An optimization method for content placement and transmission based on scalable video coding
By building a wireless caching network and optimizing caching and transmission strategies, the problems of low transmission efficiency and high latency in multi-quality video services were solved, resulting in more efficient file transfer and an improved user experience.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XIAN UNIV OF POSTS & TELECOMM
- Filing Date
- 2023-03-28
- Publication Date
- 2026-05-12
AI Technical Summary
In existing technologies, the changing demands for high-quality video services and the limitations of backhaul capacity lead to problems such as low transmission efficiency and high latency.
Construct a wireless caching network, coordinating caching and transmission through macro base stations and edge devices, optimize caching and transmission strategies, and utilize convex problem models and beamforming technology to optimize users and rates, reduce transmission latency and improve transmission efficiency.
While meeting the caching and power constraints of edge devices, the caching and transmission strategies were optimized, reducing transmission latency and improving file transfer efficiency and user service quality.
Smart Images
Figure CN116367241B_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of wireless communication technology, and in particular to an optimized method for content placement and transmission based on scalable video coding. Background Technology
[0002] In recent years, the explosive growth of mobile internet and the diversification of multimedia services have placed higher demands on service quality, including system throughput, transmission latency, and massive connectivity. To address these challenges, wireless caching is considered a promising technology and is gaining increasing appeal in 5G mobile communications.
[0003] Video traffic typically exhibits strong redundancy, allowing for improved transmission efficiency through wireless caching. Caching enables popular content to be delivered to users closer and faster. By placing cached content during off-peak hours and delivering it only when requested, edge caching provides additional performance gains over shorter distances than from a remote central server. In related technologies, the demand for multi-quality video services is increasing due to backhaul capacity limitations and evolving user needs. For example, some users require standard definition video with shorter latency when watching sports news, while demanding high-definition video for movies.
[0004] Therefore, it is necessary to improve one or more of the problems existing in the above-mentioned related technical solutions.
[0005] It should be noted that this section is intended to provide background or context for the technical solutions of this disclosure as set forth in the claims. The description herein does not constitute an admission that it is prior art simply because it is included in this section. Summary of the Invention
[0006] The purpose of this disclosure is to provide an optimized method for content placement and transmission based on scalable video coding, thereby overcoming, at least to some extent, one or more problems caused by the limitations and defects of related technologies.
[0007] According to embodiments of this disclosure, an optimized method for content placement and transmission based on scalable video coding is provided, the method comprising:
[0008] Construct a wireless caching network; wherein the wireless caching network includes a core network, macro base stations, users, and edge devices;
[0009] During the content placement phase, the macro base station transmits the cached files to the edge device. During the content transmission phase, the user sends a request message to the edge device in the cell. If the edge device has already cached the request content, the edge device will directly transmit the request content to the user. If the edge device does not store the request content, the macro base station will directly transmit the request content to the user.
[0010] Based on the content placement process, an optimization problem that minimizes user transmission latency is constructed and solved to obtain the optimal caching strategy;
[0011] Establish and solve an optimization problem that maximizes the number of users and the data rate to obtain the optimal transmission strategy.
[0012] In one embodiment of this disclosure, the step of constructing and solving an optimization problem that minimizes user transmission latency based on the content placement process to obtain the optimal caching strategy includes:
[0013] Based on the minimized transmission latency of the macro base station, a latency optimization model is constructed;
[0014] The time delay optimization model is transformed into a convex problem model.
[0015] Based on the transformed latency optimization model, the optimal caching strategy is obtained.
[0016] In one embodiment of this disclosure, the minimum transmission delay D of the macro base station with edge device assistance is determined according to formula (1):
[0017]
[0018] Where, p f,l This represents the probability of requesting the l-th level of the f-th file, with a value of [0,1]; z f,l A cache indicator variable representing binary data; s f,l Indicates the size of the cache file; R h Indicates the transmission rate of the edge device; R b Indicates the transmission rate of the backhaul link; R m D represents the transmission rate of the macro base station; h This indicates the capacity of the edge device.
[0019] In one embodiment of this disclosure, the step of transforming the delay optimization model into a convex problem model includes:
[0020] Introducing a slack variable t, such that D ≤ t, the original optimization problem can be transformed into:
[0021]
[0022] Where t is a slack variable.
[0023] In one embodiment of this disclosure, the step of establishing and solving an optimization problem that maximizes users and rates to obtain the optimal transmission strategy includes:
[0024] Construct a signal transmission model based on channel conditions;
[0025] Based on the transmitted signal, expressions for users and rate are obtained, and an optimization problem maximizing users and rate is constructed and solved to obtain the optimal beamforming vector.
[0026] In one embodiment of this disclosure, the step of constructing a signal transmission model based on channel conditions includes:
[0027] According to formula (3), when retrieving cached files from the edge device, the k-th user requests the l-th file. k The signal-to-noise ratio of the layer:
[0028]
[0029] in, This represents the channel gain vector between all edge devices and the k-th user within the network. This represents the channel gain vector between all edge devices and the i-th edge device; Represents the set of beamforming vectors; This indicates that user k requested l k Beamforming vector between time and edge device i; It is additive white Gaussian noise;
[0030] According to formula (4), when obtaining the request file from the macro base station, the k-th user requests the l-th file. k The signal-to-noise ratio of the layer:
[0031]
[0032] in, This represents the channel gain between the base station and the k-th user; This indicates that the k-th user requested the l-th request. k Beamforming vector at layer; The variance is the additive white Gaussian noise.
[0033] In one embodiment of this disclosure, the step of obtaining expressions for users and rates based on the transmitted signals, constructing an optimization problem to maximize users and rates, solving the constructed optimization problem, and obtaining the optimal beamforming vector includes:
[0034] Determine the maximum user's sum rate according to formula (5):
[0035]
[0036] Among them, P max and These represent the maximum transmit power of the buffer device and the base station, respectively. and These represent the buffer device and the base station transmitting the lth bit for the kth user, respectively. k The minimum quality of service that needs to be met at each layer.
[0037] In one embodiment of this disclosure, a transformation method using semidefinite relaxation, continuous convex approximation, and geometric mean inequality is employed to transform a non-convex problem into a convex problem of second-order cone programming form, which is then solved by a CVX solver to obtain a beamforming matrix.
[0038] In one embodiment of this disclosure, if the rank of the beamforming matrix is 1, then the optimal beamforming vector is obtained by eigenvalue decomposition.
[0039] In one embodiment of this disclosure, if the rank of the obtained beamforming matrix is not 1, the optimal beamforming vector is obtained by using Gaussian randomization.
[0040] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects:
[0041] In the embodiments of this disclosure, the above-described optimization method for content placement and transmission based on scalable video coding achieves the following: First, it obtains an optimal caching strategy while satisfying edge device cache size constraints; second, it obtains an optimal transmission strategy at both the macro base station and the edge device while satisfying user quality of service constraints and power constraints. Third, it effectively improves file transfer efficiency, reduces transmission latency, and enhances user quality of service. Attached Figure Description
[0042] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.
[0043] Figure 1 The diagram illustrates the steps of an optimized method for content placement and transmission based on scalable video coding in an exemplary embodiment of this disclosure.
[0044] Figure 2 A flowchart illustrating the calculation of the optimal transmission strategy in an exemplary embodiment of this disclosure is provided.
[0045] Figure 3 A schematic diagram of a wireless caching network in an exemplary embodiment of this disclosure is shown;
[0046] Figure 4 This illustration shows a curve illustrating the variation of content placement latency with cache size in an exemplary embodiment of this disclosure.
[0047] Figure 5 This illustrates the variation curve of content placement delay as a function of backhaul link rate in an exemplary embodiment of this disclosure;
[0048] Figure 6 The diagram illustrates the variation of latency of the content transmission portion with power in an exemplary embodiment of this disclosure. Detailed Implementation
[0049] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0050] Furthermore, the accompanying drawings are merely illustrative diagrams of embodiments of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities.
[0051] Below, we will refer to Figures 1 to 6 The steps of the optimized content placement and transmission method based on scalable video coding described in this example embodiment will be explained in more detail.
[0052] This example implementation first provides an optimized method for content placement and transmission based on scalable video coding. (Reference) Figure 1 As shown, the optimized method for content placement and transmission based on scalable video coding may include steps S101 to S104.
[0053] Step S101: Construct a wireless caching network; wherein the wireless caching network includes a core network, macro base stations, users, and edge devices;
[0054] Step S102: During the content placement phase, the macro base station transmits the cached file to the edge device. During the content transmission phase, the user sends a request message to the edge device in the cell. If the edge device has already cached the request content, the edge device directly transmits the request content to the user. If the edge device has not stored the request content, the macro base station directly transmits the request content to the user.
[0055] Step S103: Based on the content placement process, construct and solve an optimization problem that minimizes user transmission latency to obtain the optimal caching strategy;
[0056] Step S104: Establish and solve the optimization problem of maximizing users and rate to obtain the optimal transmission strategy.
[0057] The aforementioned optimization method for content placement and transmission based on scalable video coding achieves the following: Firstly, it yields an optimal caching strategy while satisfying edge device cache size constraints; secondly, it provides an optimal transmission strategy while satisfying user quality of service (QoS) and power constraints. Thirdly, it effectively improves file transfer efficiency, reduces transmission latency, and enhances user QoS.
[0058] like Figure 2 As shown, the method for analyzing and solving an optimization problem in a wireless buffer network to obtain the optimal transmission strategy consists of the following steps: constructing a delay optimization model, transforming the delay optimization model, constructing a signal transmission model, introducing a sum-rate optimization model, transforming the sum-rate optimization model, and determining the optimal beamforming vector. This method obtains the optimal buffering strategy by optimizing delay while satisfying the buffer size constraint of the edge device. It also optimizes the sum-rate of users while satisfying user quality of service constraints and power constraints, thus obtaining the transmission strategy at the base station and edge device. This method effectively improves the efficiency of file transfer, reduces transmission latency, and improves the user's quality of service.
[0059] like Figure 3 As shown, the application scenario of this application consists of a heterogeneous network composed of a macro base station and multiple multi-antenna edge devices with caching capabilities. Each edge device caches a portion of the files according to a designed caching scheme, and the macro base station provides services to multiple single-antenna users.
[0060] like Figure 4 As shown, transmission latency decreases as the buffer size of the edge device increases. The larger the buffer size, the more files the edge device can cache, and the fewer files it needs to retrieve from the core network via the backhaul link, thus reducing transmission latency.
[0061] like Figure 5 The diagram illustrates how transmission latency changes with the backhaul link rate. Increasing the backhaul link rate reduces transmission latency. As the backhaul link rate increases, the negative impact of backhaul capacity on content transmission decreases; when it increases to a certain level, backhaul capacity will no longer be a limiting factor for large-scale video distribution.
[0062] like Figure 6 As shown, the sum and rate performance varies with the transmit power of the macro base station. With increasing transmit power, more power is allocated to data transmission, thus increasing the sum and rate. The superiority of the proposed scheme is demonstrated by comparison with a caching scheme without edge device assistance.
[0063] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.
[0064] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.
Claims
1. An optimized method for content placement and transmission based on scalable video coding, characterized in that, The method includes: Construct a wireless caching network; wherein the wireless caching network includes a core network, macro base stations, users, and edge devices; During the content placement phase, the macro base station transmits the cached files to the edge device. During the content transmission phase, the user sends a request message to the edge device in the cell. If the edge device has already cached the request content, the edge device will directly transmit the request content to the user. If the edge device does not store the request content, the macro base station will directly transmit the request content to the user. During the content placement phase, an optimization problem that minimizes user transmission latency is constructed and solved to obtain the optimal caching strategy, including: Based on the minimized transmission latency of the macro base station, a latency optimization model is constructed; The time delay optimization model is transformed into a convex problem model. Solve the transformed convex optimization problem to obtain the optimal caching strategy; The minimum transmission delay D of the macro base station with edge device assistance is determined according to formula (1): （1） in, Indicates request number The first file The probability of the layer is [0,1]. A cache indicator variable representing binary data; Indicates the size of the cache file; Indicates the transmission rate of the edge device; Indicates the transmission rate of the backhaul link; Indicates the transmission rate of the macro base station; Indicates the capacity of the edge device; During the content layer transmission phase, an optimization problem that maximizes users and speed is established and solved to obtain the optimal transmission strategy.
2. The optimized method for content placement and transmission based on scalable video coding according to claim 1, characterized in that, The steps of transforming the time delay optimization model into a convex problem model include: Introducing slack variables , making The original optimization problem can be transformed into: （2） in, These are slack variables.
3. The optimized method for content placement and transmission based on scalable video coding according to claim 2, characterized in that, The steps to establish and solve the optimization problem that maximizes users and speed, and to obtain the optimal transmission strategy, include: Construct a signal transmission model based on channel conditions; Based on the transmitted signal, expressions for users and rate are obtained, and an optimization problem maximizing users and rate is constructed and solved to obtain the optimal beamforming vector.
4. The optimized method for content placement and transmission based on scalable video coding according to claim 3, characterized in that, The steps for constructing a signal transmission model based on channel conditions include: When determining the cache file from the edge device according to formula (3), the first... The first user request The signal-to-noise ratio of the layer: （3） in, This indicates that all edge devices within the network are connected to the first... Channel gain vector between users This indicates that all edge devices are related to the first... Channel gain vector between edge devices; Represents the set of beamforming vectors; Indicates user ask Time and edge devices Beamforming vectors between; It is additive white Gaussian noise; When determining the request file from the macro base station according to formula (4), the first... The first user request The signal-to-noise ratio of the layer: （4） in, Indicates base station and the Channel gain between users; Indicates the first The first user request Beamforming vector at layer; The variance is the additive white Gaussian noise.
5. The optimized method for content placement and transmission based on scalable video coding according to claim 4, characterized in that, Based on the transmitted signal, the steps of obtaining expressions for users and rates, constructing an optimization problem to maximize users and rates, solving the constructed optimization problem, and obtaining the optimal beamforming vector include: Determine the maximum user's sum rate according to formula (5): （5） in, and These represent the maximum transmit power of the buffer device and the base station, respectively. and These represent the cache device and the base station as the first... The first user transmission The minimum quality of service that needs to be met at each layer.
6. The optimized method for content placement and transmission based on scalable video coding according to claim 5, characterized in that, By employing a transformation method involving semidefinite relaxation, continuous convex approximation, and geometric mean inequality, the non-convex problem is transformed into a convex problem in the form of a second-order cone programming problem, which is then solved by the CVX solver to obtain the beamforming matrix.
7. The optimized method for content placement and transmission based on scalable video coding according to claim 6, characterized in that, If the rank of the beamforming matrix is 1, then the optimal beamforming vector is obtained by eigenvalue decomposition.
8. The optimized method for content placement and transmission based on scalable video coding according to claim 7, characterized in that, If the rank of the obtained beamforming matrix is not 1, the optimal beamforming vector is obtained by using Gaussian randomization.