28 results about "Collision rate" patented technology

The invention discloses a complex environment information acquisition method based on a sensor network, and relates to the technical field of sensor networks, and the method comprises the steps: building a complex environment portrait and a service level, and generating a scene configuration comprising an information freshness budget, a risk heat map and an alarm threshold; based on scene configuration, configuring mesh wireless networking, time synchronization parameters and candidate relays, and constructing observation configuration and quality rules; and generating a data stream and a real-time queue state according to a self-adaptive sampling strategy and an event mark, calculating an emergency degree and distributing a forwarding probability according to an information freshness budget by combining a candidate relay and a risk heat map, outputting uploaded data and a quality record, completing convergence and grading alarm according to an alarm threshold, and generating a disposal feedback and audit index. The state set, the uncertainty set, the link idle degree and the energy sufficiency are linked under the constraint of the information freshness budget, so that hot spot encryption, low-risk sparseness, reduction of energy consumption and conflict rate and standard observation time efficiency are realized.

Apparatuses, systems, and techniques for enhancing autonomous driving systems. In at least one embodiment, visual input corresponding to an observable environment is tokenized into object-level knowledge and provided to a large language model (LLM). Object-level tokens are processed by the LLM to enhance autonomous vehicle route-planning, reducing trajectory error and decreasing collision rates.

The invention provides an inland river intersection water area intelligent cooperative scheduling method based on multi-model fusion, and belongs to the technical field of inland river intelligent shipping. A three-degree-of-freedom ship kinematics model is adopted to define a ship safety distance, and a state space and an action space are defined; designing a multi-objective mixed reward function; the MADDPG algorithm architecture is improved, and the LSTM is introduced to enhance the time sequence processing capability; a centralized training and distributed execution training mode is adopted, an Actor network processes time sequence data at high frequency, a Critic network provides global value evaluation, and cooperative ship selection and multi-ship cooperative training are combined to improve the cooperative scheduling capability of ships in a complex dynamic environment; a simulation test is carried out based on AIS data, and a scheduling effect is verified by using a reward function, a collision rate, an average speed and an action change stability index. According to the method, the problem of ship scheduling in the inland river intersection water area can be solved, so that efficient dynamic scheduling optimization is realized.

The application discloses a lane change decision-making method and system for automatic driving based on Q-value masking, and belongs to the fields of automatic driving and artificial intelligence. The method adopts a hierarchical decision-making architecture, and decomposes lane change decision-making into two levels of high-level decision-making learning and low-level control execution, and realizes close integration through a Q-masking interface. The method comprises the following steps: constructing a hierarchical decision-making architecture; designing vehicle state representation and a high-level discrete action space, wherein the state comprises normalized scalar information and a time-occupancy grid, and the action comprises five types of no operation, acceleration, deceleration, left lane change and right lane change; a low-level module generates a Q-value mask according to system constraints, prior knowledge and safety detection, and applies the mask to action selection after a deep Q network outputs a Q value; and a double-buffer experience replay strategy is used for network training. The application ensures zero collision rate in the training and testing processes through the Q-value mask, simplifies reward function design, and improves training efficiency and safety.

The invention provides a data transmission method, a communication device, a system and a storage medium, which can be applied to the technical field of wireless communication. In the scheme, when an A-IoT reader monitors that the number of active users in a current cell is sharply increased, a time domain grouping shunting strategy is activated, A-IoT device in the cell is divided into a plurality of subgroups, each subgroup corresponds to a time block in an access period, and each A-IoT device is only allowed to initiate uplink data transmission in a time block window corresponding to the subgroup to which the A-IoT device belongs. According to the scheme, the A-IoT device is required to wait for the specific time block to which the A-IoT device belongs to wake up and establish the connection, and the number of potential users competing for the same resource at any moment is reduced by physically isolating massive concurrent requests on the time axis, so that the signal collision rate is greatly reduced from the source, and the user experience is improved. And stable operation of the A-IoT system under a high load is ensured.

The application provides a multi-base station two-dimensional positioning method based on a pseudo-TDMA mechanism, which requests access by sending a Blink frame by a tag, a main base station allocates a communication time slot and issues an offset, and the tag is aligned to a specified time slot to realize pseudo-TDMA orderly communication; the tag sends a Poll frame in the time slot, and multiple base stations reply a Response frame in turn according to a preset gradient delay to avoid air signal collision; the system monitors time slot drift in real time and corrects through a Response frame feedback; multi-base station ranging data is collected to construct an over-determined equation, QR decomposition is used to solve the least square to obtain a two-dimensional coordinate of the tag, and abnormal base station data is removed and redundant positioning is supported. The application has the beneficial effects that the communication collision and strict network synchronization problems in a high-density scene are effectively overcome, the application has the advantages of low collision rate, high channel utilization rate, high positioning precision and strong fault tolerance, and is particularly suitable for large-scale personnel positioning in complex environments such as underground.

The application relates to the field of natural language processing, and discloses a risk text accurate semantic recognition method based on an improved deep learning model, which comprises the following steps: calculating the displayable width of a target segment by a character width counting rule and setting an upper limit, and establishing a trigger variable that automatically changes with a delivery condition; defining a display function under the width constraint to generate visible texts in different trigger states. Further, a trigger variable group is determined for each visible text, and a collision rate index is calculated based on the prior probability of the trigger variable, which is used to quantify the overlap degree of the multi-trigger mapping. Then, according to the index, masking sampling is performed after the trigger position to generate an input sequence, and segment representation is obtained through multiple sampling of the deep learning model; then, an adjustment parameter is calculated according to the collision rate index to adaptively adjust the temperature and noise of the model, and finally, a risk score is obtained through input of a classification layer.

The invention discloses a learning automaton directional communication method for a flight ad hoc network, and belongs to the field of wireless network communication based on directional antennas. According to the method, each node is driven to autonomously select a communication action in each communication time slot in a probability control mode, wherein the communication action comprises entering a receiving mode or initiating directional transmission to a certain neighbor; the node performs online updating on the action probability vector according to the feedback of communication success or failure to realize dynamic optimization of the communication strategy; a fairness regulation and control mechanism is adopted, role deviation is determined according to historical sending and receiving behaviors of nodes, and the role deviation is fused into target probability distribution to maintain balance of communication roles. The method does not need centralized control in the application process, is low in calculation complexity, has completely distributed, adaptive and self-learning capabilities, and is suitable for a resource-limited platform; the method improves the throughput of a directional communication system, reduces the collision rate, achieves the fair access between nodes, and is suitable for large-scale unmanned aerial vehicle network communication in a low-altitude economic scene.

The invention discloses a distributed database multi-dimensional weight distribution unified Hash collision suppression method, which comprises the following steps of: adopting the same basic Hash function in data exchange and Hash table processing, and sequentially performing multi-layer processing of bit folding, non-GF (2) domain multiplication transformation and secondary folding on an initial Hash value, so as to obtain a uniform Hash collision suppression result. Therefore, differential hash results with low statistical correlation and uniform distribution are derived; according to the method, the relevance of Hash collision in different stages is effectively broken, the overall collision rate is greatly reduced on the premise of maintaining a single Hash architecture of the system, the execution efficiency of connection and aggregation operation is improved, and meanwhile, the code maintenance complexity is greatly reduced.

The invention discloses an automatic driving lane change decision-making method and system based on a Q value mask, and belongs to the field of automatic driving and artificial intelligence. According to the method, a hierarchical decision architecture is adopted, a lane change decision is decomposed into two levels of high-level decision learning and low-level control execution, and tight integration is realized through a Q-masking interface. The method comprises the following steps: constructing a hierarchical decision-making architecture; vehicle state representation and a high-level discrete action space are designed, the state comprises normalized scalar information and a time sequence occupation grid, and the action comprises five types including no operation, acceleration, deceleration, left lane change and right lane change; the low-layer module generates a Q value mask according to system constraints, priori knowledge and security detection, and the deep Q network outputs a Q value and then applies the mask to perform action selection; and performing network training by using a double-buffer empirical playback strategy. According to the method, the zero collision rate in the training and testing process is ensured through the Q value mask, the reward function design is simplified, and the training efficiency and safety are improved.

This invention relates to the field of autonomous driving technology and provides a method and system for automatically generating reversing routes. The method includes: acquiring a map of the vehicle before reversing, the vehicle's initial pose before reversing, and the pose of the final parking space; generating an initial reversing path using a reverse Reversing Route (RRT) algorithm; during the optimization process of the RRT algorithm, using a search function, selecting the node corresponding to the minimum value of the search function as the parent node of the target pose; continuing until all node poses in the random tree have reached the final parking space pose; extracting the initial reversing path based on the parent node relationships in the random tree; smoothing the initial reversing path to obtain the optimal reversing path, and displaying it in a holographic imaging system. This invention generates an initial reversing path using an improved reverse RRT algorithm and smooths it to obtain the optimal reversing path, which can reduce the collision rate of the vehicle waiting to reverse and improve the safety of reversing.

The present application relates to the technical field of communications, and provides a communication method and apparatus. After a first device fails in random access, the first device determines, on the basis of first information, whether a random access resource to be accessed when random access is re-performed is a first resource used for random access for a plurality of services or a second resource dedicated to random access for a first service. On this basis, the first device can clearly determine which random access resource to select for re-access, thereby improving data processing efficiency. In addition, in the present application, different first devices are distributed across different random access resources for access, thereby reducing the access collision rate and improving the access success rate.

This invention relates to the field of wireless communication technology, providing a method, apparatus, device, medium, and product for generating wide-spaced frequency hopping sequences to resist tracking interference. It utilizes finite fields, residual rings, and number theory to construct a set of frequency hopping sequences that simultaneously possess low collision and wide-spaced characteristics. The method includes: S1, generating a set of frequency hopping sequences based on finite fields; S2, generating a set of frequency hopping sequences on residual rings based on finite fields; and S3, constructing a new set of frequency hopping sequences based on the original set and the current set, serving as the WG-LHZ-FHS sequence set. This invention, by designing a frequency hopping strategy with low collision and wide-spaced characteristics, achieves a lower frequency collision rate in the low-collision region while ensuring a large gap between adjacent frequency hopping intervals. This prevents the next hopping carrier frequency from falling into the carrier frequency of the tracking interference, improving the multiple access capability and anti-interference capability of the FHMA system, thereby enhancing the overall performance of the communication system.

This application discloses a LoRa wireless resource allocation method, apparatus, and storage medium. The method includes: acquiring node information and channel information forwarded by a gateway; obtaining a corresponding adjustment strategy through a neural network based on the node information and the channel information; setting node parameter values ​​according to the adjustment strategy and sending them to the gateway; generating a corresponding reward value and a next state based on a preset reward function; placing the reward value and the next state into an experience pool; and training and updating the neural network based on the data in the experience pool. This reduces the collision rate of data in the LoRa channel, reduces transmission latency, and increases the number of IoT devices that can be connected to a single gateway.

The application discloses a data security union processing method and system, belongs to the technical field of data management, solves the problem that due to the inherent defect of hash algorithm, hash collision cannot be completely avoided, the introduction of cross-shard retrieval will destroy the shard parallelism, significantly increase the merging complexity, and lead to the problem that the shard number matching may cause the actual associated data to be scattered in different shards due to hash collision and cross-shard retrieval is needed. Including the following steps: dynamic sharding, according to the data heat of the primary key. Through the dynamic sharding, distributed bloom filter conflict pre-checking and local redirection query technology, combined with multi-thread parallel processing and real-time load balancing optimization, the proportion of cross-shard retrieval caused by hash collision is limited, the hash collision rate is reduced while the shard parallelism is ensured, the super large data set is merged, and the problem that the shard number matching may cause the actual associated data to be scattered in different shards due to hash collision and cross-shard retrieval is needed.

The application discloses a kind of based on receiving alignment dynamic MAC protocol implementation method.Compared with land wireless network protocol, underwater acoustic network protocol needs to consider space-time uncertainty.The existing receiving alignment idea proposes to arrange node sending time from the quantitative point of view, to realize high channel utilization, low data collision rate.But this idea has not been put into network protocol, and the low-load scene, dynamic scene and high error code characteristics of underwater acoustic channel are not considered.Aiming at the above problems, the application optimizes the data transmission efficiency in the low-load scene by increasing control information.Through the design of the initialization phase, network nodes can obtain the global information required for operation, and through the design of the restart phase, the protocol can run stably in multiple dynamic scenarios such as node exit or join, node failure or recovery.Aiming at the high error code characteristics in underwater acoustic channel, the protocol increases the Ack feedback mechanism, improves the transmission success rate of the protocol through timeout retransmission and fast retransmission.

The invention relates to the technical field of computers, and discloses an electronic tag online detecting and marking method and system. The method comprises the following steps: modeling a software defined radio detection node as a cellular automaton cell; constructing a distributed non-cooperative game model based on neighborhood information, and optimizing conflict probability and energy consumption by taking frequency and power as strategy space; dynamically adjusting radio frequency parameters and broadcasting the state; executing self-organizing anti-conflict detection, and identifying effective tags through matching of signal intensity and timestamps; and generating and writing a unique mark instruction. The system is composed of a plurality of detection nodes with state sensing and game decision-making capabilities. According to the scheme, high throughput, low conflict rate, high robustness and energy efficiency optimization in an ultra-high density scene are realized.

This invention discloses an intelligent cooperative spatial modulation method and system based on GNN-MARL, mainly addressing the antenna resource competition and energy efficiency issues in multi-user spatial modulation systems. The method includes: first, establishing a multi-user interference graph model to abstract the interference relationships between users into a graph structure; second, using a graph attention network for feature extraction and message passing to update the environmental awareness embedding; then, employing multi-agent reinforcement learning, where each user agent independently selects distributed antennas based on local embedding; subsequently, combining Polar code channel coding and CCDM probabilistic shaping techniques to spatially modulate and map information bits for transmission; and finally, performing joint detection and decoding of the signal at the receiving end. This invention not only effectively reduces the large-scale computational complexity of the system but also significantly reduces the antenna collision rate and average transmit power, greatly improving system throughput. For example, in an 8-user scenario, it controls the collision rate to 19.6% and achieves a power saving of 32.8%, providing an efficient and practical innovative solution for intelligent network distributed resource management.

The application discloses a kind of mMTC slice random access control method and system based on beam splitting and combining.The method obtains preamble collision rate of beam in mMTC slice;Beam splitting and combining are carried out according to preamble collision rate, and the beam configuration parameters of mMTC slice after beam splitting and combining are determined;Wherein, beam splitting and combining include: beam splitting or beam combining;Beam parameters of all beams in the mMTC slice are updated based on the beam configuration parameters, and the beam parameters are broadcast to the mMTC device in the mMTC slice based on the bifurcation type SIB1 broadcast beam, so that the mMTC device accesses the mMTC slice;So as to realize the preamble collision rate by splitting beam is reduced, and the access success rate of mMTC device is improved;By combining beam, system running overhead and power consumption are reduced.

The invention discloses a multi-agent reinforcement learning SCMA network resource allocation method and device and a medium, and the method comprises the steps: taking a specified machine type communication device as an independent agent, and selecting an SCMA resource block for uplink data transmission according to a local Q table; the base station receives uplink data transmission signals of the multiple agents, determines the number of competitors on each SCMA resource block, and calculates a final reward composed of a basic reward and a direct collision punishment for each agent; the base station feeds back a final reward to the intelligent agent through a downlink channel; and the agent updates a locally maintained Q table according to the received final reward. According to the method, the benefit approaching behavior of the intelligent agent can be effectively inhibited, the problems of resource collision concentration and system performance reduction under high load can be solved, the intelligent agent can be guided to form more balanced global resource occupation distribution with fewer conflicts, and the packet loss rate and collision rate of the system under the scene close to saturation and overload are reduced.

The invention discloses a terminal login access method based on satellite communication contention window dynamic management, and aims to solve the problem of large-scale terminal centralized network access of a low-orbit satellite LoRa system in the scenes of satellite maintenance, fault recovery or network restart and the like by constructing a superframe / multiframe / time slot access structure. A contention window dynamic adjustment mechanism based on collision rate feedback is introduced, and a priority backoff access strategy is combined, so that adaptive configuration of the length of the contention window is realized. Compared with the existing random access or fixed superframe multiframe access scheme, the time required for completing the access of all terminals is shorter under the condition of the same terminal login scale.

This invention discloses a multi-protocol intelligent adaptation communication switching system and method for four-way vehicles, belonging to the field of four-way vehicle communication technology. The system includes: acquiring communication signal characteristics and bus status data of the on-board perception module of the four-way vehicle; generating protocol adaptation configuration data through multi-protocol blind identification and virtual address mapping; iteratively optimizing the bus using a double-buffered ping-pong architecture and FPGA scheduling logic until the signal collision rate, bit error rate, and switching latency meet the standards, and outputting a protocol adaptation ready signal; performing seamless multi-protocol switching and bus transmission according to a time slot allocation strategy and polling priority, and collecting frame-level transmission data in real time. This invention solves the problems of heterogeneous communication protocols, bus conflicts, and high latency of multiple types of perception modules in four-way vehicles, achieving multi-protocol adaptive adaptation and seamless switching, and improving communication reliability and real-time performance.

The application discloses a protocol frame header conflict avoidance method, device and equipment and a storage medium, relates to the technical field of data transmission, and is applied to a sending end of data communication and comprises the following steps: using replacement data to replace conflict data in original data frames to obtain first data frames; determining a conflict rate according to the data amount of the conflict data and the original data frames; dynamically selecting a single-layer bitmap structure or a multi-layer bitmap structure according to the size of the conflict rate to generate a bitmap label; adding a hierarchical identifier at the head of the bitmap label and adding a check bit at the tail to obtain a complete bitmap; and adding the complete bitmap at the tail of the first data frames. The application detects and replaces data identical to frame headers at the sending end, adds a bitmap at the tail of a data packet to mark a replacement position, and generates the bitmap according to the frequency of the conflict data to dynamically select a proper bitmap structure, so that the problems of low data transmission efficiency, high processing complexity, long processing delay, insufficient robustness and rigid bitmap design are effectively solved.

The application discloses a terminal login access method based on satellite communication competition window dynamic management, and aims at the large-scale terminal centralized network access problem of a low-orbit satellite LoRa system under the scenarios of satellite maintenance, fault recovery or network restart, etc., constructs an access structure of superframes / multiframes / time slots, introduces a competition window dynamic adjustment mechanism based on collision rate feedback, and combines a priority backoff access strategy to realize adaptive configuration of the competition window length. Compared with the existing random access or fixed superframe multiframe access scheme, the application is shorter in time required for completing access of all terminals under the condition of the same terminal login scale.

The invention belongs to the technical field of data processing, model optimization and transaction management, and provides a flow source judgment method and system under multi-platform trial-investment flow interference, and the method specifically comprises the steps: firstly obtaining a conversion transaction object from a server, recognizing a contact event according to a log of the transaction object, and carrying out the recognition of the contact event; the method comprises the following steps of: firstly, establishing a monitoring window of a contact event to obtain a corresponding contact sequence, calculating an address field convergence value and a pixel convergence value, finally, performing time sequence analysis according to the address field convergence value and the pixel convergence value of each transaction object to obtain attribution hijacking loss, and eliminating attribution contribution of hijacking transactions through the attribution hijacking loss. The convergence change of an address field identifier obtained by mapping a request source IP and a screen resolution pixel identifier is utilized to quantify the public feature homogenization collapse degree caused by multi-platform concurrent trial-casting so as to fit the occurrence intensity of attribution logic hijacking caused by sharp increase of a fingerprint collision rate; and the stability of flow source judgment under the condition of multi-platform simultaneous trial-casting is improved.

The application discloses a low-overhead Top-k network flow high-precision extraction method, comprising: a small flow filter, which is used for filtering most small flows in a network, reducing resource overhead, and reducing a hash collision rate; and a large flow extractor, which is used for extracting Top-k flows in the network and improving the accuracy of Top-k flow identification. The method proposes an adaptive updating strategy based on a counter over-value proportion. Whenever the proportion of the number of counters exceeding a threshold value in the small flow filter is too high, each counter records whether it exceeds the threshold value in the current period through a flag bit, and then is reset to enter the next period, so that the continuous effectiveness of the small flow filter is maintained. Meanwhile, the large flow extractor is designed by using a segmented hash algorithm, multiple candidate positions are provided for incoming flows, and when all the candidate hash buckets are full, a replacement strategy is carried out through a voting mechanism, so that small flows can be kicked out as much as possible each time, and large flows can be saved in the hash buckets, and therefore the accuracy of Top-k flow extraction is improved.

The utility model relates to the field of TCAS (Traffic Collision Avoidance System) testing, and discloses a TCAS comprehensive testing system which is connected with tested equipment in a wired or wireless manner. The TCAS comprehensive test system comprises a computer test system, a display test system, a panel test system, a manipulation test system, a switch test system, an optical transceiver test system, a computer switching test system and a voice control device test system, and the system performs real-time test, realizes connection with a tested component, and is convenient to use. Data excitation, data receiving, data processing and other testing steps of all finished products are completed through the system, reliability, correctness and integrity acceptance of TCAS component function performance is achieved, the air anti-collision rate is reduced, and the standardization, modularization and serialization level is improved.