RF Propagation and Planning

Mobile Radio Propagation: Large-Scale Path Loss

Organization

• Basic Propagation Mechanisms – Diffraction

• Fresnel zone Geometry• Knife-edge Diffraction

– Scattering

– Reflection

Scattering

• Occurs when the radio channel contains objects whose sizes are on the order of the wavelength or less of the propagating wave and also when the number of obstacles are quite large.

• Causes the transmitter energy to be radiated in many directions

• Lamp posts and street signs may cause scattering

3.8 Scattering

RF waves impinge on rough surface reflected energy diffuses in all directions

• e.g. lamp posts, trees random multipath components

• provides additional RF energy at receiver

• actual received signal in mobile environment often stronger than predicted by diffraction & reflection models alone

Reflective Surfaces• flat surfaces has dimensions >> • rough surface often induces reflection different from specular

reflections

• surface roughness often tested using Rayleigh fading criterion

- define critical height for surface protuberances hc for given incident angle i

hc = i

sin8

(3.62)

Let h = maximum protuberance – minimum protuberance

• if h < hc surface is considered smooth

• if h > hc surface is considered roughh

stone – dielectric properties• Permittivity r = 7.51• Conductance = 0.028• Permeability = 0.95

rough stone parameters• h = 12.7cmh = 2.54

h = standard deviation of surface height about mean surface height

For h > hc reflected E-fields can be solved for rough surfaces using

modified reflection coefficient

rough = s (3.65)

s =

2sin

exp

ih (3.63)

(i) Ament, assume h is a Gaussian distributed random variable with a local mean, find s as:

(ii) Boithias modified scattering coefficient has better correlation

with empirical data

I0 is Bessel Function of 1st kind and 0 order

2

0

2sin

8sin

8exp

ihih Is = (3.64)

3.8.1 Radar Cross Section Model (RCS)• if a large distant objects causes scattering & its location is known accurately predict scattered signal strengths

• determine signal strength by analysis using - geometric diffraction theory- physical optics

• units = m2

RCS = power density of radio wave incident upon scattering object

power density of signal scattered in direction of the receiver

• dT = distance of transmitter from the scattering object

• dR = distance of receiver from the scattering object

• assumes object is in the far field of transmitter & receiver

Pr(dBm) = Pt (dBm) + Gt(dBi) + 20 log() + RCS [dB m2]

– 30 log(4) -20 log dT - 20log dR

Urban Mobile Radio

Bistatic Radar Equation used to find received power from scattering in far field region

• describes propagation of wave traveling in free space that impinges on distant scattering object

• wave is reradiated in direction of receiver by:

RCS can be approximated by surface area of scattering object (m2) measured in dB relative to 1m2 reference

• may be applied to far-field of both transmitter and receiver

• useful in predicting received power which scatters off large objects (buildings)

• units = dB m2

• [Sei91] for medium and large buildings, 5-10km

14.1 dB m2 < RCS < 55.7 dB m2

ReviewTypes• Free space propagation model

Less accurate as it considers no obstruction

• 2-Ray Model Reasonably accurate, Tower(h>50m)

Ground reflected

path

Final Rx signal

Direct Signal

ground

Ground Reflection (2-Ray Model)

The free space propagation model does not take into account signal reflections.

The signal transmitted by a land-based antenna is received by another land-based antenna in the presence of a strong ground reflection.

The model is quite accurate for predicting receivedsignal strength over several km, using tall antennas.

We have

4 ;

120

||)(

220

0

GAA

EdP eer

After some manipulations, it can be shown that

4

22

)(d

hhGGPdP rt

rttr

That means that with the two-ray model received powerdecays with 4d , rather than 2d (as in free space).

Received power falls off at 40dB/decade of distance.

Path loss Models • Analytical Model• Empirical Model

– Developed by fitting curves or expression– Actual field measurements (known & unknown

factors) – Considers a particular area , particular

frequency , limited application

• Combination of Analytical & Empirical • Lately , several classical models have

emerged to predict large scale coverage for mobile communication systems .

Path Loss Models• Path loss models are used to estimate the received

signal level as a function of distance

Log Distance Path Model

Log-normal shadowing

Classification

Log-distance path loss model

Average received signal power decreases logarithmically with distance, whether in outdoor or indoor radio channels

The average large-scale path loss for an arbitrary T-R separation is expressed as a function of distance by using path loss exponent, n

n indicates the rate at which the path loss increases with distance

Expression

(d/d0)n

or

= +10nlog(d/d0) where , the bars in the above equations denote the

average of all the possible path loss values for a given value of ‘d’

‘d’ is the Distance b/w Tx and Rx

‘d0’ is the close-in reference distance

)(dBPL

)(dPL

)( 0dPL

• When plotted on a log scale: The modeled pathloss is a straight line with a slope equal to 10n dB per decade

For free-space n=2, and for the two-ray model n=4.

Environment Path Loss Exponent, nFree space 2

Urban area cellular radio 2.7 to 3.5

Shadowed urban cellular radio 3 to 5

In building line-of-sight 1.6 to 1.8

Obstructed in building 4 to 6

Obstructed in factories 2 to 3

Path Loss Exponent for Different Environments

Log-normal Shadowing

• Shadowing occurs when objects block LOS between transmitter and receiver

• Log distance path loss model does not consider the fact that the surrounding environmental clutter may be vastly different at two different locations having the same T-R separation

• This produces a change in the measured signals which is vastly different from the average value predicted by the previous model

• A simple statistical model can account for unpredictable “shadowing” – Add a zero-mean Gaussian RV to Log-Distance PL

PL(d)[dB] = PL(d)+Xσ = PL(d0)+10nlog(d/ d0)+Xσ

and

Pr(d)[dBm] = Pt[dBm]-PL(d)[dB]where,

Xσ is the Zero –mean Gaussian distributed random variable with standard deviation σ(also in dB)

& n are derived from measurements using linear regression• minimizes difference between measured & estimated path loss • minimized in a mean-square sense over many measurements & d’s

Path Loss Model Parameters for arbitrary location & specified Tx-Rx • d0 – close in reference distance

• - clutter standard deviation• n – path loss exponent

Used for system design & analysis simulations to provide estimated Pr(d) at random locations

3.71Pr [Pr(d) > ] =

)(dPQ r

(ii) Pr(d) > or Pr(d) < is as

3.72Pr [Pr(d) < ] =

)(dPQ r

(i) PL(d) is RV with a normal distribution in dB about

• as a result, Pr(d) inherits these characteristics

)(dPL

)(dPr

3.9.3 Determination of % Coverage Area • in a given coverage area, let = desired receive signal level – could be determined by receiver sensitivity (or visa versa)

• random shadowing effects cause some locations at d to have received power, Pr(d) <

Determine boundary coverage vs % area covered within a boundary, assuming

• a circular coverage area with radius R from base station• likelihood of coverage at cell boundary is known (given)• d = r represents radial distance from transmitter

U() =

ddrrrPR

R

r ])(Pr[1 2

0 02

dArPR r ])(Pr[1

2

U() =

(3.73)

useful service area (coverage area): U() = % area with Pr(d) >

r

R

Coverage Area=Area with signal>Total Area of the cell

Left Axis = % area with Pr(R) > (coverage area-use 3.73)

Right Axis = Pr[Pr(R) > ] (boundary coverage-use 3.68)

/n = std deviation of path loss exponent

Pr[Pr(r) > ] /n U()

0.95 2 0.990.70 2 0.90.60 2 0.82

0.950.900.850.800.750.70

0.65

0.60

0.55

0.50

Pr[Pr(r) > ]1

0.95

0.90

0.85

0.80

0.75

0.70

0.65

0.60

U() %

0 1 2 3 4 5 6 7 8 /n

Example 4.9

• d0=100m P0=0dBm

• d1=200m P1=-20dBm

• d2=1km P2=-35dBm

• d3=3km P3=-70dBm

d

dndPP ii

00 log10)(

• Calculate a) n=?

b)c)

d)Pr(Pr(d)>-60dBm)=? E) UdBm

?)2( dp

Outdoor Propagation Model

• Radio propagation in mobile communications often takes place over irregular terrain.

• The profile may vary from simple curved earth profile to a highly mountainous profile.

• The presence of trees, buildings, and other obstacles need to be taken into account.

• There are a number of mobile radio propagation models to predict path loss over irregular terrain.

• These methods generally aim to predict the signal strength at a particular sector. But they vary widely in complexity and accuracy

Okumara Hata ModelOkumura–Hata Model• A well-known propagation model for a macro cell

environment to predict median radio signal attenuation• An empirical model i.e. based on field measurements• Okumura performed field measurements in Tokyo and

published results in graphical format• Hata applied the measurement results into equations• Model can be applied without correction factors for urban

areas but in case of other terrain types correction factors are needed

• Weakness of the Okumura–Hata model: Does not consider reflections and shadowing

Okumara Hata Model

• Parameter restrictions for model are:– Frequency f : 150–1500 MHz, extension 1500–2000

MHz

– Distance between MS and BTS d: 1–20 km

– Transmitter antenna height Hb: 3–200 m

– Receiver antenna height Hm: 1–10 m

– The Okumura–Hata model for path loss prediction can be written as

Okumara Hata Model– f = frequency (MHz)

– Hb = base station antenna height (m)

– a(Hm) = mobile antenna correction factor

– d = distance between BTS & MS (km)

– Lother = additional correction factor for area type correction

– Correction factor for MS antenna height for a small or medium sized city

– And for a large city

Okumara Hata Model• Hm is MS antenna height:

• Parameters A and B depend on frequency as follows

Okumara Hata Model• Cell range i.e. distance between BTS and MS is from 1 to

20 km in these calculations

• Okumura–Hata model valid for frequency ranges 150–1500MHz and 1500–2000 MHz

• Range for BS antenna height is from 30 to 200 metres

• MS antenna height from 1 to 10 meters

• With additional correction factor (Lother) model can be applied for all terrain types (different morphological areas)

• Correction factors for each area are determined using the drive tests to fine tune the model

Path loss calculation using Okumura–Hata model done with two parameter sets and compared to free space loss

Free space loss and Okumura–Hata propagation loss comparison

Okumara Hata Model• Some examples of propagation loss values

Walfisch Ikegami ModelWalfish–Ikegami Model• An empirical propagation model

for urban area• Applicable for micro cells but

also used for macro cells• Parameters related to Walfish–

Ikegami model – Mean value for street widths (w)

in metres– Road orientation angle (ϕ) in

degrees– Mean value for building heights

(hroof) is an average over calculation area in metres

– Mean value for building separation (b) calculated from centre of one building to centre of another building metres

Walfisch Ikegami Model• Walfish–Ikegami model separates into two

cases– Line-of-sight (LOS) – Non-line of-sight

• Formula for path loss prediction in LOS condition can be written as

– where d = distance (km) – f = frequency (MHz)

Walfisch Ikegami Model• For NLOS, path loss formula:

– Lrts = Rooftop–street diffraction and scatter loss – Lmsd = Multi screen diffraction loss

• Path loss in non-line-of-sight situation consists of three components– Rooftop–street diffraction and scatter loss– Multi screen diffraction loss and – Free space loss

Walfisch-Ikegami Model

Walfisch-Ikegami Model• Following rule applies

• Rooftop–street diffraction & scatter loss= loss due to radio wave propagation from closest rooftop to receiver

• LOri = Street orientation loss

Walfisch-Ikegami Model

• Multiscreen diffraction loss= due to propagation from BTS to the closest rooftop to MS

Walfsich Ikegami Model

• Where

Walfisch-Ikegami Model• Parameter ka increases path loss in case BTS is

below the rooftop• Parameters kf control the dependence of the

multi-screen diffraction loss on the the radio frequency

• Parameters for Walfish–Ikegami model – Frequency range 800–2000 MHz– Range for BS Ae height is from 4 to 50 metres– Range for MS Ae height from 1 to 3 metres – Distance between the Tx and Rx from 20 to 5000

metres

• Dominated by same mechanisms as outdoor propagation (reflection, refraction, scattering)• Classified as either LOS or OBS

3.11 Indoor Propagation Model• smaller Tx-Rx separation distances than outdoors• higher environmental variability for much small Tx-Rx separation

- conditions vary from: doors open/closed, antenna position, - variable far field radiation for receiver locations & antenna types

• strongly influenced by building features, layout, materials

Partition Losses – Same Floor• hard partitions: immovable, part of building• soft partitions: movable, lower than the ceiling

Partition Losses – Different Floor: dependent on external building dimensions, structural characteristics & materials

Log-distance path loss model: accurate for many indoor paths

PL(dB) =

00 log10)(

d

dndPL (3.93)

• n depends on surroundings and building type• = normal random variable in dB having std deviation • identical to log normal shadowing mode (3.69)

(2) Attenuation Factor Model (Seidel92b)• includes effect of building type & variations caused by obstacles • reduces std deviation for path loss to 4dB• std deviation for path loss with log distance model 13dB

nSF = exponent value for same floor measurement – must be accurate

FAF = floor attenuation factor for different floor

PAF = partition attenuation factor for obstruction encountered by primary ray tracing

)()(log10)( )( )( )(

00 dBPAFdBFAF

d

dndBdPLdBdPL SF

3.94

primary ray tracing = single ray drawn between Tx & Rxyields good accuracy with good computational efficiency

FAF

PAF(1)

PAF(2)

Rx

Tx

)(log10)()()()(

00 dBPAF

d

dndBdPLdBdPL MF

3.95

decreases as average region becomes smaller-more specific

Building Path Loss obeys free space + loss factor () (Dev90b)

• loss factor increases exponentially with d

(dB/m) = attenuation constant for channel

Replace FAF with nMF = exponent for multiple floor loss

3.96

)()(log20)()()()(

00 dBPAFdBFAFd

d

ddBdPLdBdPL

f 850MHz 0.621.7GHz 0.57

4-story bldgf

850MHz 0.481.7GHz 0.35

2-story bldg

Location n σ (dB) number of pointssame floor 2.76 12.9 501

through 1 floor 4.19 5.1 73through 2 floor 5.04 6.5 30through 3 floor 5.22 6.7 30

Path Loss Exponent & Standard Deviation for Typical Building

The standard deviation decreases as the average region becomes smaller and more site specific.

3.12 Signal Penetration into Buildings

• no exact models

• signal strength increases with height

• lower levels are affected by ground clutter (attenuation &

penetration)

• higher floors may have LOS channel stronger incident signal on walls

RF Penetration affected by - frequency: penetration loss decreases with increasing frequency- height within building: building penetration loss decreased at a rate of 1.9dB per floor from the ground level upto fifteenth floor, loss attributed to shadowing - Measurement made in front of windows indicated 6dB less penetration loss

penetration loss • decreases with increased frequency • loss in front of windows is 6dB less than without windows• penetration loss decreases 1.9dB with each floor when < 15th floor• increased attenuation at <15 floors – shadowing affects from taller buildings

• metallic tints result in 3dB to 30dB attenuation• penetration impacted by angle of incidence

Frequency

(MHz)

Attenuation

(dB)441 16.4

896.5 11.61400 7.6

Ray Tracing & Site Specific Models• rapid acceleration of computer & visualization capabilities• SISP – site specific propagation models• GIS – graphical information systems

- support ray tracing

- augmented with aerial photos & architectural drawings

Penetration Loss vs Frequency for two different building

Frequency

(MHz)

Attenuation

(dB)900 14.2

1800 13.42300 12.8

(1) (2)