78 results about "Cognitive wireless sensor networks" patented technology

Two-way (full-duplex) wireless links in facilitating network management and improve network performance. Once aspect includes methods for network management using an overlaid network for control signaling. Another aspects include methods to facilitate practical realization and improve performance of some of the network information theoretic configurations, such as Space-Division Multiple Access (SDMA) in uplink and downlink, Interference Channel, and other forms of distributed collaborative signaling schemes. Another aspect includes methods to support cognitive wireless networks.

The invention provides a coal mine down-hole fire monitoring system based on a wireless sensor network. The system comprises a monitoring host, a communication master station and the wireless sensor network, wherein the wireless sensor network communicates with the monitoring host through the communication master station, is a ZigBee wireless self-organized network and comprises a wireless sensorand a wireless gateway; and the wireless sensor is used for acquiring coal mine safety data and wirelessly transmitting the coal mine safety data and comprises a wireless carbon monoxide sensor, a wireless wind pressure sensor and a wireless temperature sensor. Therefore, according to the coal mine down-hole fire monitoring system based on the wireless sensor network provided by the embodiment ofthe invention, coal mine down-hole fire conditions can be timely and accurately monitored, the energy consumption of a wireless sensor network node can be effectively controlled, and the service lifeof the wireless sensor network can be prolonged.

The invention relates to a cognitive wireless network system with a cognitive radio function and a method for transmitting cognitive streams thereof. Base stations or wireless access points and terminals of the cognitive wireless network are all additionally provided with corresponding functional entities at a physical layer, a radio link layer and a high layer through a layering protocol stack, a centralized physical transmission channel and a distributed physical transmission channel are respectively established, based on a general control channel of the cognitive streams, data and parameters obtained by cognitive nodes through a physical channel are unifiedly represented as information which can be processed by the functional entities for intelligence reasoning and decision-making in the wireless system, and efficient, integral and reliable transmission scheme for cognitive information is realized by joint processing of the functional entities and the channels to lay a foundation for intelligent decision-making and dynamic reconfiguration inside the cognitive nodes in a network. In the invention, as a layering realization mechanism is adopted, the cognitive wireless network system can be flexibly adapted to changes of the network structure and the wireless environment; in addition, the cognitive wireless network system disclosed by the invention is highly compatible with the existing wireless protocol structure, thus having good popularization and application prospects.

The invention discloses a method for spectrum allocation in a distributed cognitive wireless sensor network on the basis of Q study. The average throughput and the average energy efficiency ratio of the maximized distributed cognitive wireless sensor network are taken as objects, nodes in the cognitive wireless sensor network study from one another according to peripheral authorization frequency spectrum state change and allocation strategies of other nodes and finally adapt, the process is mapped into a distributed multi-agent Q study process, and the best spectrum allocation strategy is approximated by executing the best response Q study iterative algorithm in a timing sequence alternation mechanism. The method has the characteristics that the convergence speed is high, the calculation complexity is low, and the average throughput and the average energy efficiency ratio of the cognitive wireless sensor network are improved.

The invention provides a clustering frequency spectrum perception method based on energy consumption in a cognitive sensor network. In the method, an LEACH clustering algorithm based on node energy is introduced. Firstly, the each node in the cognitive sensor network is divided into several clusters according to the clustering algorithm. Then, in the each cluster, a utility function, which can taken detection performance and energy consumption into consideration, is constructed. Based on the utility function, an optimum cooperation user number and a user are selected so that the detection performance and the energy consumption can reach a good compromise in the each cluster. Finally, an OR rule is used on a sink node so as to fuse perception information sent by a cluster head and then a final decision result can be obtained. By using the method of the invention, survival time of the cognitive sensor network can be effectively prolonged. Energy consumption of the network can be saved and the good detection performance can be guaranteed.

The invention provides a method for cross layer resource distribution and grouped dispatch in a cognitive wireless network, which belongs to the technical field of wireless communication. In the method, the following factors are integrally considered: the service priority level of each user in the cognitive wireless network; the line length in a buffer pool formed by sub users waiting for the frequency spectrum distribution and the grouping time-out condition; the minimum speed requirement of the users; and information of the emitting power upper limit of a cognitive wireless base station and the like. The cross layer configuration can be carried out on the parameters of media access control (MAC) layers and physical layers of user sub carrier distribution, dynamic modulation modes, multi-user grouped data service sequence, power and bit distribution and the like according to an improved cross generation elitism selection heterogeneous recombinant cataclysmic mutation resource management (CHCRM) algorithm, and the cross layer integral optimization on the cognitive wireless network is realized. The average time delay of a system is reduced, and the system packet loss is reduced.

The invention relates to wireless network security, particularly to a multi-user reinforcement learning-based cognitive wireless network anti-hostile interference method. Cognitive source nodes adopt a multi-user reinforcement learning strategy to automatically select transmitted power by observation of status information of a master user working condition, self-adaptive jammer transmitted power and the like. Learning of multiple cognitive source nodes is performed at the same time, and each time transmission of a data packet is finished, according to obtained immediate returned report and a state of the next moment, an update state, a behavior and a mapping relation, and according to feedback information, the learning rate of the multi-user reinforcement learning algorithm is replaced, thereby improving the signal to interference ratio of a receiving end, and finally obtaining the optimal transmitted power. Each cognitive source node can assist forwarding of the data packet or transmit data by itself. The method utilizes a multi-user reinforcement learning mechanism, and through a method of attempting and comparison, improves communication efficiency of a cognitive wireless network in a scene of an intelligent hostile jammer.

The invention discloses a life optimization method for retransmission-aware clustered wireless sensor networks. The method comprises steps as follows: preliminarily deploying clustered wireless sensor networks according to a model; establishing an energy consumption model for wireless sensor nodes; establishing a retransmission model for the clustered wireless sensor networks; establishing an energy consumption model for the retransmission-aware clustered wireless sensor networks; establishing a transmission success probability calculation model for the retransmission-aware clustered wireless sensor networks; establishing a life optimization model for the clustered wireless sensor networks under the evenly deployed condition and performing solving. According to the method, the purpose is energy-consumption-aware network life maximization, constraint conditions comprise network connectivity, coverage and the data transmission success probability, the life optimization model for the retransmission-aware clustered wireless sensor networks is established, distances among wireless sensors and the number of deployment layers of the wireless sensors are optimized with a genetic algorithm, and problems that the energy consumption is excessively high, the coverage rate is insufficient, the data transmission success probability is not high and the like are solved.

The invention discloses a cognitive wireless sensor network spectrum access method based on deep Q learning. The cognitive wireless sensor network spectrum access method comprises the following steps:step 1, constructing a Q neural network: selecting a training sample to update a weight parameter of the Q neural network by taking the state values of all channels of a t-2 time slot as an input layer and taking the q values of all channels of a t-1 time slot as an output layer; obtaining an experience sample before the t-1 time slot, calculating the priority, summing the arrangement of the binary tree according to the priority accumulation, and performing sampling to obtain a training sample; step 2, taking the state values of all channels of the t-1 time slot as an input layer, inputting the state values into a Q neural network to obtain q values of all channels of the t time slot, and selecting a channel corresponding to the maximum q value; and step 3, sensing the channel energy, accessing if the state value is idle, and not accessing if the state value is busy. The method has the beneficial effects that the energy consumption is low, the convergence speed is high, the diversityloss of experience samples is avoided, the overfitting phenomenon is avoided, and the prediction accuracy is high.

The invention provides a method and system for managing a wireless sensor node. The method comprises the following steps: the wireless sensor node sends a registration request to a gateway in the event of being accessed in a wireless sensor network; and the gateway establishes registration information and parameters related to security, management and service for the wireless sensor node. By means of the method and system disclosed by the invention, parameters of the wireless sensor node can be configured by the gateway; the normal operation of the wireless sensor network service is ensured; security parameters of the gateway can be configured through a telecommunication network so as to well ensure the security of the gateway for configuring and networking the wireless sensor network subsequently.

The invention relates to a clustering-based multi-hop multi-channel cognitive wireless sensor network communication method. In the method, the frame structure of a node is designed into a segmental structure, and a work period of the node is divided into a channel cognition and selection stage, a channel allocation stage, a data transmission stage and a dormant stage. According to the invention, a media access criteria is designed for the node in each cluster to provide intra-cluster uncontested communication, and at the same time, in order to alleviate problems, such as hidden terminals, etc., with inter-cluster communications, on the basis of the media access criteria, an assignment process in which channel weighing is performed according to the channel state is designed, and in order to better reduce the energy consumption, a channel selection criteria is further designed. The method of the invention can be used to realize advantages of high network throughput, low time delay and low packet loss rate on the basis of reducing the data packet transmission capacity, and is suitable for the spectrum access and spectrum switching strategy in a cognitive wireless sensor network.

The invention discloses a cognitive wireless sensor network MAC (media access control) implementing method in combination of power control, belonging to the technical field of wireless sensors. In the cognitive wireless sensor network MAC implementing method in combination of the power control, selection of a data channel is negotiated on a control channel through a pair of nodes of data to be transmitted, and in a channel selecting process, 1/2 maximum radius coverage including sending end conflict detection and receiving end conflict detection is combined with the conflict detection to implement the MAC. By the cognitive wireless sensor network MAC implementing method in combination of the power control, energy consumption can be effectively saved; the lifetime of the network can be prolonged; and the throughput of the network can be increased by increasing concurrent transmission amount. The cognitive wireless sensor network MAC implementing method aims to make each pair of communication nodes realize communication at a required minimum power.

The invention discloses a multi-relay and multi-antenna-based cognitive wireless sensor network performance optimization method. According to the method, a cognitive wireless sensor network system model with multiple antennas and multiple relays is adopted; multi-relay cooperative cognition, relay selection and beamforming technologies are adopted, and therefore, the throughput of a cognitive wireless sensor network system can be improved, and at the same time, the interruption probability of the system can be decreased. With the method adopted, the accuracy of sensing results of the cognitive wireless sensor network system and high spectrum utilization rate can be ensured, the throughput of the whole system can be reduced, and at the same time, the interruption probability of the overall system can be reduced.

The invention provides a cognitive wireless sensor network spectrum detection method based on node information, namely, a method for efficiently detecting spectrum through a proposed chunking algorithm and a twice-detection mechanism based on sensor node geographical information, so as to improve the detection performance of a CRSN system and improve the energy efficiency of the system. The specific scheme of the invention comprises the following steps: a primary detection mode pre-embedding scheme is designed, and a monitoring area is partitioned based on node geographical location information; a PU (Primary User) is quickly perceived through primary detection, and whether a SU (Secondary User) can quickly access a channel or whether the system needs to enter a secondary detection process can be judged; a FC (Fusion Center) calculates a secondary detection area, the PU is perceived by a more reliable detection method during secondary detection; and data is fused and the state of the PU is judged in order to determine whether the SU can access a channel. By adopting the method of the invention, the detection accuracy and high performance of CRSN can be ensured, and the energy consumption of the network can be reduced.

The invention relates to a decoding forward collaboration-based simultaneous wireless information and power transfer method in a cognitive sensor network. In the method, a source sensor node sends information to a relay sensor node, the relay sensor node segments a received signal by using a power segmentation factor, one part of the signal is used for energy collection and the left part is used for information receiving, and the relay sensor node decodes and forwards the information of the source sensor node to a target sensor node by using all energy E received by the relay sensor node. Themethod fully considers interference of the master user on the cognitive sensor node, so that the performance of the cognitive sensor network can be acquired accurately, further, a sending power of thesource sensor node and a power segmentation factor optimal value of the relay sensor node can be acquired rapidly through a two-step decomposition method.

The invention provides a wireless sensor network routing protocol based on a mobile sink node and ant colony optimization. The mobile sink node is placed on the edge of a sensing area of the wireless sensor network; the sensing area of the wireless sensor network is divided into a plurality of equal parts and each part is a cluster set; a cluster head is determined in each cluster set, other wireless sensor nodes in the cluster set send information to the cluster head, and the cluster head integrates the information in the cluster set; and the mobile sink node finds the optimum path of accessing each cluster head according to the ant colony optimization and then accesses each cluster head in sequence. According to the protocol, the problems of energy holes, non-uniform cluster head distribution and network delay in the prior art are overcome, network traffic loads are mitigated, and a life cycle of the wireless sensor network is greatly prolonged.

The invention discloses a spectrum sensing and information transmission method with energy collection in a cognitive wireless network, comprising the following steps that: a cognitive user utilizes signals from a main user transmitter for spectrum sensing and energy collection, and uses the collected energy for information transmission; in detecting the main user phase, the cognitive user and N cognitive relays jointly detect whether the main user occupies the spectrum; in the reporting phase, the cognitive user activates the energy collection or information fusion function according to whether it detects that the main user is occupying the spectrum; and in the information transmission phase, the cognitive user performs energy collection or information transmission according to the spectrum sensing final decision result. The invention provides working energy for cognitive users, prolongs the service life of cognitive users, and reduces or eliminates periodic battery replacement while obtaining high spectrum sensing performance.

The invention discloses a clustering cooperative spectrum sensing hard fusion method for a cognitive wireless sensor network. All cognitive sensing nodes are clustered firstly, a cluster head of each cluster is selected, the cognitive sensing nodes achieve spectrum sensing according to the signal energy of a master user, local spectrum sensing information is acquired, then first-time fusion is carried out on all the local spectrum sensing information in the clusters through the cluster heads, the spectrum sensing information of the corresponding cluster is acquired, and finally fusion is carried out on the spectrum sensing information of all the clusters through a fusion center to obtain the final spectrum sensing information. Through cluster head screening and two times of fusion, the computation burden of the fusion center is reduced, and the effect of fast judging whether frequency spectrum is free or not and improving the correct probability of detection is achieved.

The invention relates to a wireless communication technology, provides a clustering routing method based on a cognitive wireless sensor network, and the clustering routing method comprises the following steps: dynamic spectrum sensing clustering: clustering nodes in the range of the cognitive wireless sensor network by adopting a hierarchical clustering algorithm in combination with available channels and distances among the nodes obtained by spectrum sensing, and constructing a clustering topological structure; triggering data routing by an event, and forwarding the data triggered by each region of the cognitive wireless sensor network to a sink node in an intra-cluster sink and inter-cluster relay alternate iteration mode according to the constructed clustering topological structure; andadaptive re-clustering based on frequency spectrum change and communication service quality: triggering the cognitive wireless sensor network to perform adaptive re-clustering based on available channel change caused by PU behavior change of a main user or interference of poor clustering effect on the communication service quality. According to the invention, the spectrum utilization rate and theenergy efficiency of the network can be effectively improved while the network monitoring period is prolonged.

A heterogeneous cognitive wireless sensor network clustering routing method relates to the technical field of wireless sensor networks, solves the problems of high energy consumption, short network life cycle, spectrum resource shortage and hardware condition limitation of a wireless sensor network, and comprises the following steps: randomly deploying cognitive nodes and common nodes; judging whether the residual energy of the cognitive node is greater than Emax, if so, forming a cluster head, otherwise, judging whether the residual energy of the cognitive node is less than Emin, if not, exiting, otherwise, randomly selecting a number between [0, 1], comparing the number with the cluster head selection probability, if so, exiting, and otherwise, forming the cluster head; and the non-cluster head node selecting the cluster head to enter the cluster according to the energy magnification times under the free transmission mode and the multipath transmission mode, the distance from the non-cluster head node to the base station and the distance from the non-cluster head node to the cluster head, and determining the cluster head selection probability according to the number of spare channels and the marginal degree. According to the invention, the network energy consumption is reduced, the network life cycle is prolonged, the frequency spectrum shortage is relieved, and the problem of high hardware requirement is avoided.