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Propagation measurements and models for wireless channels

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Propagation measurements and models for wireless channels

  1. 1. PropagationMeasurements and Models for WirelessCommunications Channels To achieve ubiquitous PCS, new and novel waysof classifying wireless environmentswill be needed that are bothwidely encompassingand reasonablycompact. Jargen Bach Andersen, Theodore 5. Rappaport, and Susumu Yoshida JGRGEN BACHANDER- SEN is u professor at Aalborh. Universipand head of thc Centerfor Personkommn- nikation. THEODORE S. RAPPA- PORT 0 un associareprafes- sor of electrical rngineenng at Viwnia Tech. SUSUMU YOSHIDA u profawr of electricalengi- neering at Kyoto Universip. ireless personal communica- tionscouldinprincipleusesev- era1 physical media, ranging from sound to radio tolight. Sincewewant toovercome the limitations of acoustical com- munications, we shall concentrateon propagation of electromagnetic wavcs in the frequency range from some hundreds of MHz to a few GHz. Although thereisconsiderable interest atthe moment in millimeter wave communications in indoor environments, theywillbe mentionedonlybrieflyin this survey of propagation of signals. Itisinteresting to observe that propagation results influence personal communications systems in severalways. First thereisobviouslythe distribution ofmeanpoweroveracertainareaorvolumeofinter- est, which is the basic requirement for reliable communications. The energy should be sufficient for the link in question, but not too strong,in order not to create cochannel interfcrcnce at a distance in another cell. Also, since the radio link is highly variable over short distances, not only the mean poweris significant; the statistical dis- tribution is also important. This is especially true when the fading distribution is dependent on thc bandwidth of the signal. Secondly. evenif there is sufficient power availablefor communications, the qualityof the signalmay be such that large errors occur anyway. This results from rapid movement through thescatteringenvironment,or impairments due to long echoes leading to inter-symbol-inter- ference. A basic understanding of the channel is important forfindingmodulation andcodingschemes that improve thc channel, for designing equaliz- ers or,if this is not possible, for deploying basc station antcnnas in such away that the detrimen- tal effects are lesslikely to occur. In this article we will describe the type of sig- nals that occur invarious cnvironments and the mod- eling of the propagation parameters. Models are essentially of two classes.The first class consists of parametric statistical models thaton average describcthephenomenonwithinagivenerror.They are simple to use, but relativcly coarse.In the last fewyearsa secondclass ofenvironment-specificmod- e1shasbeenintroduced.Thesemodelsareofamore deterministicnaturc,characterizingaspecificstreet, building, etc. They are necessarily more time con- sumingtouse,but arealsomore revealingconcerning physical details and hopefully morc accurate. Firstsome keyparametersandthemeasurement ofthemwill be discussed and then the differentwire- less environmentswill be treated. The latter topic is divided here into outdoor environments, indoor environments, and radio penetration from out- door to indoor environments. The Physics of Propagation Themechanismswhich governradio propagation are complex and diverse, andthey can general- ly be attributed to threebasic propagation mech- anisms: reflection, diliraction, and scattering. Reflection occurs when a propagating electro- magnetic wave impinges upon an obstruction with dimensions very large compared to the wavelength of thc radio wave. Reflections from the surface of the earth and from buildings pro- duce rcflcctedwaves that may interfere construc- tively or destructively ata receiver. Diffraction occurs when the radio path between thetransmitterandreceivcrisobstructedbyanimpen- etrablebody. BasedonHuygen’sprinciple,secondary waves are formed behind the obstructing body even though there is no line-of-sight (LOS) between the transmitter and receiver. Diffraction explains how radio frcquency(RF) energy can travel in urban and rural environments without a LOS path. This phenomenonis also called “shad- owing,”becausethediffractedfieldcanreacharecciv- er even when itis shadowed by an obstruction. Scatteringoccurswhenthcradiochannelcontains objects with dimensions that are on the orderof thewavelengthor1cssofthepropagatingwave.Scat- tering, which follows the same physical principles as diffraction, causes energy from a transmitterto be reradiatedin many different directions.Ithasproven to be the mostdifficultof the three propagationmech- anisms to predictin emerging wireless personal communication systems. For example, in urban microccllular systems, lamp posts and street signs 42 IEEE Communications Magazine January 1995 ~~ -
  2. 2. ~ ~~ scatter energy in many directions, thereby prowding RF coverage to locations which might not rcccive energyviareflectionordiffnction. The three mech- anisms are illustrated in Fig. 1. As a mobile radio moves throughout a cover- age area, the three propagation mechanismshave an impact on theinstantaneous received signal in differentways. Forexample, ifthemobile hasaclear LOS path to the base station, diffraction andscat- tering arenot likely to dominate the propagation. Likewise, if the mobile is at streetlevel in a large metropolitan areawithout aLOSto thebase statlon. diffraction and scattering aremost likely to domi- nate thepropagati0n.k the mobilemovesoversmall distances. thc instantaneous received narrowband signal strength will fluctuate rapidly giving rise to small-scale fading.The reasonfor this isthat thefield isasumofmanycontributionscomingfromdifferent directionsand since the phases are random, the sum bchaves as a noise signal,Le.. Rayleigh fading. In small-scale fading, thereceived signal power may vary by as much as threeor four orders o f magni- tude (30 or 30 dB) when the receiverIS moved by only a fraction of a wavelength. As the mobile moves awayfromthe transmitter over largerdistances, the local average received signalwill gradually decrease. Typically, the local average signalis computed over receiver movementsof 5 to 40 wavelengths 11-31, Figure 2 demonstrates the effects of small-scale fading andlarge scale signal variation foran indoor radiocommunication system. Notice in the figure that thesignal fades rapidly as thereceivermoves,butthelocalave.eragesignalchanges much mure slowly with distance. In mobile radio systems, communications engineers are generally concernedwith two main radio channelissues: link budget and time disper- sion. The link budget is determined by the amount of received power that may expected at a particu- lar distance orlocation from a transmitter, and it determines fundamental quantities such as trans- mitterpowerrequirements, coverage areas,andbat- tery life. Time dispersion arises due to multipath propagationwherebyreplicasof the transmittcdsig- nal reach thereceiver with different propagation delays due to the propagation mechanisms described above. The time-dispersive nature of the channel determines the maximum data rate that may be transmitted without requiring equal- ization and also determines the accuracyof navi- gational servicessuch as vehicle location. Propagation parameters Path loss -Link budget calculations requirean estimate of the power levelso that a signal-to-noise ratio (SNR) or, similarly, a carrier-to-intcrference (QI) ratio may be computed. Because mobile radio systems tendto be interferencelimited (due tootheruserssharing thesamechanne1)rather than noise limited,the thermal and man-madenoise effects are often insignificant compared to thesignal levels of cochannel users. Thus, understanding the propa- gation mechanismsin wireless systems becomes important for notonly predictingawerage to a partic- ular mobile user,but alsoforpredicting theinterfering signalsthatuserwillexperiencefromotherRFsources. Weusepathloss(PL) heretodenotethelocalaver- age received signal power relative to the transmit power. Thisisausefulquantity,since receivedpower is usuallymeasured as a local spatial averagerather A W Figure 1. Sketch of three lmpottantpropagation mechanisms: rejlection (R). scattering (S),diffraction (Dl. I W Figure 2. Tvpicalreceived simal levelsfor anindoor radio communication sy'tem. ,'otic> that small .scak fading produceslevel changes of 20 db or more, where the local average signallevelchanges much moreslowly with distance. thananinstantaneousvalue.Inrealisticmob~leradio channels, free space does notapply. A general PL model that has been demonstrated through mea- surements [l,4) uses a parameter, n, to denote the powerlaw relationship between distance and received power. As a function of distance, d, PL (in decibels) is expressed as PL(d) = PL(d0) + 10n log(d/do)+Xo (1) where n = 2 for free space, andis generally high- er for wireless channels. ThetermPL(do)simplygivesPLataknownclose in reference distance do which is in the farfield of the transmitting antenna (typically 1 km for large urban mobile systems, 100 m for microcell sys- tems, and 1 m for indoorsystems) andX , denotes a zero mean Gaussian random variable (with units of dB) that reflects the variationin average receivedpower that naturallyoccurswhenaPL model of this type is used.SincethePL modelonlyaccounts for the distancewhich separates the transmitter IEEE CommunicationsMagazme January 1995 43
  3. 3. 140 130 120 1 0 110 f loo 2 m I - 90 88 All measurement locations n=A .. . 70 0.1 1 2 3 4 10 T- R separation tkm) n=3 n=2 n=l HFigure 3. Scatterplot ofpath loss vs. distancefor measurements in five Ger- man cities. Thepath loss isreferenced to afree space reference measurement at do = I O 0m. Note that CY has a value of 11.8dB dure to the large spreud ofPL values relativeto the straight-linefit. and receiver, and notany of the physical features of the propagation environment,itisnatural forsev- eral measurements to have the same T-R separa- tion, but to have widelyvarying PL values. Thisis due to the fact that shadowingmay occur at some locations and not others, etc. The precisionof a PL model is thus measuredby the standard devi- ation 6 ofthe random variable&, with a smaller value of CY reflecting a more accuratePL predic- tion model. Figure 3 demonstrates measured valuesof PL asafunctionofdistanceinfivecitieswithinGermany and shows the above model superimposedon the measured values. Thistype of plot is called a scat- ter plot, andit is useful for quickly assessing the tendencies and variationsof path loss throughout a radio system. To achieve lower values of6, more site-specific information about the environ- ment is required or smaller coverage distances are used when applyingthe PL model above[5]. Mulfipafhdelayspread-Timedispersionvaries widely in a mobile radio channel dueto the fact that reflections and scattering occur at seemingly randomlocations,andtheresultingmultipathchan- ne1 response appears random, aswell. Because time dispersion is dependent upon the geometric relationships between transmitter, receiver, and the surroundingphysicalenvironment,communications engineers often are concerned with statistical models of time dispersion parameters such as the average rmsor worst-case values. To demon- strate how rapidly the multipath characteristicsmay change, consider Fig.4,which illustrates oneof the worst casesof multipath time dispersion ever reported in aU.S.cellular radio system. Figure4 indicates that multipath energy18dSdown from the first arriving signal incurred a100-psexcess prop- agation delay. This corresponds to anexcess trav- el distanceof over 30 km! When the receiverwas moved by just a few meters, the observed multipath characteristics became much more tame,with an observed excessdelay of no more than 1 0 ~ s .In typ- ical urban cellular systems, the worst case excess delays (at99percent probability levels)for echoes which are within 10dB of the maximum signal are less than 25 ~s [6]. A collection of power delay profiles, such asis showninFig.4,canbedoneinmanyways.Typically, a channel sounderis used to transmit a wideband signal whichis received at many locations within a desired coverage area. This channel soundermay operate in the timeor frequency domain. The time domain responsewillappear asin Fig.4,and a swept frequency response will reveal that the channelis frequency-selective, causing some portionsof the spectrumtohave muchgreater signallevelsthan oth- erswithinthemeasurementband.Ofcourse,thetwo measurement techniques are equivalent and can be related by the Fourier transform. Power delay profiles may be averagedover time oroverspaceasthereceivermovesabout.Theaver- aging interval is key to determining the applica- bility of the time dispersion statistics, derived from power delay profiles[6-8]. Some important time statisticsmay be derived from power delay profiles, and can be used to quantify time dispersionin mobile channels. They are: maximum excess delay atX dB down from maximum (MED), mean excess delay(T), and rms delay spreada,. The MED is simplycomputed by inspecting a power delay profile and noting the valueof excess time delay at which the profile monotonically dips below the X dB level. For example, in Fig. 4, the MED at 10dB down would be lops. It should be noted that these parame- ters are alsoof interest when they are derived from instantaneous impulse responses. The mean excess delay (7)is the first central moment of the power delay profile and indicates the averageexcessdelayoffered bythe channel. Therms measure of the spreadof power about the value of 7,aT,is the most commonly used parameter to describe multipath channels. Chuang[9] and more recent simulation studies have confirmed that a good rule-of-thumbis as follows: if a digital signal has a symbol duration whichis more than ten times the rms delay spreada,,then an equal- izer is not required for bit error rates better than For such low values of spread, the shapeof thedelayprofileisnot important.On the other hand, if values of approach or exceed 1/10 the dura- tionofa symbol,irreducibleerrorsdue the frequency selectivity of the channelwill occur, and the shape of the delay profilewill be a factorin deter- mining performance. Outdoor Propagation Frequencyreuseisobtainedusingacellularstruc- tureofcoveragezonesfrombasestations.1ntext- books, one usually sees a honeycomb structure of hexagonallyshapedcells. Unfortunately, arealenvi- ronment changes the propagation conditions such that a cell, defined as the areain which pathlossis at or below a givenvalue, has amuch more irregular shape. Furthermore, at isolatedplaces the cellswill hdvepocketsinsideeachother,perhapsduetoheight 44 IEEE CommunicationsMagazine January 1995
  4. 4. variations from natural terrain or from man-made structures. Often interference condition prevent the optimal use of the cellular system because reality does not correspond to the simple mathe- matical models. Increasing the power to cover dead spotswouldcreateotherproblems.Thenetworkplan- ner hassome possibilities though,thl ouyhplacingof the base station antenna and tosonic extent choos- ingitsradiationpattcrn,toshapethec~ilextent.Tilt- ingthe antennain avertical plane isanormal mcasure and by choosing the height above o r helow rooftops, maybe even down tu street level, v m e - thing can be done to control thehire ot the cell. Cells are typically classified roughly according tosizeasmacrocells andmicrocells. TableIpresents some distinctive cell features. Macrocells The average path loss ISwhat remains after aver- aging the pathloss over the fast fading due to multipath.The macrocellswere thebasis for thc first generationsystcmsmeant for mobileusers,and they generallyhavebase stationsathighpointslikebroad- casting systems, witha coverage of several kilo- meters. Thekey problem is t o make some order of the seemingly noise-like path lossexistingover an undulatingterrainwithavarietyoflandcover,mked land and sea, etc. Thefast Rayleigh fading corre- spondstoatruenoisedistribution,buttheslowshad- owingtypevariationisremarkablywelldescribedby a log-normal distribution, i,e., the average path loss in dB has a normal distribution.A good rea- son for this could be that the average pathloss is the result of forward scattering overa great many obstacles, each contributinga random multiplica- tive factor. When converted to dB this givesa sum of random numbers,which leads toa normal distribution in the centrallimit. In the carlydays, planning wasmainly based on empirical formulas with an experimental back- ground. Okumurd[101did thefirst comprehensive measurements in 1968for Japanese environments, and the derived curves have later been trans- formed into parametric formulasby Hata [4].It was noted that a good model for the pathloss (or the field strength)was a simplepower law where theexponentncouldvaryasafunctionoffrequency, antenna heights etc. Expressed simply.on a log-log- scale, thisis a linear dependency(Eq.1). The rela- tionship is strictly empirical, butit has proven ex- tremely robust overthe years notonly inJapanese surroundings, butinother surroundings aswell.The reason for this general validity, also for indoor environments, is not completely clear;Walfisch and Bertoni[ll]getgoodagreementwithdiffractionover a multiplicity of absorbing screens.There aresimple physical situations where the modelis exact. One is ofcourse freespace corresponding ton =2, anoth- er is asymptotic propagation overa flat, finitely conducting surface(n=4),and finally, there is for- ward scattering over a numberof absorbing screens of equal height and distance(n = 4). The real world in outdoor macrocells leads ton’s between2 and 4,withvaluescloserto4inurbansituations. Weshall meet the same modelin the indoor case aswell. The modelshave been refined with a number of correction factors dependingon the land cover, different degreesofbuilt-up areas,forestsand rural areas, andin some cases supplementedwith one or two knife-edge diffractions. Neither Geo- ~~ -85 -90 -95 -1oa -105 -1la -115 csf47 I I I , , / Displa threshold = -111.5 dBm per 40 ns RMS &lay spread = 22.85 ps Worst caw San Franciscomeasurement Mansell St.h Excess delay time, Cs) Figure 4. One ufthe wor.sr cases of multipath time disperslon observedin a 2 cellular rudlo s).srern. Meawement mademSan Francisco, California. .Table 1. Typica/parameters for macrocells and microcells. metrical Theory of Diffraction (GTD) nor Uniform Theory of Diffraction (UTD) arereally successful in macrocellssince we are dealingwith forwardmul- tiplescatteringin the transitionzoneswhere nogood theories exist. The resulting prediction power normally leads toa standard deviation of errors between 6 and 10dB,which is not really impressive. Even the availability of modern computers and the use of topographical data bases havc not resulted in a real break-through in better predictions. Thetime domainmayalsobe modeledusinggeo- graphical data bases, andwme success has been achieved in mountainous regions and large cities [12].Ingeneral,theraytracingroutineslackthecon- trhutions from random scatterers. Microcells Microce//u/arSystems -Microcells are attracting much attention simply because they can accom- modate more subscribers per unitservice area than macrocells. Also, they permit access by low-power portables. Propagation in microcells differssig- nificantly from that in macrocells As suggested in Table 1,smaller cell coverage with lowerantenna height andlower transmissionpower resultsinmilder propagationcharacteristicswhencomparedtomacro- cellular systems. Thesmaller multipathdelay spread andshallow fading implythefeasibilityofbroadband signal transmission without excessive counter- measure techniques against multipath fading. Microcells are most frequently plannedin an IEEE CommunicationsMagazine * January 1995 45
  5. 5. 0I A o"0awn log (distance) (C) W Figure 5. Ideal urban street layour:a )typicalpath loss cuwes along an LOS street b)and along a NLOS vtreetafter turning a corner. urban area where theheaviest tclctraffic is expect- ed. If a transmitter antennaheight is lower than the surrounding building helght. then most ot the signal power propagates along the street. The coverageareaextendsalongthestreet. thusthename "street microcell" is often used. In suburban areas, microcells might be usedtorealize alast quar- ter mile connection to a wired network. In this case, cell coverage might be circular hut strongly affected by the buildings and obstacles. StreetMicrocells-Anumberofstudieshavebeen done regarding street microccll propagation where mostofthesignalpowerpropagatesalongthestr~et. Let us assume an ideal rectangular street grid with building blocks of relatively uniform height as portrayed in Fig. 5a. In this case. typical path loss curves along the line-of-sight (LOS) path are shown to be characterized by two slopesand a single breakpoint. The path loss exponent is around two, as in free space propagation, from the transmitter up to the breakpoint.Beyond the breakpoint theloss exponent isaround four, implyingasteeper decrease of the signal strengthas illustrated in Fig. 5b. This breakpointisapproximatclygiven byZrdz,Jt,,ih where hb is the base antenna height,h, is the mobile antenna height. However,if the receiver turns the corner from theLOS street intoa non-line- of-sight(NLOS) street, thenthe receiver experiences adramaticdecreaseofthesignalstrengthbyaround ZOdBasshowninFig.Sc,thoughthisvariesdcpend- ing on the streetwidth and the distance between the transmitter and the corner[131. On a NLOS street, the signal envelope tends to follow a Rayleigh distribution. On a LOS path. the signal envelope follows not a Rayleigh but a Nakagami-Rice distribution, Multipath delay spread is usually small due to the existenceof a dominating, direct signal component. Modeling and Prediction- Various propaga- tion models for the street microcells based ona rwoptic theory have been proposed. Prediction ofmicrocell coveragebasedon theraymodel Israther accurate comparedtothe case of macrocells. Afour- ray model consisting of direct ray, ground-reflected ray. and the two rays reflected by the building walls along the street is often as+umed..4 six-ray model that takes doubly reflected rays by the building wall$ or larger-number-ol-ray models are reported t o give more accurate prediction at the cost of Increasedcomputation time [14]. Corner diffractionis another problem attracting much attention. Various modelshave been inbestigated StZlrtingfrom a simple knife-edge or wedge diffrac- tlon t() GTD or UTD with a multiplicity ut rays. An analytical path loss model describing mlcro- cellular propagation including reflectedrays and corner diffractionhas been prehented in [151. Due to the irregularityofthebulldingstructures, excessive overlap or non-overlapping of the micro- cell+are sometimes found. Thus, measurement- based methods are also adopted to enhance the accuracy of the prediction [16]. Coverage area is strongly affected by the location of the transmit- ter antenna. Whenit is installed in the intenec- tion of the streetsin Manhattan. for instance, the waves propagate along the streetsin four direc- tions with subsequent corner diffractionsat each encounteredcorner.Thisgeneratesacoveragearea similar to the shapeof a diamond. Whena trans- mitter is located ona street between intersec- tions, this makes the cell more elongatedin the direction along that street [17j. Indoor Propagation 1 . . . .ndoor radio communication systems are becom- mg mcreasmgly Important for extendingvoiceand data communication services within the work- place. Recent trials by major telephone compa- nies show a huge demand and customeracceptance of indoor wireless communications. Some wire- IesssystemsinterconnectwiththePSTNorIocalPBX to provide a seamless extensionof the convention- dlofficetelephonesystem,whileothersystemsoffer services separate from the PSTN. Indoorsystems can be broken down into three main classes: cordless telephone systems; in-building cellular systems: and local area networks (LANs). Eachof thesetypesofemergingcommunicationsystemsmust he designedwith the indoor channelin mind. Forindoor communicationsystems,many design issues such as the distance between servers, expectedportable batterylife,customerperformance expectations, and the appropriate radiolink bud- get aredirectly linkedto the propagation environ- ment. The amountof RF interference that canhe expectedfromcochannelusersisanequallyimportant parameter, which is a direct functlon of the prop- agation characteristics inside buildings. Propagation inside Single-story Buildings Agreat manypropagationmeasurementshave been conducted by telecommunication companies, research laboratories, anduniversities in order to determine reasonabledesign guidelines and prop- agation parameters for indoor systems. These measurements show that the particular typeof 46 IEEE Communications Magazine * Januar?. IYY5
  6. 6. Retail stores I914 1 Office, hard partition I1500 13.0 I 7.0 1 I Office, soft partition I1900 I 2.6 I 14.1 1 1 Metalworking 1 1300 HTable 2.Path loss evponent and standard dum- lion nleuured in diffrrenr huildings. building has a direct impact on thc obscrvcd propagation characterictics. This has motivated more recent research that predicts indoor propagation using either statistical or deterministic models. In order to differentiate propagation phenom- ena, researchers often classify buildingsby the followingcategorics: rcsidential homesinsuburban area5, residential homesin urban areas, tradition- a l older office buildings with fixed walls (hard partitioni), open plan buildings with movable wall panels (soft partitions), factory buildings, grocery stores, retail stores, and sports arenas. Hard partitions describe obstructions within the build- ing which cannot be easily moved such as existing walls and aislcs. Soft partitions describe movable obstructions such asoffice furniture panels,which have a height less than the cciling height. Inside a building, propagation geometrymay be classifiedas lineofsight (L0S)where the transmitter andreceiv- er are visible to one another or obstructed (OBS), where objects in the channelblock a visible prop- agationpath. Often,physicalsimilaritiesexistbetween diffcrcnt typcs of buildings. For example, factory buildings and grocery stores both contain a large amount of metal inventory and oftcn havc fcw hard partitic~nswithinthe building. Traditionaloffice buildings,withmanywallsmadeofplasterandmetal lathe,often hal.esimilarpropagationcharacteristics to large residential homes or retails stores that contain many partitions. Asdiscussedinthesectiononpropagationphysics, there arca number of important propagationevents that must he measured or modclcd before areli- ahlzwirelesssystemean bedesigned. Measurements by many researchershave more or lescprovided sim- ilar results, w,hich are summari& below. Temporal Fadingfor Fixed and Moving Ter- minals - For fixed terminals within buildings, measurements have shown that ambicnt motion by people throughout the building causes Ricean fading.with theratio of specular signal powertomul- tipath signal having a valueof about 10dB. This results in a typical variation of less than 15 dB for 99.9percent of the time. Ingeneral. a portablereceiver moving inabuild- ing experienccs Raylcigh fading for OBS propa- gation paths and Ricean fading forLOS paths, regardless of the type of building.The RiceanK factor can vary from2 to 1 0 dB for portable Ler- minals depending on the structureof the building and the number ofmultipathcomponents thatarrive at thereceiver. Multipath DelaySpread - Buildings that have fewer metal and hard partitionstypically have small rms delay spreads, on the ordero f 30 to 60 ns. Such buildings cansupport dald ratesin excessof several Mb/s without the needfor equalization. However, larger buildings with a great dealof metal and openaisles can have rms delay spreads as largc as300 ns. Such buildings are limited to data ratesof a few hundred kilobits per second without equalization. Path Loss -Path loss is a measure of the aver- age RF attenuation inside a building, andit is measured by averaging the received signal over several wavelengths at the receiver. Equation(1) describes the pathloss situation also for indoor situations whcre the standard deviation is easily derived from the scatter plotof measured data.A smaller value of cs implies that the pathloss model provides a better prediction for actualloss within a building. Equation (I) is well suited for system analysisor Monte Carlo simulationwhen the impact of a large numberof users within a building must be considcrcd. Typical valuesof path-loss cxponents and standard deviations for different classes of buildings are given in the literature. Table 2 provides a range of typical values that have been measured in the past. Molkdar's survey paper on the subject of indoor propagationcontainsasummaryofnumerousprop- agationmeasurementsandmcdelsthat havebeendevel- oped [18].The early worksby Devasirvatham [19] and by Salch and Valenzuela [20]have provided a foundation for propagationwork inindoor channels. Propagation Between Floors Predicting radiocoverage between floors of build- ings has proven to bedifficult, but measurements have shown that there are general rules-of-thumb that apply. Quantifying this propagation condi- tion isimportant for in-buildingwirelesssystemsfor multifloored buildings that needto share fre- queneieswithinthebuilding.1nordertoavoidcochan- ne1 interference, frequencies must be reused on different floors. The typeof building material used between floors has been shown to impact the RFattenuation betweenfloors. Poured concrete overmetallathingisapopularmodernconstruction techniquc which provides less RF attenuation than does solid steel plankswhich were used to separate floors in older buildings. The aspect ratio of the building sides also makes a difference. Buildings that have a square footprinthave higher attenuation levelsbetweenfloors than buildings that are rectangular. Also, windows with mctallic tint impedc RF transmission, thus causing greater -Indoor radio communica- tion systems are becoming increasingly important for extending voice and data com- munication services within the workplace. IEEE CommunicationsMagazine * January I995 47
  7. 7. -During the past few years, indoor propagation prediction techniques based on ray tracinghave been used to reconstruct the many possible reflections porn wall surfaces within a building. .~ ~ ~ 60 60 70 80 90 Tran [Path loss error] 59 meters 4 90 80 59 meters I 1 Figure 6. Error contour whch compares measuredand predicted path loss using a wtnple sire specificpur- 1 lition model described itt(51. Note that error is less fhun3 dl3 over 80percenr of the coverage area. attenuation between floors of a building. Measurements have shownthat the lossbetween floors does not increase linearly in dB with increasing separation distance. Rather, the great- esttloorattenuationfactor(F4F)indBoccurswhen the transmitter and receiver are separated by a single floor. The overall pathloss increases at a smaller rate as the number of floors increase. This phenomenon is thought to be caused by diffrac- tion o f radio energy along the sidesof a huild- ing, as well a scattercd energy from neighboring buildings, which can be reccived on different floors of the samebuilding [Zl]. Typical values of attenuation between floors is15 dB for onefloor of separation and an additional6 to 10dB per tloor of separation up tofour floors of separation. For five or morefloors of separation, pathloss will increase by only a few dB foreach additional floor. Computer-aided Design for In-building Propagation Prediction Statisticalpropagationmodelsdonotexploltknowl- edge of the physical surroundings to the degree that building drawings can provide. State-of-the art propagation prediction uses computer-aided designdrawingsof theindoor environment asameans of representing thephysical locations of base sta- tions, receivers, and partitions.For economic rea- sons,transceiversmustbe placed strategicallysothat only desired portionsof the building are provided with radio coverage. CAD tools enable a system designer to interactively model the performance of indoor systems.Underthis interactive framework, propagation models can be modifiedto provide a wide range of scenarios and base stations can be added, repositioned, or deletedinteractively. Fur- thermore, communication parameters such as received carrler-to-noise thresholds canbe adjust- ed by the user as needed. Computer-aided design touls.such asAutoCAD. can display both single-floor and multifloor build- ings. Building partitions can be identified in AutoCAD and assigned an attribute,so that appropriate propagation models may bc applied. Figure h shows an example of the modules pro- videdinatvpicalsitemodelingtool.Workin[22,23] demonstrated that asimple and surprisingly accu- rate way tc) predict RF path loss inside a building is to count partitions between a line drawn between transmitterandrecewer. Ernpiricallyderived attenuation factors (AFs)may lhen he applied to each partitionwhich intersects theline. Through an interactive proccss. parameters suchas FAFand AF can be tunedfor a particularclass ofbuildings. Mea- surements madewithin the environment can then be added to the CAD modeling toolas a means of updating the modelsin order t o provide more accurate mcasurernents at future sites. During the pastfcw years, indoor propagation prediction techniques based on ray tracing have beenusedtoreconstructthemanypossiblcreflections from wall surfaceswlthin a building. This approach can easily be accommodatedin computer aided design tools and shows promise for reducingthe standard deviationo to within 4 dB over a50 or bo dB dynamic range within buildings[23-251. RF Penetration into Buildings T.he signal strength received insideof a build- mg due to an external transmitteris impor- tant fur wireless systems that share frequencies 48 IEEE Communications Magarme January 1995
  8. 8. withneighboringbuildingsorwithoutdoorsystems. LikeKFpenetration measurementsbetweenfloors, it is difficult to determineexact models for pene- tration asonly a limited number of experiments havc bccn published, and they are sometimesdif- ficult to comparc. However, some generalizations can be made from the literature. In measure- ments reportedto date,signalstrengthreceived inside a building increases with height. At thc lower floorsofabuilding,theurbanclutterinducesgreater attenuationandreducesthelevelofpenetratic~n.At higher floors, a LOS path may exist. thus causing a stronger incident signal at the exterior wallof the building. RF penetration has bccn foundto be afunction of Crequency as well as height within thc building. Most measurements haveconsideredoutdoortrans- mitters with antenna heights farless than the maximum height of the building under test. Mea- surcmcntsinLiverpool[26]showedthatpenetration loss decreascs with increasing frequency. Specifi- cally, penetration attcnuation valuesof 16.4, 11.6, and 7.6 dB were measured on the ground floorof a buildiug at frequenciesof 441 MHz, 896.5 MHz, and 1400 MHz, respectively. Measure- ments in [27] showed penetrationloss of 14.2, 13.3.and 12.8 dB for 900 MHz, 1800 MHz, and 2300 MHz, respectively. Measurements madein front of windows indicated 6dB less penetration loss on average than did measurements made in parts of the building without windows. Walker [ZX] measured radio signals into 14 different buildings in Chicago from seven exter- nal cellular transmitters. Results showed that building penetration loss decreased at a rateof 1.9 dB per floor from the ground level upto the 15th floor and then began increasing above the 15th floor. The increase in penetrationloss at the higher floors was attributed to shadowing effects ol' adjacent huildings. Similarly, [26] reported penetration loss decreased at a rateof 2 dB per floor from the ground levelup to the 9th floor and then increasedabovetheYthfloor. Similarresults were also reported in [29]. Measurements have shown that the percent- age of windows, when compared with the build- ing face surface area, impacts the levelof RI; penetration loss.asdoes the presenceof tinted metal in the windows. Metallic tints can provide from3 to 30 dBof RF attenuation in a single paneof glass.Theang1eofincidenceofthetransmittedwave upon theface of thebuilding alsohasa strong impact on the penetrationloss as shown in [30]. Conclusion Despitetheenonnouseffortsandprogrcsstodate, much work remains in the understanding and characterization of wireless communications channels.Atrend in3Dnumericalmodeling isseen, from which time delay statistics as well as cover- age and interfercnccmight be inferred.This isespe- cially important with the extension to ever-higher datarates. Angle-of-arrival statisticsindifferentenvi- ronmentswill also need to be better modeledfor use with adaptiveantennas. In general, we mayconclude that to achieve ubiquitousPCS new and novel ways of classifying wireless environn~entswill be nccdcd that are both widely encompassing and reasonably compact. References [ l ] D Cox. R Murray, and A Norrls, "800 MHz Atlenuatlon Measured in and Around Suburban Houses," AT&T BellLaboratories Tech. 1.. "01. 673. no. 6, July-Aug, 1984. pp 921-954 I21W. C.Y. Lee, Mobile Communfcatlonr Deslgn Fundamentals. (Wiley. Second Edltion, 1993). I31T 5. Rappaport, "Indoor Radio Comrnunicatlons for Factories of the Future," IEEE Commun. Mag., May 1989. pp. 1524 L41M Hata."Emplrlcalformulaeforpropagat~onloss~nlandmob~lerad~o services," IEEE Trans.Veh.Tech., L7-29, 1980, pp 317-325. I51 5.Y. Seldel and T. 5. Rappaport, "914 MHz Path Loss Predlctlon Models for Indoor Wireless Communtrailons ~nMultlfloored 161T 5 Rappapon. et al ,"900 MHz MultlpathPropagation Measure Bulldmgs." IEEE Trans. Ant. Prop, vol. 40. no. 2. Feb 1992. "01.39, no. 2, May 1990. pp 132-139. mentsforU.S.DigltalCellularRad~otelephone."iEEETrans.Veh.Tech , I71D. C. Cox and R. P. Leck, "Distnbutjonsof MultipaihDelay Spreadand Average Excess Delay for 910 MHz Urban MobileRadlo Paths." 1811. Bach Andersen. "Distribution of phase derivatlvesIn moblle com- IEEE Trans Ant Prop, "01. AP 23. March 1975, pp. 206-213 191J. C-I Chuang. "The Effects of Time Delay Spread on Portable Radlo munlcatlons."lEEProc,RH. "01. 137, no 4,Aug1990, pp 197.201 Communicatlons Channelswtth Digital Modulation:' IEEEJSAC. YOI 5,no 5, June 1987. pp 879 - 889 [lo] Y.Okumura et.a/., "Field strength and its variablllty in VHF and UHF landmobllerad10m c e , " Rw of the ECL MI 16. 1968, pp. 825-873. I l l ] 1. Walflsch and H. Bertani, "ATheoret~calModel of UHF Propaga- tlon InUrban Envlronments;' IEEE Trans. Antennas and Propaga- 1121T Kurner. D. J Cichon. and W. Wiesbeck. "Concepts and Results tion. voI 36.no 12. Dec 1988. pp 1788.1796 JSAC. vol. 11, no. 7,Sept. 1993, pp 1002 -1012 far 30 Dlgntal Terraln-Based Wave Propagatlon Models." IEEE I131Y. Nagata. et. ai.. "Measurement and modehng of 2 GHr-band out-of-saghi radlo propagainoncharactemtics under mlcrocellular I14lA J Rustako,Jr et.al."Radiopropagationatmtcrowavefrequenc~es environments," Proc. PIMRC'91. Sept. 1991. pp. 341-346. forl~ne-of-sightmicrocellularmobileandpersonalcommunicat~ons," IEEE Trans Veh. Techn, "01. 40, no. 1,Feb 1991, pp 203-210 I1511 Wiart."M~cro-cellularModel~ngwhenBaseStationAniennairbelow Roof Tops," Proc. IEEE Vehicular Technology Conference, June I161 W.T Webb, "Sizing up themicrocellfor rnoblle rad10 communica- 1994, Stockholm, pp. 200-204. I171A. J. Goldsmith and L. 1. Greenstem. "A Measurement-Based tlons. "Electronrcs and Commun. Eng J., pp. 133-140.June 1993 vol 1 l . m 7,Sept1993,pp1013-1023 ModelforPredlctlngCoverageAreasofUrbanMicrocells."lEEEJSAC. 1181D. Molkdar. "Review on Radlo Propagatlon Into and Within B u W ingr,"IEFProc voI 138. no 1.Feb 1991 1191D. Oevasirvatham, '71me Delay Spread and Slgnal Level Measure- mentsof850MH~rad~owaver1nbu~ld~ngenv~ranments."lEEFTram Ant. Prop.. YOI. AP-34, no. 11, NO". 1986. pp. 1300 1308. 1201A.Saleh and R Valenzuela, "A statlstlcal model for Indoor multl- [21]W.Honcharenko,H.L.BeRon~,andJ.Da~ling,"MechanlsmsGoverning path propagabm,"IEEEJC4C. MI. SAC 5 , no 2, Feb 1987, pp 138.146 Propagatton Between Floors ~nBulld!ngs." IEEE Tram Antennas i221A. Motley and 1. Keenan, "Rad10 Coverage In Bulldlngs." Brrttsh andPropagation, "01. 41, no. 6. June 1993, pp. 787-790. Telecom Tech.1.."01.8, no. 1,Jan 1990, pp 19-24. 12315. Y.Seidel and T. S Rappapon. "A Ray Tracing Tcchnlque io Pre- dlct Path tors and Delay Spread mslde Buildings." IEEE GLOBE- 1241 R. Valenzuela. "A Ray Traclng Approach to Predictlng Indoor COM,Dec. 1992, pp. 1825-1829. 1251C. M. P. Ho, et. ai.. "Antenna Effectson Indoor Obstructed wire^ W~relersTransmlsrlan." IEEE Veh. Tech. Conf. 1993. pp. 214-218. l e s ~Channels and a Determmlsttc Image-Bared Wldeband Propa- I Wirelesslnfo. Networks, "01. 1, no. 1, 1994. pp. 61-76. gationMod~forIn-BuildingPersonalCommunicat~onSystems,"lnf'l 1261A. M. D. Turkmanl, 1. D. Parson, D. G.Lewis, "Radio Propagatton on Land Moblle Radlo,Dec 1987. Into Buildings at 441, 900. and 1400 MHz." Proc 4th Intl. Conf. 1271A M 0. Turkmani.A. F. Toledo. "Propagation Into and Wlthln build^ fngr at 900, 1800, and 2300 MHz." 1992 IEEEVehTech C o d 1281E H. Walker. "Penetration of Radio Stgnals Into Bulldmgs ~nCellu- lar RadloEnvlronments:' BellSys. Tech. 1.. vol. 62.no 9. 1983. [29]J.M.Durante,"BuildingPenetrationLossai900MHr."lEEEVeh.Tech. Conf., 1993. I301J Hortklshl. et a/, "1 2 GHz Band Wave Propagatlon Measure- mentsinConcreteBuildingsforlndoorRadioCommunications:'lEEE TransVehTech.. L7-35. no. 4, 1986. Biographies IBRGEN BACH ANOERSEN IF '921 il a professor at Aalborg UnlverSlty. Aalborg. Denmark and head of Center for Personkommunikatlan He IS actlve in International research concerning mobile communlcatlons bemg chalrman of COST 231 Warklng Group on UHF prapagatlon He IS also actwe ~nthe area of bloelectromagnetlrs and is presently "Ice- president for URSI, the lnternatlonal Sclentlflc Radio Union THEODORES RAPPAPORT ISM '91II S an asroclate professor of electrical englneermg and founder of the Moblle& Portable Rad10 Rerearch Group (MPRG) at Virginia Tech, Blacksburg, Virginla. Susuvu YOSHIDA15 a professor of electrical engineering at Kyoto Unl- versity. Kyoto, Japan, leading a research group on wlreless personal communtcationr He IS Involved ~n multlpath propagatmn modellng and predlrtlon, rector-antenna dsverslty, anti-multlpath modulation schemes, and u-servlce multlpath delay spread monitoring, eic -The percentage of windows, compared with the buildingface sueace area, impacts the level of RF penetration loss, as does thepresence oftinted metal in the windows. IEEF Cummunications Magazine January 1995 49

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