123 results about "Macro base stations" patented technology

The invention provides a network side mobility management method and device, a gateway, a network management server and a base station, and relates to the technical field of communication. The method is applied to a gateway, and comprises the following steps: receiving a first switching request sent by core network equipment; the first switching request carries a first cell code corresponding to the target small base station group and identification information of a source macro base station; obtaining a small base station list under the coverage of the source macro base station according to a neighbor relation information table between the macro base station and the small base station; determining a target small base station corresponding to the first cell code from a small base station list covered by the source macro base station; sending a second switching request to the target small base station; the second switching request carries switching access dedicated resource group information; receiving a switching request confirmation message sent by the target small base station; and sending a first switching signaling to a core network device, wherein the first switching signaling carries the switching access dedicated resource group information. According to the scheme of the invention, the switching from the macro base station to the small base station can be realized.

The invention relates to the technical field of coal mine telecommunication, and discloses a coal mine underground integrated private network coverage system based on a 5G communication and AR double-transmitting selective-receiving technology, an efficient transmission and baseband processing network is constructed by taking a macro base station as a core on the ground and matching with PTN equipment and a BBU, a 5G micro base station and an RRU are deployed under the ground for a complex environment, and low-loss signal coverage is realized through optical fibers. The AR double-transmitting selective-receiving module ensures that underground data are not lost and have no error through redundant coding and double-link transmission; the edge computing module sinks data processing to the underground, reduces transmission delay and optimizes resource allocation; and the system monitoring and interference suppression unit monitors the operation state in real time, performs multi-stage alarm and resists multipath effect and electromagnetic interference, and finally realizes integration of communication above and under the well, reliability of data transmission, high efficiency of resource utilization and stability of system operation, thereby providing solid communication support for safety production, equipment management and control and personnel scheduling under the coal mine.

A method, device and system for performing wireless communication in a wireless communication system that includes a low power node and a macro base station with common baseband and user equipment. The user equipment communicates with the low power node and the macro base station via a plurality of component carriers. The method includes: receiving, by the user equipment, a downlink signal transmitted by the low power node and the macro base station; and transmitting uplink signals to the low power node and the macro base station, wherein the method further includes: transmitting all first uplink signals of the uplink signals to the low power node as a receiving node. Accordingly, efficiency of uplink power control of a terminal may be increased and / or the burden for uplink control channel transmission of a macro cell may be reduced.

The invention belongs to the technical field of signal processing, and discloses an unmanned aerial vehicle sensing task allocation method based on a communication and sensing integrated base station, which comprises the following steps: acquiring a macro base station sensing situation; the macro base station evaluates and calculates the sensing time resource consumption of the sensing integrated base station; the macro base station completes task allocation scheme characterization and problem modeling; the macro base station optimizes an unmanned aerial vehicle perception task allocation scheme; the sensing integrated base station senses the unmanned aerial vehicle and obtains the low-altitude situation of the unmanned aerial vehicle. According to the method, the communication perception common front end and time-division working integrated base station is utilized, the unmanned aerial vehicle perception task allocation method with multi-base-station cooperation is optimally designed, the low-altitude unmanned aerial vehicle perception problem is effectively solved, the time resource utilization rate is greatly improved, and meanwhile, compared with an offline optimal scheme with long time consumption, the method has the advantage that the method is easy to implement. Under the condition that performance is hardly lost, algorithm complexity is greatly reduced, and the requirement for real-time task allocation is met.

The invention discloses an RAN (Radio Access Network) slice resource allocation method based on user association under assistance of an unmanned aerial vehicle, which belongs to the field of mobile communication and comprises the following steps of: constructing a heterogeneous network model consisting of a macro base station, a pico base station, a femto base station and users of three service types in a heterogeneous network area assisted by the unmanned aerial vehicle; a bilateral matching game is adopted to obtain an optimal association scheme of the unmanned aerial vehicle and the ground base station; modeling user association and slice resource allocation problems, and decoupling the problems into two sub-problems; a Lagrangian multiplier method is adopted to solve the problem of user association, and a multi-agent depth deterministic gradient strategy algorithm is adopted to solve the problem of slice resource allocation. According to the method, the game theory, the Lagrangian multiplier method and the multi-agent depth deterministic gradient strategy algorithm are combined, the problems of user association and slice resource allocation in a heterogeneous network scene assisted by the unmanned aerial vehicle are solved, and the effectiveness of the whole system is maximized while different requirements of different types of users are met.

The invention discloses an edge computing unloading and transmitting power optimization method based on a double-leader game, and belongs to the technical field of edge computing and wireless communication networks. A macro-micro heterogeneous three-layer network model is constructed, the model comprises a cloud computing layer, an edge layer and a user layer, the user layer is composed of a plurality of terminal user devices, the edge layer is composed of a plurality of micro base stations, a macro base station and a terminal user are connected through the micro base stations, and unloading of a computing task at the network edge by the terminal user is achieved. According to the method, a Stein Kolberg game model is constructed, a macro base station serves as a main leader, a micro base station serves as an auxiliary leader, and a user serves as a follower to participate in task unloading and power distribution decision making. According to the method, optimal allocation of computing resources and transmitting power can be realized under a game framework, so that the total energy consumption of the system is effectively reduced, and the network performance is improved.

The invention discloses a heterogeneous cellular network task unloading method oriented to location privacy protection, and belongs to the technical field of communication. The invention provides a heterogeneous cellular network task unloading method oriented to location privacy protection, aiming at solving the problem that location privacy leakage is possibly caused when a mobile user unloads a task to a micro base station edge server to which the mobile user belongs in heterogeneous cellular network edge calculation. According to the method, the privacy leakage risk of task unloading is evaluated according to user position distribution, the number of unit tasks to be unloaded and the resource state of each edge server, the position correlation between users and target servers is weakened by using a relay forwarding mechanism of a macro base station, and a deep reinforcement learning method is adopted, so that the task unloading efficiency is improved. And the position privacy risk and the task unloading strategy of the user are dynamically learned and optimized, so that the position privacy protection of the user is effectively realized and the average unit task energy consumption is minimized under the constraint of average unit task tolerance time delay.

The invention discloses an Internet of Vehicles secure unloading and cache optimization method based on a graph neural network, relates to the field of intelligent traffic and edge computing, and aims to solve the problems of low resource scheduling efficiency, insufficient privacy protection and task and cache processing separation of the Internet of Vehicles. The method comprises the following steps: S1, constructing an Internet of Vehicles system model, a communication model comprising a vehicle-roadside unit-macro base station architecture, an orthogonal frequency division multiple access and dedicated short-range communication protocol, and a calculation model comprising local processing and partial remote unloading; s2, Gaussian noise is introduced to realize differential privacy protection, and asynchronous federated learning is combined with a long-short-term memory network to predict task popularity; and S3, constructing a dynamic heterogeneous graph, extracting spatio-temporal features by means of a graph neural network, inputting a near-end strategy optimization algorithm, and jointly optimizing an unloading target, a proportion and a caching strategy. According to the method, the collaborative improvement of privacy security, low system total time delay, high cache hit rate and resource utilization rate is realized, and the method adapts to the dynamic topology and complex task requirements of the Internet of Vehicles.

At a high level, the technology disclosed herein relates to methods, systems, media, etc., for a network coverage optimization engine. In embodiments, network coverage can be optimized by applying particular updates, changes, etc., to a network configuration for one or more coverage areas provided by one or more base stations (e.g., a macro base station, another type of outdoor base station, an indoor cell, a distributed antenna system). For example, the network configuration can be determined based on one or more particular radio frequency (RF) performance metrics for a coverage area being below a threshold. In embodiments, one or more machine learning models may be implemented to predict signal coverage changes upon applying the determined network configuration based on the collected data for the coverage area (e.g., network data, user device network feedback, user device location data, environmental profiles for the coverage area, etc.).

The application discloses a kind of unmanned aerial vehicle base station resource allocation method, device and equipment based on hierarchical game, storage medium, it is related to data communication technical field, including: obtaining the access link transmission information and backhaul link transmission information when macro base station, unmanned aerial vehicle base station and user end carry out wireless information backhaul operation, and the flight position information of unmanned aerial vehicle base station, and the unmanned aerial vehicle base station resource allocation problem is split into the associated relationship optimization problem corresponding to user level and the transmission resource optimization problem corresponding to resource level;The receiving rate of user end and the transmission resource of target base station are modeled respectively to obtain corresponding first game model and second game model;Determine the corresponding target personal utility and target resource backhaul utility of two models in game equilibrium state to obtain the target resource allocation strategy of unmanned aerial vehicle base station for wireless information backhaul operation.This way, the user association state can be accurately analyzed, and the optimal allocation of unmanned aerial vehicle base station resources is realized.

The invention discloses an unmanned aerial vehicle base station resource allocation method and device based on a hierarchical game, equipment and a storage medium, and relates to the technical field of data communication, and the method comprises the steps: obtaining access link transmission information and return link transmission information when a macro base station, an unmanned aerial vehicle base station and a user side carry out wireless information return operation, the unmanned aerial vehicle base station resource allocation problem is divided into an incidence relation optimization problem corresponding to a user level and a transmission resource optimization problem corresponding to a resource level according to the user level and the flight position information of the unmanned aerial vehicle base station; respectively modeling the receiving rate of the user side and the transmission resource of the target base station to obtain a corresponding first game model and a corresponding second game model; and determining a target personal utility and a target resource backhaul utility corresponding to the two models in the game equilibrium state to obtain a target resource allocation strategy for the unmanned aerial vehicle base station to carry out wireless information backhaul operation. In this way, the user association state can be accurately analyzed, and optimal allocation of unmanned aerial vehicle base station resources is achieved.

The present disclosure relates to a model learning method, a model learning device and a storage medium. The model learning method is applied to a macro base station and includes: in response to receiving a model training request sent by an operation maintenance management (OAM) entity, sending the model training request to a first number of micro base stations; wherein the communication coverage range of the first number of micro base stations is within the communication coverage range of the macro base station. Through the present disclosure, the interaction between the macro base station and the micro base station is realized, the task allocation of the trained model is realized, the signal quality number is fast, the data transmission rate is improved, and the utilization rate of the wireless access network is improved.

The invention relates to an air conditioner control method and device for a wireless communication macro base station, and the method comprises the steps: obtaining the log information of each device in the base station, and calculating the average load of a past set time interval based on the log information; on the basis of the obtained average load, the average load of a future set time interval is obtained in combination with the current date, workday information, temperature and moment; based on the obtained average load of the future set time interval, combining with a pre-configured rated load upper limit to obtain an average load rate; and generating a target temperature of the air-conditioning system based on the average load rate, and sending the target temperature to the air-conditioning system. Compared with the prior art, the method has the advantages that the corresponding target temperature acting on the air conditioning system is generated through the load rate of the equipment of the macro station, so that the target temperature can be reduced when the load is small, and the communication quality is not affected while the electric energy consumption of the macro station air conditioning system is reduced.

The present invention belongs to the field of wireless communication technology, and specifically relates to a method for realizing air interface synchronization of 4G signals on an optical fiber repeater and a small base station FPGA. The method comprises the following steps: performing power-on detection on a 4G optical fiber repeater or an integrated small base station to complete device initialization; performing synchronization channel capture configuration on the initialized 4G optical fiber repeater or the integrated small base station, shutting downlink processing of the 4G optical fiber repeater or the integrated small base station, and configuring the device to work in an uplink full-receiving mode; executing a signal processing algorithm in the FPGA of the optical fiber repeater or the integrated small base station, capturing a synchronization channel of a macro base station, and processing the capture correlation of a main synchronization channel; generating a new 10ms pulse according to the captured synchronization channel to complete time synchronization; optimizing the BOM list of a product, reducing a wireless communication module, and reducing material costs; optimizing the structural design of the product, and reducing the space occupied by the product.

Embodiments of the present application provide a distributed virtual cell deployment method, network device and mobile communication network, wherein the present application proposes to deploy one or more virtual base stations by grouping small base stations and setting the first network device between the small base station group and the macro base station in the mobile communication network, and control the number of virtual cells provided by each virtual base station, and respectively provide virtual cell feature information for each virtual base station to configure the virtual cells, so that the multiple small base stations contained in the same virtual cell use the same physical cell identifier and frequency point, and on this basis, record the above information in the neighbor cell relation table. Since the number of virtual base stations is much smaller than the number of small base stations in mutual neighbor cell relation with the macro base station, thus, the purpose of simplifying the neighbor cell relation configuration and reducing the maintenance and operation cost can be achieved. Further, using the neighbor cell relation table for service cell switching management is also more simple, fast and efficient.

A method, device and system for performing wireless communication in a wireless communication system that includes a low power node and a macro base station with common baseband and user equipment. The user equipment communicates with the low power node and the macro base station via a plurality of component carriers. The method includes: receiving, by the user equipment, a downlink signal transmitted by the low power node and the macro base station; and transmitting uplink signals to the low power node and the macro base station, wherein the method further includes: transmitting all first uplink signals of the uplink signals to the low power node as a receiving node. Accordingly, efficiency of uplink power control of a terminal may be increased and / or the burden for uplink control channel transmission of a macro cell may be reduced.

The present disclosure relates to a terminal detection and cell allocation method using image sensing data acquired from a plurality of small base stations (SBSs). A method performed by a macro base station (MBS) of the present disclosure may comprise the steps of: receiving at least one piece of image sensing data from at least one SBS; generating voxel data on the basis of the at least one piece of image sensing data; identifying, on the basis of the voxel data, at least one SBS having a line of sight (LoS) path to at least one terminal; and transmitting, to the identified at least one SBS, information about the at least one terminal having the LoS path.

The application discloses an energy-saving task offloading method considering load balancing and time delay, and comprises the following steps: first, a vehicle networking task offloading model containing a macro base station, a MEC server and a vehicle is established; then, the model is solved by using NSGA-Ⅱ improved based on a BP neural network, so that excellent individuals can be screened by using the BP neural network before a real fitness vector is calculated, and a more excellent offspring solution set is obtained.

The invention provides an inter-base-station switching method and device based on a super cell and network equipment, and relates to the technical field of communication. The method comprises the following steps: a gateway receives a first switching request message sent by a core network, and determines a small base station matched with a super cell identifier in the first switching request message; and after a first switching completion message sent by a target small base station in the small base stations is received, replacing a first real cell identifier, carried in the first switching completion message, of a cell where user equipment under the target small base station is located with a super cell identifier, and sending a second switching completion message carrying the super cell identifier to the core network. The scheme provided by the invention can ensure that the cell identifier reported to the core network is matched with the macro base station identifier of the neighbor cell corresponding to the super cell when the switching is completed, thereby avoiding the core network from misjudging that the switching is failed, and solving the problem that the switching between the base stations is failed due to the fact that the small base stations in the super cell possibly belong to different gateways.

The invention provides an indoor distribution cell uplink interference suppression method, an indoor distribution cell uplink interference suppression device and a storage medium, which are applied to an indoor distribution RRU, and the method comprises the following steps: receiving a configuration message sent by an indoor distribution BBU; and adjusting the uplink power offset value based on the configuration message to suppress the uplink interference of the macro base station on the indoor distribution cell under the same-frequency networking. According to the invention, the uplink power offset is adjusted based on the configuration message, the uplink power attenuation of the indoor distribution cell is increased, the uplink boundary moves towards the indoor distribution base station side, and the range of a problem area is narrowed, so that the uplink interference of the macro base station on the indoor distribution cell is reduced under the scene that the macro base station and the indoor distribution base station are networked at the same frequency, and the user experience is improved. And meanwhile, the utilization rate of spectrum resources is ensured, the throughput rate of downloading and uploading services by the user is also improved, and the experience feeling of the user is improved.

The embodiment of the present disclosure relates to an optimization method for content placement and transmission based on scalable video coding. The method comprises: constructing a wireless cache network; in the content placement stage, a macro base station transmits cached files to edge devices; in the content transmission stage, a user sends request information to an edge device in a cell; if the edge device has cached the requested content, the edge device directly transmits the requested content to the user; if the edge device does not store the requested content, the macro base station directly transmits the requested content to the user; in the content placement stage, an optimization problem for minimizing user transmission delay is constructed and solved to obtain an optimal cache strategy; in the content layer transmission stage, an optimization problem for maximizing user sum rate is established and solved to obtain an optimal transmission strategy. The embodiment of the present disclosure effectively improves the efficiency of file transmission, reduces transmission delay, and improves the service quality of users.

The present invention proposes a smart energy-saving method for base stations based on a fuzzy logic system and deep reinforcement learning, belonging to the field of base station energy saving. Specifically, in a communication scenario with macro base stations and micro base stations, each micro base station reports its user and base station information to the macro base station in real time. The macro base station counts the total number of all users in the scenario and determines whether it changes. If so, the macro base station uses an energy-saving access algorithm based on fuzzy logic and deep reinforcement learning to obtain the energy-saving control strategy of the micro base stations and the access base station selection strategy of the users, and issues them to the micro base stations for execution, taking into account both base station energy saving and user experience. Otherwise, each micro base station uses an energy-saving handover algorithm based on fuzzy logic to adjust the user access distribution in real time, thereby further preventing emergencies. The present invention balances the contradiction between energy saving and user service quality; utilizes the prediction ability of the energy consumption evaluation factor for future energy consumption to perform predictive user handovers and make a more proactive response to emergencies.

Disclosed in the present invention are an unmanned-aerial-vehicle on-demand spectrum transaction system and method based on a two-level Stackelberg game. The system comprises: a macro base station, which serves as an authority and is used for supervising a spectrum transaction; a micro base station, which is used for storing and managing general movement situations and resource states of unmanned aerial vehicles in a region, and uploading to the macro base station transaction records of spectrum resource buyers and sellers, wherein an unmanned aerial vehicle chooses to become a transaction subject on the basis of its own spectrum resource conditions and resource demands, a participant with an increased communication demand serves as a buyer of an unmanned-aerial-vehicle spectrum, and a participant having free spectrum resources becomes a provider of the unmanned-aerial-vehicle spectrum; and an unmanned-aerial-vehicle user that is used for providing a communication service for a mobile user to satisfy user demands having low latency requirements. In the present invention, an optimal pricing and transaction volume strategy in a two-level Stackelberg game is effectively calculated by using a gradient-based iterative search algorithm, and a higher total system utility is obtained and the requirements of users for a transmission rate and quality of service are satisfied, thereby improving the spectrum transaction volume and the spectrum utilization rate.

The invention provides a network optimization method, device and equipment based on geometry and deep learning fusion, and belongs to the field of network resource allocation. The method comprises the following steps: generating random distribution of a macro base station, a road side unit and a vehicle by adopting a Poisson point process so as to construct a topological structure of a communication network; constructing a channel analytic function of the communication network according to the topological structure; deriving an analytic function to obtain a performance analysis result of the communication network; constructing a deep deterministic policy network by taking an analysis result as a precondition; in combination with a deep deterministic policy network and a near-end policy optimization algorithm, resource allocation and power control of the communication network are jointly optimized to obtain a preliminary communication network; and performing local optimization on the preliminary communication network according to the optimization limiting function to obtain a target communication network. By combining stochastic geometry, a deep learning algorithm and local optimization, the wireless network performance is effectively improved, the link outage probability is reduced, and the resource utilization efficiency is improved.

The invention relates to the technical field of cell dynamic networking planning, in particular to a cell dynamic networking planning method for a distributed base station system, and the method comprises the steps: enabling the distributed base station system to comprise macro base stations and micro base stations, and recording the macro base stations and the micro base stations as base stations; forming a user group set of any base station by identity codes of users communicating with any base station within a preset duration, and determining a user track weight of each user at each moment; determining the base station overlapping degree between any two base stations; randomly generating individual vectors on the basis of the possible condition that each micro base station is divided into a cell to which each macro base station belongs; determining the self-adaption degree of each individual vector; and based on the self-adaption degree of each individual vector, obtaining an optimal individual vector by using a genetic algorithm, and performing cell dynamic networking planning on the distributed base station system. According to the invention, the rationality of cell dynamic networking planning is improved, and the communication quality is improved.

The application provides a mobility management method and device, electronic equipment and storage medium, and relates to the technical field of communication. The method comprises the following steps: a gateway performs a cell switching operation based on a target super link, so that a UE is switched from a macro base station to a target small base station, the target super link is a link established between the gateway and a core network element according to a first macro base station identifier corresponding to a target super cell; when a first switching notification message sent by the target small base station is received, the gateway determines a second switching notification message according to the first switching notification message, the first switching notification message carries a base station identifier corresponding to the target small base station, and the second switching notification message is used for notifying the core network element that the UE has been switched to the target small base station; and the gateway sends the second switching notification message to the core network element through the target super link, the core network element provides services for the UE through the target small base station, and the successful switching of the UE from the macro base station to the small base station under the super cell scheme is realized.

This invention discloses a method for determining the weather boundary based on 5G service migration characteristics, comprising: acquiring historical rainfall data covering 5G cells, extracting service migration characteristics and corresponding weather conditions from the data for regression analysis, and establishing a weather boundary determination model based on 5G service migration characteristics; monitoring and extracting service migration characteristics one from real-time service data of 5G cells, and inputting it into the weather boundary determination model to obtain weather condition one; extracting cells with weather boundaries in weather condition one, and determining the weather boundary between the cells based on macro base station information within the cells. The weather boundary determination method disclosed in this invention can achieve more refined weather monitoring. By incorporating dense 5G data, it can effectively improve the resolution of weather boundaries and determine them more accurately; simultaneously, based on existing 5G equipment, it does not incur additional costs.

The invention relates to an ocean traffic communication platform which comprises a three-section type buoy frame structure, the three-section type buoy frame structure is provided with a communication cabin, an energy cabin and a ballast cabin, protective barriers are installed on the communication cabin, the energy cabin and the ballast cabin respectively, and trusses are installed on the tops of the energy cabin and the ballast cabin respectively. The tops of the two trusses are connected to the bottoms of a communication cabin and an energy cabin respectively, a 5G macro base station, a satellite antenna, a microwave relay antenna and a transparent antenna are deployed at the top of the communication cabin, a lightning rod is installed in the middle of the top of the communication cabin, and a solar panel is installed on the energy cabin. And an energy storage battery pack, a wave / wind driven generator, a communication processing unit and a master control room are mounted in the energy cabin. According to the technical scheme, the dual-mode structural design is adopted, flexible switching between fixing and moving of the platform is achieved through the modular buoy system and the telescopic anchoring device, and the requirements of different sea areas are met.

1. Name of the design product: Large base station (BS01). 2. Use of the design product: For data storage and network connection. 3. Design key points of the design product: Lies in the shape. 4. Picture or photo that best shows the design key points: Perspective view.

The application discloses a home base station switching method, device, equipment and medium. The method is applied to a macro base station and comprises the following steps: obtaining home base station information in capability information of an access user equipment; when receiving a switching measurement report of the user equipment, issuing a measurement instruction to the user equipment, and switching the user equipment into a target home base station corresponding to the home base station information according to the home base station information and the measurement report fed back by the user equipment. The home base station information is written into the capability information of the user equipment, so that the information of the target home base station can be obtained from the capability information of the user equipment when the user equipment is switched from a macro base station cell to a home base station, and the switching process is completed. Therefore, the switching can be completed without configuring adjacent area and adjacent station information in the macro station, that is, without establishing an SCTP connection, so that the problem that the adjacent area of the macro base station is limited is avoided. The automatic switching of the home base station is realized, and the experience of users is improved.