Mobile Wireless Networking CS691 004 Spring 2005

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Mobile Wireless Networking CS691 004 (Spring
2005)

• Radio Propagation Models (Part I)

Xiaoyan Hong UA CS Department hxy_at_cs.ua.edu
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Outline

• Physics of radio propagation
• Two types of propagation models
• Outdoor vs. indoor radio propagation models
• Simple link budget calculations

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Physics of radio propagation

• Radio propagation affects
• Tx area, data rate, battery drain, etc
• Physics
• Free-space propagation
• Refraction
• Diffraction
• Scattering
• Reflecting
• absorption
• Coupling loss
• Federal Standard 1037C
• http//glossary.its.bldrdoc.gov/fs-1037/

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Radio Propagation two effects

• Large-Scale effects
• variation in mean received signal strength over
  large T-R distances (100s or 1000s of meters) and
  long time-scales
• measured by averaging over 5? to 40?, i.e. 1-10m
  in cellular/PCS 1-2GHz band.
• models
• Small-scale effects
• fluctuations of the received signal strength
  about a local mean over small travel distances
  (few ?s) and short time intervals (seconds)

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Small-scale and Large-scale Fading (Indoors)

• Signal varies rapidly as T-R separation changes,
  but the local average signal changes much more
  slowly
• variation of received signal strength with
  distance from the transmitter
• shadow fading (large timescale) caused by large
  obstructions
• fading caused by local scatterers around the
  receiver
• Three effects mean path loss, slow variation
  about the mean, rapid variation

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path loss

• http//glossary.its.bldrdoc.gov/fs-1037/dir-026/_3
  873.htm
• path loss In a communication system, the
  attenuation undergone by an electromagnetic wave
  in transit between a transmitter and a receiver.
• Note 1 Path loss may be due to many effects such
  as free-space loss, refraction, reflection,
  aperture-medium coupling loss, and absorption.
• Note 2 Path loss is usually expressed in dB.
  Synonym path attenuation.

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path loss (contd)

• path loss
• free-space loss The signal attenuation that
  would result if all absorbing, diffracting,
  obstructing, refracting, scattering, and
  reflecting influences were sufficiently removed
  so as to have no effect on propagation.
• Note Free-space loss is primarily caused by
  beam divergence, i.e. , signal energy spreading
  over larger areas at increased distances from the
  source.
• coupling loss
• 1. The loss that occurs when energy is
  transferred from one circuit, circuit element, or
  medium to another.
• Note Coupling loss is usually expressed in the
  same units--such as watts or dB--as in the
  originating circuit element or medium.
• 2. In fiber optics, the power loss that occurs
  when coupling light from one optical device or
  medium to another.

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dn Path Loss Model

• Assume average power (in dB) decreases
  proportional to log of distance
• PL(d0) is the mean path loss in dB at close-in
  reference distance d0.
• D0 1m, indoor environment
• D0 100m or 1km, outdoor environment
• n is the empirical quantity. n 2 free space.

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log-normal shadowing

• Measurements show that at a given path loss has a
  normal distribution d
• is a zero-mean Gaussiona r.v. (in dB) with
  standard deviation (in dB)
• says how good the model is.

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Free Space (FS) Propagation Model

• Used when transmitter and receiver have a clear,
  unobstucted, line-of-sight (LOS) path.
• E.g., satellite channels, microwave LOS radio
  links
• FS Power at a receiver antenna at a distance d
  from transmitter antenna is
• Where and are antenna gains
• Lgt1 is the system loss factor not related to
  propagation (e.g., losses due to filter losses,
  hardware etc0
• Path loss
• Predicts Pr only for large enough d (wavelength,
  linear dimension of antenna, etc).

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Free Space (FS) Propagation Model (contd)

• Large-scale models use a received power
  reference point d0
• Pass loss can be expressed as path loss at
  reference point d0
• Without implicit measure of PL at d0, it can be
  measured as below

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Example PL calculation for FS and Urban

• Evaluate the path loss at a distance of 10km for
  a radio signal with a carrier frequency of 900MHz
  for free space and standard urban channels
• Solution
• (a) for FS
• let d0 1km, n 2,
• 20log10(4 d0/ )
  91.5 dB
• PL(d) 10 n log10(d/d0)
  111.5dB
• (b) For standard urban
• Let d0 1km, n 4,
• PL(d) 10 n log10 (d/d0)
  131.5dB
• So in the urban case, there is 20dB more loss
  over the 10 km path

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A summary

• dn Path Loss Model
• Free Space (FS) Propagation Model

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Propagation Mechanisms in Space with Objects

• Reflection (with Transmittance and Absorption)
• radio wave impinges on an object gtgt ? (30 cm _at_ 1
  GHz)
• surface of earth, walls, buildings, atmospheric
  layers
• if perfect (lossless) dielectric object, then
  zero absorption
• if perfect conductor, then 100 reflection
• reflection a function of material, polarization,
  frequency, angle
• Diffraction
• radio path is obstructed by an impenetrable
  surface with sharp irregularities (edges)
• secondary waves bend around the obstacle
• explains how RF energy can travel even without
  LOS
• a.k.a shadowing
• Scattering (diffusion)
• when medium has large number of objects lt ? (30
  cm _at_ 1 GHz)
• similar principles as diffraction, energy
  reradiated in many directions
• rough surfaces, small objects (e.g. foliage, lamp
  posts, street signs)

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Reflection, Diffraction, and Scattering in
Real-Life

• Received signal often a sum of contributions from
  different directions
• random phases make the sum behave as noise
  (Rayleigh Fading)

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Example Ground Reflection (2-Ray) Model

• Model found a good predictor for large-scale
  signal strength over distances of several
  kilometers for mobile systems with tall towers
  (heights gt 50m) as well as for LOS microcell
  channels
• Can show (physics) that for large
• Much more rapid path loss than expected due to
  free space

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Link budget Calculation using Path Loss Model

• Bit-error-rate (BER) is a function of SNR
  (signal-to-noise ratio) at the receiver
• SNR Pr / N
• The greater the SNR the better the reception
  quality
• Link budget calculations allow one to compute SNR
• requires estimate of power received from
  transmitter at a receiver
• Tx antenna, Rx antenna, Rx amplifier, path loss
  (free space, shadowing)
• also, estimate of noise and power received from
  interferers
• SNR (dB) Pr(d) (dBm) N
  (dBm)
• Where, thermal noise N KT0BF, or
• N (dBm) -174 (dBm) 10 log
  B (in Hz) F (dB)
• where B is the receivers bandwidth , and F is
  the noise figure of the receiver
• And, K 1.3810(-23) J/K is the Boltzmanns
  constant,
• T0 290K standard temperature.
• And, Pr(d) (dBm) Pt (dBm) Gt(dBm) Gr (dBm)
  PL (d) (dB)

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Example1 Link Budget Calculation

• Received power vs. distance for FS and urban area
• Given
• cellular phone with 0.6W transmit power, Pt
  0.6W 27.78dBm
• unity gain antenna, 900 MHz carrier frequency, f
  900MHz
• What is the received power in dBm at a FS
  distance 5km?
• What is the Pr(5km) in a shadowed Urban area with
  
• FS for dlt1km, and n 4 for dgt1km?
• Solution given, d0 1km, Gt and Gr 0,
• c/f 3108 / (9108) 1/3 m,
• ((4 )2d02)/ 1.42109
  91.53dB
• (a) FS n 2, d 5km,
• PL(d) (dB) 10nlog10(d/d0)
  105.53dB
• Pr Pt (dBm) Gt Gr PL(d) (dB) 27.8 0
  0 105.5 -77.7dBm
• (b) Urban n 4, d 5km
• PL(d) 119.5 dB,
• Pr -91.7dBm

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Example2 Link Budget Calculation (contd)

• Maximum separation distance vs. txed power (with
  fixed BW)
• Given
• cellular phone with 0.6W transmit power, Pt
  0.6W 27.78dBm
• unity gain antenna, 900 MHz carrier frequency, f
  900MHz
• SNR must be at least 25 dB for proper reception
• receiver BW is B 30 KHz, and noise figure F
  10 dB
• What will be the maximum distance?
• Solution (previous resultsd0 1km,
  91.5 dB)
• N -174 dBm 10 log 30000 10 dB -119 dBm
• For SNR gt 25 dB, we must have Pr gt (-11925)
  -94 dBm
• This allows path loss PL(d) Pt - Pr lt 122 dB
• (a) FS n 2,
• so that 122 gt 91.5 102log(d/(1 km)), d lt
  33.5 km
• (b) shadowed urban with n 4,
• So that 122 gt 91.5 104log(d/(1 km)), d lt 5.8
  km

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Example3 Link Budget Calculation (contd)

• Maximum BW vs. txed power (with fixed separation
  distance)
• Given
• cellular phone with 0.6W transmit power, Pt
  0.6W 27.78dBm
• unity gain antenna, 900 MHz carrier frequency, f
  900MHz
• SNR must be at least 25 dB for proper reception
• Max separation is 5km, and noise figure F 10 dB
• What will be the maximum BW?
• Solution
• (a) FS n 2,
• previous results at d 5km PL(d) 105.5 dB, Pr
  -77.7dBm
• Assume SNR must be 25dB, max noise power
• N -77.7 25 -102.7dB.
• N -174 dBm 10 log10 (B) 10 dB -102.7 dBm
  , so B 1.349MHz.
• (b) shadowed urban with n 4,
• At d 5km, PL(d) 119.5dB, Pr -91.7dBm
• max noise power N -91.7 25 -116.7dB
• N -174 dBm 10 log10 (B) 10 dB -116.7 dBm
  , so B 53.7kHz (20 times smaller for the same
  quality of reception than FS!)

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Indoor Path Loss Models (e.g. for WLANs)

• Two characteristics of indoor environments
• - small distances
• - much greater environmental variability even
  for small T-R separations
• e.g. doors closed vs. opens, ceiling vs. desk
  mounted antennas,
• walls, floors, furniture, people
  moving around
• Partition losses on same floor
• - wide variety of partitions.... with different
  electrical physical characteristics
• - hard partitions (to the ceiling) vs soft
  partitions
• - extensive databases of measurements
• Partition losses between floors
• - depends on construction material, number of
  windows, presence of tinting...
• - characterized by Floor Attenuation Factors
  (FAF)
• The Log-normal shadowing path loss model, found
  to be valid!

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Indoor Path Loss Models (contd)

• Log-normal shadowing path loss model
• Attenuation factor model
• where is the exponent value for same
  floor measurement

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Indoor Path Loss Models (contd)
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More on Large Scale Path Loss

• RF signal penetration into buildings
• - depends on building material, height,
  percentage of windows, height, orientation,
  transmission frequency
• e.g. signal strength inside the building
  increases with height (LOS to upper floor walls)
• e.g. metallic tints can provide 3 to 30 dB
  attenuation in a single glass pane
• - n is between 3.0 and 6.2, with average of 4.5
• Ray tracing CAD tools for site specific modeling
• deterministically model indoor and outdoor
  propagation using ray tracing
• e.g. use building blueprints from, say, AutoCAD,
  or, aerial photographs
• replacing statistical models

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Reading list for this lecture

• T. S. Rappaport, K. Blankenship, and H. Xu,
  "Propagation and Radio System Design Issues in
  Mobile Radio Systems for the GloMo Project,"
  tutorial from Virginia Tech. Available in pdf.

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Capacity of Wireless Networks

• Slides are from Sachin Adlakha

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Channel Capacity

• In 1948 Claude Shannon showed that the maximum
  rate at which information can be transferred is
  limited by capacity of the channel. This is
  Channel coding theorem.
• For Gaussian channel the capacity is given by
• C W log2(1 SNR/W) bits/sec
• Here W is the channel bandwidth

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Communication Network

• Multiple Transmitters and receivers introduce
  interference and thus reduce the capacity.
• How Much traffic can a wireless network carry?

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Model

• n nodes located in a region of area 1 sq.m.
• Each node can transmit at W bits per second.
• Packets are sent from source to destination in a
  multihop fashion.
• Packets can be buffered at intermediate nodes
  while awaiting transmission.

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Arbitrary Networks

• n nodes are arbitrary located in a disk of unit
  area.
• Each node has arbitrary chosen destination at
  some arbitrary rate.
• Each node can choose arbitrary range and power
  level for each transmission.

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Random Networks

• In a random scenario , n nodes are randomly
  located i.e. independently and uniformly located
  on surface S2 of 3D sphere of unit area or disk
  of unit area.
• All nodes are homogeneous i.e. all transmission
  employ same nominal range or power.

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When are packets successfully received?

• Protocol Model
• Receiver R should be
• Within r of its transmitter T
• Outside footprint (1?)r of any
• other transmitter T using range r
• Physical model
• Models a situation where a minimum SIR is
  required

r
(1?)r
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Transport Capacity of arbitrary network

• Define one bit-meter when one bit is transported
  over distance of one meter.
• Main result 1
• Under protocol model, the transport capacity of
  arbitrary network is
• bit meters per
  second.
• Main result 2
• Under physical model, is
  feasible while
• is not for appropriate c, c.
• Thus each node can send approx.
  bit-meters/sec

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Random Network Scenario

• Define throughput capacity as the average of
  number of bits per second that can be transmitted
  by every node to its destination.
• A throughput is of the order if
  ? constants c ? 0 and c lt ? ?
• Main result 3
• In case of both surface of sphere and planar disk
  the order of the throughput capacity is

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• Main result 4
• For the physical model, a throughput of
• bit per second
  is feasible ,
• while is not for
  appropriate c and c.

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• Random networks the throughput capacity is
• Implications
• Throughput decreases with n. Design networks
  with smaller number of users.
• For random networks, selecting appropriate power
  levels is imperative for network to be connected,
  while limiting interference.
• Designing MAC protocols that avoid collisions and
  approach the capacity as derived above

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Adding Mobility!!!

• The results derived above are for static
  networks.
• What if the nodes are mobile??
• Grossglauser and Tse proved that asymptotically
  mobility increases the capacity of ad-hoc
  networks.

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How to exploit mobility?

• Exploit diversity by giving up latency
  constraints
• Transfer packets from source to destination only
  when they are close.
• However the fraction of time the nodes are close
  to each other is small.
• So distribute the packets to many different nodes
  as possible.
• Similar to Opportunistic transmission or
  multi-user diversity

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Mobility Model

• n nodes lying in the open disk of unit area
• The location of ith node at time t is given by
  Xi(t)
• Xi(t) is stationary and ergodic with stationary
  distribution uniform on the the open disk
• Trajectories of different users are independent
  and identically distributed
• Two cases
• No relaying of packets packets directly to
  destination
• Nodes can serve as relays have infinite buffer

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• Model of successful transmission is same as
  physical model
• Throughput definition
• Let ? be a scheduling and relaying policy
• Let Mi?(t) be number of packets that destination
  d(i) receives at time t under policy ?.
• The throughput ?(n) is feasible if there is a
  policy ? such that for every source-destination
  pair

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Mobile Nodes without relaying

• Minimum interference requirement places an upper
  bound on number of successful transmission at any
  time.
• Main result
• For no relaying, the achievable throughput per
  S-D goes to zero at least as fast as i.e.

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Mobile nodes with relaying

• Direct transmission increases interference.
• So use multi-hop i.e relay the packet to large
  number of intermediate relay nodes.
• Two stage algorithm
• Stage 1 Schedule packets from sources to relays
  (or final destination
• Stage 2 Scheduling packets from relays to final
  destination

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Throughput with relaying nodes

• For the scheduling policy ?, the expected number
  of feasible sender receiver pair is O(n).
• Main result
• The two phased algorithm achieves a throughput
  per S-D pair of O(1), i.e. there exists a
  constant c gt 0 such that

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Key Facts

• This is asymptotic throughput capacity of
  wireless ad-hoc networks.
• Exploits long range fluctuations in fading
  process due to node mobility
• Key idea is that every node can get close to any
  other node
• The result is purely theoretical in nature i.e it
  might take large delay for such capacity to
  achieve.
• Not applicable to real time communications.

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Other Issues

• Design MAC protocol, power assignments and
  routing to achieve theoretical throughput
• Recent work by Kumar et al focuses on achieving
  the theoretical bounds
• Also how would the capacity of mobile network
  change if we place a bound on tolerable delay??

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Conclusions

• Communication capacity of wireless networks is
  limited due to multiple access.
• Each transmission consumes valuable resource
  space thereby limiting number of simultaneous
  transmissions.
• Mobility provides diversity by trading off
  latency to improve capacity asymptotically