33 results about "Coverage probability" patented technology

The invention discloses a risk-aware deep learning-driven limit transmission capacity adjustment method, which includes the following steps: embedding the limit transmission capacity predictor into the adjustment model, replacing the most complicated and time-consuming calculation part, and obtaining deep confidence A two-layer model assisted by a network agent; construct a prediction interval based on a deep confidence network, and adjust the prediction interval according to the coverage probability of the prediction interval, the normalized average bandwidth of the prediction interval, and the cumulative bandwidth deviation, and obtain the optimal prediction interval through integrated learning training; Based on the trained prediction interval, the probability R of the TTC value falling within the interval is obtained, and the risk probability of prevention and control failure is evaluated according to the probability R; the probability R is introduced into the objective function of the two-layer model assisted by a deep confidence network agent, and the limit transmission capacity is adjusted. value. Through the invention, the balance between adjusting cost and controlling risk can be realized.

The invention discloses a short-term wind power interval probability prediction method, which includes: obtaining a number of historical wind power of a wind farm as a sample set; constructing an optimization criterion by combining the coverage probability of the prediction interval, the root mean square of the bandwidth of the prediction interval, and the average offset; The short-term wind power interval prediction model of the worker bee colony neural network uses the artificial bee colony algorithm to optimize the optimization criteria and update the weight threshold of the neural network; establishes the neural network according to the optimal weight threshold, and performs interval prediction of the wind power to be predicted; The state of wind power is divided, the Markov chain prediction model is established, and the state transition probability of each state is calculated; the wind power power interval is predicted through the Markov chain state transition probability combined with interval prediction, and the probability is calculated for the numerical points in the prediction interval. The present invention considers the probability distribution of numerical points in the interval while predicting the short-term wind power interval, and provides a basis for optimizing the system.

The invention provides a heterogeneous cellular network base station deployment method based on a Poisson cluster process. The method comprises the following steps: on the basis of a random geometry theory, according to a hypothetical system model and adopting an instantaneous SINR cell selection mechanism as a cell selection mechanism of a user, deducing an SINR model based on the Poisson cluster process; carrying out analysis and inference on an interference model of a multi-layer heterogeneous cellular network by utilizing characteristics of the Poisson cluster process and a probability generation function thereof to obtain an interference distribution model; with the SINR model and the interference distribution model being combined, deducing a coverage probability model of the multi-layer heterogeneous cellular network; and carrying out simulated comparison and analysis on difference of coverage probabilities of the Poisson cluster process and a Poisson point process. The method is much closer to real communication scenes, is larger in coverage probability, can analyze coverage probability and throughput capacity better, and is of great importance in study of the heterogeneous cellular network in the future.

The invention discloses an interference coordination method based on an interference protection area. The present invention includes the following steps: Step 1. For each user who needs base station services, calculate the user's interference protection radius r according to the user coverage probability P greater than the threshold value β 0 ; Step 2, take the user as the center, and the circular area with the interference protection radius as the radius is the interference protection area of ​​the user; Step 3, record the available wireless resource set of the macro base station and all small base stations as Ω, and the current user interference protection area The wireless resource occupied by the base station is denoted as R, where the available wireless resource of the current user can only be selected from the wireless resource set Ω\R, that is, the small base station inside the interference protection area of ​​the current user cannot communicate with the main service of the current user The base stations share radio resources. The present invention can effectively suppress co-frequency interference, improve frequency spectrum utilization, increase system coverage probability, and improve user performance at the same time.

The invention discloses an energy efficiency fairness optimization method based on energy capture. The method comprises the following steps: obtaining initial data comprising base station transmittingpower, a path loss factor, a network receiving threshold, the distance between a user and the base station of a single-layer network, a total network bandwidth and the interference of the base station of other layers of networks on the user; in the case of orthogonal frequency spectrum segmentation, obtaining an average logarithm of the coverage probability according to the path loss factor and the network receiving threshold; establishing a network energy efficiency model with the maximum network energy efficiency value as the target according to the average logarithm of the coverage probability, the total network bandwidth and the network receiving threshold, and obtaining an implicit function of the network receiving threshold based on the network energy efficiency model; and inputtingthe initial data in the implicit function of the network receiving threshold to obtain an optimal network receiving threshold and an optimal network energy efficiency value. By adoption of the energyefficiency fairness optimization method, the energy fairness of the whole network is effectively improved while the quality of service of the user is guaranteed.

The invention relates to a dynamic spectrum distribution method based on covering frequency in a heterogeneous wireless network. The method is characterized by comprising total frequency spectrum benefit maximization and interference control, wherein the interference control is based on a coverage probability threshold, and the interference control model is p[n,m](A)>=beta n (1); and based on the interference control model, modeling of a covering frequency based dynamic spectrum distribution algorithm (CP-DSA) is defined in the description in the interference control model based on coverage probability, user signal interference noise ratio and base station coverage performance requirement are considered at the same time, starting from the purpose of ensuring the base station coverage probability requirement, to achieve the purpose of ensuring user service quality requirement in a cell; and by adopting the dynamic spectrum allocation algorithm CP-DSA based on covering frequency, the total frequency spectrum benefit can be improved, interference between base stations is effectively controlled, and under the condition of an actual shadow fading channel, the user SIR (signal interference noise ratio) requirement is met.