7results about How to "Ensure communication efficiency" patented technology

This invention discloses a control method and a wireless communication circuit. The control method includes: a processing module acquiring current channel status information of the current operating channels corresponding to at least two communication paths, and sending the current channel status information to a co-frequency coexistence confirmation module; the co-frequency coexistence confirmation module confirming the channel status between each pair of current operating channels based on the current channel status information; and, if the channel status between each pair of current operating channels satisfies a first channel status, the processing module performing a channel reallocation operation on the current operating channels of the communication paths to obtain target operating channels corresponding to each communication path, wherein the channel status between each pair of target operating channels satisfies a second channel status. This invention enables wireless communication systems to reduce co-frequency interference while communication paths operating in the same frequency band are working simultaneously, thus ensuring communication quality and efficiency.

The application discloses a method for constructing a MAC protocol of a UAV network, a transmission process of data packets with different priorities is modeled by a finite state Markov chain, and a cross-level priority promotion mechanism based on failure counting is introduced. The method aims to solve the problem of long-term blocking of low-priority services caused by traditional fixed-priority protocols in post-disaster emergency communication scenarios, thereby improving the overall throughput, reducing the average delay, and enhancing the fairness among multiple types of services while ensuring the strict service quality of high-priority services.

This invention provides a parameter self-learning signal control method based on cloud-edge collaboration, solving problems such as heavy reliance on traffic parameter configuration, excessive dependence on training samples, and difficulty in achieving real-time, all-weather, and all-scenario application of traffic signal algorithm control. The method mainly includes: collecting traffic holographic trajectory data and performing edge-sensing signal control; extracting holographic sensing control parameters from the holographic data through a parameter self-learning method; establishing a cloud-edge collaborative control architecture, interacting with parameter self-learning data, and controlling traffic signals in real time. By determining the traffic state of each phase through holographic data, employing the parameter self-learning method, and establishing a cloud-edge collaborative control system, it achieves all-weather, all-scenario application of traffic control, possessing advantages such as strong real-time control capabilities, adaptability to various traffic flow conditions and scenarios, and avoiding the computational power and trial-and-error costs required for parameter learning.

The invention discloses a multi-card cluster inter-card communication synchronization system and synchronization method. The system comprises a first list construction unit, a second list construction unit and board card nodes, the first list construction unit is used for constructing an ordered list based on the board card nodes in the communication board card set; the second list construction unit is used for determining a destination node list and a source node list of the board card node in the communication process based on the ordered list; a synchronous lock list constructed based on the ordered list is stored in a shared memory of the board card node, and the board card node is used for setting a synchronous lock identifier in the synchronous lock list based on the destination node list and the source node list in the communication process so as to realize state synchronization between the board cards. According to the method, state synchronization is achieved by maintaining the synchronization lock list in the shared memory, complexity caused by using a traditional synchronization primitive is avoided, dependence on hardware is reduced, the single-point bottleneck problem caused by a centralized root process can be avoided, and communication efficiency is effectively guaranteed.

The invention discloses a DQN-based network-on-chip arbitration intelligent optimization method, and belongs to the field of computer system structure network-on-chip interconnection. In an application task execution process, data packet arrival information of an input port of an on-chip network router is collected in real time, time density characteristics and fluctuation characteristics reflecting traffic intensity and time sequence fluctuation characteristics are extracted, and operation state information such as a router cache utilization rate, a port competition degree and an injection rate is combined, so that the data packet arrival information of the input port of the on-chip network router is obtained. And multi-dimensional state description of the router is constructed. A plurality of candidate basic arbitration strategies are preset, a deep Q network reinforcement learning model is adopted, and dynamic selection is carried out among the candidate arbitration strategies according to real-time router state information, so that a better arbitration strategy is selected under the constraint of communication delay and power consumption. Through continuous interactive learning with a network-on-chip operation environment, the method can adaptively match arbitration strategies under different load and flow scenes, effectively reduce communication delay and tail delay, and improve communication efficiency and energy efficiency of the network-on-chip.

This invention discloses a GPU ensemble communication method, system, device, medium, and product. The method first maps ensemble communication interfaces from different GPU device manufacturers to a unified standard API interface based on GPU device manufacturer information, generating an interface mapping relationship. When responding to a ensemble communication request initiated by a user calling the API interface, the method translates the ensemble communication request into a corresponding manufacturer's ensemble communication interface request based on the GPU type used by the user and the interface mapping relationship, thereby invoking the corresponding manufacturer's ensemble communication interface to perform ensemble communication operations. Using this invention can reduce the development and maintenance complexity of multi-GPU ensemble communication systems and improve the overall performance and efficiency of distributed training of AI models.

This application relates to a battery communication system and its operation method. The battery communication system is used for communication among several battery cells. The operation method of the battery communication system includes the following steps: In a wireless daisy-chain communication path of the battery communication system, a first wireless communication unit transmits a transmission signal to an adjacent second wireless communication unit via a wireless transmission or coupling method. In the wireless daisy-chain communication path of the battery communication system, the first wireless communication unit and the second wireless communication unit execute an automatic power control program to automatically adjust the output power of one of the first wireless communication units.