CN-121985344-A - Intelligent communication reliable transmission and resource optimization method and device for super-dense networking

CN121985344ACN 121985344 ACN121985344 ACN 121985344ACN-121985344-A

Abstract

The invention discloses a reliable transmission and resource optimization method and device for intelligent communication of an ultra-dense networking, the method comprises the steps of establishing an architecture and a topology model of the ultra-dense networking system, establishing an ultra-dense networking communication model, designing an orthogonal strategy and an interference suppression mechanism, establishing an optimization problem with information age minimization as an objective function, decomposing the optimization problem into a limited main problem and a pricing sub-problem and solving the problem to obtain a limited main problem resource allocation result and a pricing sub-problem negative cost path result, establishing a redundant backup resource optimization algorithm based on a column generation algorithm frame based on the limited main problem resource allocation result and the pricing sub-problem negative cost path result, executing the redundant backup resource optimization algorithm based on the column generation algorithm frame, outputting the optimization result, and issuing a main and backup path allocation and resource allocation strategy to each node. The invention can reduce the information age of information leveling uniformity under dense networking under low complexity and improve the service transmission capability.

Inventors

LIN SIYU
ZHU SHUO
WANG ZIJING
AI BO
WANG HONGWEI
LI YANG
WANG XI
CHEN JUNQI

Assignees

北京交通大学

Dates

Publication Date: 20260505
Application Date: 20251212

Claims (9)

1. A reliable transmission and resource optimization method for intelligent communication of an ultra-dense network is characterized by comprising the following steps: Establishing an ultra-dense networking system architecture and a topology model; establishing an ultra-dense networking communication model based on an ultra-dense networking system architecture and a topology model, and designing an orthogonal strategy and an interference suppression mechanism; constructing an optimization problem taking information age minimization as an objective function; decomposing the optimization problem into a limited main problem and a pricing sub-problem and solving the limited main problem and the pricing sub-problem to obtain a limited main problem resource allocation result and a pricing sub-problem negative cost path result; Establishing a redundant backup resource optimization algorithm based on a column generation algorithm frame based on a limited main problem resource allocation result and a pricing sub-problem negative cost path result; And executing a redundant backup resource optimization algorithm based on a column generation algorithm framework, outputting an optimization result, and issuing a primary and backup path configuration and resource allocation strategy to each node.
2. The method of claim 1, wherein the ultra-dense networking communication model comprises a channel propagation model, a link layer model, and an antenna and interference control model; The specific method for constructing the channel propagation model comprises the following steps: Constructing a channel propagation model based on 3GPP standards, wherein the channel propagation model is respectively modeled aiming at a line-of-sight propagation scene and a non-line-of-sight propagation scene; selecting a macro cell model as a channel propagation model in an open area, and selecting a micro cell model as the channel propagation model in a dense area; the differentiated configuration is performed for different link types in the network by configuring UMa a channel model for the backhaul link and Indoor Office a channel model for the access link.
3. The method of claim 2, wherein the link layer model comprises a first link layer model and a second link layer model; The specific method for constructing the first link layer model comprises the following steps: constructing a link effective capacity model, wherein the expression is as follows: In the formula, For QoS index of Time link Is used for the effective capacity of the (c) a, For traffic flows Is provided for the end-to-end rate of (c), As a natural logarithmic function, For the operation of the desired value(s), A base number that is a natural logarithm; setting a rate interrupt probability constraint, wherein the expression is as follows: In the formula, The probability of interruption is indicated and, Indicating the data transmission rate requirements of the data, A rate outage probability threshold; Based on the link effective capacity model and the rate interruption probability constraint, a first link layer model is constructed, and the expression is as follows: ; the specific method for constructing the second link layer model comprises the following steps: an information age evolution model is constructed, and the expression is as follows: In the formula, Representing time slots The age of the corresponding information is determined, Representing time slots The corresponding information age; for time slots A packet arrival indicator of (c) and, when a new packet arrives, Otherwise ; Constructing a delayed interrupt probability model, wherein the expression is as follows: In the formula, Representing links The time delay in the process is up to the time delay, Representing links Is a backlog probability of (2); Constructing a second link layer model according to the information age evolution model and the delay interruption probability model, wherein the expression is as follows: In the formula, Is an information age threshold.
4. A method according to claim 3, wherein the specific method for constructing the antenna and interference control model is as follows: A model of a single antenna element is constructed, the expression of which is: In the formula, A radiation pattern of a single antenna element is shown, Indicating the gain of the individual antenna elements, For the horizontal angle between the signal transmitting direction and the signal receiving direction, As the vertical angle between the signal transmitting direction and the signal receiving direction, Indicating the horizontal gain decay and, Representing the vertical gain decay, Representing the maximum front-to-back ratio of a single antenna element; an array model of the IAB node is constructed, and the expression is as follows: In the formula, A radiation pattern of the array antenna elements is shown, Representing the correlation coefficient between the antennas, Representing the number of horizontal elements of the antenna array, Representing the number of vertical elements of the antenna array; Calculating antenna gain of main transmitting direction and antenna gain of interference direction based on IAB node array model, wherein the antenna gain of main transmitting direction is : The gain in the interference direction is : In the formula, Representing nodes And node The horizontal included angle between the two, Representing nodes And node A vertical included angle between the two; Based on the main transmitting direction gain and the interference direction gain, constructing a total link interference model, wherein the expression is as follows: In the formula, Representing nodes The total interference in the interference range is, Representation of At the moment at the node A set of nodes in the interference range, Is a node Is used for the transmission power of the (c), Is a node And node The gain of the channel between them, Representing nodes And node The path loss between them and the optical path, Representing nodes And node A distance therebetween; calculating according to the total link interference model to obtain a link Signal to noise ratio at the point, the expression is: Wherein, the Representing links At the signal-to-noise ratio of the signal-to-noise ratio, Representing nodes Is used for the transmission power of the (c), Is a node And node The gain of the channel between them, Node And node The path loss between them and the optical path, Is a node And node The distance between the two plates is set to be equal, Indicating the link scheduling policy at this time; Representing the thermal noise power of the system; The beam main lobe overlapping constraint condition is constructed, and the expression is as follows: In the formula, 、、 All are node indexes, and represent IAB donor nodes or IAB nodes; For a link With links The included angle between the two parts is that, And V represents IAB donor node and IAB node set.
5. The method of claim 1, wherein the orthogonal policies include a node orthogonal policy and a link orthogonal policy, wherein the link orthogonal policy allows an intermediate node to be shared between an access link set and a backhaul link set of a primary and backup path of a same information flow, and wherein the node orthogonal policy does not allow other nodes except a source node and a destination node to be shared between the access link set and the backhaul link set of the primary and backup path of the same information flow.
6. The method of claim 5, wherein the optimization problem with information age minimization as an objective function includes an objective function and constraints; Constraint conditions include a link scheduling primary constraint and a redundant link orthogonality constraint; the redundant link orthogonality constraint is specifically: In the formula, For the main link to schedule decision variables, Representing traffic flows At the moment of time Through a link The transmission is carried out by a computer, Representing the backup link scheduling decision variables, Representing traffic flows At the moment of time Through a link Transmitting; the link scheduling main constraints include: half duplex constraints, expressed as: In the formula, A set of traffic flows is represented and, Representation and node The other nodes of the connection are connected to each other, In order to schedule the decision variables, Representing traffic flows At the moment of time Through a link Transmitting; in order to schedule the decision variables, Representing traffic flows At the moment of time Through a link V represents IAB node and IAB node set; A link resource exclusion constraint whose expression is: In the formula, Representing a set of access links and return links in an ultra-dense networking system architecture and a topology model; a multi-beam transmit-receive constraint, expressed as: In the formula, An upper beam concurrency limit; the link scheduling order constraint is expressed as: In the formula, In order to schedule the decision variables, Representing traffic flows At the moment of time Through a link Transmitting; The link capacity constraint is expressed as: In the formula, Representing the primary link and the primary link, For the length of the sub-frame, For the capacity of the channel, Is the link outage probability; The objective function is specifically: In the formula, For the age of the traffic flow information received by the receiver, Information age for the backup link.
7. The method according to claim 6, wherein the constrained main problem after decomposing the optimization problem is specifically: In the formula, Represents the maximum value of the information age in the primary and secondary paths, Representing a link-node topology matrix of the system, An end-to-end information matrix representing the information flow; The pricing sub-problem after decomposing the optimization problem is specifically: In the formula, Representing reduced cost of solving links In order to solve for the routing path length, Represents the maximum value of the path length, Representing the effective channel capacity of the information stream, Representing the outage probability of the link.
8. The method according to claim 7, wherein the redundant backup resource optimization algorithm based on the column generation algorithm framework is specifically: Obtaining dual variables of constraint conditions in an optimization problem taking information age minimization as an objective function based on a solving result of a limited main problem; the obtained dual variables are brought into each candidate path of the pricing sub-problem negative cost path result to calculate correction cost, and consistency of the path and the main problem optimization direction is evaluated according to the correction cost; Re-running a solving algorithm of the pricing sub-problem on each surviving main path which passes the evaluation, generating a candidate backup path set corresponding to the surviving main path, and selecting a path with the largest cost reduction in the candidate backup path set as an optimal backup path; Calculating a cost reduction value for each surviving main path and the corresponding optimal backup path, and if the cost reduction value is smaller than 0, updating the solution of the limited main problem by taking the surviving main path and the corresponding optimal backup path as an improvement scheme; when the surviving main path with the reduced cost less than 0 is not combined with the optimal backup path, ending the redundant backup resource optimization algorithm; The solution of the main problem after the redundant backup resource optimization algorithm is finished is the optimal redundant networking configuration, and the method comprises the steps of main and standby link route planning meeting orthogonal constraint in redundant backup transmission, time slot scheduling strategy meeting constraint of each link and realizing average information age minimization of service flows.
9. An apparatus based on the reliable transmission and resource optimization method of the smart communication of the ultra-dense network according to any one of claims 1 to 8, which is characterized by comprising: The network topology module is used for establishing an ultra-dense networking system architecture and a topology model; The communication link module is used for establishing an ultra-dense networking communication model based on the ultra-dense networking system architecture and the topology model, and designing an orthogonal strategy and an interference suppression mechanism; the constraint function module is used for constructing an optimization problem taking information age minimization as an objective function; The decision making module is used for decomposing the optimization problem into a limited main problem and a pricing sub-problem and solving the limited main problem resource allocation result and the pricing sub-problem negative cost path result, and establishing a redundant backup resource optimization algorithm based on a column generation algorithm frame based on the limited main problem resource allocation result and the pricing sub-problem negative cost path result; and the resource optimization module is used for executing a redundant backup resource optimization algorithm based on the column generation algorithm framework, outputting an optimization result and issuing a primary and backup path configuration and resource allocation strategy to each node.

Description

Intelligent communication reliable transmission and resource optimization method and device for super-dense networking Technical Field The invention relates to the technical field of resource optimization of super-dense networking, in particular to a method and a device for reliable transmission and resource optimization of intelligent communication of super-dense networking. Background Ext> withext> theext> developmentext> ofext> 5ext> Gext> -ext> Aext> andext> 6ext> Gext> technologiesext>,ext> ultraext> -ext> denseext> networkingext> isext> aext> coreext> meansext> forext> improvingext> networkext> capacityext>.ext> The 3GPP proposes an integrated access Backhaul (IAB, integrated Access and Backhaul) network architecture, which realizes seamless coverage of a high-density area through cooperation of an IAB donor node and a large number of IAB access+backhaul fusion nodes. And based on the in-band backhaul technology, no special fiber optic cable is required to be additionally deployed or an authorized frequency band is required to be purchased. The method can meet the requirements of ultra-dense networking on low cost, flexible deployment and large bandwidth of the backhaul network. In the ultra-dense networking scenario, the number of user equipment is large, the service types are complex, and the requirements on communication reliability and time delay are strict. But the high-frequency band signal has large transmission loss, weak diffraction capacity and easy shielding influence, and the problems of beam interference and common-frequency interference among dense nodes are outstanding, and the service continuity and timeliness are difficult to ensure by single link transmission. At present, the reliable transmission and resource optimization method for the high-frequency band IAB super dense networking generally considers the route and the link scheduling independently, ignores the strong coupling relation between the route and the link scheduling, and does not consider a redundant backup mechanism. In the current ultra-dense networking system resource optimization, independent decision of routing and link scheduling is performed, the strong coupling relation that the routing path selection influences the link load distribution and the link resource availability restricts the routing decision space is ignored, and the scheme complexity grows exponentially with the number of nodes. The resource optimization and reliable transmission with low complexity are not realized, and the contradiction between high-reliability redundancy and high-efficiency resource utilization is solved. For example, the Chinese patent inventions with publication numbers of CN 120711473A and CN 116056149A respectively have redundancy characteristics by avoiding interference influence through communication path adjustment, but do not consider return link orthogonality guarantee, and the main link and the standby link are easy to share an interference source. The Chinese invention patent with publication numbers of CN 119211943A, CN 118804005A and CN 120034868A respectively adopts a static single-hop or double-hop loop transmission network, and the whole throughput of the system is improved by the provided optimization method, but interference suppression, route and link scheduling optimization are not considered, and the timeliness of the system information is not improved. In summary, the nodes in the super-dense networking are dense, the beam overlap is serious, the existing scheme does not design a targeted beam constraint mechanism, and meanwhile, a redundancy mechanism is not considered, the primary and secondary links do not realize orthogonal separation of node or frequency band resources, and when the shared node fails or the frequency band is interfered, the primary and secondary links fail at the same time. In addition, the existing resource optimization method does not combine with the service timeliness requirement to dynamically allocate resources, has high solving complexity in the super-dense networking scene, and cannot meet the real-time scheduling requirement. Disclosure of Invention Aiming at the defects in the prior art, the method and the device for optimizing the reliable transmission and the resources of the intelligent communication of the ultra-dense network solve the problems of high algorithm complexity, low service transmission timeliness, insufficient reliability, weak interference suppression capability and low resource utilization rate in the prior art. In order to achieve the above object, the present invention provides a reliable transmission and resource optimization method for intelligent communication of an ultra-dense network, comprising: Establishing an ultra-dense networking system architecture and a topology model; establishing an ultra-dense networking communication model based on an ultra-dense networking system architecture and a topology model, and designing an orthogonal strategy and an