CN113411862B - Cache placement and user access method and device in dynamic cellular network - Google Patents
Cache placement and user access method and device in dynamic cellular network Download PDFInfo
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Abstract
The application discloses a cache placement and user access method and device in a dynamic cellular network. The method comprises the steps of initializing cache placement and user access of the base station in a random mode according to the number of the base stations, the number of users and the number of cacheable contents in the cellular network; obtaining user access information by using a belief propagation algorithm in a short time scale according to the distribution position of the base station and the cache placement information; according to the distribution position of the base station and the user access information, obtaining cache placement information by using a depth certainty strategy gradient algorithm on a long-time scale; and repeating iterative calculation to obtain final cache placement and user access information. By adopting the technical scheme, the cache placement and the user access are jointly optimized on the basis of introducing the cache in the cellular network, so that the average transmission delay can be reduced, and the user experience can be improved.
Description
Technical Field
The present application relates to the field of cellular network communications technologies, and in particular, to a method and an apparatus for cache placement and user access in a dynamic cellular network.
Background
In recent years, with the popularity of mobile devices and the increasing maturity of multimedia applications, mobile data traffic and content diversity have increased explosively, and traditional network architectures have been unable to accommodate such rapidly increasing traffic. Research on content distribution technologies for mobile internet applications in cellular networks has become a hotspot. Aiming at the problems of network congestion and backhaul link overhead caused by the repetition of a large amount of data content generated by the distribution of mobile internet data content, the concept of edge cache is provided in a cellular network, and the transmission of repeated content on a backhaul link is avoided at the network edge through hot content cache, so that the burden of the backhaul link is reduced, the response time of a content request is reduced, and the system performances such as spectrum efficiency, energy efficiency, transmission delay, backhaul cost, throughput and the like can be optimized.
Because the user follows twenty-eight distribution when requesting the file, most flow is composed of a small part of content, and the content is cached in the base station, the repeated transmission of the same content in the backhaul link is avoided, the time delay of content transmission is reduced, the network bandwidth resource is saved, and the backhaul link pressure is reduced. However, the application of the edge caching technology faces the contradiction between the limited storage space of the base station and the requirement of massive content, and therefore, the problem of placing the multimedia content in the caching space, namely the caching placement, is particularly important for multimedia content distribution in a mobile network. In addition, the cache placement strategy is strongly coupled with the user access strategy, the cache strategy directly influences the deployment of the user access strategy, and the user access result indirectly influences the design of the cache strategy. Therefore, it is also very critical to what strategy a user accesses the base station while considering the buffer placement.
For a communication network composed of a plurality of base stations with cache devices and a core network, the work of the predecessors does not consider cache placement and user access to be optimized jointly while considering the mobility of users, the change of content popularity and the diversity of channel environments. First, in practical applications, the user location, the user request, and the wireless channel environment all change dynamically, and the optimization at a certain point in time cannot guarantee the optimization over a long period of time. And in a practical scenario, the wireless channel environment dynamically changes in milliseconds as much as time units, and the popularity change interval is relatively slow and much. Due to dynamic changes in user location and channel environment, user access should change in a short time scale. On the other hand, the popularity of the content changes slowly. For example, a newly released movie may continue to be popular for the first few days and then may become less popular. Since content cache placement is largely influenced by content popularity. The content cache placement should change over a longer time scale. If the content cache placement and the user access decision are placed on the same time scale, the edge server needs to frequently update the cached service, and considering the memory capacity and bandwidth limitation of the edge server, frequent updating of the service cache is unrealistic and can bring extra burden to the system, and the user experience can be reduced. Secondly, the current position of the user determines the relative position between the base station and the user, i.e. the signal-to-interference-and-noise ratio between the base station and the user, thereby influencing the user access. When a base station accessed by a user can provide local cache for the user, the user has better user experience, namely cache placement and user access are mutually influenced. Therefore, how to provide a policy to enable a user to obtain requested content quickly is an urgent problem to be solved.
Disclosure of Invention
In order to solve the problems in the background art, the method and the device for cache placement and user access in the dynamic cellular network are constructed, and the problems of cache placement and joint optimization when the content popularity is unknown in the dynamic network environment are researched aiming at the base station cache in the cellular network, so that the network throughput is improved, the system delay and the overhead are reduced, and the like.
The application provides a cache placement and user access method in a dynamic cellular network, comprising the following steps:
initializing the cache placement and user access of the base station by a random mode according to the number of the base stations, the number of users and the number of cacheable contents in the cellular network;
repeatedly and iteratively calculating user access information by using a belief propagation algorithm according to the distribution position of the base station and the cache placement information until the time frame is finished;
and repeatedly and iteratively calculating cache placement information by using a depth certainty strategy gradient algorithm according to the distribution position of the base station and the user access information until the algorithm converges or reaches an iteration threshold value, and obtaining the final cache placement and user access information.
The above-mentioned cache placement and user access method in a dynamic cellular network, wherein, in the information initialization processor, the cache placement X of the base station is initialized in a random manner according to the number of base stations, the number of users and the number of cacheable contents in the cellular network 0 Subscriber access L 0 To obtain communication information between the initializing base station and the user.
The cache placement and user access method in the dynamic cellular network, as described above, wherein, after inputting the base station distribution location and the cache placement information in the time frame in the optimal user access processor, according to the user location information input in each time slot, a belief propagation algorithm is used to solve the optimal user access in the time slot; the cache placement information is a cache placement initial value X in the primary calculation 0 。
The cache placement and user access method in the dynamic cellular network, wherein the user access information is obtained by using a belief propagation algorithm, specifically includes the following sub-steps:
inputting cache placement information, randomly initializing user access information, and setting the maximum iteration times;
constructing a factor graph, converting the problem of solving the optimal user access into an unconstrained optimization problem, mapping the optimization problem onto the factor graph, and initializing message values between function nodes and variable nodes;
updating message values between the function nodes and the variable nodes according to a belief propagation algorithm calculation rule, and updating the belief of each variable node;
and after one-time belief propagation is finished, judging whether the belief is converged, if not, continuing to carry out belief propagation until the maximum iteration times is reached, and if so, obtaining the optimal user access information of the time slot.
The cache placement and user access method in the dynamic cellular network as described above, wherein, in the base station optimal cache allocation processor, according to the input base station distribution position and the user access information in the last time frame, the optimal base station cache placement X is obtained by using a depth deterministic policy algorithm; and obtaining a base station cache placement scheme of the time frame by utilizing a depth certainty strategy algorithm according to the input base station distribution position information, content popularity information and user access information, and determining the cache placement scheme by calculating and comparing transmission time delay of content cached in the base station.
As described aboveThe cache placement and user access method in the dynamic cellular network, wherein the solution of the base station cache placement scheme is mapped into a Markov decision process, wherein the state space S is the state E of the content popularity T And a represents the action set, i.e. the cache placement policy,
representing an instant reward; the long-term loss of motion is described by defining the Q value in a small motion space, specifically expressed as
Wherein 0 ≦ γ < 1 represents a discount factor; in each iteration, according to the user access strategy L in the T-1 time frame t ,L 2t ,L,L nt Get the best solution for user transmission delay and content popularity in T time frame
I.e. the optimal cache placement scheme X T 。
The cache placement and user access method in the dynamic cellular network as described above, wherein the best user access L of each time slot in the time frame is obtained by using a belief propagation algorithm according to the base station cache placement information and the user location information of each time slot in the current time frame t Will { L t ,L 2t ,L,L nt Using the data as input, and obtaining optimal cache placement information X through a depth certainty strategy gradient algorithm; and repeatedly calculating the user access information and the cache location information until the maximum iteration times is reached to obtain the final cache location and user access information.
The present application further provides a cache placement and user access device in a dynamic cellular network, comprising: the system comprises an information initialization processor, an optimal user access processor, a base station optimal cache allocation processor and an optimization control processor;
the information initialization processor is connected with the optimal user access processor and used for initializing the system;
the optimal user access processor is connected with the optimal cache allocation processor and the information initialization processor of the base station, and the optimal user access information is obtained by utilizing a belief propagation algorithm according to the input base station position distribution information, the user position distribution information and the cache information;
the base station optimal cache distributor is connected with the optimal user access processor and the optimization management processor, and obtains optimal cache distribution information by adopting a depth certainty strategy gradient algorithm according to the input base station position distribution information, the popularity information of the time frame and the user access information in the previous time frame;
the optimization control processor is connected with the optimal user access processor and the optimal cache allocation processor, outputs optimal cache placement and user access information in the current iteration process, judges whether the iteration times are less than the maximum iteration times, and starts a new iteration if the iteration times are less than the maximum iteration times; otherwise, ending the processing process and outputting the final cache placement and user access information.
The present application also provides a base station on which the cache placement and user access device in a dynamic cellular network is deployed.
The beneficial effect that this application realized is as follows:
(1) the idea of caching is introduced into a cellular network, and the advantages of base station communication and caching are combined by deploying a caching device in a base station, so that the time delay for acquiring required content through a backhaul link is greatly reduced, the pressure of the backhaul link is relieved, and the user experience is improved.
(2) Cache placement is optimized jointly with user access on the basis of the introduction of cache in the cellular network. When a user accesses, the relative position of the user and the base station is considered, and the base station with good channel condition is selected for accessing; meanwhile, whether the base station caches the requested content or not can be considered when the user accesses, the preference of the user to the content and the mobility of the user position can be considered when the base station caches the requested content, and compared with a traditional method which is considered and optimized independently, the method can further reduce the average transmission delay and improve the user experience.
(3) The cache placement is solved by adopting multiple time scales and utilizing a long-time scale depth certainty strategy algorithm, and the user access problem is solved by utilizing a short-time scale belief propagation algorithm. The transmission delay is reduced, the pressure of a return link is relieved, and meanwhile, the overhead caused by the updating of the cache content of the system is considered, so that the performance of the whole network is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings can be obtained by those skilled in the art according to the drawings.
Fig. 1 is a schematic diagram of a cache placement and a user access device in a dynamic cellular network according to an embodiment of the present application;
fig. 2 is a flowchart of a cache placement and user access method in a dynamic cellular network according to a second embodiment of the present application;
FIG. 3 is a flowchart illustrating the operation of obtaining user access information using a belief propagation algorithm;
FIG. 4 is a flowchart illustrating the detailed operation of optimizing cache placement.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
As shown in fig. 1, an embodiment of the present application provides a cache placement and user access device 100 in a dynamic cellular network, where the device is deployed on a base station and optimizes cache placement and user access of the entire dynamic cellular network. The device specifically comprises an information initialization processor 110, an optimal user access processor 120, a base station optimal cache allocation processor 130 and an optimization control processor 140; wherein:
and the information initialization processor is connected with the optimal user access processor and used for initializing the system. The system initialization specifically comprises the following steps: constructing a cache allocation indication matrix in a dynamic cellular network according to the number of base stations and cacheable content, and acquiring initialized cache deployment information by using a random cache; and constructing an access indication matrix according to the number of the users and the number of the base stations, and acquiring initialized user access information by utilizing random access.
And the optimal user access processor is connected with the optimal cache allocation processor and the information initialization processor of the base station, and obtains the optimal user access information of the time slot by utilizing a belief propagation algorithm according to the input base station position distribution information, the user position distribution information and the cache information.
And the base station optimal cache distributor is connected with the optimal user access processor and the optimization management processor, and obtains optimal cache distribution information by adopting a depth certainty strategy gradient algorithm according to the input base station position distribution information, the popularity information of the time frame and the user access information of the last time frame.
And the optimization control processor is connected with the optimal user access processor and the optimal cache allocation processor. And the optimal cache placement and user access information in the current iteration process are output in the optimization control processor. Judging whether the iteration times are smaller than the maximum iteration times or not, and starting a new iteration if the iteration times are smaller than the maximum iteration times; otherwise, ending the processing process and outputting the final cache placement and user access information.
Example two
In order to effectively reduce the long-term content transmission delay in the dynamic cellular network, the second embodiment of the present application provides a joint optimization method for cache placement and user access under multiple time scales, which alleviates the backhaul link pressure as much as possible, reduces the system overhead, and improves the user experience.
Scene assumption is as follows: in a communication network formed by a plurality of base stations provided with a cache device, M base stations are distributed, and the set of the base stations is denoted as M ═ 1, 2.., M }; assume cache space coherence for base stationsDenote sbits, where K ═ 1, 2., K } denotes a user set, and Nn ═ 1, 2., N denotes a set of user request files, where the user request files are all available from the core network, and all content sizes are fbits; the whole cache placement process is represented by a time sequence Tn ═ {1, 2., T }, where T represents a time frame, that is, a long time scale, and at each time frame T, cache content deployment and update operations are performed; each time frame is assumed to be divided into a certain number of equal-length time slots T ═ 1, 2.., T, where T denotes a time slot, i.e., a short time scale. p is a radical of m,k Distributing the transmission power for the user K to the base station m; the system bandwidth is B, the average transmission power of the base station m is p m (ii) a User location K ∈ K, c k ∈C＝＝{C 1 ,C 2 ,L,C I C is a user position state set, the user position is shifted once per time slot, and the transition probability is expressed as P { C t+1 |C t }. Popularity E ∈ E ═ E { E ═ E [ ] 1 ,E 2 ,L,E J -content popularity shifts once per time frame, with a transition probability denoted P { E } T+1 |E T }。
As shown in fig. 2, a method for cache placement and user access in a dynamic cellular network includes:
Defining a base station cache placement matrix X belonging to {0,1} n×m N is N, M is M, wherein
The content n of the T time frame is cached in the base station m, otherwise, the content n is 0; defining user access indication matrix L epsilon {0,1} k×m K is K, M is M, where l k,m 1 means that the user k accesses the base station m, otherwise 0; the initial cache placement and the user access are respectively as follows: x 0 ，L 0 ；
In the information initialization processor, the base stations are initialized in a random manner according to the number of base stations, the number of users and the number of cacheable contents in the cellular networkCache Placement X 0 Subscriber access L 0 To obtain communication information between the initializing base station and the user.
the short time scale T in the step is the iteration number of the user access calculation, the whole cache placement process comprises a plurality of (such as k) long time scales, each long time scale comprises a plurality of (such as k ') short time scales T, when the iteration number reaches the maximum value k ' of the short time scales, k ' user accesses are obtained, and then the cache placement calculation of the k long time scales T is performed through the iteration calculation.
In the optimal user access processor, after inputting the distribution position of a base station and the cache placement information in the time frame, solving the optimal user access in each time slot by adopting a belief propagation algorithm according to the user position information input in each time slot; the cache placement information in the initial calculation is the initial cache placement value X in step 210 0 ；
Specifically, as shown in fig. 3, obtaining the user access information by using a belief propagation algorithm specifically includes the following sub-steps:
and 340, judging whether the confidence coefficient is converged after one-time belief propagation is finished, if not, continuing to carry out belief propagation until the maximum iteration times is reached, and if so, obtaining the optimal user access information.
Referring back to fig. 2, step 240, according to the base station distribution position and the user access information, circularly obtaining cache placement information by using a depth deterministic strategy gradient algorithm;
the long-time scale T in the step is the iteration number of cache placement calculation, the whole cache placement process comprises a plurality of (such as k) long-time scales, each long-time scale comprises a plurality of (such as k ') short-time scales T, when the iteration number reaches the maximum value k ' of the short-time scales, k ' user accesses are obtained, and then the cache placement calculation of the k long-time scales T is performed through iterative calculation.
And step 260, finishing iteration, and outputting the final cache placement and user access information.
Specifically, in a base station optimal cache allocation processor, according to an input base station distribution position and user access information at the last moment, an optimal base station cache placement X is obtained by utilizing a depth certainty strategy algorithm; obtaining a base station cache placement scheme by utilizing a depth certainty strategy algorithm according to input base station distribution position information, content popularity information and user access information, and determining the cache placement scheme by calculating and comparing transmission time delay of content cache in a base station;
mapping a solution base station cache placement scheme into a Markov decision process, wherein a state space S is a state E of content popularity T And a represents the action set, i.e. the cache placement policy,
representing an instant reward; the long-term loss of motion is described by defining the Q value in a small motion space, specifically expressed as
Wherein 0 ≦ γ < 1 represents a discount factor; in each iteration, an optimal solution is obtained according to a user access strategy in a T-1 time frame, user transmission delay and content popularity in the T time frame
I.e. the optimal cache placement scheme X T ；
The method aims to optimize cache placement and user access respectively under multiple time scales, minimize content transmission delay and improve system performance on the premise that a base station cache space is limited, namely solving the following optimization problems:
the content request arrivals and departures occur at a shorter time scale than the time scale of the content cache placement decision update. Therefore, the method adopts a time scale separation mode to realize the user access decision and the cache placement decision, and divides the optimization problem into the following two sub-problems: short-time scale user access solving and long-time scale cache placement solving;
(1) short timescale user access solution:
converting the optimization problem into an unconstrained optimization problem:
wherein the content of the first and second substances,
mapping the optimization problem to a factor graph, respectively updating function nodes and variable nodes, circularly iterating until convergence, and outputting optimal user access information L t (ii) a In the time frame, the optimal user access processor calculates and outputs optimal user access information in each time slot;
within t time slot, according to user position C t Content request probability E T With known cache content policy X T The minimum content acquisition delay is obtained as follows:
(2) and (3) long-time scale cache placement solving:
t time frame, optimal user connection { L ] in T-1 time frame based on the solution t ,L 2t ,L,L nt Solving an optimal cache placement decision by taking the minimized long-term content distribution time delay as an optimization target:
when the content requested by the user is cached in the base station in advance, the base station directly provides service for the user without obtaining the content from a core network through a return link, so that the time delay is greatly reduced, and the user experience is improved; the buffer space of each base station is limited, and the purpose of optimizing the buffer placement scheme is to place the content requested by the user accessing the base station in the base station as much as possible; as shown in fig. 4, optimizing cache placement specifically includes the following sub-steps:
Step 420: the operator network outputs a cache placement policy.
Step 430: and solving the optimal user access in the time slot by adopting a belief propagation algorithm.
Step 440: judging whether the short time scale t reaches the maximum iteration time, if so, executing the step 450, otherwise, adding 1 to the iteration time t, and continuing to execute the step 430;
step 460: judging whether the long-time scale T reaches the maximum iteration number, if so, executing a step 470, otherwise, adding 1 to the iteration number T, and returning to execute the step 420;
and 470, finishing the iteration and outputting the cache placement information.
Referring back to fig. 2, step 240, repeat the iterative computation to obtain the final cache placement and user access information.
After the calculation, the cache placement in a time frame and the user access information of each time slot in the time frame are obtained in one iteration; in the optimization control processor, judging whether the current iteration number is smaller than the maximum iteration number, if so, calculating the obtained cache placement and user access information as the input of a new iteration to obtain the optimal cache placement and user access in the next iteration period, and repeating the iteration until reaching a preset iteration number threshold to obtain the final cache placement and user access information; otherwise, ending iteration and outputting optimal cache placement and user access information;
the iteration process specifically comprises the following steps: according to the base station cache placement information and the user position information of each time slot in the current time frame, the best user access L of each time slot in the time frame is obtained by utilizing a belief propagation algorithm t Will { L t ,L 2t ,L,L nt Taking the cache as an input to carry out the next step, and obtaining optimal cache placement information X through a depth certainty strategy gradient algorithm; and repeating the two links until the maximum iteration times is reached to obtain the final cache placement and user access information.
Through continuous iteration of step 220 and step 230 until reaching the maximum iteration number, the optimal cache placement and user access are obtained, the content transmission delay is reduced, and the system performance is improved.
The above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the present disclosure, which should be construed in light of the above teachings. Are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. A method for cache placement and user access in a dynamic cellular network, comprising:
initializing the cache placement and user access of the base station by a random mode according to the number of the base stations, the number of users and the number of cacheable contents in the cellular network;
repeatedly and iteratively calculating user access information by using a belief propagation algorithm according to the distribution position of the base station and the cache placement information until the time frame is finished;
repeatedly and iteratively calculating cache placement information by using a depth certainty strategy gradient algorithm according to the distribution position of the base station and the user access information until the algorithm converges or reaches an iteration threshold value to obtain final cache placement and user access information;
mapping a solution base station cache placement scheme into a Markov decision process, wherein a state space S is a state E of content popularity T ，E T A state representing the content popularity for timeframe T, a represents the set of actions, i.e. the cache placement policy,
representing an instant reward; the long-term loss of motion is described by defining the Q value in a small motion space, specifically expressed as
Wherein gamma is more than or equal to 0 and less than 1, which represents a discount factor, and E is an operation symbol, which represents the mean value calculation; in each iteration, according to the user access strategy L in the T-1 time frame t ,L 2t ,...L nt Get the best solution for user transmission delay and content popularity in T time frame
I.e. the optimal cache placement scheme X T ，L t ,L 2t ,...L nt The best user access information of t and 2t … nt time slots are respectively represented.
2. The dynamic cache placement and subscriber access method in a cellular network as claimed in claim 1, wherein in the information initialization processor, the method is based on a cellular networkThe number of inner base stations, the number of users and the number of cacheable contents, and the cache placement X of the base stations is initialized in a random mode 0 Subscriber access L 0 To obtain communication information between the initializing base station and the user.
3. The cache placement and user access method in a dynamic cellular network according to claim 2, wherein after the base station distribution location and the cache placement information in the time frame are inputted in the optimal user access processor, a belief propagation algorithm is used to solve the optimal user access in each time slot according to the user location information inputted in each time slot; the cache placement information is a cache placement initial value X in the primary calculation 0 。
4. The method of cache placement and subscriber access in a dynamic cellular network as claimed in claim 1, wherein the obtaining of subscriber access information using a belief propagation algorithm comprises the substeps of:
inputting cache placement information, randomly initializing user access information, and setting the maximum iteration times;
constructing a factor graph, converting the problem of solving the optimal user access into an unconstrained optimization problem, mapping the optimization problem onto the factor graph, and initializing message values between function nodes and variable nodes;
according to the calculation rule of the belief propagation algorithm, updating the message values between the function nodes and the variable nodes, and updating the belief of each variable node;
and after one-time belief propagation is finished, judging whether the belief is converged, if not, continuing to carry out belief propagation until the maximum iteration times is reached, and if so, obtaining the optimal user access information.
5. The method of claim 1, wherein in the base station optimal cache allocation processor, according to the inputted base station distribution location and the user access information of the last time frame, a deep deterministic policy algorithm is used to obtain an optimal base station cache placement X; and obtaining a base station cache placement scheme of the time frame by utilizing a depth certainty strategy algorithm according to the input base station distribution position information, content popularity information and user access information, and determining the cache placement scheme by calculating and comparing transmission time delay of content cached in the base station.
6. The method of claim 1, wherein the best user access L per timeslot in the time frame is obtained by a belief propagation algorithm based on the base station buffer placement information and the user location information per timeslot in the current time frame t Will be taken as input, L t ,L 2t ,...L nt Respectively representing the optimal user access information of t and 2t … nt time slots, and obtaining the optimal cache placement information X by a depth deterministic strategy gradient algorithm T (ii) a And repeatedly calculating the user access information and the cache location information until the maximum iteration times is reached to obtain the final cache location and user access information.
7. A cache placement and user access apparatus in a dynamic cellular network, characterized in that the apparatus performs the cache placement and user access method in the dynamic cellular network according to any of claims 1-6; the device specifically comprises: the system comprises an information initialization processor, an optimal user access processor, a base station optimal cache allocation processor and an optimization control processor;
the information initialization processor is connected with the optimal user access processor and used for initializing the system;
the optimal user access processor is connected with the optimal cache allocation processor and the information initialization processor of the base station, and the optimal user access information is obtained by utilizing a belief propagation algorithm according to the input base station position distribution information, the user position distribution information and the cache information;
the base station optimal cache distributor is connected with the optimal user access processor and the optimization management processor, and obtains optimal cache distribution information by adopting a depth certainty strategy gradient algorithm according to the input base station position distribution information, the popularity information of the time frame and the user access information of the last time frame;
the optimization control processor is connected with the optimal user access processor and the optimal cache allocation processor, outputs optimal cache placement and user access information in the current iteration process, judges whether the iteration times are less than the maximum iteration times, and starts a new iteration if the iteration times are less than the maximum iteration times; otherwise, ending the processing process and outputting the final cache placement and user access information.
8. A base station, characterized in that cache placement and subscriber access means in a dynamic cellular network according to claim 7 are deployed on said base station.
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