Methods of simplifying network simulation
View Patent ↗In a method of simplifying simulation of a wireless communication network, the network may be divided into one or more neighborhoods. A neighborhood may be represented by a given cell to be evaluated and possibly one or more neighbor cells of the given cell. A desired simulation of one or more of the neighborhoods may be implemented in order to evaluate network performance. The neighborhood may be determined as a function of reverse link interference information, path loss information, or on a geographic distance between cells.
1. A method of simplying simulation of a wireless communication network, comprising:
dividing the network into one or more neighborhoods, a neighborhood represented by a given cell to be evaluated and one or more neighbor cells of the given cell, each cell having a different radio frequency terminal station, and
implementing a desired simulation of one or more of the neighborhoods to evaluate network performance at a neighborhood level, wherein the desired simulation is implemented on a neighborhood by neighborhood basis such that each simulation includes the given cell and at least one of the neighbor cells.
2. The method of claim 1 , wherein dividing includes defining a neighborhood including the given cell based on reverse link interference information.
3. The method of claim 2 , wherein defining includes:
measuring reverse link interference values at the given cell for mobiles owned by or in communication with another cell, wherein the another cell may or may not be part of the same neighborhood as the given cell to be evaluated,
comparing each reverse link interference value to a threshold, and
selecting cells whose reverse link interference value exceeds the threshold for the neighborhood of the given cell to be evaluated.
4. The method of claim 3 , wherein the threshold is based on a multiple of the linear mean of interference power at the given cell.
5. The method of claim 1 , wherein dividing includes defining a neighborhood including the given cell based on path loss information between cells.
6. The method of claim 5 , wherein defining includes:
measuring path loss at the given cell from one or more cells,
comparing each measured path loss value to a threshold, and
selecting cells whose path loss value is below the threshold for the neighborhood of the given cell to be evaluated.
7. The method of claim 1 , wherein dividing includes defining a neighborhood for the given cell based on a threshold relating to the geographical distance of other cells from the given cell.
8. The method of claim 7 , wherein the threshold is embodied as a set number of cells to be evaluated that are closest to the given cell, the closest cells selected as belonging to the neighborhood to be simulated.
9. The method of claim 8 , wherein the value of the set number of cells can be varied based on the structure of the network to be simulated.
10. The method of claim 1 , wherein implementing includes iterating at least one of a greedy heuristic-based algorithm and a simulated annealing-based algorithm using one or more of the neighborhoods to determine network performance.
11. The method of claim 1 , wherein the desired simulation includes:
selecting a given cell in the network to be evaluated, measuring reverse link interference values at the given cell for the mobiles owned by or in communication with another cell, wherein the another cell may or may not be part of the same neighborhood as the selected cell,
comparing the reverse link interference values to a threshold, and
selecting cells whose reverse link interference value exceeds the threshold as cells of the neighborhood including the given cell to be evaluated.
12. The method of claim 11 , wherein the threshold is based on a multiple of the linear mean of interference power at the given cell.
13. The method of claim 1 , wherein the desired simulation includes:
selecting a given cell in the network to be evaluated,
measuring path loss between the given cell and one or more points in the vicinity of another cell,
comparing each measured path loss value to a threshold, and selecting cells near those points having path loss value less than the threshold as cells of the neighborhood.
14. The method of claim 1 , wherein the desired simulation includes:
selecting a given cell in the network to be evaluated, and
defining a neighborhood for the given cell based on a threshold relating to the geographical distance of other cells from the given cell.
15. The method of claim 1 , wherein at least one radio frequency terminal station is a base station.
16. A method of accelerating the computational processing of an optimization algorithm used for evaluation of a wireless communication network, comprising:
dividing the network into one or more neighborhoods, a neighborhood represented by a given cell to be evaluated and one or more neighbor cells of the given cell, each cell having a different radio frequency terminal station,
invoking the optimization algorithm using one or more of the neighborhoods for evaluating network performance to reduce the computational complexities of the optimization by reducing the number of cells to be evaluated in a given evaluation of the network or iteration of the optimization algorithm, and
evaluating network performance at a neighborhood level, wherein the optimization algorithm is implemented on a neighborhood by neighborhood basis such that each simulation includes the given cell and at least one of the neighbor cells.
17. The method of claim 16 , wherein dividing includes defining a neighborhood including the given cell based on a reverse link interference information.
18. The method of claim 17 , wherein defining includes:
measuring reverse link interference values at the given cell for mobiles owned by or in communication with another cell, wherein the another cell may or may not be part of the same neighborhood of the given cell to be evaluated,
comparing each reverse link interference value to a threshold, and
selecting cells whose reverse link interference value exceeds the threshold for the neighborhood of the given cell to be evaluated.
19. The method of claim 18 , wherein the threshold is based on a multiple of the linear mean of interference power due to each mobile owned by or in communication with the another cell.
20. The method of claim 16 , wherein the optimization algorithm invoked is at least one of a modified greedy algorithm and a modified simulated annealing algorithm that is iterated on a neighborhood-by-neighborhood basis to determine network performance.
21. A method of assessing quality of a neighborhood of cells determined for a cell of interest, the neighborhood representing a subset of cells of an entire network, the neighborhood and the entire network to be evaluated, the method comprising:
performing one of a simulation and a measurement at the neighborhood level to determine a first parameter, wherein the neighborhood includes a given cell to be evaluated and one or more neighbor cells of the given cell, each cell having a different radio frequency terminal station,
performing one of a simulation and a measurement of the entire network to determine a second parameter, the simulation being performed on a neighborhood by neighborhood basis such that each simulation includes the given cell and at least one neighbor cells, and
determining a correlation coefficient between the neighborhood and entire network as a function of the first and second parameters, a value of the correlation coefficient indicative of the quality of the neighborhood, as used for the simulation or measurement, as compared to the entire network.
22. A method for simulating performance of a wireless communication network, comprising:
providing a computational model of a network into a simulator, in which the network is subdivided into cells, and each cell is defined with reference to a particular radiofrequency terminal station;
selecting at least one cell as a given cell to be evaluated;
evaluating a distance between each given cell and a plurality of other cells of the network;
defining one or more other cells as neighbors of the given cell corresponding to the distance;
dividing the network, in the computational model, into one or more neighborhoods, wherein a neighborhood is represented by a corresponding given cell and one or more neighbor cells of said given cell; and
implementing, in the simulator, a desired simulation of one or more of the neighborhoods to evaluate network performance at a neighborhood level, wherein the desired simulation is implemented on a neighborhood by neighborhood basis such that each simulation includes the given cell and at least one of the neighbor cells.