WO2018129251A1 - Method of improving performance of a wireless coummunication network with consideration of multiple parameters - Google Patents

Method of improving performance of a wireless coummunication network with consideration of multiple parameters Download PDF

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Publication number
WO2018129251A1
WO2018129251A1 PCT/US2018/012483 US2018012483W WO2018129251A1 WO 2018129251 A1 WO2018129251 A1 WO 2018129251A1 US 2018012483 W US2018012483 W US 2018012483W WO 2018129251 A1 WO2018129251 A1 WO 2018129251A1
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Prior art keywords
locations
parameters
aggregate
priority
priority rankings
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PCT/US2018/012483
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French (fr)
Inventor
Alberto E. RUBIO
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Clearsky Technologies, Inc.
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Publication of WO2018129251A1 publication Critical patent/WO2018129251A1/en

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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W24/00Supervisory, monitoring or testing arrangements
    • H04W24/02Arrangements for optimising operational condition
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W16/00Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18Network planning tools

Definitions

  • the invention relates to the field of communication networks of types in which communications are carried wirelessly in a least a portion of the network. More particularly, the invention relates to a method for improving the performance of such a network by deploying a radio access network (RAN) asset at a location determined from data specifying the quantitative values of each of a plurality of parameters at multiple locations within a service area of a wireless network and the positions those locations.
  • RAN radio access network
  • a relative priority ranking is determined based on the quantitative values and those relative priority rankings are aggregated, or weighted and aggregated, on a location-by-location basis to generate a set of aggregate priority rankings, or aggregate weighted priority rankings, and the radio access network (RAN) asset is deployed at a location determined based on the aggregate priority rankings, or aggregate weighted priority rankings.
  • RAN radio access network
  • the invention provides a method by which the performance of a wireless communication network may be improved or evaluated based on a data representing any two, or an arbitrary greater number, of parameters desired to be taken into account in improving performance of the network.
  • Such parameters may include at least one parameter of a qualitatively different nature that one or more others of those parameters. Accordingly, the nature or aspects of network performance which can be improved using the present method are myriad and can be flexibly defined to take into account an arbitrarily large number of parameters.
  • Certain embodiments may utilize data specifying both a quantitative value of each one of a plurality of parameters at each respective one of multiple geographic locations within a service area of at least a portion of the network and a position of each of said locations.
  • a relative priority ranking corresponding to each respective one of the locations is determined.
  • the relative priority ranking is determined for each location based on a comparison of the value of the parameter at that location with an extreme value of the same said parameter among all of the locations.
  • the relative priority rankings may be determined in accordance with a relative weighting factor assigned for each parameter to represent its importance relative to other ones of the parameters.
  • the weighting factors are selected such that the sum of all of the relative weighting factors is equal to unity.
  • the relative priority rankings corresponding to each respective one of the locations may be aggregated for all of the parameters collectively to determine a set of aggregate priority rankings which include an aggregate priority rank for each respective one of the locations and a radio access network (RAN) asset is deployed at one of the locations which is selected based on the aggregate priority rankings.
  • RAN radio access network
  • the invention thus provides a powerful and flexible method for improving the performance of a wireless communication with regard to a plurality of parameters which may include virtually any parameters which a particular a network owner, network operator, network manager, property owner, property manager, wireless communication services customer or other user of the method may be deem consequential to their particular objective(s).
  • Fig. 1 is a schematic diagram conceptually illustrating input data specifying the positions of multiple locations within a service area of a wireless network and the respective values of each of a plurality of parameters at each of those locations.
  • Fig. 2 is a flowchart illustrating preferred embodiments of a method according to the present invention.
  • any two or more parameters P 1; P 2 .. P n desired to be taken into consideration in connection with technical, business and/or other aspects of performance of a wireless communication network 19 may be taken into account using the present invention.
  • the number, n, of parameters, P n> considered may be two or any greater number.
  • any one or more of those parameters P n may be of a qualitatively different nature than one or more of the others.
  • the communication network 19 may comprise a cellular network.
  • the communication network 19 may comprise a wireless local area networks (WLAN)
  • the communication network 19 may comprise a wireless wide area network.
  • P2...Pn are ones relating to technical considerations relevant to performance of network 19.
  • parameters in such category may include any one or more of: signal strength; interference (e.g. signal-to-noise ratio); path loss; clutter; signal coverage; , signal attenuation; communications signal traffic throughput (peak, mean and/or other); bandwidth and/or communications signal traffic capacity. While all the parameters just mentioned are of a technical nature relating in some respect to the propagation of signals in the network 19, they are of a qualitatively different nature in that at least some of them may be characterized by non-equivalent units of measurement.
  • signal strength is typically expressed in units specifying relative signal power such as dBm or sometimes decibel- milliwatts ( dB mW ) whereas signal traffic or signal traffic capacity are a different quantity, namely data rates, are generally expressed in units such as megabytes per second.
  • P 2 .. P n are ones relevant to various other aspects of the technological performance of network 19 nonlimiting examples of which may include assessments of downtime or uptime such as, frequency of outages (peak, mean, median and/or other) and/or duration of outages (peak, mean, median and/or other), and/or mean time between failures (MTBF).
  • assessments of downtime or uptime such as, frequency of outages (peak, mean, median and/or other) and/or duration of outages (peak, mean, median and/or other), and/or mean time between failures (MTBF).
  • MTBF mean time between failures
  • parameters in such category may include any one or more of: land use category (e.g. urban, suburban, rural, residential); customer locations; customer class e.g. business, residential, business by nature of business (e.g. manufacturing, financial, farming, SIC code), annual gross sales volume of the business, number of employees, etc.
  • Such parameters may also include one or more demographic factors such as household income, occupation, language spoken, age, gender, level of education or others.
  • Such parameters may also include one or more types of telecommunications business parameters churn rates (e.g.
  • customer complaints by one or more subcategories of reason such as complaints about cost, signal strength, dropped calls or other reasons
  • While some or all of the parameters P 1; P 2 ...P n desired to be taken into consideration may be ones capable of being specified in specific units such as dBm, decibel- milliwatts, dollars, megabytes per second, outages per month etc. and may have quantitative values of an integer or decimal nature, such is not necessary to practice the invention.
  • the method of the invention is operable even if one or more of the parameters P 1; P 2 ...P n parameters is specified by a quantitative value which is dimensionless (in the sense of not being specifiable in units) even parameters of a binary nature, such as by way of nonlimiting example, whether the customer at a particular location owns a car or not.
  • a set 25 of suitable data, D n , for a given parameter P n may be expressed as:
  • n represents the number of parameters P 1; P 2 ...P n desired to be taken into consideration;
  • L represents the number of geographic locations 30, and
  • b n (x L, Yl ) represents the quantitative value of that given parameter at a location
  • Fig. 1 conceptually depict shows a set 18 of data D n which includes data 21 for parameter Pi, data 22 for parameter P 2 , and data 23 for parameter P n
  • data 21, 22, 23 includes data which specifies a quantitative value, b n (X Y ) , of each of those parameters Pi, P 2 ,... P n at each respective one of multiple, different geographic locations 30 within an existing or prospective service area 35 of at least a portion of the network 19 as well as the respective positions (X L ,Y L ) of each of those locations 30.
  • b n X Y
  • locations 30 are indicated by the dots appearing inside service area 35 but for sake of clarity, some but not all of those locations 30 have been marked with a corresponding reference numeral. While Cartesian coordinate notation has been used by way of non-limiting example, it is to be understood that positions of the locations 30 can be specified in any desired manner.
  • data D n for one or more of the parameters P n may be in a raster data format.
  • data D n may be in the form of a raster map. Any raster mapping format including but not limited to those known types associated with the file extensions .grd, .img, .bmp, .tif, or other raster mapping format may be used in such embodiments.
  • certain embodiments of a method 10 may commence with or include a step 20 of providing data D n , which is sufficient to specify both a qualitative value of each one of the parameters, P n , in a set 18 which includes any number, n, of such parameters where the number, n is greater than or equal to two (2).
  • a relative priority ranking 37 corresponding to each one of the locations 30 may be determined for each respective one of the parameters in set 18.
  • the priority rankings 37 for each individual parameter, P n may be relative priority rankings 37 determined based on a comparison of the quantitative value of that parameter at a given individual location 30 with an extreme value, b n> E, of the same parameter among all of the locations 30.
  • a priority ranking 37 is determined for each individual location 30.
  • the extreme value, b n> E, of a given parameter P n may be a relative maximum value of that same parameter among all locations 30. That is, extreme value, b N ,E may be the quantitative value of that particular parameter which is the greatest among the quantitative values b n (x L, Y l > of that parameter for any of the locations 30. In certain embodiments, the extreme value, b n ,E may be a relative minimum value of the parameter among all locations 30, that is, the quantitative value of that parameter which is the lowest among its values for any of the locations 30. In certain embodiments, the extreme value, b n> E may be a relative maximum value for one or more of the parameters P n in set 18 and may be a relative minimum value for one or more others of the parameters in set 18.
  • a relative priority ranking 37 of the quantitative value for each respective one of locations 30 for a parameter P n may be determined based on a comparison carried out by determining the ratio of the value of the parameter at that particular location 30 with the relative extreme value of that same parameter P n among all locations 30
  • ranking step 40 may be carried out to determine relative priority rankings 37 according to Equation 2 below.
  • R n (x L, Yl ) represents the relative priority ranking 37 of parameter P n at an individual location 30 whose position is (X L , Y L );
  • b n (x L, Yl ) represents the quantitative value of the same parameter, P n , at that same location 30, and
  • E represents whichever quantitative value of the same parameter, P n , is a relative extreme value among all locations 30.
  • a relative priority ranking 37 determined according to Equation 2 will be a dimensionless number ranging from zero to one (0 to 1), which can alternatively be expressed as a corresponding percentage ranging from zero to one hundred percent (0 to 100%).
  • P n For each parameter, P n , a relative priority ranking 37 is determined for each individual location 30.
  • the extreme value, b N,E for each given parameter P n may be a selectable value and may be specifically selectable to be a particular quantitative value which a user regards as being the worst value of that particular parameter, P n , among all the values of that same parameter, P n for any of the locations 30, irrespective of whether the quantitative value is the numerically highest or lowest. Doing so provides the particular advantage of permitting performance of wireless network 19 to be improved relative to the performance the user may subjectively or objectively regards as relatively best or worst from a performance standpoint of all data D n under consideration for each respective parameter P n .
  • locations 30 having a corresponding relative priority ranking 37 of unity (1) would represent locations 30 associated with the worst relative performance of network 19, and those having a relative priority ranking 37 of zero (0) (or if expressed as a percentage, 0%) would represent locations 30 associated with the best relative performance of network 19.
  • the rankings could be reversed such that a ranking value 40 of unity (1) (or if expressed as a percentage, 100%) could represent the best relative performance, and a ranking value 40 of zero (0) (or if expressed as a percentage, 0%) could represent the worst relative performance of network 19.
  • the relative priority rankings 37 corresponding to each respective one of the locations 30 are aggregated for all of the parameters, P 1; P 2 ...P n , on a location-by-location basis for each individual location 30 to determine a set 52 of aggregate priority rankings 55 which includes an individual aggregate priority ranking 55 for each respective one of the locations 30.
  • aggregating step 50 may be carried out as an unweighted aggregating step 50A in which each parameter P n is accorded the same relative importance as all of the other parameters P n .
  • an unweighted aggregating step 50A may be carried out according to Equation 3 below.
  • (x L> YL) represents an aggregate unweighted priority ranking 55 A at an individual location 30 whose position is (X L , Y L ) ;
  • Ri(x L, YL) represents the priority ranking 37 of parameter Pi at the same location L;
  • P-2(x L, YL) represents the priority ranking 37 of parameter P 2 at the same location L;
  • R n (x L, YL) represents the priority ranking 37 of parameter P n at the same location L.
  • a set 52A of unweighted aggregate priority rankings 55A may result from unweighted aggregating step 50A and may be expressed as: Expression 2: ⁇ ⁇ ( ⁇ 1> ⁇ ⁇ ) , ⁇ ( ⁇ 2> ⁇ 2)> ... A (XL; YL) ⁇ where:
  • ( ⁇ 1; Yx ) represents an aggregate unweighted priority ranking 55A at an individual location 30 whose position is (Xi, Yi);
  • (x L> Yl ) represents an aggregate unweighted priority ranking 55 A at an individual location 30 whose position is (X L , Y L ).
  • locations 30 having a corresponding aggregate unweighted priority ranking 55 A of unity (1) would correspond to locations 30 associated with the worst relative performance of network 19, taking into consideration all of the parameters Pi, P 2 , ... P n , collectively, and those locations 30 having an aggregate unweighted priority ranking 55 A of zero (0) (or if expressed as a percentage, 0%) would correspond to locations 30 associated with the best relative performance of network 19 taking into consideration all of the parameters Pi, P 2 ,... P n , collectively.
  • the rankings 55A could be reversed such that a ranking value 40 of unity (1) (or if expressed as a percentage, 100%) could represent the best relative performance, and a ranking value 40 of zero (0) (or if expressed as a percentage, 0%) could represent the worst relative performance of network 19 taking into consideration all of the parameters Pi, P 2 , ... P n , collectively.
  • aggregating step may be carried out as a weighted aggregating step 50B so that the various parameters P 1; P 2 .. P n can be taken into consideration in accordance to what a particular user of the method may regard to be the relative importance of respective ones of those parameters.
  • a weighing factor 61 may be assigned to, or otherwise associated with, each of parameters P 1; P 2 ...P n
  • each aggregate priority ranking 50 comprises what shall be referred to herein as an aggregate weighted priority ranking 55B.
  • a respective weighting factor 61 may be assigned to, or otherwise associated with, each of parameters P 1; P 2 . .
  • weighting factors 61 may be determined based on a software-defined weighing list 64 in which a user may assign, that is, enter and/or change, a respective weighting factor 61 associated with one or more of the parameters P 1; P 2 . . P n
  • a weighted aggregating step 50B may be carried out according to Equation 4 below.
  • a W( x L> Y l) represents an aggregate weighted priority ranking 55B at an individual location 30 whose position is (XL, YL) ;
  • Ri ( x L, Y l) represents the priority ranking 37 of parameter Pi at the same location L;
  • F 1 represents the weighting factor 61 for parameter P 1;
  • R2 ( x L, Y l) represents the priority ranking 37 of parameter P 2 at the same location L;
  • F 2 represents the weighting factor 61 for parameter P 1;
  • Rn ( x L, Y l) represents the priority ranking 37 of parameter P n at the same location L
  • F n represents the weighting factor 61 for parameter P n.
  • a set 52B of aggregate weighted priority rankings 55B may be expressed as: Expression 3 : ⁇ A W(XL; YL) , A W( X 2; Y 2); ... A W ( X L; YL) ⁇ where: W (x 1; ⁇ ⁇ ) represents an aggregate weighted priority ranking 55B at an individual location 30 whose position is (Xi, Yi) ;
  • W(x 2> Y2 ) represents an aggregate weighted priority ranking 55B at an individual location 30 whose position is (X 2 , Y 2 ), and
  • W(x L> Yl ) represents an aggregate weighted priority ranking 55B at an individual location 30 whose position is (X L , Y L )-
  • the aggregate weighted priority rankings 55 A determined based on Equation 4 will dimensionless number conveniently ranging from zero to one (0 to 1), which can alternatively be expressed as a corresponding percentage ranging from zero to one hundred percent (0 to 100%).
  • locations 30 having a corresponding aggregate weighted priority ranking 55B of unity (1) would represent locations 30 associated with the worst relative performance of network 19 taking into consideration all of the parameters Pi, P 2 , ... P n , collectively, and those having an aggregate weighted priority ranking 55B of zero (0) (or if expressed as a percentage, 0%) would represent locations 30 associated with the best relative performance of network 19 taking into consideration all of the parameters Pi, P 2 , ... P n , collectively, including their respective weighting factors 61.
  • Method 10 may optionally but advantageously include a displaying step 60 which comprises displaying at least some of the aggregate priority rankings 55 at their respective locations on a map.
  • the optional nature of displaying step 60 is denoted in Fig. 2. by the use of broken lines.
  • the aggregate priority rankings 55 displayed in displaying step 60 may comprise aggregate unweighted priority rankings 55A which in other embodiments, they may comprise aggregate weighted priority rankings 55B.
  • the aggregate priority rankings 55 displayed in displaying step 60 may comprise aggregate unweighted priority rankings 55 A and aggregate weighted priority rankings 55B, with either one, the other or both of same being displayed at a given time on a computer display screen on a user-selectable basis.
  • communications network 19 is physically altered by deploying at least one radio access network (RAN) asset 94 for network 19 at at least one location 30, that location 30 being selected based on based on the aggregate priority rankings 55.
  • RAN radio access network
  • such location 30 may be selected based on aggregate priority rankings 55 comprising aggregate unweighted priority rankings 55 A.
  • such location 30 may be selected based on aggregate weighted priority rankings 55B.
  • such location 30 may be selected based on either aggregate unweighted priority rankings 55 A or based on aggregate weighted priority rankings 55B, whichever alternative may be specified by a user on a selectable basis.
  • the word “deploying” may include, but is not limited to, installing a radio access network (RAN) asset that was not previously present at the location 30. Rather, the word “deploying” may include any one or more of: (a) installing a radio access network (RAN) asset that was not already present at the location 30, (b) replacing a access network (RAN) asset that was already present at location 30 with one of either a same, similar or dissimilar type, (c) upgrading a access network (RAN) asset that was already present at the location 30 to provide that asset with improved or additional functionality and/or capacity, including but not limited to upgrading which may be carried out by replacing an antenna and/or one or more other component parts of the asset with one or more other component parts which alters the functionality of the asset, (d) repairing a radio access network (RAN) asset that was already present at the location 30 to at least partially restore lost or degraded operability, functionality or capacity of that asset, (e) changing at least one operational setting of a radio access network (RAN)
  • RAN radio access network
  • the radio access network (RAN) asset 94 may comprise a wireless communications base station 102 and/or a component 104 of a wireless communications base station 102.
  • Such component 104 may in certain embodiments comprise one or more of: (a) an antenna, (b) a radio transmitter (irrespective of transmission frequency, whether RF, microwave or other), (c) a repeater, (d) software, and/or (e) firmware.
  • the wireless communication base station 102 may comprise a cellular base station 106.
  • the cellular base station 106 may comprise one or more of the respective types commonly known as a macro cell, a small cell, a micro cell and/or a femtocell.
  • the location 30 selected in deploying step 90 may be selected as one having an aggregate priority ranking 55 at which meets at least one criterion 99.
  • aggregate priority ranking 55 may comprise either an aggregate unweighted priority ranking 55 A or an aggregate weighted priority ranking 55B.
  • the criterion 99 may be one which specifies a threshold aggregate priority ranking 110.
  • the threshold aggregate priority ranking 110 has a value which is selectable and changeable by a user.
  • the criterion 99 may be one which specifies a range 115 of aggregate priority rankings 55 which, in some embodiments may be a range of aggregate unweighted priority rankings 55 A and/or a range of aggregate weighted priority rankings 55B.
  • the range 115 is one selectable and changeable by a user.
  • a determination of locations 30 whose aggregate priority rankings 55, whether aggregate unweighted priority rankings 55A or aggregate weighted priority rankings 55B, satisfy criterion 99 may be made according to an optional filtering step 110, the optional nature of which is denoted in Fig. 2 by the use of broken lines. Although indicated in Fig. 2 as distinct step, filtering step 110 may in certain embodiments be carried out as a substep of another step, such as for example deploying step 90.
  • Filtering step 110 may be carried out in some embodiments by selecting from either a set 52 A of aggregate unweighted priority values 55 A or a set 52B of aggregate weighted priority values 55B, those of said vales 55 A or 55B which meet or exceed threshold aggregate priority ranking 110. Filtering step 110 may be carried out in some embodiments by selecting from either a set 52 A of aggregate unweighted priority values 55 A or a set 52B of aggregate weighted priority values 55B, those of said values 55 A or 55B within a range of such values.
  • filtering step 100 may be carried out specifying criterion 99 according to a Boolean expression and applying such Boolean expression to either a set 52 A of aggregate unweighted priority values 55 A or a set 52B of aggregate weighted priority values 55B
  • optional displaying step 60 may optionally be repeated one or more times after a filtering step 80 has been carried out.
  • Method 10 may be carried out as an automated method by a computer programmed in accordance with the method as described above.

Abstract

In a preferred embodiment, performance of a wireless communication network is improved by deploying a radio access network (RAN) asset at a location determined from data specifying the quantitative values of each of a plurality of parameters at multiple locations within a service area of the network and the positions those locations, at least of those parameters being of a nature qualitatively different from at least one other of those parameters, and, for each respective parameter and each respective location, determining a relative priority ranking based on the quantitative values and aggregating those relative priority rankings on a location-by-location basis to generate a set of aggregate priority rankings, the radio access network (RAN) asset being deployed at a location determined based on the aggregate priority rankings.

Description

METHOD OF IMPROVING PERFORMANCE OF A WIRELESS COMMUNICATION NETWORK WITH CONSIDERATION OF MULTIPLE
PARAMETERS
FIELD OF THE INVENTION
[001] The invention relates to the field of communication networks of types in which communications are carried wirelessly in a least a portion of the network. More particularly, the invention relates to a method for improving the performance of such a network by deploying a radio access network (RAN) asset at a location determined from data specifying the quantitative values of each of a plurality of parameters at multiple locations within a service area of a wireless network and the positions those locations. For each respective parameter and each respective location a relative priority ranking is determined based on the quantitative values and those relative priority rankings are aggregated, or weighted and aggregated, on a location-by-location basis to generate a set of aggregate priority rankings, or aggregate weighted priority rankings, and the radio access network (RAN) asset is deployed at a location determined based on the aggregate priority rankings, or aggregate weighted priority rankings.
BRIEF SUMMARY OF THE INVENTION
[002] The invention provides a method by which the performance of a wireless communication network may be improved or evaluated based on a data representing any two, or an arbitrary greater number, of parameters desired to be taken into account in improving performance of the network. Such parameters may include at least one parameter of a qualitatively different nature that one or more others of those parameters. Accordingly, the nature or aspects of network performance which can be improved using the present method are myriad and can be flexibly defined to take into account an arbitrarily large number of parameters. [003] Certain embodiments may utilize data specifying both a quantitative value of each one of a plurality of parameters at each respective one of multiple geographic locations within a service area of at least a portion of the network and a position of each of said locations. For each respective one of the parameters, a relative priority ranking corresponding to each respective one of the locations is determined. In some preferred embodiments, the relative priority ranking is determined for each location based on a comparison of the value of the parameter at that location with an extreme value of the same said parameter among all of the locations. In some embodiments, the relative priority rankings may be determined in accordance with a relative weighting factor assigned for each parameter to represent its importance relative to other ones of the parameters. In some such embodiments, the weighting factors are selected such that the sum of all of the relative weighting factors is equal to unity. The relative priority rankings corresponding to each respective one of the locations may be aggregated for all of the parameters collectively to determine a set of aggregate priority rankings which include an aggregate priority rank for each respective one of the locations and a radio access network (RAN) asset is deployed at one of the locations which is selected based on the aggregate priority rankings.
[004] The invention thus provides a powerful and flexible method for improving the performance of a wireless communication with regard to a plurality of parameters which may include virtually any parameters which a particular a network owner, network operator, network manager, property owner, property manager, wireless communication services customer or other user of the method may be deem consequential to their particular objective(s).
BRIEF DESCRIPTION OF THE DRAWINGS
[005] Fig. 1 is a schematic diagram conceptually illustrating input data specifying the positions of multiple locations within a service area of a wireless network and the respective values of each of a plurality of parameters at each of those locations. [006] Fig. 2 is a flowchart illustrating preferred embodiments of a method according to the present invention.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[007] Any two or more parameters P1; P2.. Pn desired to be taken into consideration in connection with technical, business and/or other aspects of performance of a wireless communication network 19 may be taken into account using the present invention. The number, n, of parameters, Pn> considered may be two or any greater number. Moreover, any one or more of those parameters Pn may be of a qualitatively different nature than one or more of the others. In certain embodiments the communication network 19 may comprise a cellular network. In certain embodiments the communication network 19 may comprise a wireless local area networks (WLAN) In certain embodiments the communication network 19 may comprise a wireless wide area network.
[008] One category of parameters which may be included among parameters PI,
P2...Pn are ones relating to technical considerations relevant to performance of network 19. By way of non-limiting examples, parameters in such category may include any one or more of: signal strength; interference (e.g. signal-to-noise ratio); path loss; clutter; signal coverage; , signal attenuation; communications signal traffic throughput (peak, mean and/or other); bandwidth and/or communications signal traffic capacity. While all the parameters just mentioned are of a technical nature relating in some respect to the propagation of signals in the network 19, they are of a qualitatively different nature in that at least some of them may be characterized by non-equivalent units of measurement. For example signal strength is typically expressed in units specifying relative signal power such as dBm or sometimes decibel- milliwatts ( dBmW) whereas signal traffic or signal traffic capacity are a different quantity, namely data rates, are generally expressed in units such as megabytes per second.
[009] Another category of parameters which may be included among parameters P1;
P2.. Pn are ones relevant to various other aspects of the technological performance of network 19 nonlimiting examples of which may include assessments of downtime or uptime such as, frequency of outages (peak, mean, median and/or other) and/or duration of outages (peak, mean, median and/or other), and/or mean time between failures (MTBF). It will be appreciated at least some such parameters are of a qualitatively dissimilar nature than others. For example, a parameter such as frequency of outages, which is inherently in units of the inverse of time cannot be directly compared to a parameter such as MTBF which in inherently in units of time. ] Another category of parameters which may be included among parameters P1;
P2...Pn are ones which may be relevant to performance of the network 19 with respect to various business or financial objectives. By way of non-limiting examples, parameters in such category may include any one or more of: land use category (e.g. urban, suburban, rural, residential); customer locations; customer class e.g. business, residential, business by nature of business (e.g. manufacturing, financial, farming, SIC code), annual gross sales volume of the business, number of employees, etc. Such parameters may also include one or more demographic factors such as household income, occupation, language spoken, age, gender, level of education or others. Such parameters may also include one or more types of telecommunications business parameters churn rates (e.g. number of customers discontinuing or not renewing subscriptions for communication services from a communication service provider within a specified period); customer complaints; customer complaints by one or more subcategories of reason such as complaints about cost, signal strength, dropped calls or other reasons; customer complaints by one or more demographic subcategories characterizing the complaining customer by one or more demographic factors such as household income, occupation, hobby, language spoken, age, gender, level of education or other characteristic such as whether or not the customer rides a motorcycle or owns a car, boat, home or airplane etc. It will be appreciated at least some such parameters are of a qualitatively dissimilar nature than others. ] While some or all of the parameters P1; P2...Pn desired to be taken into consideration may be ones capable of being specified in specific units such as dBm, decibel- milliwatts, dollars, megabytes per second, outages per month etc. and may have quantitative values of an integer or decimal nature, such is not necessary to practice the invention. The method of the invention is operable even if one or more of the parameters P1; P2...Pn parameters is specified by a quantitative value which is dimensionless (in the sense of not being specifiable in units) even parameters of a binary nature, such as by way of nonlimiting example, whether the customer at a particular location owns a car or not.
[012] For each parameter, Pn, in a set 18 of two or more such parameters, {P1;
P2.. Pn}, data, Dn, sufficient to specify at least the respective geographic positions, (XL, YL), of multiple geographic locations 30 and the quantitative value, bn (xL, Yl>, of that parameter at each respective one of the locations 30 may be used. For certain embodiments, a set 25 of suitable data, Dn , for a given parameter Pn , may be expressed as:
Expression 1 : Dn = { bn (χ1; Yl) , bn2> γ2> ... bn (xL; YL> }
where:
n represents the number of parameters P1; P2...Pn desired to be taken into consideration;
L represents the number of geographic locations 30, and
bn (xL, Yl) represents the quantitative value of that given parameter at a location
30 whose position is (XL, YL).
[013] By way of non-limiting illustration of an embodiment in which five (5ea.) parameters Pn are taken into consideration, Fig. 1 conceptually depict shows a set 18 of data Dn which includes data 21 for parameter Pi, data 22 for parameter P2, and data 23 for parameter Pn For each respective one of those parameters, data 21, 22, 23 includes data which specifies a quantitative value, bn (X Y ), of each of those parameters Pi, P2,... Pn at each respective one of multiple, different geographic locations 30 within an existing or prospective service area 35 of at least a portion of the network 19 as well as the respective positions (XL ,YL) of each of those locations 30. In Fig. 1, locations 30 are indicated by the dots appearing inside service area 35 but for sake of clarity, some but not all of those locations 30 have been marked with a corresponding reference numeral. While Cartesian coordinate notation has been used by way of non-limiting example, it is to be understood that positions of the locations 30 can be specified in any desired manner.
[014] In certain embodiments, data Dnfor one or more of the parameters Pnmay be in a raster data format. In certain embodiments, data Dn may be in the form of a raster map. Any raster mapping format including but not limited to those known types associated with the file extensions .grd, .img, .bmp, .tif, or other raster mapping format may be used in such embodiments.
[015] As illustrated in the flow chart of Fig. 2, certain embodiments of a method 10 according to the present invention may commence with or include a step 20 of providing data Dn, which is sufficient to specify both a qualitative value of each one of the parameters, Pn, in a set 18 which includes any number, n, of such parameters where the number, n is greater than or equal to two (2).
[016] According to a ranking step 40 a relative priority ranking 37 corresponding to each one of the locations 30 may be determined for each respective one of the parameters in set 18. In certain embodiments, the priority rankings 37 for each individual parameter, Pn, may be relative priority rankings 37 determined based on a comparison of the quantitative value of that parameter at a given individual location 30 with an extreme value, bn> E, of the same parameter among all of the locations 30. For each parameter, Pn, a priority ranking 37 is determined for each individual location 30.
[017] In certain embodiments, the extreme value, bn> E, of a given parameter Pn, may be a relative maximum value of that same parameter among all locations 30. That is, extreme value, bN,E may be the quantitative value of that particular parameter which is the greatest among the quantitative values bn (xL, Yl> of that parameter for any of the locations 30. In certain embodiments, the extreme value, bn,E may be a relative minimum value of the parameter among all locations 30, that is, the quantitative value of that parameter which is the lowest among its values for any of the locations 30. In certain embodiments, the extreme value, bn> E may be a relative maximum value for one or more of the parameters Pn in set 18 and may be a relative minimum value for one or more others of the parameters in set 18.
[018] In certain embodiments, a relative priority ranking 37 of the quantitative value for each respective one of locations 30 for a parameter Pn, may be determined based on a comparison carried out by determining the ratio of the value of the parameter at that particular location 30 with the relative extreme value of that same parameter Pn among all locations 30 For example, in certain embodiments ranking step 40 may be carried out to determine relative priority rankings 37 according to Equation 2 below.
Equation 2 : Rn (xL> Yl> = bn (xL, Yl) / bn> E
where:
Rn (xL, Yl) represents the relative priority ranking 37 of parameter Pn at an individual location 30 whose position is (XL, YL);
bn (xL, Yl) represents the quantitative value of the same parameter, Pn , at that same location 30, and
bn, E represents whichever quantitative value of the same parameter, Pn , is a relative extreme value among all locations 30.
[019] It will be appreciated, that a relative priority ranking 37 determined according to Equation 2 will be a dimensionless number ranging from zero to one (0 to 1), which can alternatively be expressed as a corresponding percentage ranging from zero to one hundred percent (0 to 100%). For each parameter, Pn, a relative priority ranking 37 is determined for each individual location 30.
[020] In certain embodiments, the extreme value, bN,E for each given parameter Pn may be a selectable value and may be specifically selectable to be a particular quantitative value which a user regards as being the worst value of that particular parameter, Pn, among all the values of that same parameter, Pn for any of the locations 30, irrespective of whether the quantitative value is the numerically highest or lowest. Doing so provides the particular advantage of permitting performance of wireless network 19 to be improved relative to the performance the user may subjectively or objectively regards as relatively best or worst from a performance standpoint of all data Dn under consideration for each respective parameter Pn. In such embodiments, locations 30 having a corresponding relative priority ranking 37 of unity (1) (or if expressed as a percentage, 100%) would represent locations 30 associated with the worst relative performance of network 19, and those having a relative priority ranking 37 of zero (0) (or if expressed as a percentage, 0%) would represent locations 30 associated with the best relative performance of network 19. Alternatively, the rankings could be reversed such that a ranking value 40 of unity (1) (or if expressed as a percentage, 100%) could represent the best relative performance, and a ranking value 40 of zero (0) (or if expressed as a percentage, 0%) could represent the worst relative performance of network 19.
[021] In an aggregating step 50 carried out based on the results or ranking step 40, the relative priority rankings 37 corresponding to each respective one of the locations 30 are aggregated for all of the parameters, P1; P2...Pn, on a location-by-location basis for each individual location 30 to determine a set 52 of aggregate priority rankings 55 which includes an individual aggregate priority ranking 55 for each respective one of the locations 30.
[022] In certain embodiments, aggregating step 50 may be carried out as an unweighted aggregating step 50A in which each parameter Pn is accorded the same relative importance as all of the other parameters Pn. In certain embodiments, an unweighted aggregating step 50A may be carried out according to Equation 3 below.
Equation 3 : xL, YL) = ^ι¾> y L) + ^2(X L> Y L) + ^N (X L> Y L) where:
(xL> YL) represents an aggregate unweighted priority ranking 55 A at an individual location 30 whose position is (XL, YL) ;
Ri(xL, YL) represents the priority ranking 37 of parameter Pi at the same location L;
P-2(xL, YL) represents the priority ranking 37 of parameter P2 at the same location L; and
Rn (xL, YL) represents the priority ranking 37 of parameter Pn at the same location L.
Thus, a set 52A of unweighted aggregate priority rankings 55A may result from unweighted aggregating step 50A and may be expressed as: Expression 2: { Α(χ1> γι), Α(χ2> γ2)> ... A(XL; YL)} where:
1; Yx) represents an aggregate unweighted priority ranking 55A at an individual location 30 whose position is (Xi, Yi);
(x2> Y2) represents an aggregate unweighted priority ranking 55A at an individual location 30 whose position is (X2, Y2), and
(xL> Yl) represents an aggregate unweighted priority ranking 55 A at an individual location 30 whose position is (XL, YL).
[023] In certain embodiments, locations 30 having a corresponding aggregate unweighted priority ranking 55 A of unity (1) (or if expressed as a percentage, 100%) would correspond to locations 30 associated with the worst relative performance of network 19, taking into consideration all of the parameters Pi, P2, ... Pn, collectively, and those locations 30 having an aggregate unweighted priority ranking 55 A of zero (0) (or if expressed as a percentage, 0%) would correspond to locations 30 associated with the best relative performance of network 19 taking into consideration all of the parameters Pi, P2,... Pn, collectively. In alternative embodiments, the rankings 55A could be reversed such that a ranking value 40 of unity (1) (or if expressed as a percentage, 100%) could represent the best relative performance, and a ranking value 40 of zero (0) (or if expressed as a percentage, 0%) could represent the worst relative performance of network 19 taking into consideration all of the parameters Pi, P2, ... Pn, collectively.
[024] In certain alternative embodiments of the present method, aggregating step may be carried out as a weighted aggregating step 50B so that the various parameters P1; P2.. Pn can be taken into consideration in accordance to what a particular user of the method may regard to be the relative importance of respective ones of those parameters. In certain ones of such embodiments, a weighing factor 61 may be assigned to, or otherwise associated with, each of parameters P1; P2...Pn In such embodiments, each aggregate priority ranking 50 comprises what shall be referred to herein as an aggregate weighted priority ranking 55B. [025] In certain embodiments, a respective weighting factor 61 may be assigned to, or otherwise associated with, each of parameters P1; P2. . Pn such that the value of a weighting factor 61 for at least one of the parameters is selectable by a user of the method. In some embodiments of the type just mentioned, weighting factors 61 may be determined based on a software-defined weighing list 64 in which a user may assign, that is, enter and/or change, a respective weighting factor 61 associated with one or more of the parameters P1; P2. . Pn
[026] In certain embodiments, a weighted aggregating step 50B may be carried out according to Equation 4 below.
Equation 4: Aw(xL> Yl) = (Ri(xL, Yl) * Fi) + (R2(xL, Yl) * F2) + ... ( Rn (xL, Yl> * Fn) where:
AW(xL> Yl) represents an aggregate weighted priority ranking 55B at an individual location 30 whose position is (XL, YL) ;
Ri(xL, Yl) represents the priority ranking 37 of parameter Pi at the same location L;
F1 represents the weighting factor 61 for parameter P1;
R2(xL, Yl) represents the priority ranking 37 of parameter P2 at the same location L;
F2 represents the weighting factor 61 for parameter P1;
Rn (xL, Yl) represents the priority ranking 37 of parameter Pn at the same location L, and
Fn represents the weighting factor 61 for parameter Pn.
Thus, a set 52B of aggregate weighted priority rankings 55B may be expressed as: Expression 3 : {AW(XL; YL), AW(X2; Y2); ... AW (XL; YL)} where: W(x1; γχ) represents an aggregate weighted priority ranking 55B at an individual location 30 whose position is (Xi, Yi) ;
W(x2> Y2) represents an aggregate weighted priority ranking 55B at an individual location 30 whose position is (X2, Y2), and
W(xL> Yl) represents an aggregate weighted priority ranking 55B at an individual location 30 whose position is (XL, YL)-
[027] It will be appreciated that in embodiments in which the relative priority rankings 37 are determined according to Equation 2 if the weighting factors 61 are selected such that the sum of all weighting factors 60 is unity, as indicated by Equation 5 below, the aggregate weighted priority rankings 55 A determined based on Equation 4 will dimensionless number conveniently ranging from zero to one (0 to 1), which can alternatively be expressed as a corresponding percentage ranging from zero to one hundred percent (0 to 100%).
Equation 5 : F1 + F2 + ... Fn = l
[028] In certain ones of such embodiments, locations 30 having a corresponding aggregate weighted priority ranking 55B of unity (1) (or if expressed as a percentage, 100%) would represent locations 30 associated with the worst relative performance of network 19 taking into consideration all of the parameters Pi, P2, ... Pn, collectively, and those having an aggregate weighted priority ranking 55B of zero (0) (or if expressed as a percentage, 0%) would represent locations 30 associated with the best relative performance of network 19 taking into consideration all of the parameters Pi, P2, ... Pn, collectively, including their respective weighting factors 61.
[029] Method 10 may optionally but advantageously include a displaying step 60 which comprises displaying at least some of the aggregate priority rankings 55 at their respective locations on a map. The optional nature of displaying step 60 is denoted in Fig. 2. by the use of broken lines. In some embodiments, the aggregate priority rankings 55 displayed in displaying step 60 may comprise aggregate unweighted priority rankings 55A which in other embodiments, they may comprise aggregate weighted priority rankings 55B. In yet other embodiments, the aggregate priority rankings 55 displayed in displaying step 60 may comprise aggregate unweighted priority rankings 55 A and aggregate weighted priority rankings 55B, with either one, the other or both of same being displayed at a given time on a computer display screen on a user-selectable basis.
[030] In a deploying step 90, communications network 19 is physically altered by deploying at least one radio access network (RAN) asset 94 for network 19 at at least one location 30, that location 30 being selected based on based on the aggregate priority rankings 55. In some embodiments, such location 30 may be selected based on aggregate priority rankings 55 comprising aggregate unweighted priority rankings 55 A. In some embodiments, such location 30 may be selected based on aggregate weighted priority rankings 55B. In certain other embodiments, such location 30 may be selected based on either aggregate unweighted priority rankings 55 A or based on aggregate weighted priority rankings 55B, whichever alternative may be specified by a user on a selectable basis.
[031] As used herein and in the claims, the word "deploying" may include, but is not limited to, installing a radio access network (RAN) asset that was not previously present at the location 30. Rather, the word "deploying" may include any one or more of: (a) installing a radio access network (RAN) asset that was not already present at the location 30, (b) replacing a access network (RAN) asset that was already present at location 30 with one of either a same, similar or dissimilar type, (c) upgrading a access network (RAN) asset that was already present at the location 30 to provide that asset with improved or additional functionality and/or capacity, including but not limited to upgrading which may be carried out by replacing an antenna and/or one or more other component parts of the asset with one or more other component parts which alters the functionality of the asset, (d) repairing a radio access network (RAN) asset that was already present at the location 30 to at least partially restore lost or degraded operability, functionality or capacity of that asset, (e) changing at least one operational setting of a radio access network (RAN) asset that was already present at the location 30, (f) updating, debugging, repairing, revising or changing any portion of software or firmware which may control any aspect of operation of a radio access network (RAN) asset that was already present at the location 30. [032] In certain embodiments, the radio access network (RAN) asset 94 may comprise a wireless communications base station 102 and/or a component 104 of a wireless communications base station 102. Such component 104 may in certain embodiments comprise one or more of: (a) an antenna, (b) a radio transmitter (irrespective of transmission frequency, whether RF, microwave or other), (c) a repeater, (d) software, and/or (e) firmware. In certain embodiments, the wireless communication base station 102 may comprise a cellular base station 106. In some embodiments the cellular base station 106 may comprise one or more of the respective types commonly known as a macro cell, a small cell, a micro cell and/or a femtocell.
[033] In certain preferred embodiments, the location 30 selected in deploying step 90 may be selected as one having an aggregate priority ranking 55 at which meets at least one criterion 99. Such aggregate priority ranking 55 may comprise either an aggregate unweighted priority ranking 55 A or an aggregate weighted priority ranking 55B. In certain embodiments the criterion 99 may be one which specifies a threshold aggregate priority ranking 110. In some embodiments, the threshold aggregate priority ranking 110 has a value which is selectable and changeable by a user. In certain embodiments the criterion 99 may be one which specifies a range 115 of aggregate priority rankings 55 which, in some embodiments may be a range of aggregate unweighted priority rankings 55 A and/or a range of aggregate weighted priority rankings 55B. In some embodiments, the range 115 is one selectable and changeable by a user.
[034] In certain embodiments, a determination of locations 30 whose aggregate priority rankings 55, whether aggregate unweighted priority rankings 55A or aggregate weighted priority rankings 55B, satisfy criterion 99 may be made according to an optional filtering step 110, the optional nature of which is denoted in Fig. 2 by the use of broken lines. Although indicated in Fig. 2 as distinct step, filtering step 110 may in certain embodiments be carried out as a substep of another step, such as for example deploying step 90. [035] Filtering step 110 may be carried out in some embodiments by selecting from either a set 52 A of aggregate unweighted priority values 55 A or a set 52B of aggregate weighted priority values 55B, those of said vales 55 A or 55B which meet or exceed threshold aggregate priority ranking 110. Filtering step 110 may be carried out in some embodiments by selecting from either a set 52 A of aggregate unweighted priority values 55 A or a set 52B of aggregate weighted priority values 55B, those of said values 55 A or 55B within a range of such values. In some such embodiments filtering step 100 may be carried out specifying criterion 99 according to a Boolean expression and applying such Boolean expression to either a set 52 A of aggregate unweighted priority values 55 A or a set 52B of aggregate weighted priority values 55B
[036] As indicated by the broken arrow 120 in Fig. 2, in certain embodiments, optional displaying step 60, may optionally be repeated one or more times after a filtering step 80 has been carried out.
[037] Method 10 may be carried out as an automated method by a computer programmed in accordance with the method as described above.
[038] While the invention has been described with reference to various embodiments, it will be understood by those skilled in the art that changes may be made and equivalents substituted without departing from the scope of the invention.

Claims

What is claimed is:
1. A method of improving the performance of a wireless communication network, said method comprising the steps of:
(a) providing data specifying both a quantitative value of each one of a plurality of parameters at each respective one of multiple geographic locations within a within a service area of at least a portion of the network and a position of each of said locations, at least of said parameters being of a nature qualitatively different from at least one other of said parameters;
(b) for each respective one of said parameters, determining a relative priority ranking corresponding to each respective one of said locations, said priority ranking being determined based on a comparison of the said value of said parameter at said one of said locations with a one of said values which is an extreme value of the same said parameter among all said multiple locations;
(c) for all of said parameters collectively, aggregating said priority rankings corresponding to each respective one of said locations to determine a set of aggregate priority rankings which include an aggregate priority rank for each respective one of said locations; and
(d) deploying a radio access network (RAN) asset at a one of said locations selected based on said aggregate priority rankings.
2. A method as claimed in claim 1 wherein said data comprises data in a raster data format.
3. A method as claimed in claim 1 wherein said one of said locations at which said a radio access network (RAN) asset is deployed is selected by filtering at least a portion of said set of aggregate priority rankings according to at least one criterion.
4. A method as claimed in claim 3 wherein said criterion comprises a threshold aggregate priority ranking.
5. A method as claimed in claim 3 wherein said criterion comprises a range of threshold aggregate priority rankings.
6. A method as claimed in claim 1 further comprising the step of displaying at least some of said aggregate priority rankings at corresponding ones of said locations on a map.
7. A method as claimed in claim 6 wherein said aggregate priority rankings are displayed in color using different colors to represent different said aggregate priority rankings.
8. A method as claimed in claim 1 wherein said quantitative value comprises a binary value for at least one of said parameters and comprises a non-binary value for at least one other of said parameters.
9. A method as claimed in claim 1 further comprising the step of storing said aggregate priority rankings in a raster data format.
10. A method of improving the performance of a wireless communication network, said method comprising the steps of:
(a) providing data specifying both a quantitative value of each one of a plurality of parameters at each respective one of multiple geographic locations within a service area of at least a portion of the network and a position of each of said locations, at least of said parameters being of a nature qualitatively different from at least one other of said parameters;
(b) for each respective one of said parameters, determining a weighted relative priority ranking corresponding to each respective one of said locations, said weighted relative priority ranking being determined based on (i) a comparison of the said value of said parameter at said one of said locations with a one of said values which is an extreme value of the same said parameter among all said multiple locations and (ii) a weighting factor representing a relative importance of the said parameter as compared to others of the parameters in said set of parameters;
(c) for all of said parameters collectively, aggregating said weighted relative priority rankings corresponding to each respective one of said locations to determine a set of aggregate weighted priority rankings which include an aggregate weighted priority rank for each respective one of said locations; and
(d) deploying a radio access network (RAN) asset at a one of said locations selected based on said aggregate weighted priority rankings.
11. A method as claimed in claim 10 wherein said data comprises data in a raster data format.
12. A method as claimed in claim 10 wherein said weighting factor for each said parameter is assignable and changeable by a user.
13. A method as claimed in claim 10 wherein said one of said locations at which said a radio access network (RAN) asset is deployed is selected by filtering at least a portion of said set of aggregate weighted priority rankings according to at least one criterion.
14. A method as claimed in claim 13 wherein said criterion comprises a threshold aggregate weighted priority ranking.
15. A method as claimed in claim 13 wherein said criterion comprises a range of threshold aggregate weighted priority rankings.
16. A method as claimed in claim 10 further comprising the step of displaying at least some of said aggregate weighed priority rankings at corresponding ones of said locations on a map.
17. A method as claimed in claim 16 wherein said aggregate weighted priority rankings are displayed in color using different colors to represent different said aggregate priority rankings.
18. A method as claimed in claim 10 further comprising the step of storing said aggregate priority rankings in a raster data format.
19. A method as claimed in claim 10 wherein said quantitative value comprises a binary value for at least one of said parameters and comprises a non-binary value for at least one other of said parameters.
20. A method for evaluating the performance of a wireless communication network, said method comprising the steps of:
(a) providing data specifying both a quantitative value of each one of a plurality of parameters at each respective one of multiple geographic locations within a within a service area of at least a portion of the network and a position of each of said locations, at least of said parameters being of a nature qualitatively different from at least one other of said parameters;
(b) for each respective one of said parameters, determining a relative priority ranking corresponding to each respective one of said locations, said priority ranking being determined based on a comparison of the said value of said parameter at said one of said locations with a one of said values which is an extreme value of the same said parameter among all said multiple locations, and
(c) for all of said parameters collectively, aggregating said priority rankings corresponding to each respective one of said locations to determine a set of aggregate priority rankings which include an aggregate priority rank for each respective one of said locations.
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