Method and system for determining whether a terminal belongs to a target space in a communication network, related network and computer program product

• US 20090023461A1
• Filed: 10/15/2004
• Published: 01/22/2009
• Est. Priority Date: 10/15/2004
• Status: Active Grant

• Current Assignee: Telecom Italia S.p.A.
• Original Assignee: Telecom Italia S.p.A.
• Inventors: Filizola, Davide, Grimani, Emanuele, Parata, Dario
• Granted Patent: US 8,175,619 B2
• Time in Patent Office: Days
• US Class Current: 455/456.300
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

The system allows determining whether at least one terminal belongs to a target space in a communications network in order to provide a set of services linked to the fact that the terminal belongs or does not belong to the above target space. The belonging is determined depending on at least one determination parameter. The services are associated with, preferably through a model, respective service specifications indicating the allowable error margin in determining whether the terminal belongs or does not belong to the target space. The determination parameters are changed depending on the above service specifications.

Claims

1-20. -20. (canceled)

21. A method for determining whether at least one terminal belongs to a target space in a communications network in order to provide a set of services linked to the fact that said terminal belongs or does not belong to said target space, said belonging being determined depending on at least one determination parameter, comprising the steps of:

associating with the services of said set, respective service specifications indicative of the allowable error margin, for a respective service, in determining whether said terminal belongs or does not belong to said target space; and

varying said at least one determination parameter depending on said service specifications.

22. The method according to claim 21, comprising the steps of:

determining at least one indicator selected from;

i) the probability that said at least one terminal placed outside said target space is detected as placed inside said target space, and

ii) the probability that said at least one terminal placed inside said target space is detected as placed outside said target space; and

determining said service specifications depending on said at least one indicator.

23. The method according to claim 21, comprising the steps of:

determining at least one indicator selected from;

i) the probability that said at least one terminal placed inside said target space is detected as placed outside said target space, and

ii) the ratio between the size of the space detected as space belonging to said target space and the actual size of said target space; and

determining said service specifications depending on said at least one indicator

24. The method according to claim 21, comprising the step of generating a signal that indicates the passage of said at least one terminal between inside and outside said target space.

25. The method according to claim 21, comprising the step of determining said service specifications as a model.

26. The method according to claim 25, wherein said model is based on:

the probability that said at least one terminal placed inside said target space is detected as placed outside said target space;

the ratio between the size of the space detected as space belonging to said target space and the actual size of said target space; and

a radial size that, together with the target space centre, describes the space in which the estimated position of said at least one terminal must be located, so that said at least one terminal is detected inside said target space.

27. The method according to claim 25, comprising the step of generating said model through:

collecting experimental data from geo-referenced measures of quantities used by the location methods and/or the localised triggers in a plurality of target spaces having at least one different size or morphologic characteristic within said communications network; and

processing data collected in order to generate said model.

28. The method according to claim 27, comprising the steps of:

periodically determining, in following estimation times, the estimated position of said at least one terminal;

verifying whether the estimated position in the previous estimation time is inside a space having as a centre the centre of said target space and a given radial size; and

generating at least one signal that provides updated information of the result of said step of verifying.

29. The method according to claim 28, wherein said step of verifying is performed with a periodicity chosen depending on the required speed in recognising the entry or exit of said at least one terminal with respect to said target space.

30. The method according to claim 26, comprising the steps of:

configuring said communications network as a cellular communications network comprising a plurality of cells that are subjected to serve said at least one terminal;

identifying, within said plurality, a set of cells with barycentre inside a space whose centre is in the centre of said target space and radius equal to said radial size; and

estimating whether said at least one terminal is in said target space, verifying whether the cell of said cellular communications network that at that time serves said at least one terminal is a cell belonging to the identified set.

31. The method according to claim 30, wherein the following are considered as barycentre of a cell of said set:

in case of an omni-directional cell, the geographic spot in which the cell site has its seat; and

in case of a unidirectional cell, the located geographic spot, considering along the maximum cell gain direction, the geographic spot that is at a distance from the geographic spot in which the cell site has its seat, equal to half the distance between the geographic spot in which the cell site has its seat, whose barycentre has to be known, and the geographic spot in which the nearest cell site has its seat.

32. The method according to claim 21, comprising the steps of:

configuring said communications network as a cellular communications network comprising a plurality of cells that are subjected to serve said at least one terminal;

generating a neural network having, as input nodes, input neurons each one of which is associated with one of the cells of said plurality and, as output node, an output neuron that provides the result of the detection whether said at least one mobile terminal belongs to one of the cells of said plurality.

33. The method according to claim 32, comprising the steps of training said neural network having a given number of input nodes, to recognise a given target space providing to the neural network a set of points inside and outside the target space itself, with an indication of the cells of said plurality and the related simulated powers in the spots of said set and with an indication that said at least one terminal is inside or outside the target space for every spot in said set.

34. The method according to claim 33, comprising the steps of:

providing the input nodes of said neural network with homologous power values detected in the spot in which said at least one terminal can be found, so that said neural network estimates whether said at least one terminal is inside or outside with respect to the target space; and

generating at least one signal that provides information related to the fact whether said at least one terminal is inside or outside with respect to the target space.

35. The method according to claim 32, comprising the steps of:

determining with said target space, at least one indicator selected from;

i) probability that said at least one terminal located in said target space is detected by said neural network as placed outside said target space; and

ii) ratio between the size of the space detected by said neural network as space belonging to said target space and the actual size of said target space; and

determining the number of input nodes of said neural network depending on said at least one indicator.

37. A system for determining whether said at least one terminal belongs to a target space in a communications network in order to provide a set of services linked to the fact that said terminal belongs or does not belong to said target space, said belonging being determined depending on at least one determination parameter, the system being configured to perform the method according to claim 21.

38. A communications network configured in order to provide services based on whether a terminal belongs or does not belong to a target space, the network comprising a system according to claim 37.

39. A cellular communications network comprising a communications network according to claim 38, and a plurality of cells that are subjected to serve said at least one terminal.

40. A program product adapted to be loaded in the memory of at least one processor and comprising portions of software code capable of performing the method according to claim 21.

36. A method for determining whether at least one terminal belongs to a target space in a communications network in order to provide a set of services linked to the fact that said terminal belongs or does not belong to said target space, said belonging being determined by associating with the services of said set, through a model, respective service specifications indicating the allowable error margin in determining whether said terminal belongs or does not belong to said target space.