5 results about "Cognitive user" patented technology

The application discloses a decision fusion method, device and system for wideband spectrum sensing. The decision fusion method comprises judging the type of cognitive user. If the cognitive user is a reference cognitive user, the original decision symbol sequence of the cognitive user is kept and sent to a fusion center so that the fusion center makes a fusion decision. If the cognitive user is a non-reference cognitive user, the original decision symbol sequence of the cognitive user is extended to obtain an extended decision symbol sequence. Then, the extended decision symbol sequence is subjected to segmentation and majority voting operation in sequence to obtain a compressed decision symbol sequence, wherein the compressed decision symbol sequence has the same length as the original decision symbol sequence of the reference user. Finally, the compressed decision symbol sequence is sent to the fusion center so that the fusion center makes a fusion decision. The application can ensure the reliability of spectrum sensing, significantly reduce the system sensing and transmission overhead, and improve the energy efficiency and realizability of cooperative spectrum sensing.

The invention discloses an Internet of Vehicles spectrum allocation method, apparatus and device, and a medium, and belongs to the technical field of vehicle communication. The method comprises the following steps: acquiring the total bandwidth of a frequency spectrum of a base station, the number of terminal users connected with the base station, the idle bandwidth of an idle frequency spectrum, an alternative coefficient of the frequency spectrum, and the service security weight, the unit frequency spectrum income and the transmission frequency spectrum efficiency of each cognitive user; the service security weight is used for representing the security of the service; according to the total bandwidth, the number of the terminal users, the idle bandwidth, the replaceable coefficient, the security weight of each service, the income of each unit spectrum, the efficiency of each transmission spectrum, a preset authorized user profit function and a preset cognitive user profit function, the bandwidth of each service is obtained; and determining the optimal shared bandwidth rented to each cognitive user in the idle spectrum and the optimal unit spectrum renting price given by each cognitive user. According to the method, the idle spectrum of the authorized user can be allocated to the cognitive user, and the utilization rate of the spectrum is improved.

The invention discloses an SVM (Support Vector Machine) cooperative spectrum sensing method and system based on PSO (Particle Swarm Optimization), and relates to the technical field of cognitive radio. The system at least comprises a cognitive user, an authorized user and a fusion center, an authorized user, namely a primary user (PU), transmits a signal in an authorized frequency band, and the signal is influenced by path loss and fading in a propagation process; a cognitive user is a secondary user SU, a plurality of SUs are randomly distributed in a network, energy sampling is periodically carried out on a target frequency band, and local observation data are obtained; the fusion center, namely, FC, receives observation data uploaded by each SU and is used for unified judgment; and a PSO module and an SVM judgment module are deployed at the fusion center. According to the method, a hyper-parameter automatic optimization module based on particle swarm optimization (PSO) is introduced into a fusion center, so that a kernel parameter and a penalty factor of an SVM classifier can be adaptively adjusted under the conditions of a dynamic channel and different signal-to-noise ratios, and a better compromise is obtained among detection precision, robustness and calculation efficiency.

The invention relates to the technical field of cognitive radio, in particular to a self-adaptive perception threshold setting method and device based on main user power detection, and the method comprises the following steps: 1, calculating a high threshold and a low threshold of cognitive users SU, sending a signal-to-noise ratio of a received signal to a fusion center by each SU, and calculating a weighting factor of each user, each SU adaptively adjusts a decision threshold according to the weighting factor; 2, the SU compares the current energy with a decision threshold value, if the current energy is larger than a high threshold value, it is judged that a primary user PU exists, and if the current energy is between the high threshold value and a low threshold value, the average value of the historical energy queue is taken as the current energy, and the next round of detection is started; 3, if the average value of the historical energy is between the high threshold value and the low threshold value, calculating a single threshold value; and step 4, determining that the PU exists as long as one cognitive node detects the signal. According to the method, the processing efficiency of the algorithm is improved, and the detection performance of energy detection can be remarkably improved.

This invention proposes a spectrum switching method for cognitive radio networks that comprehensively considers information age and energy consumption. The method is applicable to narrowband sensing cognitive radio networks with preset information age and energy consumption weight parameters. N The method consists of one authorized user and one cognitive user, with each authorized user assigned an authorized channel. Based on the relative value iterative algorithm theory, a spectrum switching strategy related to information age and energy consumption weight parameters is designed. The effectiveness of the method is ensured by constructing a value function and a relative value function that reflect the influence of the weight parameters and proving the convergence of the functions. Then, the convergence value and threshold structure of the proposed strategy are obtained through iterative calculation. Specifically, at the beginning of each time slot, the cognitive user updates its state based on the switching and transmission decisions of the previous time slot. Based on Bayesian theory, it estimates the occupancy status of each channel using the obtained local known information and channel information. Then, by comparing the expected information age and energy consumption cost of all channels, it determines the channel selected for the current time slot and decides whether to transmit data packets based on the channel perception results.