Base station dormancy method, system and medium based on correction encoding cooperation cache, macro base station

Abstract

The application provides a base station dormancy method, system, medium and macro base station based on error correction coding cooperation cache, which comprises the following steps: predicting the user request frequency of each file in each micro base station within a preset time period; splitting the file into a first number of segments with the same size; generating a second number of coding cache packages from the segments, so that the file can be recovered based on any first number of coding cache packages; wherein the second number is greater than the first number; for each file, based on the user request frequency, a matching number of coding cache packages are cached to the corresponding micro base station; and the state of each micro base station is monitored, and the micro base station in the idle state is closed. The base station dormancy method, system, medium and macro base station based on error correction coding cooperation cache of the application realize base station dormancy based on the file storage architecture of the information center network and the erasure coding technology, which greatly reduces the system energy consumption.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a base station sleep method, system, medium, and macro base station based on bias correction coding cooperative buffering. Background Technology

[0002] With the rapid development of communication technologies and applications, "content-driven," "broadband," and "mobile" have become the main themes of network development, and people's demand for traffic and content is becoming increasingly strong. According to the prediction of the Visual Network Index, by 2022, global Internet traffic will be equivalent to 127 times the global Internet capacity in 2005, and traffic from wireless and mobile devices will account for more than 63% of total IP traffic. With the explosive growth of network demand, the traditional host-centric network architecture will be unable to meet the current requirements for network service quality. To this end, Information-Centric Networking (ICN) has been proposed as a new network architecture. In ICN, the content information required by users is often stored in the memory at the network edge. ICN can realize the separation of content and location, and the network's built-in caching, thereby better meeting the needs of large-scale network content distribution, mobile content access, and network traffic balancing. As an important form of future networks, ICN is attracting the attention of researchers around the world. With the rapid development of advanced technologies such as high-definition video, virtual reality, autonomous driving, and vehicle networking, the demand for latency-sensitive and computationally intensive data services in mobile networks is growing at an unprecedented rate. Mobile networks should provide lower response latency and higher transmission rates, but this will result in additional energy consumption. To address these challenges, edge caching is considered an important technology in next-generation communications, and it is also a crucial feature of data-centric networks.

[0003] Building upon the aforementioned information-centric network concept, existing technologies propose caching entire files at the network edge. Unlike traditional wireless networks where users request data via multi-hop mapping along the backhaul link, users request files from their respective base stations based on the desired filename. If the base station's memory caches the file, it returns it to the user through its outgoing interface. If not, the filename is added to the forwarding interest table in the memory, and the router forwards the interest packet to the macro base station (MBS) based on information in the forwarding information base (FIB) and the router's adaptive forwarding policy (if the MBS also lacks the corresponding data, the interest packet is forwarded to the content producer in the core network) until the required file is obtained. Existing technologies also propose distributing file encoding packets at the network edge; however, redundant encoding cache packets still consume additional cache space, and the number of file encoding cache packets cannot be adjusted according to changes in user request density. Simply putting the base station into sleep mode can also negatively impact the quality of service for users.

[0004] With the advent of the 5G era and the rapid growth in network traffic and the number of user devices, ultra-dense network deployment has become the norm to provide users with good coverage and access quality. In ultra-dense networks (UDNs), while deploying buffers at the network edge is an important method to reduce energy consumption, overly dense base station deployments consume additional power. Although simply shutting down idle base stations can improve base station energy consumption, this prevents the full utilization of the buffered content in idle base stations, thus increasing system energy consumption due to the lack of access to some edge buffers.

[0005] To improve edge caching performance, erasure coding caching has been proposed as a promising technology in recent years and has attracted widespread attention due to its recoverability and robustness. Like error-correcting and error-detecting codes, erasure coding is a linear block code. It can recover lost data with limited redundancy. However, deploying only the coded cache packet can waste base station cache space. Summary of the Invention

[0006] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a base station hibernation method, system, medium, and macro base station based on correction coding cooperative caching. The base station hibernation is achieved based on the file storage architecture of the information center network and the erasure coding technology, which greatly reduces system energy consumption.

[0007] In a first aspect, the present invention provides a base station sleep method based on bias correction coding cooperative caching, applied to a macro base station. The method includes the following steps: predicting the user request frequency of each file in each micro base station within a preset time period; splitting the file into a first number of segments of the same size; generating a second number of coding cache packets from the segments to restore the file based on any first number of coding cache packets; wherein the second number is greater than the first number; for each file, caching a matching number of coding cache packets to the corresponding micro base station based on the user request frequency; monitoring the status of each micro base station and shutting down micro base stations in an idle state.

[0008] In one implementation of the first aspect, the macro base station predicts the frequency of user requests for each file at each micro base station within a preset time period, including the following steps:

[0009] Get the popularity of each file;

[0010] according to Predict the frequency of user requests for file f at each micro base station, where F represents the total number of files and δ represents the distribution value of the popularity of file f.

[0011] In one implementation of the first aspect, the encoded cache packet uses a maximum distance divisible code generated based on the fragment.

[0012] In one implementation of the first aspect, the number of matches is the number of encoded cache packets that each micro base station needs to cache when the total system energy consumption is minimized; the total system energy consumption is the sum of cache energy consumption, cooperative transmission energy consumption, and energy consumption for requests along the backward link.

[0013] In one implementation of the first aspect, the characteristic is that the number of matching encoded buffer packets corresponding to each micro base station is obtained through any of the following methods:

[0014] Acquisition based on DQN network of deep reinforcement learning;

[0015] Based on particle swarm optimization algorithm.

[0016] Secondly, the present invention provides a base station sleep system based on bias correction coding cooperative caching, applied to a macro base station, the system comprising a prediction module, a coding module, a caching module and a monitoring module;

[0017] The prediction module is used to predict the frequency of user requests for each file at each micro base station within a preset time period.

[0018] The encoding module is used to split the file into a first number of segments of the same size; generate a second number of encoded cache packets of the segment in a maximum distance divisible code format, so as to recover the file based on any first number of encoded cache packets; wherein, the second number is greater than the first number;

[0019] The caching module is used to cache a matching number of encoded cache packets to the corresponding micro base station for each file, based on the user request frequency.

[0020] The monitoring module is used to monitor the status of each micro base station and shut down micro base stations that are in an idle state.

[0021] Thirdly, the present invention provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described base station sleep method based on bias correction coding cooperative caching.

[0022] Fourthly, the present invention provides a macro base station, comprising: a processor and a memory;

[0023] The memory is used to store computer programs;

[0024] The processor is used to execute the computer program stored in the memory, so that the macro base station performs the base station sleep method based on the bias coding cooperative caching described above.

[0025] Fifthly, the present invention provides a base station sleep system based on bias correction coding cooperative caching, including the aforementioned macro base station and multiple micro base stations;

[0026] When a user requests a file from a micro base station, the micro base station searches for the encoded cache packet of the file in its cache, and the number of the encoded cache packets is N;

[0027] When N is greater than or equal to the first quantity, the micro base station provides the encoded cache package to the user so that the user can recover the file based on the encoded cache package;

[0028] When the number of the encoded cache packets is less than the first number, the user requests encoded cache packets from other micro base stations until the sum of the number of requested encoded cache packets and N equals the first number, so that the user can restore the file based on all the requested encoded cache packets;

[0029] When the number of encoded cache packets requested from all micro base stations is less than the first number, the user requests encoded cache packets from the content server through the micro base station and the macro base station until the sum of the number of requested encoded cache packets and N equals the first number, so that the user can restore the file based on all the requested encoded cache packets.

[0030] As described above, the base station sleep method, system, medium, and macro base station based on bias correction coding cooperative caching of the present invention have the following beneficial effects:

[0031] (1) Base station hibernation is achieved based on the file storage architecture and erasure coding technology of the information center network, which greatly reduces system energy consumption;

[0032] (2) By deploying an encoding cache package on the micro base station side, even if some idle micro base stations are shut down, the complete content can be restored by relying on the encoding cache package stored in the active base station. This effectively solves the problem that files in the shut-down micro base stations cannot be requested due to simply shutting down the micro base stations, and at the same time reduces the cache redundancy caused by the encoding cache.

[0033] (3) By predicting the popularity of files and the number of user requests for each base station, the number of encoding cache packets for each micro base station is optimized and corresponding base station sleep strategies are formulated, thereby greatly reducing the energy consumption of micro base stations. Attached Figure Description

[0034] Figure 1 The flowchart shown is a representation of an embodiment of the base station sleep method based on bias coding cooperative caching of the present invention;

[0035] Figure 2 The diagram shown is a structural schematic of a two-layer wireless network according to an embodiment of the present invention.

[0036] Figure 3 The diagram shown is a structural schematic of a base station sleep system based on bias coding cooperative caching according to an embodiment of the present invention;

[0037] Figure 4 The diagram shown is a structural schematic of a macro base station according to an embodiment of the present invention. Detailed Implementation

[0038] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0039] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0040] This invention relates to a base station hibernation method, system, medium, and macro base station based on a file storage architecture of an information-centric network and erasure coding technology to achieve base station hibernation. Specifically, by deploying coded cache packages on the micro base station side, even if some idle micro base stations are shut down, the complete content can be restored using the coded cache packages stored in active micro base stations, thereby significantly reducing system energy consumption and demonstrating high practicality.

[0041] like Figure 1 As shown, in one embodiment, the base station sleep method based on bias coding cooperative caching of the present invention is applied to a macro base station, and the method includes the following steps:

[0042] Step S1: Predict the frequency of user requests for each file at each micro base station within a preset time period.

[0043] Specifically, such as Figure 2 As shown, in a two-layer wireless network, the base stations consist of one macro base station (MBS) and N small base stations (SBS). The micro base stations communicate with the macro base station via data packets, while the macro base stations communicate with the content server in the core network. A limited number of mobile users are distributed throughout the system, each requesting the data they need. According to sociological research, the probability of all users requesting files roughly follows a Zipf distribution. Therefore, the macro base station predicts the frequency of user requests for each file at each micro base station within a preset time period using the following steps:

[0044] 11) Obtain the popularity of each file. Specifically, the macro base station statistically analyzes user requests over a period of time and predicts the popularity of all users' requested files in the next period based on the statistical data. In this invention, the popularity can be obtained using existing algorithms, which will not be elaborated upon here.

[0045] 12) According to The predicted frequency of user requests for file f at each micro base station is calculated, where F represents the total number of files and δ represents the distribution value of the popularity of file f. A larger δ indicates a more concentrated distribution of user-requested files.

[0046] Here, assuming there are a total of F files that the macro base station predicts will be requested by the user, the probability of file f (1≤f≤N) being requested is: Where δ≥0 reflects the popularity of a file, the larger δ is, the greater the likelihood that more users will request a few popular files.

[0047] Step S2: Split the file into a first number of segments of the same size; generate a second number of encoded cache packages from the segments to recover the file based on any first number of encoded cache packages; wherein the second number is greater than the first number.

[0048] Specifically, assuming that the cache space of all micro base stations can only hold N files, these N files are arranged in descending order of popularity as {F1, F2, ..., F...} N}. Using file F j For example, take file F j Divide into any first quantity n of the same size j If there are fragments, then file F j The fragment can be represented as F j ={f 1,j ,f 2,j ,……,f n,j}. Using these file fragments, an encoding buffer pack {e1} is created according to the encoding rules of Maximum Distance Separable Code (MDS). j e2 j ,……,e E(j) j}, where E(j) is F j The number of encoded cache packets, i.e., the second number. Wherein, E(j) should satisfy E(j)>n j .

[0049] Therefore, the encoded file F j It can be parameterized as (E(j), n j Using the decoding principle of MDS codes, any n can be used. j The encoded cache package recovered the entire F j document.

[0050] Step S3: For each file, based on the user request frequency, cache a matching number of encoded cache packets to the corresponding micro base station.

[0051] Specifically, during the content placement phase, m is introduced. j,k To represent the file F cached in micro base station k j The number of encoded cache packets. Since the file request frequency varies for each micro base station, the number of encoded cache packets in different micro base stations should also vary. Therefore, for each micro base station in the system, M... k =[m 1,k ,m 2,k ,……,m N,k ] TThis is defined as the number of encoded buffer packets cached for each file in the micro base station k. Therefore, the encoded buffer packet matrix can be represented as M = [M1, M2, ..., M]. K ].

[0052] Step S4: Monitor the status of each micro base station and shut down any micro base stations that are in an idle state.

[0053] Specifically, the micro base station state matrix S is defined as [s1, s2, ..., s...]. K The state of a micro base station is represented by ], where the elements in S are binary variables. If micro base station k is active, then s k =1; if SBS k is off, then s k =0. To reduce system power consumption, shut down micro base stations that are in an idle state.

[0054] It's important to note that in an information-centric network, the base station's memory contains three data structures: a Pending Interest Table (PIT), a Forwarding Information Table (FIB), and a Content Cache (CS), to determine whether, when, and where to forward each interest packet. The PIT stores all interest packets that have been forwarded by the router but not yet satisfied. Each PIT entry records the data name carried in the interest packet, as well as the incoming and outgoing interfaces. When a user's interest packet arrives, the information-centric network router first checks the CS for matching data. If a matching data exists, the router returns the packet on the interface where the interest packet arrived; otherwise, the router queries the PIT for the name. If a matching entry exists, it simply records the incoming interface of the interest packet. If no matching PIT entry exists, the router forwards the interest packet to the macro base station based on the information in the FIB and the router's adaptive forwarding policy. If the macro base station also lacks corresponding data, the interest packet is forwarded to the content server located in the core network. When a router receives interest packets with the same name from multiple downstream nodes, it only forwards the first interest packet upstream of the data producer. The FIB itself is populated by a routing protocol based on name prefixes, with each prefix having multiple outgoing interfaces. Whether data in the content caching structure is cached depends on the popularity of the files requested by users in the region to which the base station belongs.

[0055] Therefore, when a user u attached to a micro base station k requests content F j The specific steps are as follows:

[0056] (a) In the attached micro base station k, first search for file F. j The number of encoded cache packets, if the number of encoded cache packets satisfies s k ·m j,k ≥n jThe found encoded cache package will then be sent to user u, so that the user can recover file F based on all the requested encoded cache packages. j Among them, s k ·m j,k This represents the number of encoded cache packets for the j-th file cached in micro base station k.

[0057] (b) If the number of encoded buffer packets satisfies s k ·m j,k <n j It is necessary to request the remaining file packets from other micro base stations via the X2 link using certain methods, such as broadcasting or multicasting, and then transmit them to user u so that the user can recover file F based on all the requested encoded cache packets. j .

[0058] (c) If the encoded cache packets in all the micro base stations in a micro base station cluster are insufficient to recover the file, i.e. Then the remaining Each encoded cache packet needs to be requested from the micro base station k and macro base station along the backward link to the content server in the core network, and then transmitted to the user u, so that the user can recover file F based on all the requested encoded cache packets. j .

[0059] The calculation of system power consumption in this invention is related to the user request process. In this invention, system energy consumption mainly consists of three parts: cache energy consumption, cooperative transmission energy consumption, and energy consumption for requests along the backward link. Based on the popularity of the requested file and the user request frequency, the above three parts of energy consumption can be obtained from the file popularity and user request frequency, thus yielding a closed-form solution for the total power consumption of the base station. By optimizing the total power consumption of all micro base stations under control, the macro base station can determine the sleep strategy and micro base station cache strategy for each micro base station, and then distribute them to each micro base station for execution.

[0060] Specifically, cache energy consumption can be expressed as Cooperative transmission energy consumption can be expressed as The energy consumption of a request along the backward link is expressed as

[0061]

[0062] Therefore, the total energy consumption is

[0063]

[0064] The problem of minimizing energy consumption can be expressed as:

[0065]

[0066]

[0067]

[0068]

[0069] Here, C represents the storage space constraint for each micro base station. This energy minimization problem can be solved using the particle swarm optimization algorithm, or by other traditional optimization algorithms and deep reinforcement learning algorithms such as DQN. The particle swarm optimization algorithm is as follows:

[0070]

[0071] It should be noted that this invention does not impose specific restrictions on the specific details of transmission, such as how to route, how to allocate time and frequency resources to users, and how to add memory to the base station.

[0072] The protection scope of the base station sleep method based on bias coding cooperative caching described in this embodiment of the invention is not limited to the execution order of the steps listed in this embodiment. Any solution implemented by adding, deleting, or replacing steps in the prior art based on the principle of this invention is included within the protection scope of this invention.

[0073] This invention also provides a base station sleep system based on bias correction coding cooperative caching. The base station sleep system based on bias correction coding cooperative caching can implement the base station sleep method based on bias correction coding cooperative caching described in this invention. However, the implementation device of the base station sleep system based on bias correction coding cooperative caching described in this invention includes, but is not limited to, the structure of the base station sleep system based on bias correction coding cooperative caching listed in this embodiment. All structural modifications and substitutions of the prior art made according to the principles of this invention are included within the protection scope of this invention.

[0074] like Figure 3 As shown, in one embodiment, the base station sleep system based on bias correction coding cooperative caching of the present invention is applied to a macro base station. The system includes a prediction module 31, a coding module 32, a caching module 33, and a monitoring module 34.

[0075] The prediction module 31 is used to predict the frequency of user requests for each file at each micro base station within a preset time period.

[0076] The encoding module 32 is used to split the file into a first number of segments of the same size; generate a second number of encoding cache packets of the maximum distance divisible code format from the segments, so as to recover the file based on any first number of encoding cache packets; wherein the second number is greater than the first number.

[0077] The caching module 33 is connected to the prediction module 31 and the encoding module 32, and is used to cache a matching number of encoded cache packets to the corresponding micro base station for each file based on the user request frequency.

[0078] The monitoring module 34 is used to monitor the status of each micro base station and shut down micro base stations that are in an idle state.

[0079] The structure and principle of the prediction module 31, the encoding module 32, the caching module 33 and the monitoring module 34 correspond one-to-one with the steps in the base station sleep method based on the above-mentioned correction coding cooperative caching, so they will not be described again here.

[0080] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, or methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of apparatuses or modules or units may be electrical, mechanical, or other forms.

[0081] The modules / units described as separate components may or may not be physically separate. The components shown as modules / units may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules / units can be selected to achieve the objectives of the embodiments of the present invention, depending on actual needs. For example, the functional modules / units in the various embodiments of the present invention may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0082] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0083] This invention also provides a computer-readable storage medium. Those skilled in the art will understand that all or part of the steps in the base station sleep method based on bias-correction coding cooperative caching in the above embodiments can be implemented by a program instructing a processor. The program can be stored in a computer-readable storage medium, which is a non-transitory medium, such as random access memory, read-only memory, flash memory, hard disk, solid-state drive, magnetic tape, floppy disk, optical disc, and any combination thereof. The storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. This available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital video disc (DVD)), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0084] This invention also provides a macro base station. The macro base station includes a processor and a memory.

[0085] The memory is used to store computer programs.

[0086] The memory includes various media capable of storing program code, such as ROM, RAM, magnetic disk, USB flash drive, memory card, or optical disk.

[0087] The processor is connected to the memory and is used to execute the computer program stored in the memory so that the macro base station performs the base station sleep method based on the bias correction coding cooperative caching described above.

[0088] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0089] like Figure 4As shown, the macro base station of the present invention is manifested in the form of a general-purpose computing device. The components of the macro base station may include, but are not limited to: one or more processors or processing units 41, a memory 42, and a bus 43 connecting different system components (including the memory 42 and the processing unit 41).

[0090] Bus 43 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. Examples of these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0091] Macro base stations typically include a variety of computer system readable media. These media can be any available media that can be accessed by the macro base station, including volatile and non-volatile media, and portable and non-portable media.

[0092] Memory 42 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 421 and / or cache memory 422. The macro base station may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 423 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 4 Not shown; usually referred to as a "hard drive"). Although Figure 4 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 43 via one or more data media interfaces. Memory 42 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0093] A program / utility 424 having a set (at least one) of program modules 4241 may be stored, for example, in memory 42. Such program modules 4241 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 4241 typically perform the functions and / or methods described in the embodiments of the present invention.

[0094] The macro base station can also communicate with one or more external devices (e.g., keyboard, pointing device, display, etc.), one or more devices that enable a user to interact with the macro base station, and / or any device that enables the macro base station to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed through input / output (I / O) interface 44. Furthermore, the macro base station can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) through network adapter 45. Figure 4 As shown, network adapter 45 communicates with other modules of the macro base station via bus 43. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the macro base station, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0095] In one embodiment, the base station dormancy system based on bias correction coding cooperative caching of the present invention includes the aforementioned macro base station and multiple micro base stations.

[0096] When a user requests a file from a micro base station, the micro base station searches its cache for the encoded cache package of the file, where the number of encoded cache packages is N. When N is greater than or equal to a first number, the micro base station provides the encoded cache package to the user, allowing the user to recover the file based on the encoded cache package. When the number of encoded cache packages is less than the first number, the user requests encoded cache packages from other micro base stations until the sum of the number of requested encoded cache packages and N equals the first number, allowing the user to recover the file based on all requested encoded cache packages. When the number of encoded cache packages requested from all micro base stations is less than the first number, the user requests encoded cache packages from the content server through the micro base station and the macro base station until the sum of the number of requested encoded cache packages and N equals the first number, allowing the user to recover the file based on all requested encoded cache packages.

[0097] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A base station sleep method based on bias correction coding cooperative buffering, applied to macro base stations, characterized in that: The method includes the following steps: Predict the frequency of user requests for each file on each micro base station within a preset time period; The file is split into a first number of segments of equal size; the segments are then used to generate a second number of encoded cache packets, which are used to recover the file based on any of the first number of encoded cache packets; wherein the second number is greater than the first number; wherein encoded cache packets are created using the segments according to the maximum distance divisible code encoding rule; and using the maximum distance divisible code decoding principle, any of the first number of encoded cache packets are used to recover the file. The encoded cache package recovered the entire file F. j ; For each file, based on the user request frequency, a matching number of encoded cache packets are cached in the corresponding micro base station; for each micro base station, M... k =[m 1,k ,m 2,k ,……, m N,k ] T m is defined as the number of encoded cache packets of each file cached in the micro base station k. j,k This indicates that file F is cached in micro base station k. j The number of encoded cache packets; Monitor the status of each micro base station and shut down micro base stations that are idle; define the micro base station status matrix S=[s1,s2,……,s K The state of a micro base station is represented by s, where if micro base station k is active, then s k =1; if micro base station k is in the off state, then s k =0; The macro base station predicts the frequency of user requests for each file on each micro base station within a preset time period, including the following steps: Get the popularity of each file; according to Predict the frequency of user requests for file f at each micro base station, where F represents the total number of files. The distribution value representing the popularity of file f; When a user u attached to micro base station k requests content F j At that time, in the attached micro base station k, the file F is searched first. j The number of encoded cache packets, if the number of encoded cache packets meets the requirement. The found encoded cache package will then be sent to user u, so that the user can recover file F based on all the requested encoded cache packages. j ;in This represents the number of encoded cache packets for the j-th file cached in micro base station k; if the number of encoded cache packets satisfies The system requests the remaining file packets from other micro base stations via the X2 link and then transmits them to user u, enabling the user to recover file F based on all the requested encoded cache packets. j If the encoded cache packets in all the micro base stations within a micro base station cluster are insufficient to recover the file, then the remaining... Each encoded cache packet needs to be requested from the micro base station k and macro base station along the backward link to the content server in the core network, and then transmitted to the user u, so that the user can recover file F based on all the requested encoded cache packets. j .

2. The base station sleep method based on offset coding cooperative caching according to claim 1, characterized in that: The encoded cache packet uses a maximum distance divisible code generated based on the fragment.

3. The base station sleep method based on bias correction coding cooperative caching according to claim 1, characterized in that: The number of matching packets is the number of encoded cache packets that each micro base station needs to cache when the total system energy consumption is minimized; the total system energy consumption is the sum of cache energy consumption, cooperative transmission energy consumption, and energy consumption for requests along the backward link.

4. The base station sleep method based on bias-correction coding cooperative caching according to claim 3, characterized in that: The number of matching encoded cache packets corresponding to each micro base station can be obtained through any of the following methods: Acquisition based on DQN network of deep reinforcement learning; Based on particle swarm optimization algorithm.

5. A base station sleep system based on bias correction coding cooperative buffering, applied to macro base stations, characterized in that: The system includes a prediction module, an encoding module, a caching module, and a monitoring module; The prediction module is used to predict the frequency of user requests for each file at each micro base station within a preset time period. The encoding module is used to split the file into a first number of segments of equal size; generate a second number of encoded cache packages from the segments, and recover the file based on any first number of encoded cache packages; wherein the second number is greater than the first number; wherein the encoded cache packages are created using the segments according to the maximum distance divisible code encoding rule; and the encoded cache packages are created using the maximum distance divisible code decoding principle, using any first number of... The encoded cache package recovered the entire file F. j ; The caching module is used to cache a matching number of encoded cache packets to the corresponding micro base station for each file, based on the user request frequency; for each micro base station, M... k =[m 1,k ,m 2,k ,……, m N,k ] T m is defined as the number of encoded cache packets of each file cached in the micro base station k. j,k This indicates that file F is cached in micro base station k. j The number of encoded cache packets; The monitoring module is used to monitor the status of each micro base station and shut down micro base stations that are in an idle state; the micro base station status matrix S=[s1,s2,……,s K The state of a micro base station is represented by s, where if micro base station k is active, then s k =1; if micro base station k is in the off state, then s k =0; The macro base station predicts the frequency of user requests for each file on each micro base station within a preset time period, including the following steps: Get the popularity of each file; according to Predict the frequency of user requests for file f at each micro base station, where F represents the total number of files. The distribution value representing the popularity of file f; When a user u attached to micro base station k requests content F j At that time, in the attached micro base station k, the file F is searched first. j The number of encoded cache packets, if the number of encoded cache packets meets the requirement. The found encoded cache package will then be sent to user u, so that the user can recover file F based on all the requested encoded cache packages. j ;in This represents the number of encoded cache packets for the j-th file cached in micro base station k; if the number of encoded cache packets satisfies The system requests the remaining file packets from other micro base stations via the X2 link and then transmits them to user u, enabling the user to recover file F based on all the requested encoded cache packets. j If the encoded cache packets in all the micro base stations within a micro base station cluster are insufficient to recover the file, then the remaining... Each encoded cache packet needs to be requested from the micro base station k and macro base station along the backward link to the content server in the core network, and then transmitted to the user u, so that the user can recover file F based on all the requested encoded cache packets. j .

6. A storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the base station sleep method based on the bias coding cooperative buffer as described in any one of claims 1 to 4.

7. A macro base station, characterized in that, include: Processor and memory; The memory is used to store computer programs; The processor is used to execute the computer program stored in the memory to cause the macro base station to perform the base station sleep method based on the bias coding cooperative caching according to any one of claims 1 to 4.

8. A base station sleep system based on bias correction coding cooperative buffering, characterized in that: Includes the macro base station and multiple micro base stations as described in claim 7; When a user requests a file from a micro base station, the micro base station searches for the encoded cache packet of the file in its cache, and the number of the encoded cache packets is N; When N is greater than or equal to the first quantity, the micro base station provides the encoded cache package to the user so that the user can recover the file based on the encoded cache package; When the number of the encoded cache packets is less than the first number, the user requests encoded cache packets from other micro base stations until the sum of the number of requested encoded cache packets and N equals the first number, so that the user can restore the file based on all the requested encoded cache packets; When the number of encoded cache packets requested from all micro base stations is less than the first number, the user requests encoded cache packets from the content server through the micro base station and the macro base station until the sum of the number of requested encoded cache packets and N equals the first number, so that the user can restore the file based on all the requested encoded cache packets.

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