channels and channel models - lth · dish antenna with effective area a, the antenna gain is...
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Channels and Channel Models
EIT 140, tom<AT>eit.lth.se
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Channel types: single-user / multi-user
Depending on the topology of the channel, we distinguish single-user channelsand multi-user channels:
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Single-user channel
Multiple-access channel
Broadcast channel
Interference channel
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Channel types: SISO, MIMO, SIMO, MISODepending on the number of ports of a user-to-user link, we distinguish
Single-input single-output (SISO) channel
Single-input multi-output (SIMO) channel
Multi-input single-output (MISO) channel
Multi-input multi-output (MIMO) channel
SISO
SIMO
MISO
MIMO
= port-to-port link
Examples:
Multi-antenna systems
Multi-pair cables
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Channel types: information theoretic view
Sometimes, all the blocks like modulation, demodulation, up-conversion,(physical) channel, down-conversion, etc. are modelled as a single entity calleddigital channel:
Modulator DemodulatorChannel
Channel
Digital
Up-Converter Down-Converter A/D ConverterD/A Converter
“digital” refers to the quantisation in amplitude (the set of outputsymbols is finite)
digital channel is described by transition probabilities p(yk |xl ), i.e., theconditional probabilities that yk is detected given that xl was transmitted
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Channel types: classification according to medium
Depending on the medium, we distinguish
guided channels
wire (e.g.: copper twisted-pairs in the access network)cable (e.g.: coax cables used in cable networks)fibre (e.g.: optical fibres in backbone networks)microwave guides (e.g.: feeder “pipes” for high-power RFtransmitters, radar)
unguided channels
wireless channelunderwater acoustic channel
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Channel properties
The transmitted waveforms may experience effects like
reflection
absorption
attenuation (scaling in amplitude)
dispersion (spreading) in time
refraction (bending due to variation of the media’s refraction index)
diffraction (scattered re-radiation, caused by an edge or an object whosesize is in the order of the wave length)
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Channel properties cont’d
The net effect of every channel can be described by
modification of the signal
addition of noise
sequence notation: r(n) = h(n)∗s(n) + w(n) matrix notation: r = Hs + w
Depending on the channel properties, a channel can be
linear / non-linear channels
time-invariant / time-variant (fading) channels
frequency-flat / frequency-selective (time-dispersive) channels
The additive noise can be
Gaussian / non-Gaussian
correlated in time/frequency, spatially (in MIMO system), over users (inmulti-user systems)
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Wireline channel: physical mechanisms/effects
essentially time-invariant, frequency-selective attenuation, orequivalently, dispersion in time
crosstalk: electromagnetic coupling among wire pairs (also calledloops) in a cable
extrinsic noise/interference (impulse noise, radio frequencyinterference)
background noise (thermal noise, front-end noise)
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Wireline channel: physical mechanisms/effects cont’d
1 12 2
......
K K
RFI impulses
FEXT NEXT
side A side B
Far-end crosstalk (FEXT)
Near-end crosstalk (NEXT)
Impulse noise
Radio frequency interference (RFI)
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Wireline channel: modelling as LTI system
Assuming proper termination, the insertion loss can be modelled as LTIsystem:
Hloop(f , d)=e− d
d0(k1
√f +k2f )
e−j d
d0k3f , (47)
where
f is the frequency in Hz
d is the length of the loop in m
k1, k2, k3 are constants depending on the diameter of the wire;exemplary values for 0.5mm loop:k1 =3.8 · 10−3, k2 =−0.541 · 10−8, k3 =4.883 · 10−5
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Wireline channel: modelling as LTI system
Assuming proper termination, the NEXT coupling and FEXT couplingcan be modelled via LTI systems:
HFEXT(f , d)=kff
f0
√
d
d0|Hloop(f , d)|, kf =10−45/20, f0 =1MHz, d0 =1 km
(48)
HNEXT(f , d)=kn
(f
f0
) 34 √
1− |Hloop(f , d)|4, kn =10−50/20, f0 =1MHz
(49)where
f is the frequency in Hz
d is the coupling length of the loops in m
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Wireline channel: receive PSDs
frequency f in MHz
PSD
indB
m/H
z
Signal
−150
−130
−110
−90
−70
−50
0 5 10 15
NEXTFEXTAWGN500m1000m2000m
Transmit signal PSD: flat −60 dBm/Hz
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Wireless channel: physical mechanisms/effects
Fixed terminals
Path lossBackground noise
Mobile terminal(s)
Path lossBackground noiseDoppler effectTime-varying impulse response
→ dispersion in frequency→ receive signal amplitude fluctuations (fading)
Dispersion in time, or equivalently, frequency selectivity
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Obstacle-free transmission: path loss
The receive signal power is given by
Pr = PtGtGrLp. (50)
Pt is the transmit power
Gt is the transmit antenna gain (ratio of the received powercompared to the power an isotropic antenna would receive; for adish antenna with effective area A, the antenna gain is roughlyG ≈ 4πA/λ2),
Gr is the receive antenna gain and
Lp is the free-space path loss, given by
Lp =
(λ
4πd
)2
(51)
d distanceλ wavelength
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Presence of obstacles: ray tracing
Simple two-ray model
d
hthr
Pr = PtGtGrh2t h2
r
d4(d2 ≫ hthr) (52)
ht height of transmit antenna
hr height of receive antenna
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Simplified path loss model
Pr = PtGtGr Pr(d0)/Pt︸ ︷︷ ︸
K
(d0
d
)γ
(53)
d0 reference distance
K ratio of receive and transmit power for d0
path loss exponent γ, depends on wavelength and environment,typically in the range 2− 8 for 1GHz
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Mobile terminal(s)
Most often, only one of the terminals is moving, which we call themobile terminal (MT). The other one, the fixed terminal (FT), doesnot move
Due to reciprocity, it does not matter whether we observe downlink(FT → MT) or uplink (MT → FT)
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Mobile terminal(s): Doppler effect
When the FT transmits a signal with frequency f = c/λ, the MTreceives this signal at frequency f + ν = f + v ′/λ, where v ′ is therelative velocity of the MT with respect to the FT.
Note that v ′ is a signed quantity
FT
MT1
MT2
v1
v2
v ′1 = v1 cos α1
v ′2 = −v2 cos α2
α1
α2
ν is called the Doppler shift (example: ν ≈ 83 Hz for 100 km/h and900 MHz)
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Mobile terminal(s): characterisation of effects
Dispersion in time
transmitted beam is reflected and scattered along the way →multi-path propagationoften, there is neither a direct beam from the FT to the MT nor astationary reflection (both of which are referred to as line of sight(LOS) components)if the beams arrive with different delays, time-dispersion of thetransmitted signal occurs
Dispersion in frequency
if either the MT or scatterers are moving, each received beam has adifferent relative velocity with respect to the MT →frequency-dispersion of the transmitted signal occursmotion is not the exclusive cause of frequency dispersion; moregenerally, frequency dispersion is caused by a time-varying channelimpulse response
Fluctuations in amplitude (fading)
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Characterisation of amplitude fluctuations (fading)
path loss (dotted green curve)
large-scale (macroscopic) fading (dashed blue curve)
small-scale (microscopic) fading (solid red curve)
time (∝ distance)
amplit
ude
indB
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Small-scale fading: Rayleigh distribution, Rice distribution
FT
MT v
ψ1
ψ2
many waves arrive from arbitrary directions
the amplitudes AI ∼ N (mI , σ2) and AQ ∼ N (mQ , σ2) of inphaseand quadrature receive component, respectively, are independentand Gaussian distributed (central limit theorem)
no LOS component: mI = mQ = 0 → amplitude U =√
A2I+ A2
Q
has Rayleigh distribution
with LOS component: mI 6= 0 and/or mQ 6= 0 → amplitude U hasRice distribution
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Small-scale fading: Rayleigh/Rice distribution cont’d
Rayleigh distribution:
pU (u) =u
σ2e− u2
2σ2 , u ≥ 0. (54)
Rice distribution:
pU (u) =u
σ2e− u2+s2
2σ2 I0(us
σ2), u ≥ 0; s =
√
m2I
+ m2Q
= A0.
(55)
u
pU
(u)
A0 = 0
A0 = 1
A0 = 2
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0 1 2 3 4 5
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Large-scale fading
Models the channel property changes caused by movement of theMT
Characterises the mean value of the small-scale fading model
The log-normal distribution has been found to yield a good matchwith measurements
The mean value in dB γdB is Gaussian distributed
pγdB(γdB) =
1√2πσdB
e− (γdB−mdB)2
2(σdB)2 , (56)
where σdB, the standard deviation of γdB, is typically in the range of6-12 dB.Then the distribution of γ = 10γdB/20 is given by
pγ(γ) =20
γ√
2πσdB ln 10e− (20 log10 γ−mdB)2
2(σdB)2 . (57)
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Charaterisation of dispersion in time and frequency
Deterministic analysis
channel is modelled as linear time-variant (LTV) system, describedby a time-variant impulse response h(τ, t)
time-variant frequency response H(f , t) = Fτ{h(τ, t)}delay Doppler spreading function s(τ, ν) = Ft{h(τ, t)}output Doppler spreading function B(f , ν) = Ft{H(f , t)}
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Charaterisation of dispersion in time and frequency
Stochastic analysis
auto-correlation function Rhh(τ1, τ2, t1, t2) = E {h∗(τ1, t1)h(τ2, t2)}of the impulse response
wide-sense stationarity (WSS) assumption: Rhh(τ1, τ2, t1, t2)depends only on the time difference ∆t = t2 − t1uncorrelated scattering (US) assumption: scatterers actindependently → it is sufficient to observe Rhh(τ, t1, t2)WSS + US → WSSUS assumption: it is sufficient to observe thedelay cross-power spectral density Rhh(τ, ∆t)
time-frequency correlation function
RHH (∆f , ∆t) = Fτ{Rhh(τ, ∆t)}scattering function Rs (τ, ν) = F∆t{Rhh(τ, ∆t)}Doppler cross-power spectral density
RB (∆f , ν) = F∆t{RHH (∆f , ∆t)}
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Exemplary system functions
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Summary of wireless channel characterisation measures
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h(τ, t)
Time-variantimpulse response
H(f , t)
Time-variantfrequency response
s(τ, ν)
Delay Dopplerspreading function
B(f , ν)
Output Dopplerspreading function
Rhh (τ, ∆t)
Delay cross-powerspectral density
RHH (∆f , ∆t)
Time-frequencycorrelation function
Rs (τ, ν)
Scattering function
RB (∆f , ν)
Doppler cross-powerspectral density
P(τ)
Delay powerdensity spectrum
RH (∆f )
Frequency correlation
RH (∆t)
Time correlation
P(ν)
Doppler powerdensity spectrumFτ (∆f )
Fτ (∆f )
Fτ (∆f )
Fτ(f
)F
τ(f
) Ft (ν)Ft (ν) F∆t (ν)F
∆t (ν) F∆t (ν)
∆f=
0∆f=
0
∆t =0∆t =0
Ct (∆t) Cf ,t (∆f , ∆t)
| · |2 Cf (∆f )
(·)−1
(·)−1
TcohCoherence
time
BdopDoppler
bandwidth
TmultiMulti-path
spread
BcohCoherencebandwidth
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Charaterisation of dispersion in time and frequency
Two functions commonly used in practice:
1 delay power density spectrum (power delay profile)P(τ) = Rhh(τ, ∆t)|
∆t=0 specifies time-dispersion (or equivalently,frequency-selectivity) characteristic
2 Doppler power density spectrum (Doppler spectrum)P(ν) = RB (∆f , ν)|
∆f =0 specifies frequency dispersion, orequivalently, the correlation of realisations observed over time of agiven coefficient of the tapped delay line filter
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Charaterisation of dispersion in time and frequency
Two scalars commonly used in practice:
1 The multi-path spread Tmulti specifies the approximate support ofthe power delay profile P(τ), or equivalently, the approximate lengthof the channel impulse response. Dual measure: coherence
bandwidth Bcoh ≈ 1/Tmulti.
2 The coherence time Tcoh specifies the approximate support of thetime correlation function RH (∆t), or equivalently, the time duringwhich the impulse response remains constant. Dual measure:Doppler bandwidth Bdop ≈ 1/Tcoh.
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Assessment of wireless channels
The parameters Tcoh and Tmulti of a wireless channel have to be seen incontext with symbol period Tsym of the system.
replacementsBdop
Bcoh
Tmulti
Tcoh
frequency selectivefast fading
frequency flatfast fading
frequency selectiveslow fading
frequency flatslow fading
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Ergodicity
useful description of a linear channel with additive noise:
r = Hs + n
s ∈ CS : channel input. r ∈ CR : channel output. H ∈ CR×S :channel matrix. n ∈ CR : additive noise.
Ergodic channelrn = Hnsn + nn.
Hn are realizations of a random process. Transmittedsymbol/codeword sn, n = 0, 1, . . . , N ; N ≫ “sees” all channelstates. Valid for fast fading channels.
Nonergodic channel: Consider the model
rn = Hsn + nn,
Here, H is constant over the symbol/codewordsn, n = 0, 1, . . . , N ; N ≫. Transmitted symbol/codeword “sees”only one state (H). Valid for slowly fading channels.
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Block fading
Interleavers spreads out codewords in time and/or frequency.
Long interleaver can thus turn a nonergodic channel (where eachcodesymbol of a codeword sees one channel state only) into anergodic channel (where each codesymbol of a codeword sees adifferent channel state)
Block fading characterizes the situation in between those twoextremes. If the interleaver is not long enough, blocks ofcodesymbols see the same channel state.
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Summary
1 Classification of channels
single-user, multi-userSISO, MIMO, MISO, SIMO“digital” channels (BSC, DMC)physical medium (copper, coax, fiber, air/space)
2 Wireline channel
essentially time-invariant, strongly frequency selective
3 Wireless channel
fixed terminals
static view on attenuation (link budget) is sufficient, limited bybackground noise
mobile terminal(s)
time-variant (frequency-dispersive), time-dispersive (frequencyselective)
ergodicity