Wireless Sensor Networks Physical Layer Based on “Protocols and Architectures for Wireless Sensor Networks”, Holger Karl, Mario Čagalj FESB, 9/4/2014.

2 Introduction: OSI model o“The Open Systems Interconnection model (OSI) is a conceptual model that characterizes and standardizes the internal functions of a communication system by partitioning it into abstraction layers.” - Wikipedia

3 Goal of this lecture oGet an understanding of wireless communication >Wireless channel as abstraction of these properties >Focus is on radio communication oImpact of different factors on communication >Frequency band, transmission power, modulation scheme, etc. >Transciever design oUnderstanding of energy consumption for radio communication

VLF = Very Low FrequencyUHF = Ultra High Frequency LF = Low Frequency SHF = Super High Frequency MF = Medium Frequency EHF = Extra High Frequency HF = High Frequency UV = Ultraviolet Light VHF = Very High Frequency 1 Mm 300 Hz 10 km 30 kHz 100 m 3 MHz 1 m 300 MHz 10 mm 30 GHz 100  m 3 THz 1  m 300 THz visible light VLFLFMFHF VHFUHFSHFEHFinfraredUV optical transmission coax cable twisted pair Radio spectrum Which part of the electromagnetic spectrum is used for communication Not all frequencies are equally suitable for all tasks – e.g., wall penetration, different atmospheric attenuation 4

Frequency allocation 5 Some frequencies are allocated to specific uses Cellular phones, analog television/radio broadcasting, DVB-T, radar, emergency services, radio astronomy, … Particularly interesting: ISM (Industrial, Scientific, Medical) frequency bands License-free operation Overcrowding leads to cognitive radio systems Some typical ISM bands FrequencyComment 13,553-13,567 MHzRFID smart cards 26,957 – 27,283 MHz 40,66 – 40,70 MHz 433,05 – 434,79 MHzEurope 902 – 928 MHzAmericas 2,4 – 2,5 GHzWLAN/WPAN microwave owen 5,725 – 5,875 GHzWLAN 24 – 24,25 GHz

GSM/UMTS (800, 1900MHz,...) (WiFi) (LAN) Wireless Fidelity 2.4 GHz, 54Mbps, 100mW-1W, 30m range (WiMAX) GHz, < 10km coverage 2-11GHz, < 20km coverage 75Mbps (theoretical), 20km, 5Mbps (typically, 5km) UWB GHz, short-range Gbps communication lower speed, longer range, localization (<2km outdoor) (Zigbee) (WPAN) (Sensor networks) 868 MHz in Europe, 915 MHz in the USA and 2.4 GHz 250kbps, 1mW, ~100m range 4 MHz 8-bit processors RFIDs Short range identification tags 1-12 m (UHF EU, MHz) Frequency allocation 6

Wireless Communication

Produced by a resonating circuit (e.g., LC) Transmitted through an antenna Basics: transmitter can send a radio wave, receiver can detect whether such a wave is present and also its parameters Parameters of a wave (e.g, a sine function) Parameters: amplitude A(t), frequency f(t), phase  (t) Manipulating these three parameters allows the sender to express data; receiver reconstructs data from the received signal Transmiting data using radio waves 8

Any periodic function/signal s(t) (with period T, i.e. fundamental frequency f 0 =1/T) can be viewed as a linear composition of sine waves where a k and b k are Fourier coefficients for k th harmonic given by and Fourier coefficients are referred to as the frequency-domain representation In general, we use Fourier transform for both periodic and non-periodic signals Signal representation – Fourier series 9

Approximating an odd square wave with A=1 and T=1 The Fourier coefficients are Leading to the following Fourier series representation of the square wave Signal representation – example 10

Signal representation – example 11

Signal spectrum refers to the plot of the magnitudes and phases of different frequency components of a given signal Example, amplitude spectrum (one-sided) of our square wave Observe, the spectrum is discrete (periodic signal) The spectrum is very wide, actually infinite (transitions in zero time) The strongest component (first harmonic) accounts for ~81% of the signal power Signal spectrum 12

Power spectrum This plot tells us how the power is divided up between different frequencies Can be calculated using the Fourier coefficients a k and b k (Parseval theorem) E.g., square wave (power of each harmonic normalized to the strongest harmonic) Signal spectrum 13

Power spectrum This plot tells us how the power is divided up between different frequencies Can be calculated using the Fourier coefficients a k and b k (Parseval theorem) E.g., square wave (power of each harmonic normalized to the strongest harmonic) Signal spectrum 14

Baseband bandwidth (B) is equal to the highest frequency of a signal or system, or an upper bound on such frequencies (due to a filter) For example, our square wave has infinite bandwidth In practice however, the signals are bandlimited to a finite bandwidth Baseband bandwidth 15 Low-pass filter B

Passband bandwidth is the difference between the upper and lower cutoff frequencies of a communication channel, or a signal spectrum Example, a filtered baseband signal (rectangular pulses with f 0 =600Hz) multiplied by the sine carrier with frequency f c =1500Hz Data rate (bit/s) supported by a channel is directly proportional to its bandwidth (Shannon–Hartley theorem: ) Passband bandwidth 16 Digital Phase Modulation: A Review of Basic Concepts by James E. Gilley, 2003 null-to-null bandwidth Channel bandwidth due to regulation restrictions

How to manipulate a given signal parameter? Set the parameter to an arbitrary value: analog modulation Choose parameter values from a finite set of legal values: digital keying Modulation? Data to be transmitted is used to select transmission parameters as a function of time These parameters modify a basic sine wave, which serves as a starting point for modulating the signal onto it This basic sine wave has a center frequency f c The resulting signal requires a certain bandwidth to be transmitted (centered around the center frequency) Signal modulation 17

Use data to modify the amplitude of a carrier - Amplitude Shift Keying (ASK) Use data to modify the frequency of a carrier - Frequency Shift Keying (FSK) Use data to modify the phase of a carrier - Phase Shift Keying (PSK) © Tanenbaum, Computer Networks Digital modulation 18

Binary PSK (BPSK): 1 bit per symbol T b bit duration, f c carrier frequency (f c >> 1/ T b ) E b transmitted signal energy per bit (i.e., ) Signal space representation This implies that the in-phase component is given as and therefore and Digital modulation - example 19 binary “0” represented by binary “1” represented by Q (quadrature) I (in-phase) bit 0 bit 1 symbol amplitude

Binary PSK (BPSK) Esentially an amplitude modulation with a square wave Digital modulation - example 20 Digital Phase Modulation: A Review of Basic Concepts by James E. Gilley,

Binary PSK (BPSK) spectrum and pulse shaping Digital modulation - example 21 Digital Phase Modulation: A Review of Basic Concepts by James E. Gilley, 2003

Demodulation of BPSK signal 22 Let r(t) be the received signal in a noise-free scenario The demodulation process Guess signal s 1 (t) (or binary 1) was transmitted if Guess signal s 0 (t) (or binary 0) was transmitted if

The simplest channel model - Additive White Gaussian Noise (AWGN) channel Transmission corrupted by noise 23 databaseband digital modulator passband channel Noise detector digital demodulator bandpass filter

Let r(t) be the received signal in a AWGN scenario The signal s i (t) is corrupted by zero-mean Gaussian noise n(t) with variance N 0 /2 (the noise spectral power density), i.e., r(t) = s i (t) + n(t) The output of the correlation receiver Here n I is a projection of n(t) onto the in-phase axis (also Gaussian and zero mean with with variance N 0 /2) Demodulation of BPSK signal in AWGN 24

Demodulation of BPSK signal in AWGN 25 We assume that bits 0 and 1 are equally likely

Demodulation of BPSK signal in AWGN 26 We assume that bits 0 and 1 are equally likely Finally, the BPSK bit error rate (BER) is given by

27 BER (bit-error rate) Bit error rate (BER) E b /N 0 [dB] bit energy to noise density ratio [SNR/bit]

Quadrature PSK (QPSK): 2 bits per symbol Digital multi-level modulation - example 28 binary “00” represented by binary “01” represented by binary “10” represented by binary “11” represented by

Quadrature PSK (QPSK): 2 bits per symbol Using the identity cos(a+b)=cos(a)cos(b)-sin(a)sin(b), we can rewrite the QPSK symbols as follows where Digital multi-level modulation - example 29 Q (quadrature) I (in-phase)

The same bit error rate as BPSK But more bits per symbol QPSK Q (quadrature) I (in-phase) Quadrature In-phase

Quadrature Amplitude and Phase Modulation (QAM) QAM-4, QAM-16, QAM-64, QAM-256 On one hand, we increase the the data rate On the other hand, denser constellations imply higher bit error rates Q I Q I QAM-4 (QPSK) QAM-16 Q I 0 1 BPSK Digital multi-level modulations 31

Bit rate = bits/second Baud (symbol) rate = symbols/second BPSK, 1 symbol encodes 1 bit QPSK (QAM-4), 1 symbol encodes 2 bits QAM-16, 1 symbol encodes 4 bits Bit rate vs. baud rate 32 Q I Q I QAM-4 (QPSK) QAM-16 Q I 0 1 BPSK

33 A resonating circuit (e.g., LC) connected to an antenna causes an antenna to emit EM waves (modulated signals) A receiving antenna converts the EM waves into electrical current Many types of antennas with different gains (G) Gain: 10-55dB Isotropic Directional Omnidirectional Gain: 2dB Antenna 33

dBm = dB value of Power / 1 mWatt Used to describe signal strength. dBW = dB value of Power / 1 Watt dBi = dB value of antenna gain relative to (0dBi is by default the gain of an the gain of an isotropic antenna isotropic antenna) The ratio of a quantity Q 1 to another comparable quantity Q 0 : Thus: and For example: 1W = +30dBm, 100mW = +20dBm Power and gain quantities 34

Antenna: Gain vs. Beamwidth (1/2) Antenna radiation pattern Reciprocity theorem: the transmitting and receiving patterns of an antenna are identical at a given wavelength Gain is a measure of how much of the input power is concentrated (radiated) in a particular direction (relative to the isotropic antenna with the same input power, e.g., 20dBi means 100 times more) Beamwidth of a pattern is the angular separation between two identical points on opposite side of the pattern maximum 35

Antenna: Gain vs. Beamwidth (2/2) 36 Power density P D = P in /4πR 2, where P in is the input/radiated power (no losses) When the angle in which the radiation is constrained is reduced, the gain goes up in that direction.

Signal propagation Wireless transmission distorts a transmitted signal Results in uncertainty at receiver about which bit sequence originally caused the transmitted signal Abstraction: Wireless channel describes these distortion effects Sources of distortion Attenuation – energy is distributed to larger areas with increasing distance Reflection/refraction – bounce of a surface; enter material Diffraction – start “new wave” from a sharp edge Scattering – multiple reflections at rough surfaces Doppler fading – shift in frequencies (loss of center) 37

Effect of attenuation: received signal strength is a function of the distance R between sender and receiver Captured by Friis equation (a simplified form) G r and G t are antenna gains for the receiver and transmiter λ is the wavelength and α is a path-loss exponent (2 - 5) Attenuation depends on the enviroment, for free-space α=2 Path loss (PL) Attenuation and path loss 38

39 WSN-specific channel models oTypical WSN properties >Small transmission range oSome example measurements > α - path loss exponent >Shadowing variance  2 >Reference path loss at 1 m Average α

Signal Propagation (Strength) 40 © D. Adamy, A First Course on Electronic Warfare XMTR RCVR Path through link Signal Strength (dBm) Transmitted Power Antenna Gain Received Power LINK LOSSES Spreading and Atmospheric Loss To calculate the received signal level (in dBm), add the transmitting antenna gain (in dB), subtract the link losses (in dB), and add the receiving antenna gain (dB) to the transmitter power (in dBm).

Receiver sensitivity The smallest signal (the lowest signal strength) that a receiver can receive and still provide the proper specified output. Example: Transmitter Power (1W) = +30dBm Transmitting Antenna Gain = +10dB Spreading Loss = 100dB Atmospheric Loss = 2dB Receiving Antenna Gain = +3dB Receiver Power (dBm) = +30dBm + 10dB – 100dB – 2dB + 3dB = -59dBm 41 Receiver 1 sensitivity is -62dBm and the receiver 2 is -65dBm: receiver 1 and 2 will receive the signal as if there is still 3dBm and 6dBm of margin on the link, respectively. Recv 2 is 3dB (a factor of two) better than recv 1; recv 2 can hear signals that are half the strength of those heard by recv1.

Wireless signal in a real environments Brighter color = stronger signal Obviously, simple (quadratic) free space attenuation formula is not sufficient to capture these effects 42 © Jochen Schiller, FU Berlin

Generalizing the attenuation formula To take into account stronger attenuation than only caused by distance (e.g., walls, …), use a larger path-loss exponent α > 2 Rewrite in logarithmic form (in dB): Take obstacles into account by a random variation Add a Gaussian random variable with 0 mean and variance  2 to dB representation Equivalent to multiplying with a lognormal random variable in metric units: lognormal fading 43 (R 0 is a referent distance)

Lognormal fading (shadowing) 44

Reflection, diffraction and scattering Reflection: when the surface is large relative to the wavelength of signal May cause phase shift from original / cancel out original or increase it Diffraction: when the signal hits the edge of an impenetrable body that is large relative to the wavelength Enables the reception of the signal even if Non-Line-of-Sight (NLOS) Scattering: obstacle size is in the order of λ Doppler shift Signal propagation In LoS (Line-of-Sight) diffracted and scattered signals not significant compared to the direct signal, but reflected signals can be (multipath effects) In NLoS, diffraction and scattering are primary means of reception 45 Reflection Scattering Diffraction

Reflections and multipath fading Multiple copies of a radio signal take different paths to the receiver The effects of multipath include constructive and destructive interference, and phase shifting of the signal at the receiver Destructive interference causes signal fading 46 Reflection

Signal-to-Noise ratio (SNR) per bit (E b /N 0 ) E b - energy per bit, E s - energy per symbol N 0 - noise power spectral density S (i.e., P rx ) - received signal power N - received noise power B - receiver’s bandwidth Ts - symbol duration R s - baud rate, R b - bit rate, r=R b /R s 47 BER (bit-error rate) E b /N 0 [dB]

48 Summary oWireless radio communication introduces many uncertainties into a communication system oHandling the unavoidable errors will be a major challenge for the communication protocols oDealing with limited bandwidth in an energy-efficient manner is the main challenge