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CN109600780A - A kind of duplicate of the document caching method based on base station sub-clustering - Google Patents

A kind of duplicate of the document caching method based on base station sub-clustering Download PDF

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CN109600780A
CN109600780A CN201910121208.1A CN201910121208A CN109600780A CN 109600780 A CN109600780 A CN 109600780A CN 201910121208 A CN201910121208 A CN 201910121208A CN 109600780 A CN109600780 A CN 109600780A
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base station
cluster
user
file
clustering
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CN109600780B (en
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余雪勇
王太宝
杜雨鑫
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Nanjing Post and Telecommunication University
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Nanjing Post and Telecommunication University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/04—Arrangements for maintaining operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/56—Provisioning of proxy services
    • H04L67/568—Storing data temporarily at an intermediate stage, e.g. caching
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
    • H04W40/32—Connectivity information management, e.g. connectivity discovery or connectivity update for defining a routing cluster membership

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  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses a kind of duplicate of the document caching methods based on base station sub-clustering, the following steps are included: step 1: receiving the interference strength size that signal generates to user according to base station and carry out sub-clustering to the base station in super-intensive heterogeneous network, so that the interference strength that the base station after sub-clustering generates the user of access is minimum；Step 2: on the basis of sub-clustering result, by the analysis of node B cache content similarity, deployment caching is carried out to the base station duplicate of the document to be accessed each in cluster.The invention has the advantages that considering that interference and user between base station access the similitude of file, it is proposed the laying method that duplicate of the document is carried out based on base station sub-clustering and according to similarity, the hit rate that user accesses content is increased, the time delay that user requests access to content is reduced, improves service quality.

Description

A kind of duplicate of the document caching method based on base station sub-clustering
Technical field
The present invention relates to the edge cache technical fields in 5G super-intensive heterogeneous network, and in particular to a kind of based on base station point The duplicate of the document caching method of cluster.
Background technique
In recent years, as the fast development of 5G technology and Internet of Things, network edge device and mobile terminal quantity sharply increase Add, is no longer satisfied requirement of the people for data acquisition speed by the technology of core of cloud computing, edge calculations technology is answered It transports and gives birth to.Wherein, edge cache technology plays important function, and edge cache refers to the storing data on network edge device, Its basic concept is to store and transmit data file in the equipment close to data source.As the 5th third-generation mobile communication system The super-intensive network of one of the key technology of system can be big in hot spot region in order to meet growing data capacity demand The small base station of Scaledeployment is to meet the needs of data capacity.On the one hand the dense deployment of small base station can increase network data and handle up Amount, and alleviate the access pressure of server end；On the other hand copy can be arranged in the hot spot data of server end and be stored in base In standing, these copies are exactly the duplicate of required file data, can more rapidly be mentioned to user by the way that copy is arranged For required file, but with the geographical distribution of base station difference, the quantity of copy and position deployment be not also identical, in order to It allows user directly to obtain the file information from base station as far as possible, copy is specifically arranged and needs to do related investigation；While with The dense deployment of small base station can also generate same layer interference and small base station and macro base between apparent influence, such as small base station Cross-layer interference between standing can generate the interference of signal to user to a certain extent, this just will affect the communication quality of user.
Summary of the invention
The object of the present invention is to provide the space utilization rates of a kind of access speed for being able to use family and base station all to be mentioned It rises, while inter base station interference can be reduced on the copy caching side of base station stored file in the super-intensive net that user communication quality influences Method.
To achieve the above object, present invention employs following technical solutions: a kind of duplicate of the document based on base station sub-clustering is slow Deposit method, comprising the following steps:
Step 1: the interference strength size of signal generation is received to the base in super-intensive heterogeneous network to user according to base station It stands and carries out sub-clustering, so that the interference strength that the base station after sub-clustering generates the user of access is minimum；
Step 2: on the basis of sub-clustering result, by the analysis of node B cache content similarity, to base station institute each in cluster The duplicate of the document to be accessed carries out deployment caching, specifically includes the following steps:
Step (2.1): the cache file similarity in cluster between target BS and other interior base stations of cluster is first calculated；
Step (2.2): setting similarity threshold, in addition to target BS, by the cachings between target BS all in cluster The base station that file similarity is greater than similarity threshold is all stored in new set ραIn, and will set ραIn base station file it is complete All it is put into set CwIn, then remove set CwIn each base station and target BS common set file, and will set CwIn Except the needed cache file after common set file is all stored in set C 'wIn；
Step (2.3): wait for the popularity size of cache file to set C ' according to base stationwIn file do sequence processing, Then according to target BS can memory space from set C 'wIn delete select need dispose caching duplicate of the document and be placed in mesh It marks in base station；
Step (2.4): the iteration that base station each in cluster carries out step (2.1)~step (2.3) as target BS is asked Solution, to carry out deployment caching to the base station duplicate of the document to be accessed each in cluster.
Further, a kind of duplicate of the document caching method based on base station sub-clustering above-mentioned, in which: in step 1, base In the cluster-dividing method of base station interference, specifically includes the following steps:
Step (1.1): assuming that base station total number is S, there is t user in each base station range, total number of users is St；Assuming that the number of base station sub-clustering is NA, the collection after sub-clustering is combined into (NA≤ S), needle C is combined into the collection of base station in each clusteri={ CI, 1, CI, 2……CI, m(i=1,2.......NA, m≤S-NA), m is indicated in cluster The number of base station；The objective function of optimization is the sum of minimum base station interference, and expression formula is as follows:
Wherein, PNAnd PMRespectively indicate the transmission signal power of small base station and the transmission signal power of macro base station；Table Show channel matrix corresponding to each user in macro base station and each cluster,Indicate that each user institute is right in small base station and each cluster The channel matrix answered,Indicate macro base station sent to user signal,Indicate other small bases in addition to local useful signal base station Stand signal, the N sent to user0Indicate the white Gaussian noise that mean value is 0, variance is 1 in signals transmission；
Wherein, expression formula constraint condition is as follows:
S.t 1≤Cmin≤NA≤Cmax≤S (7)
1<m≤S-NA (8)
Rk≥γk (11)
Formula (7) and (8) indicate to ensure to distribute at least each cluster a small base station, in formula (9)Indicate macro base station and In each cluster channel matrix corresponding to each user andIndicate letter corresponding to each user in small base station and each cluster Road matrix；In formula (10)Indicate the signal that macro base station is sent to user,Indicate that other are small in addition to local useful signal base station The signal that base station is sent to user；Formula (11) indicates each user data transmission quality of guarantee, wherein RkWhat is indicated is k-th of use The signal transmission rate at family, γkIndicate the minimum propagation threshold of k-th of subscriber signal；
Step (1.2): ergodic algorithm is used, by the N in data areaAIt is calculated one time with each numerical value traversal of m value, It sorts from small to large according in last all values acquired, selects base station sub-clustering number optimal solutionAnd the base in each cluster Number of standing optimal solution m*。
Further, a kind of duplicate of the document caching method based on base station sub-clustering above-mentioned, in which: in step (2.1), The circular of cache file similarity between two base stations is as follows:
It is assumed that base station a determines that the file set cached is Base station b determines that the file set of caching isFor base station The duplicate collection of file is combined into a, bThen the file similarity between two base stations can indicate Are as follows:
Wherein, in formulaIndicate file a1Accessed frequency,Indicate file a2Accessed frequency, with such It pushes away, H indicates the accessed frequency of file, and bottom right mark then indicates corresponding specific reference number of a document.
Further, a kind of duplicate of the document caching method based on base station sub-clustering above-mentioned, in which: in step (2.3), According to target BS can memory space from set C 'wIn delete select need dispose caching duplicate of the document number specific calculating Formula is as follows:
Wherein, SBSFor the spatial cache size of base station,For for cluster CiThe caching to cache file of interior each base station The sum of capacity, k are the copy number that base station space need to dispose,
Wherein, expression formula constraint condition is as follows:
Max k (14)
0<i≤NA (16)
1<u≤S-NA (17)
L≤ρV, t<1 (18)
Formula (16), (17) expression ensure to distribute a small base station at least each cluster, and t indicates the small base of target in formula (18) It stands, m indicates the base station for being greater than threshold value L with the similarity value of target BS；Indicate cluster CiWait for cache file in interior each base station The sum of capacity, C 'W, jIndicate that, to j file in cache file set, k is the copy number that base station space need to dispose, NAFor base It standing sub-clustering number, i indicates that base station sub-clustering score binding occurrence, S are base station total number, and u is the binding occurrence of base station number in each cluster, ρV, tIndicate the similarity value between target BS t and base station v.
Through the implementation of the above technical solution, the beneficial effects of the present invention are: proposition based on base station clustering method with point Analysis, divides according to the interference strength that base station generates user, the interference for generating the base station of the complete cluster of score to the user of access Intensity is minimum, it is ensured that the communication quality of user improves service quality；Copy deployment analysis based on content similarity, benefit Specific caching base station is determined with the similar value between base station in cluster, considers that the storage of base station itself is empty when simultaneously for file cache Between size, acquire the file set of each node B cache, reduce carrying cost, increase user access content hit rate, Reduce the time delay that user requests access to content.
Detailed description of the invention
Fig. 1 is a kind of base station system illustraton of model of the duplicate of the document caching method based on base station sub-clustering of the present invention.
Fig. 2 is the system after a kind of base station sub-clustering of the duplicate of the document caching method based on base station sub-clustering of the present invention Illustraton of model.
Fig. 3 is a kind of copy caching deployment process of duplicate of the document caching method based on base station sub-clustering of the present invention Schematic diagram.
Specific embodiment
In order to enable those skilled in the art to better understand the solution of the present invention, below in conjunction with the drawings and specific embodiments pair The present invention is described in further detail.
Present invention contemplates that the system mould formed between the small base station and WiFi of dense deployment in super-intensive heterogeneous network Type, as shown in Figure 1, including 1 MBS, S SBS and L WiFi node in system, MBS is located at the center of system, S SBS with Machine is deployed under the coverage area of MBS, and there is also one or more WiFi nodes in each SBS coverage area, and is assumed each Have t user in SBS coverage area, user, which can access WiFi net, also can be used mobile data, network structure using Macro base station centerized fusion management, it is assumed that each small base station can obtain the channel state information between small base station and user；When When user accesses data, the home base stations of request are main serving BSs, then user will receive the small base station in periphery, WiFi node And the interference of macro base station；In view of WiFi signal compares base station signal to the faint of terminal user's interference effect, therefore this hair Bright primary concern is interference effect between base station.It is more by designing when using joint cluster transmission mode under super-intensive network Main interference source can be turned to useful signal by the mode of a base stations united transmission, to greatly promote user rate.When When user UE is to home base stations demand file f, the file data in system can be sent to use by the subchannel k of small base station i Family UE, periphery SBS, MBS and WiFi node, which can generate signal interference to user UE, can also exist, the letter that user UE is received Number intensity are as follows:
First part indicates that user receives the signal strength of home base stations in formula (1), wherein PNAnd PMIt respectively indicates small The transmission signal power of base station and the transmission signal power of macro base station；Base station is equipped with F root antenna, and user terminal has G piece-root grafting by day Line,Indicate the channel matrix between small base station i and user j,Channel square between macro base station and user Battle array,Indicate the signal that small base station i is sent to user, the interference signal that Section 2 indicates that macro base station generates user j in formula is strong Degree, Section 3 indicate to remove small base station i, the signal interference that other small base stations generate user, N0It indicates in signals transmission Value is the white Gaussian noise that 0, variance is 1；The signal that user receives in this way is divided into useful signal PyWith interference signal Pn:
Expression formula based on above-mentioned signal is it can be concluded that user UE receives the Signal to Interference plus Noise Ratio (Signal of signal Interference Noise Ratio, SINR) are as follows:
The data reception rate R of user j can be obtained according to shannon formulaijAre as follows:
Rij=Blog (1+SINRij) (5)
If want promoted user data receive rate, can by increase bandwidth B or improve user Signal to Interference plus Noise Ratio, In short supply due to bandwidth resources, user will not be usually promoted by increasing bandwidth B receives rate Rij, can correspondingly lead to The Signal to Interference plus Noise Ratio of raising user is crossed to reach the requirement for receiving rate；
A kind of duplicate of the document caching method based on base station sub-clustering of the present invention, comprising the following steps:
Step 1: the interference strength size of signal generation is received to the base in super-intensive heterogeneous network to user according to base station It stands and carries out sub-clustering, so that the interference strength that the base station after sub-clustering generates the user of access is minimum；
When sub-clustering, the division range [C of number of clusters amount is defined firstmin, Cmax], numerical value is arranged to the base station number in each cluster Constraint, avoids the gap between cluster and cluster excessive, and itself relevant parameter for defaulting all small base stations is the same, with The increase of distance, the intensity of signal be also gradually reduced generation decline；Next the interference that user can be generated according to small base station Intensity does sub-clustering, will draft interference and minimum in cluster suffered by point user of complete cluster；System model such as Fig. 2 after the sub-clustering of base station It is shown；Based on the cluster-dividing method of base station interference, specifically includes the following steps:
Step (1.1): assuming that base station total number is S, there is t user in each base station range, total number of users is St；Assuming that the number of base station sub-clustering is NA, the collection after sub-clustering is combined into (NA≤ S), needle C is combined into the collection of base station in each clusteri={ CI, 1, CI, 2……CI, m(i=1,2.......NA, m≤S-NA), m is indicated in cluster The number of base station；The objective function of optimization is the sum of minimum base station interference, and expression formula is as follows:
Wherein, PNAnd PMRespectively indicate the transmission signal power of small base station and the transmission signal power of macro base station；Table Show channel matrix corresponding to each user in macro base station and each cluster,Indicate that each user institute is right in small base station and each cluster The channel matrix answered,Indicate macro base station sent to user signal,Indicate other small bases in addition to local useful signal base station Stand signal, the N sent to user0Indicate the white Gaussian noise that mean value is 0, variance is 1 in signals transmission；
Wherein, expression formula constraint condition is as follows:
S.t 1≤Cmin≤NA≤Cmax≤S (7)
1<m≤S-NA (8)
Rk≥γk (11)
Wherein, formula (6) indicates to have divided the sum of interference caused by the whole system of cluster minimum and N0For known constant, formula (7) and (8) indicate ensures to distribute a small base station at least each cluster, in formula (9)Indicate every in macro base station and each cluster Channel matrix corresponding to a user andIndicate channel matrix corresponding to each user in small base station and each cluster；Formula (10) inIndicate the signal that macro base station is sent to user,Indicate that other small base stations are to user in addition to local useful signal base station The signal of transmission；Formula (11) indicates each user data transmission quality of guarantee, wherein RkWhat is indicated is the signal biography of k-th of user Defeated rate, γkIndicate the minimum propagation threshold of k-th of subscriber signal；
Step (1.2): due to the parameter N in optimized expression formula (6)AIt is all that known variables needs are solved with m, St For known constant (S be known constant with t), therefore want to solve optimal NAIt, will be in number using ergodic algorithm when with m According to the N in rangeAIt is calculated one time with each numerical value traversal of m value, sorts, select from small to large according in last all values acquired Take out base station sub-clustering number optimal solutionAnd the base station number optimal solution m in each cluster*；
Step 2: on the basis of sub-clustering result, by the analysis of node B cache content similarity, to base station institute each in cluster The duplicate of the document to be accessed carries out deployment caching, specifically includes the following steps:
Step (2.1): the cache file similarity in cluster between target BS and other interior base stations of cluster is first calculated；
Wherein, the circular of the cache file similarity between two base stations is as follows:
It is assumed that base station a determines that the file set cached is Base station b determines that the file set of caching isFor base station a, b The middle duplicate collection of file is combined intoThen the file similarity between two base stations can indicate are as follows:
Wherein, in formulaIndicate file a1Accessed frequency,Indicate file a2Accessed frequency, with such It pushes away, H indicates the accessed frequency of file, and bottom right mark then indicates corresponding specific reference number of a document；
Step (2.2): setting similarity threshold, in addition to target BS, by the cachings between target BS all in cluster The base station that file similarity is greater than similarity threshold is all stored in new set ρα={ ρα1, ρα2……ραvIn, wherein α is The target BS to be compared, v are to meet the base station number for being greater than similarity threshold L with target BS cache file similarity； And it will set ραIn base station file be all put into set In, whereinIndicate cluster CiIt is interior Then f-th of file in base station marked as u removes set CwIn each base station and target BS common set file, and It will set CwNeeded cache file after middle removal common set file is all stored in set C 'wIn；
Step (2.3): wait for the popularity size of cache file to set C ' according to base stationwIn file do sequence processing, Then according to target BS can memory space from set C 'wIn delete select need dispose caching duplicate of the document and be placed in mesh It marks in base station；
Wherein, according to target BS can memory space from set C 'wIn delete select need dispose caching duplicate of the document The specific formula for calculation of number is as follows:
Wherein, SBSFor the spatial cache size of base station,For for cluster CiThe caching to cache file of interior each base station The sum of capacity, k are the copy number that base station space need to dispose,
Wherein, expression formula constraint condition is as follows:
Max k (14)
0<i≤NA (16)
1<u≤S-NA (17)
L≤ρV, t<1 (18)
Formula (16), (17) expression ensure to distribute a small base station at least each cluster, and t indicates the small base of target in formula (18) It standing, v indicates the base station for being greater than threshold value L with the similarity value of target BS,Indicate cluster CiWait for cache file in interior each base station The sum of capacity, C 'W, jIndicate that, to j file in cache file set, k is the copy number that base station space need to dispose, NAFor base It standing sub-clustering number, i indicates that base station sub-clustering score binding occurrence, S are base station total number, and u is the binding occurrence of base station number in each cluster, ρV, tIndicate the similarity value between target BS t and base station v；
Step (2.4): the iteration that base station each in cluster carries out step (2.1)~step (2.3) as target BS is asked Solution, to carry out deployment caching to the base station duplicate of the document to be accessed each in cluster.
The invention has the advantages that proposition and analysis based on base station clustering method, the interference generated according to base station to user Intensity divides, and the interference strength for generating the base station of the complete cluster of score to the user of access is minimum, it is ensured that the communication matter of user Amount, improves service quality；Copy deployment analysis based on content similarity is determined specific using the similar value between base station in cluster Caching base station, when simultaneously for file cache consider base station itself storage size, acquire the text of each node B cache Part set, reduces carrying cost, increase user access content hit rate, reduce user request access to content when Prolong.
The foregoing is merely a prefered embodiment of the invention, is not intended to limit the scope of the patents of the invention, although referring to aforementioned reality Applying example, invention is explained in detail, still can be to aforementioned each tool for coming for those skilled in the art Technical solution documented by body embodiment is modified, or carries out equivalence replacement to part of technical characteristic.All benefits The equivalent structure made of description of the invention and accompanying drawing content is directly or indirectly used in other related technical areas, Similarly within the invention patent protection scope.

Claims (4)

1.一种基于基站分簇的文件副本缓存方法，其特征在于：包括以下步骤：1. a file copy caching method based on base station clustering, is characterized in that: comprise the following steps: 步骤一：根据基站对用户接收信号产生的干扰强度大小对超密集异构网络中的基站进行分簇，使得分簇后的基站对访问的用户产生的干扰强度最小；Step 1: Clustering the base stations in the ultra-dense heterogeneous network according to the intensity of the interference generated by the base station to the user's received signal, so that the interference intensity of the clustered base station to the accessed user is minimized; 步骤二：在分簇结果的基础上，通过基站缓存内容相似度的分析，对簇内各基站所要存取的文件副本进行部署缓存，具体包括以下步骤：Step 2: On the basis of the clustering result, through the analysis of the similarity of the cached content of the base station, deploy and cache the copies of the files to be accessed by each base station in the cluster, which specifically includes the following steps: 步骤(2.1)：先计算簇内目标基站与簇内其他基站之间的缓存文件相似度；Step (2.1): first calculate the cache file similarity between the target base station in the cluster and other base stations in the cluster; 步骤(2.2)：设定相似度阈值，除目标基站外，将簇内所有与目标基站之间的缓存文件相似度大于相似度阈值的基站全部保存在新的集合ρα中，并将集合ρα中的基站文件全都放入集合Cw中，然后去除集合Cw中每个基站与目标基站的公共集合文件，并将集合Cw中去除公共集合文件后的所有待缓存文件全部存入集合C′w中；Step (2.2): Set the similarity threshold. Except for the target base station, all base stations in the cluster whose cache file similarity with the target base station is greater than the similarity threshold are all stored in the new set ρ α , and the set ρ All the base station files in α are put into the set C w , then remove the common set files of each base station and the target base station in the set C w , and store all the files to be cached in the set C w after removing the common set files into the set. in C'w ; 步骤(2.3)：根据基站待缓存文件的流行度大小对集合C′w中的文件做排序处理，然后根据目标基站的可存储空间从集合C′w中删选出需要部署缓存的文件副本并放置于目标基站中；Step (2.3): Sort the files in the set C'w according to the popularity of the files to be cached by the base station, and then delete the file copies that need to be cached from the set C'w according to the storable space of the target base station. placed in the target base station; 步骤(2.4)：将簇内每个基站作为目标基站进行步骤(2.1)～步骤(2.3)的迭代求解，从而对簇内每个基站所要存取的文件副本进行部署缓存。Step (2.4): Perform the iterative solution of steps (2.1) to (2.3) with each base station in the cluster as a target base station, so as to deploy and cache the file copies to be accessed by each base station in the cluster. 2.根据权利要求1所述的一种基于基站分簇的文件副本缓存方法，其特征在于：在步骤一中，基于基站干扰的分簇方法，具体包括以下步骤：2. a kind of file copy caching method based on base station clustering according to claim 1, is characterized in that: in step 1, the clustering method based on base station interference specifically comprises the following steps: 步骤(1.1)：假设基站总个数为S个，每个基站范围内有t个用户，总的用户数量为S·t个；假设基站分簇的个数为NA，分簇后的集合为 (NA≤S)，针对每个簇内基站的集合为Ci＝{Ci，1，Ci，2......Ci，m}(i＝1，2.......NA，m≤S-NA)，m表示簇内基站的个数；优化的目标函数为最小基站干扰之和，其表达式如下：Step (1.1): Assume that the total number of base stations is S, there are t users within the range of each base station, and the total number of users is S t; assuming that the number of base station clusters is N A , the clustered set for (NA ≤ S ), the set of base stations for each cluster is C i ={C i,1 ,C i,2 ...C i,m }(i=1,2.... ...NA , m≤SN A ) , m represents the number of base stations in the cluster; the optimized objective function is the sum of the minimum base station interference, and its expression is as follows: 其中，PN和PM分别表示小基站的发送信号功率以及宏基站的发送信号功率；表示宏基站和每个簇中每个用户所对应的信道矩阵、表示小基站和每个簇中每个用户所对应的信道矩阵、表示宏基站向用户发送的信号、表示除本地有用信号基站外其他小基站向用户发送的信号、N0表示信号传输过程中均值为0、方差为1的高斯白噪声；Wherein, PN and PM represent the transmit signal power of the small base station and the transmit signal power of the macro base station, respectively; represents the channel matrix corresponding to the macro base station and each user in each cluster, represents the channel matrix corresponding to the small base station and each user in each cluster, represents the signal sent by the macro base station to the user, Indicates the signal sent by other small base stations to users except the local useful signal base station, N 0 means Gaussian white noise with mean value 0 and variance 1 in the signal transmission process; 其中，表达式约束条件如下：Among them, the expression constraints are as follows: S.t 1≤Cmin≤NA≤Cmax≤S (7)St 1 ≤ C min ≤ N A ≤ C max ≤ S (7) 1＜m≤S-NA (8)1＜m≤SN A (8) Rk≥γk (11)R k ≥ γ k (11) 式(7)和(8)表示确保至少每个簇中都分配一个小基站，式(9)中表示宏基站和每个簇中每个用户所对应的信道矩阵以及表示小基站和每个簇中每个用户所对应的信道矩阵；式(10)中表示宏基站向用户发送的信号，表示除本地有用信号基站外其他小基站向用户发送的信号；式(11)表示保证每个用户数据传输质量，其中Rk表示的是第k个用户的信号传输速率，γk表示第k个用户信号最低传输阈值；Equations (7) and (8) represent ensuring that at least one small cell is allocated in each cluster, in Equation (9) represents the channel matrix corresponding to the macro base station and each user in each cluster and represents the channel matrix corresponding to the small base station and each user in each cluster; in Equation (10) represents the signal sent by the macro base station to the user, Represents the signals sent by other small base stations to users except the local useful signal base station; Equation (11) represents the guaranteed data transmission quality of each user, where R k represents the signal transmission rate of the kth user, and γ k represents the kth User signal minimum transmission threshold; 步骤(1.2)：使用遍历算法，将在数据范围内的NA和m值每个数值都遍历计算一遍，根据最后所有求得的值中从小到大排序，选取出基站分簇个数最优解及每个簇内的基站个数最优解m*。Step (1.2): Use the traversal algorithm to traverse and calculate each value of N A and m in the data range, sort the final obtained values from small to large, and select the optimal number of base station clusters. untie and the optimal solution m * of the number of base stations in each cluster. 3.根据权利要求1所述的一种基于基站分簇的文件副本缓存方法，其特征在于：在步骤(2.1)中，两个基站间的缓存文件相似度的具体计算方法如下：3. a kind of file copy cache method based on base station clustering according to claim 1, is characterized in that: in step (2.1), the concrete calculation method of the cache file similarity between two base stations is as follows: 假定基站a确定缓存的文件集合为基站b确定缓存的文件集合为对于基站a，b中文件重复的集合为则a、b两个基站之间的文件相似度ρab可以表示为：Suppose base station a determines that the set of cached files is Base station b determines that the set of cached files is For base station a, the set of duplicate files in b is Then the file similarity ρ ab between the two base stations a and b can be expressed as: 其中，式中表示文件a1被访问的频率，表示文件a2被访问的频率，以此类推，H表示文件被访问的频率，右下标则表示所对应的具体文件编号。Among them, in the formula represents the frequency with which file a 1 is accessed, Indicates the frequency that file a 2 is accessed, and so on, H represents the frequency of file access, and the right subscript represents the corresponding specific file number. 4.根据权利要求1所述的一种基于基站分簇的文件副本缓存方法，其特征在于：在步骤(2.3)中，根据目标基站的可存储空间从集合C′w中删选出需要部署缓存的文件副本个数的具体计算公式如下：4. a kind of file copy caching method based on base station clustering according to claim 1, is characterized in that: in step (2.3), according to the storable space of target base station, delete and select need to deploy from set C'w The specific calculation formula for the number of cached file copies is as follows: 其中，SBS为基站的缓存空间大小，为用于簇Ci内每个基站的待缓存文件的缓存容量之和，k为基站空间需安置的副本个数，Among them, S BS is the buffer space size of the base station, is the sum of the cache capacity of the files to be cached for each base station in cluster C i , k is the number of copies to be placed in the base station space, 其中，表达式约束条件如下：Among them, the expression constraints are as follows: Max k (14)Max k (14) 0＜i≤NA (16)0＜i≤N A (16) 1＜u≤S-NA (17)1＜u≤SN A (17) L≤ρv，t＜1 (18)L≤ρ v, t < 1 (18) 式(16)、(17)表示确保至少每个簇中都分配一个小基站，式(18)中t表示目标小基站，v表示与目标基站的相似度值大于阈值L的基站；表示簇Ci内每个基站待缓存文件的容量之和，C′w，j表示待缓存文件集合中的j个文件，k为基站空间需安置的副本个数，NA为基站分簇个数，i表示基站分簇分数约束值，S为基站总个数，u为每个簇内基站个数的约束值，ρv，t表示目标基站t与基站v之间的相似度值。Equations (16) and (17) represent ensuring that at least one small base station is allocated in each cluster, in formula (18), t represents the target small base station, and v represents the base station whose similarity value with the target base station is greater than the threshold L; Represents the sum of the capacity of the files to be cached by each base station in cluster C i , C′ w, j represents the j files in the set of files to be cached, k is the number of copies to be placed in the base station space, and N A is the number of base stations clustered number, i represents the base station clustering score constraint value, S is the total number of base stations, u is the constraint value of the number of base stations in each cluster, ρ v, t represents the similarity value between the target base station t and base station v.
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