Fundamentals and technical challenges of wireless communications

Development of Complex Curricula for Molecular Bionics and Infobionics Programs within a consortial* framework**

Consortium leader

PETER PAZMANY CATHOLIC UNIVERSITY

Consortium members

SEMMELWEIS UNIVERSITY, DIALOG CAMPUS PUBLISHER

The Project has been realised with the support of the European Union and has been co-financed by the European Social Fund ***

Ad hoc Sensor Networks

Fundamentals and technical challenges of wireless communications

Érzékelő mobilhálózatok

A vezeték nélküli kommunikáció alapjai és technológiai kihívásai

Dr. Oláh András

Lecture 1 review

• Course Information

• The Wireless Vision

• Spectrum Regulation

• Standards

• Technical Challenges

• Current Wireless Systems

• Emerging Wireless Systems

Outline

• The major technical challenges of wireless communications

• Noise- and interference-limited systems

• Components of the noise

• Link budget

• The cellular principle

• Multipath propagation in radio channel: the signal can get from Transmitter (TX) to the Receiver (RX) via a number of different propagation paths. [→ see Chapter 3]

– Fading (statistics)

– Channel impulse response (filter model) – Intersymbol Interference (ISI)

• Spectrum limitations: regulated and unregulated spectrum for wireless communication services. [→ see Chapter 1]

– Spectral efficiency (SE) [→ see Chapter 4]

– Spectrum reuse (e.g. cellular principle) [→ see Chapter 2]

• Limited energy: the user’s device is powered by one-way or rechargable

Consequences of fading:

– Error probability is dominated by the probabilty of being in a fading dip.

– Deterministic modeling of channel at each point is very difficult.

– Statistical modeling of system behavior.

Multipath propagation

ISI !!

QoS (e.g.: BER)

networks

• Scalability:the vision of ubiquitous computing where networks can be of any size. Route acqusition, service location and encryption key exchanges will require considerable overhead as the network size growing.

• Quality of Services: QoS aware solutions are being developed to meet the requirements.

• Security: ad hoc networks are particularly prone to malicious behavior.

• Energy conservation: energy conservation is currenctly being addressed in every layer of the protocol stack.

• Node cooperation: the node relays any other node’s data to receive the corresponding service from others. (Problems: priority, billing).

Noise- and interference-limited systems

• Noise-limited systems: cellular systems (e.g. WLAN, cellular mobile) operate in this mode if the user density is low and/or if no other BS is in the vicinity.

(→link budget).

• Interference-limited systems: i) the unregulated use of spectrum leads to interference; ii) in regulated spectrum the network operator can determine the location of BSs (→cellular principle).

Motivation of link budget

• QoS_IN: Signal-to-Noise Ratio (SNR=P_RX/P_N) or Signal-to-Noise-Interference Ratio ((SNIR=P_RX/(P_N+P_I) or Signal-to-Interference Ratio ((SIR=P_RX/P_I)

• QoS_OUT: the detector characteristic is different for different system design choices (e.g.: Audio SNR, Bit-Error Rate, Packet-Error Rate, etc.)

Link budget basics

• A link budget is the accounting of all of the gains (G) and losses (L) in a wireless link from the transmitter (TX), through the wireless medium to the receiver (RX).

• The link budget equation is expressed in decibel:

P_RX (dBm) = P_TX (dBm) + G (dB) − L(dB)

• Link budget can be used to compute the required transmit power (P_TX), possible range of a communication link (d) or required receiver sensitivity (Θ).

Link budget basics (cont’)

Required SNR at receiver output

(i.e. SNR ≥ Θ)

About the Decibel

• We can convert a measure x into dB scale:

x^[dB]=10 lg( x/ x_ref), where x_ref is reference value.

• The power measured in Watt [W] or milliWatt [mW], and dB notations are dB and dBm, respectively.

P^[dB]=10 lg( P/ 1W ), P^[dBm]=10 lg( P/ 1mW ), and the relation: P^[dBm]= P^[dB] +30 dB.

• The amplification (and attenuation) is already dimensionless and can be converted directly:

G^[dB]=10 lg( G ), (L^[dB]=10 lg( L ))

• Some examples:

– GSM RX sensitivity: 6.3x10^-14W = -132 dB or -102 dBm – Bluetooth P_TX: 10mW = -20dB or 10 dBm

– GSM BS P_TX: 40W = 16 dB or 46 dBm

– Nuclear powerplant: 1200 MW = 91 dB or 121 dBm

Components of the noise

• Thermal noise: is electronic noise generated by the thermal agitation of the charge carriers (usually the electrons) inside an electrical conductor at equilibrium, which happens regardless of any applied voltage. The power spectral density of thermal noise depends on the environment temperature T_e that antenna „sees”. (Note: white power spectral density, gaussian p.d.f.)

• Man-made noise: we can distinguish two types

– Spurious emmision: electric devices have it (e.g car ignitions), it is not necessarily Gaussian-distributed, but in theoretical design it assumed gaussianity anyway.

– Coexistence wireless system: wireless communication systems operate at same time in unlicensed bands (eg.: 2.45-GHz ISM band).

• Receiver noise: the amplifiers and mixers in the RX are noisy, and thus increase the total noise power. (Note: noise figure F is a measure of this effect)

Thermal noise

• Noisy power spectral density:

N₀ = k_B T_e

where k_B=1.38x10^-23 J/K is Boltmann’s constant. It is usually assumed that the environmental temperature is isotropically 300K, therefrom N₀ = -174 dBm/Hz.

• The noise power:

P_N = N₀ B

where B is the bandwidth in Hz, and using logarithmic units:

P_N^[dBm] = -174 + 10lg( B )

Man-made noise

Equivalent noise source

• To simplify the model, we can replace all noise source with a single equivalent noise source.

• How do we determine Noise from noise sources?

Equivalent noise source (cont’)

• The power spectral density of noise is given in

– Directly: N_s [W/Hz]

– Noise Temperature: T_s [K]

– Noise factor/noise figure: F_s [-]

The relations:

N_s= k T_s = k F_s T₀ , where T₀= 290 K is the room temperature.

• An example: noise temperature of antenna T_a=1600K, the power spectral density of noise is N_a= k T_a = -196.6 [dBW/Hz], and the noise figure is F = 1600/290 = 5.52 = 7.42 dB

Redefinition of the noise figure

• Noise figure: ratio of SNR on the input (SNR_IN) versus on the output (SNR_OUT):

F = SNR_IN/ SNR_OUT = (P_S^(IN)/ P_N^(IN))/(P_S^(OUT)/ P_N^(OUT))

where P_S^(IN) is the signal power and P_N^(IN) is the noise power on the input.

However, P_S^(OUT)= G P_S^(IN), the noise power on the output is expressed as:

P_N^(OUT) =F G P_N^(IN).

• Equivelant noise temperature is (F-1) T₀

The total noise figure

• Mathematically, the total noise figure F_tot of a cascade of components is:

F_tot= F₁ + (F₂-1)/G₁ + (F₃-1)/(G₁ G₂) + …, since

F = P_N^(OUT) / ( G P_N^(IN)) = P_N^(OUT) / ( G k T₀), where G = G₁G₂ , thus

F = [ G₁ G₂ k T₀ + (F₁-1) G₁ G₂ k T₀ + (F₂-1) G₂ k T₀ ] / (G₁ G₂ k T₀).

• In a well designed receive chain, only the noise factor of the first amplifier should be significant.

• Note: (Pierce’s rule) a passive attenuation L , in the case a feeder, has a noise figure equal to its attenuation, i.e:

N_f= k (F_f-1)T₀ = k (L_f-1)T₀

F_tot= F₁ + (F₂-1)/G₁+ (F₃-1)/(G₁G₂) = 1.4 + (2.5-1)/1 + (1.25-1)/10=2.925=4.7dB

Way towards the link budget: antenna

Note: This a theoretical antenna that cannot be built.

The isotropic antenna radiates

equally in all directions The λ/2 dipole antenna

• The amount of increase in the input power to the isotropic antenna, to obtain the same macimum radiation is called antenna gain (in the case of λ/2 dipole antenna it is 2.15 dB).

• Effective Isotropic Radiated Power (EIRP): EIRP^[dB] = P_TX^[dB] + G_TX^[dB]

• Path loss (L_p0): the attenuation due to propagation effects between TX and RX. (→see Chapter 3)

• Breakpoint model:

( ) ( )

TX TX RX 2 BREAK

RX

RX BREAK BREAK

BREAK

4 if

if

P G G d d

d

P d

P d d d d

d

γ

λ π

−

  

  ≤

  

= 

 

   ≥

  



γ tipically lies between 3.5 and 4.5

Way towards the link budget: fading margin

• Wireless systems suffer from temporal and spatial variations of the transmission channel (fading). (→ see Chapter 3)

• We have to add a fading margin which makes sure that the minimum P_RX is exceeded in at least, e.g., 90% of all cases.

Consider the downlink of a GSM system. The carrier frequency is f=950 MHz, the receiver sensitivity is Θ= -102dBm. The output power of the rceiver amplifier is P_TX=30 W. The antenna gain of the transmitter is G_TX=10dB, the losses in feedline and connectors are L_f=5 dB. The fading margin is M=12dB, the breakpoint is at a distance d_BREAK=100m. What is the cell radius R?

Solution: on the blackboard.(for check: R=8.8km)

Interference-limited systems

Interference-limited systems

• In a cellular system, the coverage area is divided into many small areas called „cells”. In each of these cells, there is one BS that coverage for this cell area.

• The distance between two cells that can use the same frequency channels is called reuse distance (D/R).

• The cluster of cells is defined as cells that all use different frequencies (i.e. no co-channel interference within such a cluster).

• The number of cells in a cluster is called the cluster size (N_cluster), which determines the capacity of the cellular system.

• What shapes do cells normally take on?

• (We calculate the median SIR, the fading makes this situation worse 50% of the time, so we need fading margin M to achive the reguirements on outage probability.)

• Simplified path loss model: circular cell

• Path loss + shadowing: amoeba cell

• Tessalating shape: cells can be laid next to each other with no overlap to cover the entire georgaphical region without any gaps.

– Rectangles (or squares) – Triangles

– Diamonds: for smaller cells, with BSs placed closer to the ground

Reuse Distance (D/R)

(i = 2, j = 1)

( ) (

)

2 2

3 cos(60 ) sin(60 )

3

D R i R j R j

R i ij j

= ⋅ + ⋅ + ⋅ =

= + +

(

)

3

D R = i + +ij j

( )

3 4 2 1 4.58 D R = + + =

Cell planning with hexagonal cells (cont’)

• The number of cells per cluster:

• The reuse distance:

N_cluste

r

3 4 7 9 12 13 16 19 21 25 27

D/R 3 3.5 4.6 5.2 6 6.2 6.9 7.5 7.9 8.7 9 TDMA systems

(GSM)

Analog systems

( )

2 2 2

2 2

2 2

cluster

cluster 2 2

cell

3 2 1 1 3

3 3

3 3 2

R i j ij

A D D

N i j ij

A R R R

 + + 

 

= = =   =   = + +

cluster

3 D R = N

Find the reuse distance D/R for the channel reuse for the diamond shaped cells

.

Where do we get the neccesary D/R ?

• We compute the SIR for cellular systems using orthogonal multiple access techniques (TDMA, FDMA)

• Under the simplified model, the received signal power:

P_RX=P_TX d^-γ

• The average intercell interference power is a function of the number of out-of-cell interferers (K).

– For simplicity we neglect interference from outside the first ring of M interfering cells. (K=6 for hexagonal, and K=4 for diamond cell shapes)

• In general the average SIR for uplink and downlink may be roughly same.

With K=6 co-channel cells interfering, at distances d₁, d₂, …,d₆ from the user the received interference is

Knowing that d₀≤R and d₁,d₂,…,d₆>D-R, we get

0 1

SIR P^RX P d^{TX −γ} P R^{TX −γ}  R ^−γ

= = > =  

6

TX 1

I i

i

P P d^−γ

=

=

∑

Where do we get the neccesary D/R ? (cont’)

Assume that we have a transmission system, where SIR_MIN is required to operate properly. Further due to the fading and requirements on outage probability we need a fading margin M.

SIR> 1 6

R D R

γ

 −

 

−

 

We can solve it for a save D/R by

requiring

MIN

1 SIR

6

R M

D R

γ

 −

≥ ⋅

 

−

 

We get

(

)

D M

R

≥ ⋅ γ +

The user capacity C is defined as the total number of active users per cell that the system can support while meeting a common BER constrain. For orthogonal multiple access:

C = N_cell,

where N_cell is the number of channels assigned to any given cell.

The total number of orthogonal channels of bandwidth B_s that can be created from a total system bandwidth of B is B / B_s. The reuse factor satisfies N = (B / B_s)/ N_cell, this implies:

C = (B / B_s)/ N

An example for cell planning (1)

Compute the SIR for a cellular system with diamond shaped cells, where the cell radius R=10m and the reuse distance D=60m, assuming the path loss exponent with the cell is γ₀=2 whereas the intercell interference has path loss exponent γ_I=4.

Compare with the SIR for γ₀=γ_I=4, and for γ₀=γ_I=2. Explain the relative ordering of SIR for each case.

Consider a TDMA cellular system with hexagon shaped cells, and path loss exponent γ=2 for all signal propagation in the system. Find the minimum reuse factor N needed for a target SIR of 10dB, and the corresponding user capacity C assuming a total system bandwidth B=20MHz and a required signal bandwidth B_s=100kHz.

Summary

• There are some fundamental challenges in the wireless communications, such as multipath propagation, mobility, spectrum limitation, limited energy.

• Competing and cooperating wireless systems share the spectrum.

• Channel reuse is a key element of cellular system design.

• Good cellular system designs are interference-limited, meaning that the interference power is much larger than the noise.

• Next lecture: Wireless channel characterization and models