17 results about "Heterogeneous wireless network" patented technology

The invention discloses a multi-access network intelligent selection system and method in a 5G network environment, and the system comprises a multi-network state sensing module, a service feature recognition module, an intelligent access decision module, a network switching control module, and a strategy updating and learning module. According to the present service type and service quality demand dynamic optimization, communication performance and user experience are considered, an access decision-making mechanism with an adaptive learning capability is constructed, experience can be accumulated along with time, a strategy can be continuously optimized, the frequency and cost of network switching are controlled, the communication continuity is ensured, unnecessary switching risks are reduced, and the network switching efficiency is improved. The method is suitable for various actual scenes such as a 5G mobile terminal, a vehicle-mounted communication device and an industrial terminal, the communication performance and the overall use experience of the terminal device in the 5G environment under the multi-network access condition are effectively improved, and a basic support is provided for achieving heterogeneous network convergence and intelligent communication.

The invention belongs to the technical field of power grids, and discloses a power grid heterogeneous wireless network matching game access method based on ideal solution ordering approximation, in a heterogeneous network environment, the invention provides a matching game model, realizes optimal resource allocation between equipment and a network, comprehensively considers equipment priority, network performance and energy consumption constraints, and realizes optimal resource allocation between the equipment and the network. And meanwhile, real-time environment change is adapted through a dynamic adjustment strategy. Aiming at the requirements of communication reliability and time delay, a priority matching mechanism of high-priority equipment is designed, and a standby network is quickly switched through a fault-tolerant mechanism under the condition of link interruption, so that the communication stability is guaranteed. Through a distributed lightweight algorithm, the calculation complexity is reduced, the method is suitable for remote area equipment with limited resources, the reliability, efficiency and adaptability of a power grid communication system are integrally improved, and an innovative solution is provided for stable operation of an intelligent power grid.

The invention discloses an ultra-dense heterogeneous wireless network access control method fusing prediction and reinforcement learning, and the method comprises the steps: simulating a movement track of a user through employing an SLAW model, and carrying out the normalization of the movement track; inputting the normalized moving track into the LSTM model, and outputting a predicted coordinate of the next moment; calculating the received signal strength of the user to the current access network and all other candidate networks under the predicted coordinates, and judging whether to trigger a network switching mechanism in advance according to the received signal strength; for a network switching decision problem, constructing a Markov decision model by defining a state space, an action space and a reward function; when a network switching mechanism needs to be triggered in advance or a preset decision period is reached, solving the Markov decision model by using a DDQN algorithm, selecting a target network from the candidate networks, and switching to the target network; according to the invention, the response speed and accuracy of network switching can be effectively improved, so that the user experience and the network performance are improved.

Embodiments for automatically tuning a heterogeneous wireless network are disclosed herein. In one example, performance data is received for a plurality of wireless networks. The wireless network is based on multiple wireless technologies and the performance data is based on multiple layers of a wireless technology protocol stack. One or more configuration settings to be adjusted for the one or more wireless networks are determined using the performance data. The determined configuration setting (s) is then adjusted.

The application discloses a dynamic control method and device of a base station of a heterogeneous wireless network, electronic equipment and a medium. Through application of the technical solution of the application, each data base station can feed back the traffic demand of the next moment predicted by the data base station based on the real-time mobile position of a user and a traffic prediction model to a control base station in the heterogeneous wireless network. The control base station can adjust the running state of one or more data base stations based on the overall traffic demand of the data base stations in the network. Thus, on the one hand, the data base station can combine the mobile position of the user when predicting the traffic to improve the prediction accuracy. On the other hand, the globality and stability of the regional network traffic distribution prediction are ensured, and the opening and closing of the data base station are dynamically controlled according to the real-time traffic demand of the network, so that the network energy consumption is reduced.

The invention discloses a random access control system and method for a heterogeneous wireless network, and belongs to the field of communication technology and artificial intelligence cross technology, and the system comprises a node agent module which is used for controlling a transmission control signal of an reflection type multiple access node radio frequency circuit; the observation agent module is used for periodically collecting state interaction data of all nodes in a plurality of time slots and generating semantic observation feedback and sending probability disturbance terms; the reflection agent module is used for performing strategy reasoning through the fine-tuned large language model and generating semantic reflection including specific strategy adjustment suggestions; the strategy agent module is used for updating a global sending strategy; and the memory module is used for storing state interaction data, semantic observation feedback, semantic reflection and a historical global sending strategy. According to the method, the dependence of a traditional deep reinforcement learning method on the GPU computing power is greatly reduced, and a reliable data transmission guarantee is provided for a high-real-time industrial communication system.

This application discloses a method for scheduling transmission resources in a heterogeneous wireless network. The method includes: obtaining service type field information of data to be transmitted, the service type field information including priority and transmission service quality requirements; determining a transmission mode based on the priority field information; determining a transmission path based on the transmission mode and transmission service quality requirements field information; and sending the data to be transmitted to a receiver based on the transmission path. This invention also discloses a heterogeneous wireless network transmission resource scheduling system, corresponding apparatus, and storage medium. The heterogeneous wireless network transmission resource scheduling method provided in this application can realize on-demand matching of communication methods and service requirements, improving the transmission service quality of different services.

The application claims a cross-zone cooperation adaptive handover decision method in an ultra-dense heterogeneous wireless network, belonging to the field of mobile communication, and specifically comprising the following steps: first, an improved Kalman filter position prediction model is obtained according to the historical trajectory information of a vehicle, and the positions of the terminal at two time points are predicted. Second, the candidate network set for handover and hopping is generated in advance according to the predicted positions. Then, by defining a hopping factor and using an interval number multi-attribute decision algorithm of modified Jaccard similarity, a cross-zone cooperation adaptive handover decision scheme is proposed to generate an optimal handover strategy for the terminal. Finally, experimental simulation shows that the algorithm can reduce the handover times of the vehicle-mounted terminal, reduce the handover failure rate and improve the transmission efficiency of the network.

A system described herein may maintain models that associate inputs such as handover source information, handover target information, and User Equipment (“UE”) information, with outputs such as handover thresholds. The models may be generated based on handover interruption metrics associated with a plurality of handovers performed with respect to one or more UEs that are associated with the particular UE information. The system may receive a request for handover threshold information, and may select the particular model, where selecting the particular model includes determining that the request is associated with handover source information, handover target information, and UE information associated with the particular model. The system may output, in response to the request, handover threshold information associated with the particular model. A particular UE may use the set of handover thresholds to determine whether to perform a handover from a particular handover source to a particular candidate handover target.

The application discloses a random access control system and method for a heterogeneous wireless network, and belongs to the technical field of communication technology and artificial intelligence, and comprises the following: a node agent module for controlling the transmission of control signals of a reflective multiple access node radio frequency circuit; an observation agent module for periodically collecting state interaction data of all nodes within multiple time slots, generating semantic observation feedback and transmission probability disturbance items; a reflection agent module for performing strategy reasoning through a fine-tuned large language model, generating semantic reflection including specific strategy adjustment suggestions; a strategy agent module for updating a global transmission strategy; and a memory module for storing state interaction data, semantic observation feedback, semantic reflection and historical global transmission strategies. The application greatly reduces the dependence of traditional deep reinforcement learning methods on GPU computing power, and provides reliable data transmission protection for high real-time industrial communication systems.

A system for integrating heterogeneous wireless networks, an edge-computing device, and a method for operating the same. The system includes an in-vehicle device installed in a vehicle and an edge-computing device installed in a vehicle station. The in-vehicle device generates streaming data to be transmitted via heterogeneous wireless networks. When the vehicle approaches the vehicle station, the in-vehicle device performs a handover process in response to a signal strength indicator for switching connectivity between the in-vehicle device and the edge-computing device. The edge-computing device uses a switch to perform network convergence while receiving heterogeneous wireless networking data, and uses a streaming proxy to perform source switching on the converged data received from the switch without interruption during the handover process.

The present application relates to the technical field of wireless network communication, in particular to a heterogeneous wireless network cross-system handover decision optimization method and system, the steps comprising: collecting five-layer cross-layer attribute vectors of candidate networks at a preset period to construct a multi-dimensional decision attribute matrix; performing short-term prediction on the signal quality of the current service network through a GM(1,1) grey prediction model to trigger the handover process in advance; performing admission filtering on the candidate networks based on a service QoS demand vector; using a deep Q network to adaptively output the optimal weight vector of each decision attribute; constructing a handover cost penalty vector through a handover fatigue factor and a predicted residence time; calculating a comprehensive score based on the improved TOPSIS method by fusing the weight vector and the penalty vector, and introducing a retention threshold to make a handover decision; and continuously optimizing the weight strategy through reward feedback after handover. The present application can effectively reduce the service interruption probability, improve the handover decision accuracy in multiple scenarios, and reduce the overall handover cost.

The invention discloses a heterogeneous wireless network transmission resource scheduling method, and the method comprises the steps: obtaining the service type field information of to-be-transmitted data, and the service type field information comprises a priority and a transmission service quality demand; determining a transmission mode based on the priority field information; determining a transmission path based on the transmission mode and the transmission service quality demand field information; and sending to-be-transmitted data to a receiver based on the transmission path. The invention also discloses a heterogeneous wireless network transmission resource scheduling system, a corresponding device and a storage medium. According to the heterogeneous wireless network transmission resource scheduling method provided by the embodiment of the invention, on-demand matching of communication means and service requirements can be realized, and the transmission service quality of different services is improved.

This application discloses an interference management method, apparatus, electronic device, and medium for heterogeneous wireless networks. By applying the technical solution of this application, when a portion of data base stations in a heterogeneous wireless network shut down due to a deteriorating network environment, the control base station can provide data services to the disconnected terminals. Furthermore, the control base station instructs the target data base station to aggregate new model parameters obtained from training the currently deployed interference management model, so that the interference management model deployed on each data base station is updated based on the re-aggregated updated model parameters. This enables data base stations in heterogeneous wireless networks to obtain the latest interference management model matching the current network environment in real time to manage interference for each device in the wireless network.

This disclosure relates to a wireless edge caching method based on full-duplex relay in a heterogeneous wireless network. The method includes: constructing a heterogeneous wireless network; wherein the heterogeneous wireless network includes a core network, macro base stations, relay stations, and multiple users; employing a random caching strategy based on Scalable Video Coding (SVC) technology, whereby a video content server located in the core network pre-places some files requiring caching in the local cache of the relay stations; users sending request information to the relay stations; and analyzing the transmission rate and successful transmission probability in the heterogeneous wireless network. This disclosure employs a random caching scheme based on SVC under full-duplex relay to improve data transmission rate, achieving better caching efficiency, improving the user's content experience quality, and effectively alleviating network congestion problems.

The embodiment of the application relates to the technical field of information physical system, in particular to an event-triggered information physical system wireless resource optimization method and system, the method comprises the following steps: obtaining the corresponding relationship between a packet loss rate and a transmission power of a sending end and a selection probability of a cellular network based on a bit error rate; introducing an event triggering mechanism at a controller end, optimizing the data transmission times between the controller and an actuator; analyzing the stability of a closed loop system after the event triggering mechanism is introduced, and obtaining a constraint condition for stabilizing the closed loop system; taking the constraint condition as a constraint, constructing a multi-objective optimization function; solving the multi-objective optimization function by using a genetic algorithm, and obtaining an optimal triggering coefficient, an optimal transmission power and an optimal cellular network selection probability under the premise of guaranteeing system performance. The optimization method provided by the application can balance the communication energy saving, system performance and data transmission cost of a unit-level CPS in a heterogeneous wireless network.

This disclosure provides a method for adaptive vertical handover in heterogeneous wireless networks, a terminal device, and a computer-readable storage medium. The method includes: acquiring a time series of the received signal strength of a first network; obtaining a predicted value of the received signal strength based on the time series; obtaining a prediction error based on the measured value of the received signal strength and the predicted value of the received signal strength, and obtaining a link fluctuation index based on the prediction error at multiple times; calculating a threshold shift amount based on the link fluctuation index, and synchronously shifting the reference handover threshold and reference handover back threshold of the first network by the threshold shift amount to generate a dynamic handover threshold and a dynamic handover back threshold; and when the terminal is currently connected to the first network, switching from the first network to a second network in response to the predicted value of the received signal strength being less than the dynamic handover threshold; and when the terminal is currently connected to the second network, switching from the second network to the first network in response to the measured value of the current received signal strength of the first network being greater than or equal to the dynamic handover back threshold.