Presentation is loading. Please wait.

Presentation is loading. Please wait.

Radiowave Channel Modelling for Radio Networks Costas Constantinou Electronic, Electrical & Computer Engineering The University of Birmingham, UK

Similar presentations


Presentation on theme: "Radiowave Channel Modelling for Radio Networks Costas Constantinou Electronic, Electrical & Computer Engineering The University of Birmingham, UK"— Presentation transcript:

1 Radiowave Channel Modelling for Radio Networks Costas Constantinou Electronic, Electrical & Computer Engineering The University of Birmingham, UK

2 2Mobihoc '03 Radio Channel Modelling Tutorial Electromagnetic waves Electric & Magnetic fields Basic notions Fields are mechanisms of transfer of force and energy Distributed in space and time Have direction as well as magnitude Two types of ‘arrow’ Vector Phasor Vector & Phasor addition illustrated Im Re 0 1 

3 3Mobihoc '03 Radio Channel Modelling Tutorial Electromagnetic waves Vector plane waves Frequency Wavenumber Wavelength

4 4Mobihoc '03 Radio Channel Modelling Tutorial Reflection of plane waves Reflection coefficient is a tensor The reflection coefficient can be resolved into two canonical polarisations, TE and TM and has both a magnitude and phase Plane of incidence

5 5Mobihoc '03 Radio Channel Modelling Tutorial Reflection of plane waves Typical reflection coefficients for ground as a function of the grazing angle (complement of the angle of incidence). In this instance, Pseudo-Brewster angle

6 6Mobihoc '03 Radio Channel Modelling Tutorial Common electrical constants Electrical properties of typical construction materials in UHF band ( 300MHz – 3GHz ) Material rr  Sm -1 Ground7-30; typical ; typical Fresh water Sea water814 Brick40.02 Concrete (dry)70.15 Concrete (aerated)20.08 Gypsum (plaster) board Glass Wood

7 7Mobihoc '03 Radio Channel Modelling Tutorial Electromagnetic waves Spherical waves Intensity (time-average) Conservation of energy; the inverse square law

8 8Mobihoc '03 Radio Channel Modelling Tutorial Electromagnetic waves Conservation of energy; the inverse square law

9 9Mobihoc '03 Radio Channel Modelling Tutorial Radiation Pictorial introduction to radiation from accelerated charges

10 10Mobihoc '03 Radio Channel Modelling Tutorial Radiation Pictorial introduction to radiation from accelerated charges

11 11Mobihoc '03 Radio Channel Modelling Tutorial Radiation Pictorial introduction to radiation from accelerated charges

12 12Mobihoc '03 Radio Channel Modelling Tutorial Radiation Fields around a charge in non-uniform motion

13 13Mobihoc '03 Radio Channel Modelling Tutorial Radiation Fields around a charge in non-uniform motion

14 14Mobihoc '03 Radio Channel Modelling Tutorial Radiation Fields around a charge in non-uniform motion

15 15Mobihoc '03 Radio Channel Modelling Tutorial Radiation Radiated fields proportional to charge acceleration (current proportional to charge velocity) and number of charges Radiated wave is spherical provided the observation point is far enough away from the source Radiated wave is transverse electromagnetic The field magnitude is proportional to the sine of the angle from the axis of charge acceleration Small antenna (Length & constant current ) in the far-field

16 16Mobihoc '03 Radio Channel Modelling Tutorial Antennas In general, the fields radiated by an arbitrary antenna in the far-field zone are of the form, where the last term is the antenna radiation pattern (including its polarisation characteristics) Radiation pattern: a polar plot of power radiated per unit solid angle (radiation intensity) Isotropic antenna does not exist in 3D, but is still used as a reference antenna!

17 17Mobihoc '03 Radio Channel Modelling Tutorial Antennas A general antenna pattern

18 18Mobihoc '03 Radio Channel Modelling Tutorial Antennas Radiation pattern: a polar plot of power radiated per unit solid angle (radiation intensity) Directional vs. omni- directional antenna Lobes: main lobe (boresight direction), sidelobes, backlobes Half-power beamwidth (HPBW); first null beamwidth (FNBW) Sidelobe levels (dB) Front-to-back ratio (dB)

19 19Mobihoc '03 Radio Channel Modelling Tutorial Antennas Directivity Radiation efficiency Gain (directive gain) Beamwidth and directivity (pencil beam antenna) Bandwidth: impedance vs. pattern

20 20Mobihoc '03 Radio Channel Modelling Tutorial Antennas Reciprocity and receiving effective aperture area The gain of an antenna in transmission mode is proportional to its effective aperture area in reception mode and the constant of proportionality is universal for all antennas Polarisation matching (dot product between incident electric field vector and the unit vector of antenna polarisation) Co-polar pattern Cross-polar pattern

21 21Mobihoc '03 Radio Channel Modelling Tutorial Antennas Antenna examples AntennaGain (dBi) Band- width Pola- risation Half-power beamwidth (  ) Half-power beamwidth (  ) Small dipole or loop (L<< ) 1.76N/ALinear90°Omni-directional Half-wavelength ( /2) dipole %Linear78°Omni-directional Yagi-Uda array of /2 dipoles 125%Linear65°45° Patch antenna (typical) 65%Linear80° Helical antenna: axial mode – typ. 132:1Circular20° Helical antenna: normal mode – typ %Linear78°Omni-directional

22 22Mobihoc '03 Radio Channel Modelling Tutorial Antennas Antenna arrays Multiple elements Voltages at their elements are phasors Voltage phase-shifted then added to produce maximum reception sensitivity to radiation from a particular direction (beam-forming) Radiation pattern (and gain) is the product of the element pattern and the array factor– watch for electromagnetic coupling! Phases may be shifted in real-time to have adaptive antenna MIMO antennas (more later on this one)

23 23Mobihoc '03 Radio Channel Modelling Tutorial Antenna arrays Two point sources of equal amplitude and phase Phase difference of two fields at the observation point Total field at the observation point

24 24Mobihoc '03 Radio Channel Modelling Tutorial Antenna arrays Field pattern ( )

25 25Mobihoc '03 Radio Channel Modelling Tutorial Antenna arrays Point sources Same phase  = 0, spaced /2 Phase quadrature  = 90º, /2 Phase quadrature  = 90º, /4

26 26Mobihoc '03 Radio Channel Modelling Tutorial Antenna arrays Principle of pattern multiplication Antenna array field pattern = element pattern  array pattern

27 27Mobihoc '03 Radio Channel Modelling Tutorial Antenna arrays Broadside array: main lobe perpendicular to array End-fire array: main lobe along array 2D, 3D arrays Side-lobe tapering via amplitude distribution functions Grating lobes

28 28Mobihoc '03 Radio Channel Modelling Tutorial Free space propagation Transmitted power EIPR (equivalent isotropically radiated power) Power density at receiver Received power Friis power transmission formula txrx R

29 29Mobihoc '03 Radio Channel Modelling Tutorial Free space propagation Taking logarithms gives where is the free-space path loss, measured in decibels Math reminder

30 30Mobihoc '03 Radio Channel Modelling Tutorial Basic calculations Example: Two vertical dipoles, each with gain 2dBi, separated in free space by 100m, the transmitting one radiating a power of 10mW at 2.4GHz This corresponds to 0.4nW (or an electric field strength of 0.12mVm -1 ) The important quantity though is the signal to noise ratio at the receiver. In most instances antenna noise is dominated by electronic equipment thermal noise, given by where is Boltzman’s constant, B is the receiver bandwidth and T is the room temperature in Kelvin

31 31Mobihoc '03 Radio Channel Modelling Tutorial Basic calculations The noise power output by a receiver with a Noise Figure F = 10dB, and bandwidth B = 200kHz at room temperature ( T = 300K ) is calculated as follows Thus the signal to noise ratio (SNR) is given by

32 32Mobihoc '03 Radio Channel Modelling Tutorial Basic calculations The performance of the communication system (outside the scope of this tutorial) depends on the SNR, modulation and coding (forward error correcting (FEC) coding) employed and is statistical in nature We can look up graphs/tables to convert from SNR to bit error rate, BER for each modulation scheme (next slide) Assuming that the probability of each bit being detected erroneously at the receiver is independent, we can find the probability for the number of erroneous bits exceeding the maximum number of errors the FEC code can cope with in any one packet and thus arrive at the probability (or frequency) of receiving erroneous packets

33 33Mobihoc '03 Radio Channel Modelling Tutorial Basic calculations

34 34Mobihoc '03 Radio Channel Modelling Tutorial Basic calculations In a multi-user environment we have to incorporate the the effects of the co-channel interference in these calculations In practice we need to model interferer power probabilistically These calculations are known as outage probability calculations This is not a problem,as the desired link power often needs to be modelled probabilistically too Let us turn our attention back to this problem now, by considering more realistic propagation models

35 35Mobihoc '03 Radio Channel Modelling Tutorial Propagation over a flat earth The two ray model Valid in the VHF, band and above (i.e. f  30MHz where ground/surface wave effects are negligible) Valid for flat ground (i.e. r.m.s. roughness  z , typically f  30GHz ) Valid for short ranges where the earth’s curvature is negligible (i.e. d  10–30 km, depending on atmospheric conditions) z htht hrhr d r1r1 r2r2 air,  0,  0 ground,  r,  0,  Tx Rx P   x

36 36Mobihoc '03 Radio Channel Modelling Tutorial Propagation over flat earth The path difference between the direct and ground-reflected paths is and this corresponds to a phase difference The total electric field at the receiver is given by The angles  and  are the elevation and azimuth angles of the direct and ground reflected paths measured from the boresight of the transmitting antenna radiation pattern

37 37Mobihoc '03 Radio Channel Modelling Tutorial Propagation over flat earth This expression can be simplified considerably for vertical and horizontal polarisations for large ranges d >> h t, h r,,

38 38Mobihoc '03 Radio Channel Modelling Tutorial Propagation over flat earth There are two sets of ranges to consider separated by a breakpoint

39 39Mobihoc '03 Radio Channel Modelling Tutorial Propagation over flat earth Thus there are two simple propagation path loss laws where l is a rapidly varying (fading) term over distances of the scale of a wavelength, and This simplifies to The total path loss (free space loss + excess path loss) is independent of frequency and shows that height increases the received signal power (antenna height gain) and that the received power falls as d -4 not d -2

40 40Mobihoc '03 Radio Channel Modelling Tutorial Propagation over flat earth Typical ground (earth) with  r = 15,  = 0.005Sm -1, h t = 20m and h r = 2m deep fade 1/d 2 power law regime (d < d c ) 1/d 4 power law regime (d > d c )

41 41Mobihoc '03 Radio Channel Modelling Tutorial Radio channels for MANETS Channels are: Short-range (microcellular & picocellular) Indoor or outdoor UHF band ( 300MHz  f  3GHz, or 10cm   1m ) SHF band ( 3GHz  f  30GHz, or 1cm   10cm ) Models can be: Deterministic, statistical, or empirical Narrowband, broadband Multipath propagation mechanisms of importance: Reflection Diffraction Transmission Scattering

42 42Mobihoc '03 Radio Channel Modelling Tutorial Observed signal characteristics Narrowband signal (continuous wave – CW) envelope Area mean or path loss (deterministic or empirical) Local mean, or shadowing, or slow fading (deterministic or statistical) Fast or multipath fading (statistical)

43 43Mobihoc '03 Radio Channel Modelling Tutorial Observed signal characteristics The total signal consists of many components Each component corresponds to a signal which has a variable amplitude and phase The power received varies rapidly as the component phasors add with rapidly changing phases Averaging the phase angles results in the local mean signal over areas of the order of  10 2 Averaging the length (i.e. power) over many locations/obstructions results in the area mean The signals at the receiver can be expressed in terms of delay, or frequency variation, and depend on polarisation, angle of arrival, Doppler shift, etc.

44 44Mobihoc '03 Radio Channel Modelling Tutorial Actual measurements We shall look at some examples which I have taken together with: Prof. David Edwards (Oxford) Andy Street (now at Agilent) Alan Jenkins (now in Boston) Jon Moss (O 2 ) Lloyd Lukama (BBC R&D) Junaid Mughal (Birmingham) Yuri Nechayev (Birmingham)

45 45Mobihoc '03 Radio Channel Modelling Tutorial Measurement system VNA-based Synthetic volume aperture Rx antenna on a grid of 26x26x2 positions with a cell size of 3x3x40 cm 3 : Azimuth resolution 10 o Elevation resolution 30 o (with grating lobes) Reflection measurement: f 0 = MHz; B = 80 MHz Transmission measurement: f 0 = MHz; B = 200 MHz S 21 response calibrated and checked for phase stability & repeatability

46 46Mobihoc '03 Radio Channel Modelling Tutorial Measurement location Four-storey brick building 25 cm thick exterior walls 12 cm thick interior walls Foyer near T-junction Corridor along length Offices & labs either side of corridor Staircases at ends surrounded by offices Exterior wall structure: windows with ledges, small balcony

47 47Mobihoc '03 Radio Channel Modelling Tutorial Measurement location

48 48Mobihoc '03 Radio Channel Modelling Tutorial Measurement Antennas

49 49Mobihoc '03 Radio Channel Modelling Tutorial Reflection measurement

50 50Mobihoc '03 Radio Channel Modelling Tutorial Reflection measurement LOS at 125ns and at expected path loss Specular reflection at 237ns (correct path length geometrically) and a path loss corresponding to 5dB of reflection loss Experimental reflection coefficient |  | = 0.56 (= -5 dB) Theoretical Fresnel reflection coefficient for brick with 10% moisture content (  r = j0.9 & 31 o angle of incidence) |  | = 0.54 Additional scattered energy at 249ns & nearby spatial AoA is comparable to specular reflection Non-simple “reflection” (i.e. scattering) process

51 51Mobihoc '03 Radio Channel Modelling Tutorial Transmission measurement

52 52Mobihoc '03 Radio Channel Modelling Tutorial Transmission measurement

53 53Mobihoc '03 Radio Channel Modelling Tutorial Transmission measurement DelayPath loss Path length Map dist. Possible propagation mechanism 175 ns119 dB52 m50 mGround floor tx through window 190 ns120 dB57 m54 mGround floor tx through window 249 ns121 dB75 m69 m1 st floor tx through stairwell 279 ns122 dB84 m Tx through ground floor foyer 324 ns122 dB97 m99 mArts & Watson refl and Arts diffr 409 ns125 dB123 m?Multiple scat from Arts & Watson 554 ns128 dB166 m Multiple scattering from Physics 589 ns111 dB177 m175 mArts 1 refl & Physics 2 refl 853 ns119 dB256 m?Scat from nearby tower block ?

54 54Mobihoc '03 Radio Channel Modelling Tutorial Indoor measurements Oxford indoor measurements at 5.5GHz ( 2ns resolution)

55 55Mobihoc '03 Radio Channel Modelling Tutorial Indoor measurements Oxford indoor measurements at 5.5GHz ( 2ns resolution)

56 56Mobihoc '03 Radio Channel Modelling Tutorial Outdoor to Indoor measurements Oxford outdoor to indoor measurements at 2.44Hz ( 27ns resolution)

57 57Mobihoc '03 Radio Channel Modelling Tutorial What matters to you You need to be able to calculate the probability (or frequency) with which a packet will be received successfully on a wireless link This will depend on Link signal power Interference levels Dispersion in the channel Link power can be controlled in two ways Changing the transmitted power Changing antenna gains Adopting diversity reception techniques

58 58Mobihoc '03 Radio Channel Modelling Tutorial What matters to you Interference can be controlled also in two ways Changing the transmitted power at more than one node Having an adaptive antenna radiation pattern to introduce a null in the direction(s) of the dominant interferer(s) Dispersion can be mitigated through the use of Equalisers and/or diversity schemes Adaptive antennas (filtering out multipath components) BUT, beware of Unwanted complexity/expense in receiver technology Effects on battery power Exceeding maximum permissible EIRP Size of antenna system becoming unwieldy Difficulties in optimising more than one simultaneous link

59 59Mobihoc '03 Radio Channel Modelling Tutorial Area mean models Most published models of this form are linear regression models established through measurements in macro- cellular scenarios (Hata-Okumura and Walfisch-Bertoni models and their variants) and are not applicable to MANET research The majority of models applicable to short-range propagation in open areas are based on the two-ray model (usually modified to take into account terrain undulations Short-range propagation in built-up areas is often done using deterministic techniques such as ray-tracing (more on this later)

60 60Mobihoc '03 Radio Channel Modelling Tutorial Area mean models – outdoor Range dependence for microcells is strongly influenced by street geometry Line-of-sight paths (LOS) Non-line-of-sight paths (NLOS) (Lateral vs. transverse) Tx LOS Staircase Zig-zag Transverse Lateral

61 61Mobihoc '03 Radio Channel Modelling Tutorial Area mean models – outdoor Based on measurements by AirTouch Communication in San Francisco at 900MHz and 1900MHz for h t = 3.2, 8.7 and 13.4m and h r = 1.6m Two slope models with a breakpoint distance as predicted by the two ray model for LOS case for d < d b and where the distances are measured in km and the frequency in GHz for d > d b. Note that there is a 3dB discontinuity at d = d b

62 62Mobihoc '03 Radio Channel Modelling Tutorial Area mean models – outdoor For the staircase and transverse NLOS cases in suburban environments only where and H B is the mean building height For the lateral NLOS case in suburban environments only

63 63Mobihoc '03 Radio Channel Modelling Tutorial Area mean models – outdoor For the staircase and transverse NLOS cases in high- rise urban environments only For the lateral NLOS case in high-rise urban environments only The standard deviation of the models from the actual data was found to be approximately 6–12dB

64 64Mobihoc '03 Radio Channel Modelling Tutorial Area mean models – indoor COST231 (1999) models Model 1: Model 2: L 0 is the free-space loss, L c is a constant, k wi is the number of penetrated walls of type i (type 1 is a light plasterboard/aerated concrete wall, type 2 is a heavy thick wall made of brick or concrete), L wi is the associated transmission loss, k f is the number of penetrated adjacent floors and L f is the associated floor transmission loss Model 3:

65 65Mobihoc '03 Radio Channel Modelling Tutorial Area mean models – indoor L 1 (dB)NL w1 (dB)L w2 (dB)L f (dB)b  (dBm -1 ) Dense One floor Two floors Three floors Open Large Corridor

66 66Mobihoc '03 Radio Channel Modelling Tutorial Area mean models – indoor The models were developed at 1800MHz, but subsequent measurements at 0.85, 1.9, 2.4, 4.0, 4.75, 5.8 and 11.5GHz have shown no significant frequency dependence In corridors path loss exponents less than 2 (waveguiding effects) have been reported, but were only significant in very specific cases The standard deviation of the models from the actual data was found to be approximately 10dB

67 67Mobihoc '03 Radio Channel Modelling Tutorial Area mean models The ITU, headquartered in Geneva, Switzerland is an international organization within the United Nations System where governments and the private sector coordinate global telecom networks and services ITU-R (International Telecommunications Union – Radiocommunication sector recommendations are internationally agreed models you can use and are based on numerous measurementshttp://www.itu.int You can download up to three recommendations for free from the Electronic Bookshop ITU-R P : Propagation data and prediction methods for the planning of short-range outdoor radiocommunication systems and radio local area networks in the frequency range 300 MHz to 100 GHz ITU-R P : Propagation data and prediction methods for the planning of indoor radiocommunication systems and radio local area networks in the frequency range 900 MHz to 100 GHz

68 68Mobihoc '03 Radio Channel Modelling Tutorial Local mean model The departure of the local mean power from the area mean prediction, or equivalently the deviation of the area mean model is described by a log-normal distribution In the same manner that the theorem of large numbers states that the probability density function of the sum of many random processes obeys a normal distribution, the product of a large number of random processes obeys a log-normal distribution Here the product characterises the many cascaded interactions of electromagnetic waves in reaching the receiver The theoretical basis for this model is questionable over short-ranges, but it is the best available that fits observations

69 69Mobihoc '03 Radio Channel Modelling Tutorial Local mean model Working in logarithmic units (decibels, dB), the total path loss is given by where X  is a random variable obeying a lognormal distribution with standard deviation  (again measured in dB ) If x is measured in linear units (e.g. Volts) where m x is the mean value of the signal given by the area mean model

70 70Mobihoc '03 Radio Channel Modelling Tutorial Local mean model Cumulative probability density function This can be used to calculate the probability that the signal- to-noise ratio will never be lower than a desired value and thus the bit-error-rate and packet/frame error rate will be always smaller than a given value which can be easily calculated. This is called an outage calculation Note that all this is range-dependent

71 71Mobihoc '03 Radio Channel Modelling Tutorial Local mean model In simulations, we need to generate random numbers X  from the p.d.f. and then simulate the corruption of a radio packet probabilistically from the BER model of the given communication system The variation of the log-normal fading with distance is not contained in the statistical model. We know from measurements that slow or shadow fades extend over distances of 5–300m, with the lower ranges being more appropriate to short ranges and indoor environments In MANET simulations, the slow fading needs to be computer every 5–20m with intermediate values interpolated smoothly to ensure that simulations are meaningful

72 72Mobihoc '03 Radio Channel Modelling Tutorial Fast fading models Constructive and destructive interference In spatial domain In frequency domain In time domain (scatterers, tx and rx in relative motion) Azimuth dependent Doppler shifts Each multipath component travels corresponds to a different path length. Plot of power carried by each component against delay is called the power delay profile (PDP )of the channel. 2 nd central moment of PDP is called the delay spread   P Im Re

73 73Mobihoc '03 Radio Channel Modelling Tutorial Fast fading models The relation of the radio system channel bandwidth B ch to the delay spread  is very important Narrowband channel (flat fading, negligible inter-symbol interference (ISI), diversity antennas useful) Wideband channel (frequency selective fading, need equalisation (RAKE receiver) or spread spectrum techniques (W-CDMA, OFDM, etc.) to avoid/limit ISI) Fast fading refers to very rapid variations in signal strength ( 20 to in excess of 50dB in magnitude) typically in an analogue narrowband channel Dominant LOS component  Rician fading NLOS components of similar magnitude  Rayleigh fading

74 74Mobihoc '03 Radio Channel Modelling Tutorial Fast fading models Working in logarithmic units (decibels, dB), the total path loss is given by where Y is random variable which describes the fast fading and it obeys the distribution for Rayleigh fading, where the mean value of Y is

75 75Mobihoc '03 Radio Channel Modelling Tutorial Fast fading models For Rician fading where y s is the amplitude of the dominant (LOS) component with power. The ratio is called the Rician K-factor. The mean value of Y is The Rician K-factor can vary considerably across small areas in indoor environments

76 76Mobihoc '03 Radio Channel Modelling Tutorial Fast fading models Similar but much more complicated outage calculations E.g. Rayleigh and log-normal distributions combine to give a Suzuki distribution Simulations with random number realisations for X  and Y are run as before For many nodes the same methodology can be used to calculate interferer powers to compute the total S/(N+I) ratio The spatial distribution of fades is such that the “length” of a fade depends on the number of dB below the local mean signal we are concerned with (see Parsons [5], pp ) Fade depth (dB) Average fade length ( )

77 77Mobihoc '03 Radio Channel Modelling Tutorial Delay spread models To determine whether simple propagation models are suitable for predicting the performance of digital communications systems, we need to have a simple channel dispersion model The simplest possible model for the PDP is that of an exponential decay function where S is (approximately) the r.m.s. delay spread For an indoor channel measurements at 1.9 and 5.2GHz have established that where S is measured in ns, F s is the floor space measured in m 2 (assuming omnidirectional antennas are used)

78 78Mobihoc '03 Radio Channel Modelling Tutorial Delay spread models For outdoor microcellular and picocellular channels from 2.5 to 15.75GHz and ranges m, the r.m.s. delay spread follows a normal distribution whose mean and standard deviation are range-dependent Measurement conditions aSaS SS Area f(GHz)h t (m)h r (m)CaCa aa CC  Urban Residential

79 79Mobihoc '03 Radio Channel Modelling Tutorial Angular spread models In open areas (rural environments), the angular spread S  of the received signal is fairly narrow ( S  ~ 10° or less) In urban areas in LOS situations, S   30° ( ±11° ) In urban areas in NLOS situations, S   41° ( ±18° ) In indoor environments angular spreads tend to vary significantly, with observations reported in the literature varying from S   15° to in excess of 180° All the above results are based on measurements in the band 5-8GHz

80 80Mobihoc '03 Radio Channel Modelling Tutorial Diversity Combining signals from more than one receiving channel can result in an overall improvement to the signal to noise ratio, provided these signals are appropriately combined. This is expressed as a diversity gain To have significant diversity gain, the branches (channels) of the diversity system must have a low statistical correlation and similar mean received powers Space diversity (more than one antenna location) – spatial fade statistics needed to determine minimum antenna separation Polarisation diversity (detecting more than one polarisation) Frequency diversity (transmitting on more than one frequency simultaneously) – coherence bandwidth needed to determine minimum frequency spacing Time diversity (transmitting the same message more than once) RAKE reception (exploiting temporal resolution)

81 81Mobihoc '03 Radio Channel Modelling Tutorial MIMO channels Diversity antennas at both transmitter (M antennas/ports) and receiver (N antennas/ports), but their spacing is smaller than traditional diversity antennas Can exploit any degree of de-correlation between transmitting-receiving antenna permutations due to the statistical independence of many scattering processes in the environment Use coding techniques together with singular value decomposition (SVD) to find the subspace of the MxN channels which correspond to statistically independent channels which can be exploited simultaneously

82 82Mobihoc '03 Radio Channel Modelling Tutorial How to use models in simulation To calculate the probability of packet loss Generate random numbers for the slow fading, X , and, if appropriate for the communication system in question (depends on wideband/narrowband system for the channel and/or use of diversity reception techniques), for the fast fading, Y, from the appropriate distributions Calculate the received signal in the radio link using the path loss model Repeat the calculation above for all k interfering transmitters

83 83Mobihoc '03 Radio Channel Modelling Tutorial How to use models in simulation Calculate the noise at the receiver ( B is the channel bandwidth) Combine noise and interference powers linearly Calculate the signal-to-noise-plus-interference ratio Look up what bit-error-rate this corresponds to for your system

84 84Mobihoc '03 Radio Channel Modelling Tutorial How to use models in simulation If there are n bits in each frame/packet and a maximum of m errors can be corrected for by the FEC coding, the probability that the packet has been corrupted is where p l is the probability of exactly l bits being received erroneously in the packet, given by A random decision based on P(pkt_loss) can then be made in a MANET simulation To perform more conventional outage calculations, it is simpler to use a simulator (e.g. SEAMCAT – freely available from is but one example)http://www.ero.dk/

85 85Mobihoc '03 Radio Channel Modelling Tutorial Deterministic models For more detailed simulations (which include specific instances of PDP, angles of arrival, etc.), you need to use a deterministic radio propagation prediction technique, together with an input environment database Important in trying to assess the operation and benefits of directional and/or adaptive antennas, as radiation patterns can be incorporated in the simulation explicitly Technique of choice for short-range propagation in the UHF/SHF bands ( 300MHz – 30GHz ) is ray tracing

86 86Mobihoc '03 Radio Channel Modelling Tutorial Ray tracing This is a high-frequency technique based on geometrical optics Site specific UHF and SHF propagation prediction Requires a building database Models reflected, diffracted and transmitted fields along all possible ray paths connecting the transmitter and receiver 3D predictions Coherent field coverage vs. r.m.s. power coverage. Angle of arrival, power delay profile, polarisation prediction and phase information capabilities

87 87Mobihoc '03 Radio Channel Modelling Tutorial Ray tracing (cont.) Ray tracing – geometrical calculation Image method Point and shoot method Visibility (connectivity) matrix to accelerate computation Image method slowest, but guaranteed to trace all rays (mixed reflected-diffracted paths the slowest) Point and shoot method fastest, but can miss rays (reception sphere; secondary sources) Truncation of number of interactions per ray

88 88Mobihoc '03 Radio Channel Modelling Tutorial Ray tracing (cont.)

89 89Mobihoc '03 Radio Channel Modelling Tutorial Ray tracing (cont.) Field calculation Specular reflection – GO (reflection coefficients in [7]) Diffuse scatter – non-GO process (difficult to model) Diffraction – GTD/UTD (diffraction coefficients in [7]) Transmission – GO, but interior structure of buildings unknown (transmission coefficients in [7]) Research challenges Efficient ray-tracing engines to deal with large enough problems Better physical models for propagation mechanisms

90 90Mobihoc '03 Radio Channel Modelling Tutorial Ray tracing (cont.)

91 91Mobihoc '03 Radio Channel Modelling Tutorial Impact on protocol stack MAC protocols can in principle have knowledge of the physical link states in their transmission contention zone Power control ‘games’ need path loss table information (spatially resolved version more desirable) – can potentially simultaneously optimise power consumption and interference problems Medium access control ‘games’ should be based on predictions of power control ‘games’ (i.e. base MAC protocols on predictions of physical channel state)

92 92Mobihoc '03 Radio Channel Modelling Tutorial Impact on protocol stack Transmission contention zone: Power control: determines size Don’t make this bigger than you need to Increases frequency reuse ratio Increases SNIR, decreases BER and probability of packet loss Improves battery life Can make adaptive modulation possible Impact on PHY and MAC layers (e.g. directional MAC protocol – DMAC) Usually requires a channel to be reserved as a control channel

93 93Mobihoc '03 Radio Channel Modelling Tutorial Impact on protocol stack Transmission contention zone: Adaptive antennas: determine shape Impact on MAC and Network (routing) layers Introduces complexity Improve EIRP for same transmission power Improve effective receiving aperture area Improve SNIR – can steer nulls towards interferers and main radiation pattern lobe towards wanted node (not always). Antenna size is an issue But … eavesdropping is best done omni-directionally

94 94Mobihoc '03 Radio Channel Modelling Tutorial Impact on protocol stack Directional antennas, power control, equalisation (e.g. rake reception) and adaptive modulation are closely coupled systems and their individual optimal configurations are not the same as their total optimal configuration – complex interactions; not always well understood The Physical, Data Link (including MAC) and Network layers all need to take into account and control the combined operation of all the above Protocols need path loss, angle of arrival and channel dispersion information to exercise control (determine transmission powers and modulation schemes) There is a need for standardised interface between hardware and protocol stack. Layer separation does not make sense in a highly adaptive MANETs.

95 95Mobihoc '03 Radio Channel Modelling Tutorial References [1] J.R. Pierce and A.M. Noll, Signals: The Science of Telecommunications, Scientific American Library, 1990 [2] R.E. Collin, Antennas and Radiowave Propagation, McGraw-Hill, 1985 [3] J.D. Kraus and R.J. Marhefka, Antennas For All Applications, 3 rd Edition, McGraw-Hill, 2003 [4] R. Vaughan and J Bach Andersen, Channels, Propagation and Antennas for Mobile Communications, The Institution of Electrical Engineers, 2003 [5] H.L. Bertoni, Radio Propagation for Modern Wireless Systems, Prentice Hall, 2000 [6] J.D. Parsons, The Mobile Radio Propagation Channel, Pentech,1992 [7] D.A. McNamara, C.W.I. Pistorius and J.A.G. Malherbe, Introduction to the Uniform Geometrical Theory of Diffraction, Artech House, 1990 [8] W.C. Jakes (Ed.), Microwave Mobile Communications, IEEE Press, 1974 [9] T.S. Rappaport, Wireless Communications: Principles & Practice, Prentice Hall, 1996 [10] S.R. Saunders, Antennas and Propagation for Wireless Communication Systems, Wiley, 1999 [11] L.W. Barclay (Ed.), Propagation of Radiowaves, 2 nd Ed., IEE Press, 2003

96 96Mobihoc '03 Radio Channel Modelling Tutorial Illustration credits Figures on pp.3,7 © Scientific American Library [J.R. Pierce and A.M. Noll, Signals: The Science of Telecommunications, Scientific American Library, 1990] Figures on pp.9-14 © Scientific American Library [J.A. Wheeler, A Journey into Gravity and Spacetime, Scientific American Library, 1990] Figure on p.4, © Addison-Wesley [E. Hecht and A. Zajac, Optics, Addison-Wesley, 1974] Figures on p.5, © McGraw-Hill [R.E. Collin, Antennas and Radiowave Propagation, McGraw-Hill, 1985] Figures on p.15,17,18,23-26 © McGraw-Hill [J.D. Kraus and R.J. Marhefka, Antennas For All Applications, 3 rd Edition, McGraw-Hill, 2003] Figures on p.33,40 © IEE [R. Vaughan and J Bach Andersen, Channels, Propagation and Antennas for Mobile Communications, The Institution of Electrical Engineers, 2003] Figures on pp.88, 90 © Winprop [Winprop tool documentation, stuttgart.de/Winprop/winprop_e.html]


Download ppt "Radiowave Channel Modelling for Radio Networks Costas Constantinou Electronic, Electrical & Computer Engineering The University of Birmingham, UK"

Similar presentations


Ads by Google