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`Cisco v. TracBeam / CSCO-1002
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`ISSUE SIIP STAPLE AREA(foradditional cross references)
`INITIALS
`
`POSITION.
`
`FORMALITY REVIEW
`
`1 CLL, everscee ee
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`INDEX OF CLAIMS
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`€ fh tweet.
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`DRAFTING
`
`INDEX OF CLAIMS
`
`SYMBOLS
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`Cisco v. TracBeam / CSCO-1002
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`Cisco v. TracBeam / CSCO-1002
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`RANS MITTAL
`UTILITY CCEQ@RNUATION PATENT APPLICATIG
`for new nonprovisional applications under 37 CF AQ@(b))
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`1003-1
`“SS Z== Attorney Docket No.:
`———
`==
`Inventors: Dennis J. Dupray of 1801 Belvedere Street, Golden,Colorado 80401
`==o0
`Charles L. Karr of 400 Sandbrook Lane, Tuscaloosa, Alabama 35405
`Express Mail Label No.: EL545144476US
`Title:
`“LOCATION OF A MOBILE STATION’
`
`Prior Group Art Unit:
`
`3662
`
`Prior Examiner: Dao Phan
`
`This is a Continuation application of pending prior application No. 09/194 ,367 filed November 24, 1998. The entire
`disclosure of the prior application, from which a copyof the oath or declaration is supplied, is considered to be part of the
`disclosure of the accompanying application and is hereby incorporated by reference.
`
`[x]
`
`Enclosedforfiling with the above-identified utility patent application, pleasefind the following:
` 1.
`is
`a= [x]
`td
`3.
`[X]__
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`4,
`[x]
`5.
`(]
`
`Copy of Oath/Declaration from the above-referenced pending prior application (37 CFR
`1.63(d))
`Preliminary Amendment
`Return Postcard (MPEP 503) (should be specifically itemized)
`A checkin the amount of $1,119.00 is enclosed.
`Other:
`
`FEEiCALCULATION:
`
`Cancelin this application original Claims 1 - 124 of the prior application before calculating the filing fee.
`
`Ff
`
`SMALL ENTITY
`
`LARGE ENTITY
`
`(COL. 1)
`(COL. 2°)
`NO. FILED
`NO. EXTRA
`BASIC FEE pOss00fon||s710.00
`|rora.cuams:|o6|-|20]——76|__—sxsa=|—sesaoo|on|xsre-|
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`____ MULTIPLE DEPENDENT CLAIMS
`ZERO, ENTER "O" IN COL.2.
`‘IF THE DIFFERENCE IN COL. 2 IS LESS THAN
`TOTAL:
`$1,119.00
`
`Cisco v. TracBeam / CSCO-1002
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`OTHER INFORMATION: Woneris hereby authorized to debit any un payments or credit any overpaymentto
`
`q\
`
`4
`
`1.
`
`[]
`
`The Cont
`Deposit Account No. 19-1970.
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`4.
`
`5.
`
`6.
`
`[]
`
`[]
`
`[xX]
`
`The Commissioner is hereby authorized to charge all required fees for extensions of time under
`§1.17 to Deposit Account No. 19-1970.
`
`Foreign Priority benefits are claimed under 35 USC §119 of Patent Application Serial No. filed
`
`The Small Entity Statement was filed in the above-referencedprior application. Small Entity status
`is still proper and desired.
`
`[X]
`
`The prior application is assigned to TracBeam LLC.
`
`Correspondence Address:
`
`Dennis J. Dupray, Ph.D.
`1801 Belvedere Street
`Golden,Colorado 80401
`Telephone: (303) 863-2975
`Facsimile: (303) 863-0223
`
`
`LAnthi,ZI)
`
`Ue
`Derinis J. Dupfa
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`Registration Nz.
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`5
`
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`®
`
`e
`
`WIRELESS LOCATION USING MULTIPLE SIMULTANEOUS LOCATION ESTIMATORS
`
`FIELD OF THE INVENTION
`
`The presentinventionis directed generally to a system and method for locating people or objects, and in particular, to a
`
`system and method for locating a wireless mobile station using a plurality of simultaneously activated mobile station location
`estimators.
`
`BACKGROUND OF THE INVENTION
`
`Introduction
`
` 10
`
`15
`
`- 20
`
`25
`
`30
`
`Wireless communications systems are becoming increasingly important worldwide. Wireless cellular telecommunications
`
`systems are rapidly replacing conventional wire-based telecommunications systems in manyapplications. Cellular radio telephone
`
`networks (“CRT”), and specialized mobile radio and mobile data radio networks are examples. The generalprinciples ofwireless
`
`cellular telephony have been described variously, for example in U. $. Patent 5,295,180 to Vendetti, et al, which is incorporated herein
`by reference.
`
`There is great interest in using existing infrastructures for wireless communication systemsfor locating people and/or
`
`objectsin a cost effective manner. Such a capability would be invaluablein a variety of situations, especially in emergency orcrime
`
`Situations. Due to the substantial benefits of such a location system, several attempts have been made to design and implement such
`a system.
`.
`Systems have been proposed that rely upon signal strength and trilateralization techniques to permit location include those
`disclosed in U.S. Patents 4,818,998 and 4,908,629 to Apsell etal. (“the Apsell patents”) and 4,891,650to Sheffer (“the Sheffer
`patent”). However, these systems have drawbacks that include high expense in that special purpose electronics are required.
`
`Furthermore, the systems are generally only effective in line-of-sight conditions, such as ruralsettings. Radio wave surface
`
`reflections, refractions and ground clutter cause significant distortion,in determining the location of a signal source in most
`geographical areas that are more than sparsely populated. Moreover, these drawbacks are particularly exacerbated in dense urban
`canyon (city) areas, where errors and/orconflicts in location measurements can result in substantial inaccuracies.
`
`Another example of a location system using time of arrival and triangulation for location are satellite-based systems, such
`as the military and commercialversionsof the Global Positioning Satellite system (“GPS”). GPS can provide accurate position
`determination (i.e., about 100 meters error for the commercial version of GPS) from a time-based signal received simultaneously
`from at least three satellites. A ground-based GPSreceiver at or near the object to belocated determinesthe difference between the
`
`time at which each satellite transmits a time signal and the time at which the signal is received and, based on thetime differentials,
`determines the object’s location. However, the GPSis impractical in many applications. The signal powerlevels from the satellites
`1
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`are lowand the GPS receiver 2.clear, line-of-sight path to atleastthree saecoDY horizon ofabout 60 degrees for
`
`effective operation. Accordingly, inclement weather conditions, such as clouds,terrain features, such ashills and trees, and buildings
`
`restrict the ability of the GPS receiver to determineits position. Furthermore, the initial GPS signal detection process for a GPS
`
`receiveris relatively long (i.e., several minutes) for determining the receiver's position. Such delays are unacceptable in many
`
`applications such as, for example, emergency response and vehicle tracking.
`
`Differential GPS, or DGPS systems offer correction schemes to accountfor time synchronizationdrift. Such correction
`schemesinclude the transmission of correction signals over a two-wayradio link or broadcast via FM radio station subcarriers. These
`systems have been found to be awkward and have met with limited success.
`Additionally, GPS-based location systems have been attempted in which the received GPSsignals are transmitted to a
`central data center for performing location calculations. Such systems have also met with limited success.
`In brief, each of the
`various GPS embodiments have the same fundamental problemsoflimited reception of the satellite signals and added expense and
`complexity of the electronics required for an inexpensive location mobile station or handsetfor detecting and receiving the GPS
`
`signals from the satellites.
`
`Radio Propagation Background
`
`The behavior of a mobile radio signalin the general environmentis unique and complicated.Efforts to perform
`correlations between radio signals and distance between a base station and a mobile station are similarly complex. Repeated attempts
`
`to solve this problem in the past have been met with only marginal success. Factors include terrain undulations, fixed and variable
`
`clutter, atmospheric conditions, internal radio characteristics of cellular and PCS systems, such as frequencies, antenna
`
`configurations, modulation schemes, diversity methods, and the physical geometries ofdirect, refracted and reflected waves between
`
`the base stations and the mobile. Noise, such as man-madeexternally sources (e.g., auto ignitions) and radio system co-channel and
`adjacent channelinterferencealso affect radio reception and related performance measurements, such as the analogcarrier-to-
`interference ratio (Ci), ordigital energy-per-bit/Noise density ratio (E,,,) and are particular to various points in time and space
`domains.
`
`RF Propagation in Free Space
`
`Before discussing real world correlations between signals and distance,it is useful to review the theoretical premise, that of
`radio energy path loss across a pure isotropic vacuum propagation channel, andits dependencies within and among various
`communications channel types. Fig. | illustrates a definition of channel types arising in communications:
`
`Over the last forty years various mathematical expressions have been developed to assist the radio mobile cell designer in establishing
`
`
`
`10
`
`15
`
`20
`
`25
`
`the proper balance between base station capital investment and the quality of the radio link, typically using radio energy field-
`strength, usually measured in microvolts/meter, or decibels.
`.
`
`30
`
`First consider Hata’s single ray model. A simplified radio channel can be described as:
`
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`Ores sugss
`
`(Equation !)
`
`where G, = system gain in decibels
`
`L,= free space path loss in dB,
`F = fade margin in dB,
`
`L, = transmissionline loss from coaxials used to connect radio to antenna,in dB,
`
`L,= miscellaneouslosses such as minor antenna misalignment, coaxial corrosion, increase in the receiver noise figure due
`
`to aging,in dB,
`
`10°
`
`L,= branching loss dueto filter and circulator used to combineorsplit transmitter and receiversignals in a single
`antenna
`
`G,= gain of transmitting antenna
`G= gain of receiving antenna
`
`15
`
`
`
`20
`
`25
`
`Free space path loss! L, as discussed in Mobile Communications Design Fundamentals, William C. ¥.Lee, 2nd, Ed across the propagation channel
`is a function of distance d, frequency
`f (for f values < | GHz, such as the 890-950 mHz cellular band):
`
` Po 1
`P,
`(4ndfc)’
`
`(equation 2)
`
`where Por = received powerin free space
`P= transmitting power
`
`_ c= speedoflight,
`
`The difference between two received signal powers in free space,
`
`A, =(10)log{22} - (20)oof+}(ax)
`
`or)
`
`2
`
`(equation 3)
`
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`indicatesthatthefree propaga lossis20dB perdecade. Frequencies between | & 2GHz experience increased valuesin
`
`the exponent, ranging from 2 to 4, or 20 to 40 dB/decade, which would be predicted for the new PCS1.8 - 1.9 GHz band.
`
`This suggests that the free propagation path loss is 20 dB per decade. However, frequencies between | GHz and 2 GHz experience
`
`increased values in the exponent, ranging from 2 to 4,or 20 to 40 dB/decade, which would be predicted for the new PCS 1.8 - 1.9 GHz
`
`band. One consequence from a location perspective is that the effective range of values for higher.exponentsis an increased at higher
`
`frequencies, thus providing improved granularity of ranging carrelation.
`
`Environmental Clutter and RF PropagationEffects
`
`Actual data collected in real-world environments uncovered huge variations with respect to thefree space path loss
`equation, givingrise to the creation of many empiricalformulas for radio signal coverage prediction.Clutter, eitherfixed or
`
`stationary in geometric relation to the propagationof the radio signals, causes a shadow effect of blocking that perturbs the free
`
`spaceloss effect.-Perhaps the best known modelset that characterizes the average pathloss is Hata’s, “Empirical Formulafor
`Propagation Loss in Land Mobile Radio”, M. Hata, [EEE Transactions ¥T-29, pp. 317-325, August 1980,three pathloss models, based
`on Okumura’s measurements in and around Tokyo, “Field Strength and its Variability in VHF and UHF Land Mobile Service”, Y.
`
`Okumura,et al, Review of the Electrical Communications laboratory, Vol 16, pp 825-873,Sept. - Oct. 1968.
`
`The typical urban Hata model for L, was defined as L, = L,,:
`
`Ly, = 69.55 + 26.16log(/) — 13.82 log(h,, ) — ays ) + (44.9 — 6.55 log(7,, ) log(d)[dB])
`
`,
`
`,
`
`(Equation 4)
`
`where Lyy — pathloss, Hata urban
`
`hBS = base station antenna height
`hMS= mobile station antenna height
`d= distance BS-MS in km
`
`a(ms) is a correction factor for small and medium sized Cities, found to be:
`
`all,a,ara
`och€.4
`
`
`10
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`15
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`20
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`30
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`llog(f }.... —1.56log(/ — 0.8) = a(h,,, ) ©
`
`For large cities the correction factor was found to be:
`
`a(hyc) = 3.2 [log11.75hy,5]° — 4.97
`
`assumingf is equal to or greater than 400 mHz.
`
`The typical suburban model correction was found to be:
`
`(Equation 5)
`
`(Equation 6)
`
`
`
`
`Ltrm =LHe >teeZ) -5.4[dB]
`
`fy’
`
`7
`
`(Equation7)
`
`The typical rural model modifted the urban formula differently, as seen below:
`
`Lizeurat = Lyy— 4-78 (log)? + 18.33log f- 40.94 [dB]
`20
`Although the Hata model was found to be useful for generalized RF waveprediction in frequencies under | GHzin certain
`suburban and ruralsettings,as either the frequency and/or clutter increased, predictability decreased. In current practice, however,
`
`(Equation 8)
`
`field technicians often have to make a guess for dense urban an suburban areas (applying whatever model seems best), then
`
`installing a base stations and begin taking manual measurements. Coverage problems can take upto a yearto resolve.
`
`25
`
`Relating Received Signal Strength to Location
`
`Having previously established a relationship between d and P,,, reference equation 2 above: d represents the distance
`between the mobile station (MS) and the base station (BS); P,, represents the received power in free space) for a given set of
`
`unchanging environmental conditions, it may be possible to dynamically measure P,, and then determine d.
`
`In 1991, U.S. Patent 5,055,851 to Sheffer taught that if three or more relationships have been established in a triangular
`
`30
`
`space of three or more base stations (BSs) with a location database constructed having data related to possible mobile station (MS)
`
`locations, then arculation calculations may be performed, which use three distinct P,, measurements to determine an X,Y, two
`
`5
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`dimensionallocation, which cai
`
` 4on is based on the fact that the
`
`¢ projected onto an area map. The triangulation ca i
`approximate distance of the mobile station (MS) from any base station (BS) cell can be calculated based on the received signal
`strength. Sheffer acknowledges that terrain variationsaffect accuracy, although as noted above, Sheffer’s disclosure does not account
`for a sufficient numberof variables, such as fixed and variable location shadow fading, which are typicalin dense urban areas with
`
`movingtraffic.
`
`Most field research before about 1988 has focused on characterizing (with the objective of RF coverage prediction) the RF
`
`propagation channel(i.e., electromagnetic radio waves) using a single-ray model, although standardfit errors in regressions proved
`
`dismal (e.g., 40-80 dB). Later, multi-ray models were proposed, and muchlater, certain behaviors were studied with radio and
`
`digital channels. In 1981, Vogler proposed that radio wavesat higher frequencies could be modeled using optics principles. In 1988
`
`Walfisch and Bertoni applied optical methods to develop a two-ray model, which when comparedto certain highly specific, controlled
`
`field data, provided extremely good regression fit standard errors of within |.2 dB.
`
`In the Bertoni two ray model it was assumed that most cities would consist of a core of high-rise buildings surrounded by a
`
`muchlarger area having buildingsof uniform height spread over regions comprising many square blocks, with street grids organizing
`buildings into rows that are nearly parallel. Rays penetrating buildings then emanating outside a building were neglected.Fig. 2
`providesa basis for the variables.
`
`After a lengthy analysis it was concluded that path loss was a functionof three factors: (I)the path loss between antennas
`in free space; (2) the reduction of rooftop wavefields due to settling; and (3) the effect of diffraction of the rooftop fields down to
`ground level. The last two factors were summarily termed Loy, givenby:
`
`LE, = 571+ A+log(f)+ Rk -— (18 log(A7 ))—- 18 tog|1 -
`
`2
`
`
`17H
`
`| cwaion
`
`
` 20
`
`The influence of building geometry is containedin A:
`
`= 5log [( s) ‘| ~9logd + 20log { tan [2(h—Hyjs)] 3
`
`25
`
`30
`
`(Equation 10)
`
`However, a substantialdifficulty with the two-ray modelin practice is that it requires a substantial amountof data
`regarding building dimensions, geometries, street widths, antenna gain characteristics for every possible ray path, etc. Additionally,
`it requires an inordinate amount of computational resources and such a modelis not easily updated or maintained.
`Unfortunately, in practice clutter geometries and building heights are random. Moreover,data of sufficient detail has been
`extremely difficult to acquire, and regression standard fit errors are poor; i.e., in the general case, these errors were found to be 40-
`
`60 dB. Thus the two-ray mode! approach, although sometimes providing an improvementoversingle ray techniques, still did not
`
`predict RF signal characteristicsin the general case to level of accuracy desired (< 10dB).
`
`6
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`Work by Greenstein ©.. developed from the perspective of measurementQeresion models,as opposed to the
`previous approachof predicting-first, then performing measurement comparisons. Apparently yielding to the fact that low-power,
`
`low antenna (e.g., 12-25 feet above ground) height PCS microcell coverage wasinsufficient in urban buildings, Greenstein,et al,
`authored “Performance Evaluations for Urban Line-of-sight Microcells Using a Multi-ray Propagation Model”, in IEEE Globecom
`
`Proceedings, 12/91. This paper proposed the idea of formulating regressions based onfield measurements using small PCS microcells
`ina lineal microcell geometry (i.¢., geometries in which there is always a line-of-sight (LOS) path between_a subscriber’s mobile and
`its current microsite).
`
`Additionally, Greenstein studied the communication channels variable Bit-Error-Rate (BER) in a spatial domain, which was
`
`a departure from previous research that limited field measurements to the RF propagation channelsignal strength alone. However,
`Greenstein based his finding on two suspicious assumptions: |) he assumed that distance correlation estimates were identicalfor
`uplink and downlink transmission paths; and 2) modulation techniques would be transparent in terms of improved distance
`
`correlation conclusions. Although some data held very correlations, other data and environments produced poorresults. Accordingly,
`
`his results appear unreliable for use in general location context. -
`ln 1993 Greenstein,et al, authored “A Measurement-Based Modelfor Predicting Coverage Areas of Urban Microcells”, in
`the IEEE Journal On Selected Areas in Communications, Vol. ||, No. 7, 9/93. Greenstein reported a generic measurement-based model
`of RF attenuation in terms of constant-value contours surrounding a given low-power,low antenna microcell environmentina dense,
`rectilinear neighborhood, such as New York City. However, these contours were for the cellular frequency band.In this case, LOS and
`non-LOS clutter were considered for a given microcell site. A result of this analysis was that RF propagation losses (or attenuations),
`when cell antenna heights were relatively low, provided attenuation contours resembling a spline plane curve depicted as anasteroid,
`aligned with major street grid patterns. Further, Greenstein found that convex diamond-shaped RF propagation loss contours were a
`common occurrence in field measurementsin a rectilinear urban area. The special plane curve asteroid is represented by the formula
`x22 + y? = 7. However, these results alone have not beensufficiently robust and generalto accurately locate an MS, due to the
`variable nature of urban clutter spatial arrangements...
`
`At Telesis Technology in 1994 Howard Xia,et al, authored “Microcellular Propagation Characteristics for Personal
`
`Communications in Urban and Suburban Environments”,in IEEE Transactions of Vehicular Technology,Vol. 43, No.3, 8/94, which
`
`performed measurements specifically in the PCS 1.8 to 1.9 GHz frequency band. Xia found corresponding but more variable outcome
`
`results in San Francisco, Oakland (urban) and the Sunset and Mission Districts (suburban).
`
`Summary ef Factors Affecting RF Propagation
`
`The physical radio propagation channel perturbs signal strength, frequency (causing rate changes, phase delay, signal to
`
`noise ratios (e.g., C/I for the analog case, or E,,, , RF energy per bit, over average noise density ratio for the digital case) and
`
`Doppler-shift. Signal strength is usually characterized by:
`
`~ Free Space Path Loss(L,)
`
`20
`
`25
`
`30
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`* Slowfading lossm| (a)
`
`Fast fading loss or margin (L,..)
`
`@
`
`Loss due to slow fading includes shadowing dueto clutter blockage (sometimes included in Lp). Fast fading is composed of
`
`multipathreflections which cause: |) delay spread; 2) random phase shift or Rayleigh fading; and 3) random frequency modulation
`
`5
`
`due to different Doppler shifts on different paths.
`Summing the path loss and the two fading margin loss components from the above yieldsa total path loss of:
`Listt = by + bie + bis
`
`Referring to Fig. 3, the figure illustrates key components of a typicalcellular and PCS power budget design process.Thecell designer
`10_increases the transmitted power P,, by the shadow fading margin L,,, which is usually chosen to be within the 1-2 percentile of the
`slow fading probability density function (PDF) to minimize the probability of unsatisfactorily low received powerlevel P,, at the
`
`
`
`ehalg
`
` 20
`
`receiver. The P,, level must have enoughsignal to noise energy level (e.g., 10 dB) to overcomethe receiver’s internalnoise level (e.g.,
`-118dBm in the case of cellular 0.9 GHz), for a minimum voice quality standard. Thus in the example Pix must never be below -108
`dBm,in order to maintain the quality standard.
`
`15
`
`Additionally the short term fast signal fading due to multipath propagationis taken into account by deployingfast fading
`
`margin L,..». which is typically also chosen to be a few percentiles of the fast fading distribution.The | to 2 percentiles compliment
`
`other network blockage guidelines. For example the cell base station traffic loading capacity and network transport facilities are
`
`usually designed for a |-2 percentile blockage factor as well. However, in the worst-case scenario both fading margins are
`
`simultaneously exceeded, thus causing a fading margin overload.
`
`In Roy , Steele’s, text, Mobile Radio Communications, {EEE Press, 1992, estimates for a GSM system operating in the 1.8
`
`GHz band with a transmitter antenna height of 6.4m and an MSreceiver antenna height of 2m, and assumptions regardingtotal
`
`pathloss, transmitter power would be calculated asfollows:
`
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`Table 1: GSM Power Budget Example
`
`Lasta
`
`Min. RX pwr required
`
`
`
`
`
`
`
`
`
`
`
`TXpwr = 27 dBm
`
`
`
`
`
`
`
`Steele's samplesize in a specific urban London area of 80,000 LOS measurements and data reduction found a slow fading variance of
`
`o = 7dB
`
`10_assuming lognormalslow fading PDF and allowingfora 1.4% slow fading margin overload,thus
`
`slow = 20 = 14dB
`
`The fast fading margin was determined to be:
`
`is
`
`Efast = 74B
`
`In contrast, Xia’s measurements in urban and suburban California at 1.8 GHz uncovered flat-land shadow fades
`
`on the orderof 25-30 dB when the mobile station (MS) receiver was traveling from LOS to non-LOS geometries.in hilly terrain fades
`
`of +5 to -50 dB were experienced. Thus it is evident that attemptsto correlate signal strength with MS ranging distance suggest that
`
`error ranges could not be expected to improve below 14 dB, with a high side of 25 to 50 dB. Based on 20 to 40 dB perdecade,
`
`20
`
`Corresponding error rangesfor the distance variable would then be on the orderof 900feetto several thousand feet, depending upon
`
`the particular environmental topology and the transmitter and receiver geometries.
`
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` 3
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`ve£m
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`

`SUMMARY OF THE INVENTION
`
`OBJECTS OF THE INVENTION
`
`It is an objective of the present invention to provide a system and method for to wireless telecommunication systemsfor
`accurately locating people and/or objects ina cost effective manner. Additionally,it is an objective of the present invention to provide
`suchlocation capabilities using the measurements from wireless signals communicated between mobile stations and a network of base
`stations, wherein the same communication standard orprotocolis utilized for location as is used by the networkof base stations for
`providing wireless communications with mobile stations for other purposes such as voice communication and/or visual
`communication (such as text paging, graphical or video communications). Related objectives for the present invention include
`providing a system and methodthat:
`(lJ)
`can be readily incorporated into existing commercial wireless telephony systems with few,if any, modifications of a typical
`telephony wireless infrastructures
`.
`(12)
`canuse the nativeelectronics oftypical commercially avaitable telephony wireless mobile stations (e.g., handsets) as
`location devices;
`|
`
`(13)
`
`can be used foreffectively locating people and/or objects wherein there are few (if any) line-of-sight wireless receivers for
`
`receiving location signals from a mobile station (herein also denoted MS);
`(1.4)
`can be used not only for decreasing location determiningdifficulties due to multipath phenomena butin fact uses such
`multipath for providing more accuratelocation estimates;
`(1.5)
`can be used forintegrating a wide variety of location techniquesin a straight-forward manner; and
`(1.6)
`can substantially automatically adapt and/or (re)train and/or (re)calibrate itself according to changes in the environment
`and/orterrain of a geographical area where the present inventionis utilized.
`Yet another objective is to provide a low cost location system and method, adaptable to wireless telephony systems, for
`using simultaneously a plurality of location techniquesfor synergistically increasing MS location accuracy and consistency.
`In
`particular, at least someofthe following MS location techniques can be utilized by various embodiments of the present invention:
`(2.1)
`time-of-arrival wireless signal processing techniques;
`
`10
`
`15
`
`20
`
`3ach.
`
`
`b*hi
`
`
`ah
`
`25
`(2.2)__time-difference-of-arrival wireless signal processing techniques;
`
`(23)
`adaptive wireless signal processing techniques having, for example, learning capabilities and including, forinstance,
`artificial neural net and genetic algorithm processing:
`.
`(2.4)_signal processing techniques for matching MSlocation signals with wireless signal characteristics of known areas;
`(25)
`conflict resolution techniques for resolving conflicts in hypotheses for MSlocationestimates;
`(2.6)
`enhancement of MS location estimates through the use of both heuristics and historical data associating MS wireless signal
`
`30
`
`characteristics with known locations and/or environmental conditions.
`
`10
`
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`

`
`
`an be used to establish motion,
`rovide location estimates in terms of time vectors,3
`Yet another objective
`speed, and an extrapolated next location in cases where the MS signal subsequently becomes unavailable.
`
`DEFINITIONS
`
`Thefollowing definitions are provided for convenience.In general, the definitions here are also defined elsewhere in this
`document as well.
`
`The term “wireless” herein is, in general, an abbreviation for “digital wireless”, and in particular, “wireless”refers to
`3.1)
`digital radio signaling using one of standard digital protocols such as CDMA, NAMPS, AMPS, TDMA and GSM,as oneskilled in the art
`will understand.
`
`(3.2)
`
`As used herein, the term “mobile station” (equivalently, MS)refers to a wireless device that is at least a transmitting
`
`device, and in most cases is also a wireless receiving device, such as a portable radio telephony handset. Note that in some contexts
`
`herein instead or in addition to MS,the following termsare also used: “personal station” (PS), and “location unit” (LU). In general,
`
`these terms may be considered synonymous. However, the later two terms may be used when referring to reduced functionality
`
`communication devices in comparison to a typical digital wireless mobile telephone.
`
`The term,“infrastructure”, denotes the network of telephony communication services, and moreparticularly, that portion
`(33)
`of sucha network that receives and processes wireless communications with wireless mobile stations. In particular, this infrastructure
`includes telephony wireless base stations (BS) such as those for radio mobile communication systems based on CDMA, AMPS, NAMPS,
`
`TDMA, and GSM wherein the base stations provide a network of cooperative communication channels with anair interface with the
`MS, and a conventional telecommunicationsinterface with a Mobile Switch Center (MSC). Thus, an MSuser within an area serviced by
`the base stations may be provided with wireless communication throughout the area byuser transparent communication transfers
`(ie., “handoffs”) between the user’s MS and these base stations in order to maintain effective telephony service. The mobile switch
`
`center (MSC) provides communications and control connectivity among base stations and the public telephone network.
`
`10
`
`15
`
`20
`
`seepa
`hee
`Lig