33 results about "Coverage probability" patented technology

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 a method for predicating interval probability of short-term wind power. The method comprises the following steps: acquiring a number of historical wind power from a wind power plant as a sample set; establishing optimization criteria according to the prediction interval coverage probability, the prediction interval bandwidth mean square root and the prediction interval average offset; establishing the interval predicating model of the short-term wind power based on an artificial bee colony nerve network, optimizing and updating a nerve network weight threshold to the optimization criteria through an artificial bee colony algorithm; according to the optimal weight threshold, establishing a nerve network and performing interval predication to the wind power to be predicated; performing state division to the historical wind power, establishing a Markov chain prediction model, and calculating the transition probability of each status; predicating the wind power interval according to the Markov chain status transition probability and the interval predication, and calculating the probability of the numerical point in the predication interval. When the short-term wind power interval predication is executed, the probability distribution of the numerical point in the interval is considered, thus the method can provide the basis to an optimization system.

The invention discloses a method for acquiring Femtocell coverage probability. The method comprises that the position of a Femtocell station is modeled to be random and complies with Poisson point distribution, and the coverage probability is calculated according to the position of a macro cell where the Femtocell station is located on this basis. As a random geometry mathematical analysis tool is adopted in the calculating process and influences imposed on the coverage performance by environmental factors are considered, so that the method can acquire the Femtocell coverage probability more accurately, thereby providing an effective and accurate method for network coverage performance analysis and comparison.

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.

The invention relates to a wireless router deployment method, a wireless router deployment device, a computer readable storage medium and electronic equipment. The wireless router deployment method disclosed by the embodiment of the invention is used for determining the deployment position of a wireless router in a space area, and comprises the following steps of: obtaining first position information of a plurality of alternative nodes which are distributed in the space area and are used for deploying the wireless router; Respectively calculating the network coverage probability and the network energy efficiency value when each alternative node deploys the to-be-deployed wireless router based on the first position information; Calculating a network quality score of each alternative node according to the network coverage probability and the network energy efficiency value; And selecting the alternative node with the highest network quality score as the deployment position of the to-be-deployed wireless router. According to the method, high coverage of the whole space wireless network is realized, the network communication quality is ensured, the waste of network resources can be avoided, and the deployment cost of the network equipment is reduced.

The invention discloses a garbage collection method of a storage system, comprising the following steps of: obtaining IO coverage states corresponding to IO characteristics and IO characteristics, carrying out machine learning and training treatment according to the IO characteristics and IO coverage states, and obtaining a coverage probability prediction model; according to the coverage probability prediction model, respectively carrying out prediction processing on each large block space to obtain a plurality of coverage probabilities; marking a large block space whose coverage probability is smaller than a preset coverage probability as a large block space to be recovered; carryingout garbage collection treatment on all large chunks of space to be collected. Through the prediction modelof machine learning training to determine whether the effective data in the large space will soon become garbage data, so as to avoid the garbage collection treatment of this large space, improve theIO performance of the IO storage system, and avoid the waste of IO performance. The present application also discloses a garbage collection system, a server and a computer-readable storage medium, which have the above beneficial effects.

The invention relates to a method for allocating service nodes in a vehicle-mounted Ad hoc network, which comprises the following steps of: modeling an urban road environment into an undirected graph G=G(V, E); setting a service node group Z: [H1, ......, HM} and initializing each service node group Hi: [Si1, ......, SiN] in the service node group Z; and optimizing and updating service node positions contained in all the service node groups of the service node group Z, finding an optimal node group gbest of the service node group Z, correcting the positions of the service nodes of the optimalnode group gbest, and then allocating the corresponding service nodes on an urban road according to the corrected effective service node positions. The invention belongs to the technical field of mobile communication and can find the allocation position of an optimal service node in the shortest time under the condition that a certain network extension coverage probability is satisfied, thereby minimizing the number of the service node and saving investment cost.

The invention discloses a millimeter wave network performance analysis method based on a three-level transmission power mechanism, and belongs to the field of wireless communication. The three-level transmission power mechanism implements the following strategy: transmission power is divided into single power, half power and zero power; each base station sets three levels of thresholds for the number of users accessed; when the number of users accessing each base station is smaller than the high threshold and greater than the low threshold, the base station implements half power; and when the number of users accessing each base station is reduced to below the low threshold, the base station transfers the existing users to an appropriate neighboring base station, and implements zero power. When the number of users accessing a base station is greater than a super threshold, part of users are transferred to an appropriate base station selected or to a nearest dormant base station awakened to ensure smooth communication. The network performance is analyzed by reference to coverage probability, transmission capacity and regional spectrum efficiency. The method of the invention, which is built on the basis of power control performed by base stations, can better reflect the actual network performance and further achieve the goal of green communication.

The invention discloses a vehicle-mounted self-organization network performance analysis method based on millimeter waves. The method comprises steps of establishing a vehicle-mounted self-organization network based on millimeter waves, wherein vehicle nodes in the vehicle-mounted self-organization network based on millimeter waves are distributed in a unidirectional straight road, the arrival process meets the Homogeneous poisson process, the communication link is divided into a sighting distance link and a non-sighting distance link, and the channel fading meets the index distribution, and establishing an analysis model of a millimeter wave vehicle-networking self-organization network; according to the millimeter wave vehicle-networking self-organization network, calculating the networkcoverage probability, the transmission capacity, the region frequency spectrum frequency and the reachable speed coverage probability. Compared with the prior art, by comprehensively considering the effects of vehicle node space distribution, shade effects, channel shading and same-frequency interference effect factors in a wireless communication process, and fully using characteristics of narrowwave beams of millimeter waves and high directivity, the power of signals is improved and same frequency interference is inhibited; and an actual communication scene of the vehicle-networking self-organization network can be well reflected.

The invention provides a method for determining a D2D network model and a method for evaluating the performance of the D2D network model, and the coverage probability of the D2D user and the cellularuser in the network and the area frequency spectrum efficiency of the D2D network can be improved. The method for determining the D2D network model comprises modeling the cellular network as a poissonpoint process based on a heterogeneous network in which the cellular user and the D2D user coexist; setting an isolation ring around the macro base station, so that the D2D user located in the isolation ring cannot reuse the resources of the cellular user, and modeling the clustered D2D network in a mode of combining the poisson hole process with the Thomas clustering process to obtain the D2D network model based on the poisson hole cluster process. The method is suitable for the field of D2D heterogeneous network deployment.

The invention provides an energy-efficient spectrum sharing and base station sleep combined method, which is used for solving the problems in the prior art that only a single partial spectrum sharing PSR or base station sleep BSS strategy is adopted for improving energy efficiency of a heterogeneous network, and the improvement effect of the energy efficiency of the heterogeneous network by adopting the two kinds of single methods is not obvious. The energy-efficient spectrum sharing and base station sleep combined method provided by the invention comprises the steps of: determining a spectrum reuse factor beta of a micro base station layer which minimizes energy loss of the whole system; and determining optimal active probability ratios gamma, which maximize coverage probability of a macro base station layer and the micro base station layer simultaneously, of the macro base station layer and the micro base station layer according to the spectrum reuse factor beta of the micro base station layer. The energy-efficient spectrum sharing and base station sleep combined method optimizes the PSR coefficient beta, and combines the active probability ratios of a macro base station and a micro base station with the PSR coefficient beta, so that the coverage probability and energy efficiency of the macro base station layer and the micro base station layer are maximized under the condition of a given threshold value of signal to interference and noise ratio.

The invention discloses a method and apparatus for outputting network coverage performance evaluation reference. The method comprises the following steps: determining expected deployment density of base stations; and outputting the distribution of average coverage probabilities of a mobile terminal under the expected deployment density to serve as coverage performance evaluation references of networks obtained according to the expected deployment density according to the expected deployment density, a probability distribution model of a first distance and a communication quality model of the mobile terminal, wherein the first distance is the distance between the mobile terminal and a closest target base station, the average coverage probabilities of the mobile terminal under the expected deployment density are average values of probabilities in which the obtained communication quality is greater than a first preset value after the mobile terminal accesses the closest target base station under the expected deployment density. By adoption of the method and apparatus, the relationship between the network coverage performance and the base station deployment density can be obtained, and thus guidance can be provided for determining the reasonable deployment density of the base stations.

The invention discloses a risk-aware deep learning-driven extreme transmission capacity adjustment method. The method comprises the steps of embedding an extreme transmission capacity predictor into an adjustment model to replace the most complex and time-consuming calculation part in the adjustment model to obtain a deep belief network agent-assisted double-layer model; constructing a predictioninterval based on a deep belief network, adjusting the prediction interval according to the coverage probability of the prediction interval, the normalized average bandwidth of the prediction intervaland the accumulated bandwidth deviation, and obtaining an optimal prediction interval through ensemble learning training; obtaining a probability R that the TTC value falls in the interval based on the trained prediction interval, and evaluating a risk probability of prevention and control failure according to the probability R; and introducing the probability R into a target function of a double-layer model assisted by a deep belief network agent, and adjusting the limit transmission capacity value. According to the invention, the balance between adjustment cost and control risk can be realized.

The invention discloses an interference coordination method based on an interference protection area. The method comprises the steps of: 1, calculating interference protection radiuses r0 of users needing base station services according to the fact that a user coverage probability P is greater than a threshold value [beta]; 2, taking the users as centers, and taking circular areas in which the interference protection radiuses are taken as radiuses as interference protection areas of the users; and 3, marking an available wireless resource set of a macro base station and all small-sized base stations as [omega], and marking wireless resources already occupied by the base stations inside the interference protection area of a current user as [R], wherein [R] is a proper subset of [omega], and the available wireless resources of the current user can only be selected from a wireless resource set [omega]\R, namely, the small-sized base stations inside the interference protection area of the current user cannot share the wireless resources with a master service base station of the current user. Through adoption of the interference coordination method, same frequency interference can be suppressed effectively; the spectrum utilization ratio is increased; the system coverage probability is increased; and the performance of the users is improved at the same time.

The present invention provides an energy-efficient spectrum reuse and base station sleep combined method, used for solving the problems that only a single PSR (Partial Spectrum Reuse) or BSS (Base Station Sleep) strategy is adopted for improving energy efficiency of a heterogeneous network in the prior art, and neither of the methods can greatly improve the energy efficiency of the heterogeneous network. The energy-efficient spectrum reuse and base station sleep combined method provided by the present invention comprises the steps of: determining a spectrum reuse factor beta of a micro base station layer achieving the minimal energy loss of the whole system; and determining an optimal active probability ratio Gamma of a macro base station layer and the micro base station layer simultaneously achieving the maximum coverage probability of the macro base station layer and the micro base station layer according to the spectrum reuse factor beta of the micro base station layer. According to the energy-efficient spectrum reuse and base station sleep combined method of the present invention, the PSR coefficient beta is optimized, and the active probability ratio of a macro base station and a micro base station is combined with the PSR coefficient beta, so that the coverage probability and the energy efficiency of the macro base station layer and the micro base station layer can achieve maximization under a given SINR threshold condition.

The invention belongs to the technical field of data analysis, and particularly relates to a method for establishing a correlation matrix of a wireless base station and a line segment type geographic ground object. The method comprises the following steps: extracting training data; extracting and establishing ground object information; segmenting the line segment type ground object; associating the TrainData with the PoiData through a geographic relationship; establishing a relation matrix Rcp _ train and Rpc _ train based on the training data; calculating the coverage intensity from each wireless base station cell to each segment point by using a propagation model, and deducing the coverage probability; establishing a coverage probability matrix Rline _ cov from all cells to all segmentation points; calculating an adjoint trusted matrix Bline of the training matrix; integrating the three matrixes of Rpc _ train, Rline _ cov and Bline to establish a cell-ground object a relation matrix Rline; and updating the relation matrix Rline by adopting a periodic sliding window method. The method provides basic data for social geographic information for the mobile phone user after accurately judging the residence place of the mobile phone user, and provides a basic model for public security, disaster prevention and reduction, smart cities, marketing and other personnel position-based applications.