Various embodiments relate to a computer system for providing a service consumption plan for efficient service migration in a mobile edge computing (MEC) environment, and a method thereof. The computer system and the method may be configured to construct a graph representing edges indicating a plurality of road segments and a plurality of MEC servers covering the road segments, detect the service consumption plan for maximizing a ratio of a utilized journey time, which is served through at least one of the MEC servers for a total journey time, with respect to paths between a starting vertex and a goal vertex set by a user by using the graph, and provide the user with the service consumption plan.

The present invention provides a network coverage planning method and apparatus of an evolution communication system, wherein the method includes: obtaining the theoretical coverage parameter of a single base station of the evolution communication system by link budget; obtaining the theoretical coverage parameter of an entire network of the evolution communication system by network stimulation; calculating a reception level value of the evolution communication system under the wireless environment of a current network communication system in the same planning area to estimate a simulative measured coverage parameter of the evolution communication system; and planning the coverage parameter of the entire network of the evolution communication system according to the theoretical coverage parameter of the single base station, the theoretical coverage parameter of the entire network and the simulative measured coverage parameter.

The present invention provides a network coverage planning method and apparatus of an evolution communication system, wherein the method includes: obtaining the theoretical coverage parameter of a single base station of the evolution communication system by link budget; obtaining the theoretical coverage parameter of an entire network of the evolution communication system by network stimulation; calculating a reception level value of the evolution communication system under the wireless environment of a current network communication system in the same planning area to estimate a simulative measured coverage parameter of the evolution communication system; and planning the coverage parameter of the entire network of the evolution communication system according to the theoretical coverage parameter of the single base station, the theoretical coverage parameter of the entire network and the simulative measured coverage parameter.

A cross-platform application is disclosed for shared spectrum operations and CPI management. The application and platform provide an exchange of information usable for CPIs to improve collection of the information required for reporting to the SAS. Some embodiments provide methods to map a floor plan by ray tracing to provide some of the information. In another embodiment, a method includes generating contour information of a floor(s) from two-dimensional and three dimensional models.

A method, a recording medium and an electronic device of 3D geolocation are provided. The method includes the following steps: distributing a plurality of samples that are already 2D-geolocated into a plurality of geographic areas according to 2D locations of the samples, wherein each sample includes a measurement report provided by a user equipment attached to a mobile network; generating a relative sequence of altitudes of the samples in each geographic area according to altitude-related data obtained from the samples in the geographic area; and determining the altitudes of the samples in each geographic area according to the relative sequence of the geographic area.

A method is disclosed of training a network status classification model. The method includes obtaining measurements of network parameters of a communications network, converting the measurements into a plurality of first images representing the measurements and training a deep convolutional generative adversarial network, DCGAN, with the first images. The method also includes generating a plurality of second images representing artificial measurements of the network parameters using the DCGAN, and training a network status classification model with the plurality of second images.

A method is disclosed of training a network status classification model. The method includes obtaining measurements of network parameters of a communications network, converting the measurements into a plurality of first images representing the measurements and training a deep convolutional generative adversarial network, DCGAN, with the first images. The method also includes generating a plurality of second images representing artificial measurements of the network parameters using the DCGAN, and training a network status classification model with the plurality of second images.

A network design apparatus for designing a network, comprising: an input unit that receives input of a configuration condition for a network having a communication layer and at least one computing layer, a cost condition for the network, and a demand condition representing uncertain demand for the network; an operation unit that performs an operation for solving an adjustable robust optimization problem in which an objective function is to minimize a sum of a fixed cost and a variable cost for a resource placed at each base in the communication layer and the computing layer; and an output unit that outputs placement and capacity of a resource obtained by the operation unit, wherein the adjustable robust optimization problem has a constraint condition using a variable indicating a ratio of, in a case where demand is assigned to a resource, a portion assigned to the resource with respect to total volume of the demand, and the variable is a variable that depends on a set of generated demands.

Various embodiments are described that relate to a visualization. A visualization can be produced that relates to a coverage area for an element in the network. A user of this element can read the visualization and make decisions in view of the coverage area. In one instance, the user can read the visualization and select a route of travel such that a likelihood of coverage being lost during travel is relatively small.

An embodiment provides a network parameter optimization method and apparatus, to implement online network parameter optimization. The method includes: sending, by a first function entity, an evaluation model to a second function entity, where the evaluation model is used by the second function entity to determine a first network parameter adjustment action performed by a network element in a first network environment state; receiving, by the first function entity, information about the first network parameter adjustment action; updating, by the first function entity, the evaluation model based on information about the first network environment state, the information about the first network parameter adjustment action, information about a return obtained after the network element performs the first network parameter adjustment action, and information about a second network environment state after the network element performs the first network parameter adjustment action.