraint, i.e. bit error rate ε i and rate constraint R i .

5. The transmission link selection method based on statistical QoS according to claim 1, characterized in that: The step (2) calculates the maximum achievable rates of two types of services, including Q1 type services and Q2 type services, and then obtains the effective capacity of the services.

6. The transmission link selection method based on statistical QoS according to claim 1, characterized in that: The step (2) comprises: (2.1) The maximum achievable rate of service i belonging to type Q1 is defined as: The effective capacity of service i of type Q1 can be calculated as: Effective capacity is defined as the maximum constant arrival rate that a service can support while meeting given quality of service requirements; Represents the random variable γ ij expectations; (2.2) The maximum achievable rate of service i belonging to type Q2 is defined as: Among them, l represents the code length of the short packet, C(γ ij ) and V(γ ij ) are respectively expressed as channel capacity and channel dispersion, which are defined as: The effective capacity of service i of type Q2 is calculated as:

7. The transmission link selection method based on statistical QoS according to claim 1, characterized in that: The step (3) comprises: (3.1) The optimization problem is defined as service i selects the effective capacity EC while meeting the statistical QoS requirements. ij The largest network j is used for transmission, and the optimization goal is to maximize the effective capacity of all services of the current terminal, which is defined as: s.t.R i ≥R i，th Among them, R i，th is the rate threshold, C(γ ij ) and V(γ ij ) are respectively represented as channel capacity and channel dispersion; (3.2) Use heuristic algorithms or reinforcement learning to solve the optimization problem, which is a mixed integer programming problem.

8. The transmission link selection method based on statistical QoS according to claim 1, characterized in that: The heuristic algorithm of step (3.2) adopts genetic algorithm.

9. The transmission link selection method based on statistical QoS according to claim 1, characterized in that: The constraints of step (3.1) include: rate constraint; total transmission power constraint of each access network; total bandwidth constraint of different network transmission links; and restriction on each service flow to select one network transmission link.

10. The link system of the transmission link selection method based on statistical QoS according to any one of claims 1 to 9, characterized in that: It includes high-orbit satellites, low-orbit satellites and multiple communication terminals. A single communication terminal sends multiple service flows. Through the transmission link selection method, each service flow is selectively allocated to multiple network resources of high-orbit satellites and low-orbit satellites, and corresponding power and bandwidth are allocated to each service flow to maximize the total effective capacity of the terminal.

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