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Chapter Two Mobile Radio Channel Modelling & Mitigations 2.2 Mitigation Techniques for Fading Wireless Channels By : Amare Kassaw
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Chapter Two Mitigation Techniques

Jul 17, 2016

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Amare Kassaw

Mitigation Techniques for Wireless communication channels
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Page 1: Chapter Two Mitigation Techniques

Chapter Two

Mobile Radio Channel Modelling & Mitigations

2.2 Mitigation Techniques for Fading Wireless Channels

By : Amare Kassaw

Page 2: Chapter Two Mitigation Techniques

Goal of the Lecture

� Radio channel is dynamic because of multipath fading and

Doppler spread

� Fading cause the signal at the receiver to fade

� How to improve link performance in hostile mobile environment.

� Apart from better transmitter and receiver technology, mobile � Apart from better transmitter and receiver technology, mobile

communications require signal processing techniques that

improve the link performance

� Mitigation techniques: Channel equalization, diversity, spread

spectrum, interleaving, channel coding,

Page 3: Chapter Two Mitigation Techniques

Lecture Outlines

� Introduction

� Equalization Techniques

� Diversity Techniques

� Coding Techniques

� Summery

Page 4: Chapter Two Mitigation Techniques

Used Acronyms

• DFE : Decision feedback equalizer

• ISI: Inter symbol interference

• FTF: Fast transversal filter

• LMS : least mean square

• ZF: Zero forcing

• RLS: Recursive least square

Page 5: Chapter Two Mitigation Techniques

Introduction

� Mobile radio channel is particularly dynamic due to

� Multipath fading

� Doppler spread

� As a result, the channel has a strong negative impact on BER of

any modulation and transmission techniques

� To improve received signal quality in hostile mobile radio � To improve received signal quality in hostile mobile radio

environment, we need

� Equalization

� Diversity

� Channel coding, ..

� Each can be used independently or in tandem

Page 6: Chapter Two Mitigation Techniques

� Equalization: compensates for inter symbol interference (ISI)

created by multipath in time dispersive(frequency selective )

channels

� Recall pulse shaping filters that also compensate for ISI

� ISI is the result of frequency selective channel

� Equalizers must be adaptive since the channel is generally � Equalizers must be adaptive since the channel is generally

unknown and time varying

� It may be linear equalization or nonlinear equalizer

Page 7: Chapter Two Mitigation Techniques

� Diversity: compensates for fast fading channel impairments

� It is employed to reduce the depth and duration of the fades

experienced by a receiver

� Idea: create independent (or at least highly uncorrelated) signal

“channels” for communication

� Types of diversity:� Types of diversity:

� Spatial diversity, Frequency diversity, Time diversity,

Polarization diversity

� Spatial diversity: usually implemented by using two or more

receiving antennas and widely used

Page 8: Chapter Two Mitigation Techniques

� Channel Coding: improves mobile communication link

performance by adding redundant data bits in the transmitted

message

� It is used by the Rx to detect or correct some (or all) of errors

introduced by the channel in a particular sequence of message bits

(fading or noise).(fading or noise).

� Post detection technique

� Examples: Block codes and convolutional codes

Page 9: Chapter Two Mitigation Techniques

� A general framework of fading effects and their mitigation

techniques.

Page 10: Chapter Two Mitigation Techniques

Equalization Techniques

� ISI is one of the major obstacles to high speed data transmission

over mobile radio channels.

� If BS>BC of the radio channel (frequency selective fading),

modulated pulses are spread in time, causing ISI.

� An equalizer at the front end of a receiver compensates for the � An equalizer at the front end of a receiver compensates for the

average range of expected channel amplitude and delay

characteristics.

� Equalizers must track the time-varying characteristics of the

mobile channel and therefore should be time varying or

adaptive.

Page 11: Chapter Two Mitigation Techniques

�Equalizers are widely used in TDMA systems

�Three factors affect the time span over which an equalizer

converges:

� Equalizer algorithm, equalizer structure, and time rate of change

of multipath radio channel

�Two operating modes for an adaptive equalizer are:�Two operating modes for an adaptive equalizer are:

� Training mode

� Tracking mode

� Adaptive equalizer training mode operation:

� Initially a known fixed length training sequence is sent by the

Tx so that the Rx equalizer may average to a proper setting.

Page 12: Chapter Two Mitigation Techniques

�Training sequence is typically a pseudo-random binary signal or

a fixed prescribed bit pattern.

�The training sequence is designed to permit an equalizer at the

receiver to acquire the proper filter coefficient in the worst

possible channel condition.

� An adaptive filter at the receiver thus uses a recursive algorithm � An adaptive filter at the receiver thus uses a recursive algorithm

to evaluate channel and estimate filter coefficients to

compensate for the channel.

Page 13: Chapter Two Mitigation Techniques

� Adaptive equalizer tracking mode operation:

� When the training sequence is finished the filter coefficients

are near optimal.

� Immediately following the training sequence, user data is sent.

� When the data of the users are received, the adaptive

algorithms of the equalizer tracks the changing channel.algorithms of the equalizer tracks the changing channel.

� As a result, the adaptive equalizer continuously changes the

filter characteristics over time.

Page 14: Chapter Two Mitigation Techniques

Mathematical Frame Work of an Equalizer

Page 15: Chapter Two Mitigation Techniques

� Equalizer is usually implemented at baseband or at IF in a receiver

Page 16: Chapter Two Mitigation Techniques

� The signal received by the equalizer is given by

� If the impulse response of the equalizer is heq(t), the output of

the equalizer is

� With nb(t) equal to zero, to be y(t)=d(t),

Ῡ(t) = d (t) * h (t) * heq (t) + nb (t) * heq (t) = d (t)* g (t) + nb(t) * heq (t)

b

� Hence the main goal of any equalization process is to satisfy this

equation optimally.

Page 17: Chapter Two Mitigation Techniques

� In frequency domain it can be written as

� Thus an equalizer is actually an inverse filter of the channel

� For frequency selective channel: to provide a flat composite

received frequency response and linear phase response;

� The equalizer enhances the frequency components with small

amplitudesamplitudes

� Attenuates the strong frequencies in the received frequency

spectrum

� For time varying channel: the equalizer is designed to track the

channel variations so that the above equation is approximately

satisfied.

Page 18: Chapter Two Mitigation Techniques

Generic Adaptive Equalizer:

� Basic Structure : Transversal filter with N delay elements, N+1

taps, and N+1 tuneable complex weights.

� Weights are updated continuously by an adaptive algorithm

� The adaptive algorithm is controlled by the error signal ek: Fig

Page 19: Chapter Two Mitigation Techniques

� An adaptive equalizer is a time-varying filter that is retuned

constantly

� In the block diagram:

� The subscript k represents discrete time index

� There is a single input yk at any time instant

� It is a transversal filter that has N delay, N+1 taps and N+1

tuneable multiplier called weights

� The value of yk depends upon

� Instantaneous state of radio channel and specific value of

noise

Page 20: Chapter Two Mitigation Techniques

� The second subscript( k) of the weights show that they vary with

time and are updated on a sample by sample basis

� The error signal ek

� Controls the adaptive algorithm

� The error signal is derived by comparing the output of the

equalizer with some signal d which is eitherequalizer with some signal dk which is either

� Replica of transmitted signal xk or

� Which represents a known property of the transmitted signal

� ek is used to minimize a cost function and iteratively update

equalizer weights so as to reduce the cost function

Page 21: Chapter Two Mitigation Techniques

� The Least Mean Square (MSE) algorithm searches for the

optimum or near optimum weight by

� Computing the error between the desired signal and the

output of the equalizer and minimizes it

� It is the most common cost function

Page 22: Chapter Two Mitigation Techniques

Adaptive Equalization Classification

Used to mitigate more

severe fading channel

Page 23: Chapter Two Mitigation Techniques

�Performance measures for an adaptive algorithm

� Rate of convergence

� Mis-adjustment

� Computational complexity and numerical properties

� Factors that dominate the choice of an equalization structure and

its algorithm

�The cost of computing platform

� The power budget

�The radio propagation characteristics

Page 24: Chapter Two Mitigation Techniques

�Algorithms types

� Zero Forcing (ZF)

� Least Mean Squares (LMS)

� Recursive least square (RLS)

Page 25: Chapter Two Mitigation Techniques

�The speed of the mobile unit determines the channel fading rate

and the Doppler spread

�Which is related to the coherent time of the channel directly

� The choice of adaptive algorithm, and its corresponding rate of

convergence, depends on the channel data rate and coherent time

�The number of taps used in the equalizer design depends on the �The number of taps used in the equalizer design depends on the

maximum expected time delay spread of the channel

� The circuit complexity and processing time increases with the

number of taps and delay elements

Page 26: Chapter Two Mitigation Techniques

Diversity Techniques

� Diversity exploits the random nature of radio propagation by

finding independent (or at least highly uncorrelated) signal

“channels or paths” for communication

� Idea: “don’t put all of your eggs in one basket”

� In fading channels, a signal power will fall below any given � In fading channels, a signal power will fall below any given

fade margin at finite probability exists

� Send copies of a signal using multiple channels

�Time, frequency, space, antenna

� If one radio path undergoes a deep fade, another independent

path may have a strong signal

Page 27: Chapter Two Mitigation Techniques

� Assumption: Individual channels experience independent fading

events

� By having more than one path to select from, SNR at a receiver

may be improved (by as much as 20 to 30 dB). Figure

� Advantage: Diversity requires no training overhead

� It provides significant link improvement with little added cost� It provides significant link improvement with little added cost

� Assume that we have M statistically independent channels

• This independence means that one channel’s fading does not

influence, or is not correlated with, another channel’s fading

Page 28: Chapter Two Mitigation Techniques

� Examples: Using antenna (or space) diversity

� Microscopic diversity: Mitigates small-scale fading effects

(deep fading)

� Macroscopic diversity: Reduces the large-scale fading

(selecting different base stations), can also be used for uplink

• Selecting an antenna which is not shadowed• Selecting an antenna which is not shadowed

Page 29: Chapter Two Mitigation Techniques

Types of Diversity

�Time diversity

� Repeatedly transmits information at time spacing that exceed

the coherence time of the channel, e..g., interleaver

� Spreading the data out over time & better for fast fading

channel

Page 30: Chapter Two Mitigation Techniques

�Frequency diversity

� Transmits information on more than one carrier frequency

� Frequencies separated by more than the coherence bandwidth

of the channel will not experience the same fads (eg., FDM)

� Also spread spectrum (spread the signal over a larger frequency

bandwidth) or OFDM (use multiple frequency carriers)bandwidth) or OFDM (use multiple frequency carriers)

� Used to mitigate the frequency selective fading channel

Figure . Frequency diversity

Page 31: Chapter Two Mitigation Techniques

�Space diversity

� Transmit information on spatially uncorrelated channels

� Requires multiple antennas at transmitter and/or receiver

• Example: MIMO, SIMO, MISO, virtual antenna systems

� Multipath fading changes quickly over space

• Hence, the signal amplitude received on the different • Hence, the signal amplitude received on the different

antennas can have a low correlation coefficient

� Space diversity doesn't require additional

• Signals to be transmitted

• Bandwidth for transmission

2/λ

2/λ

Tx Rx

Page 32: Chapter Two Mitigation Techniques

� Reception methods for space diversity includes:

• Selection combining

• Maximal-ratio combining

• Equal gain combining

Selection Combining:

� The receiver branch, having the highest instantaneous SNR, is � The receiver branch, having the highest instantaneous SNR, is

connected to the demodulator

� The antenna signals themselves could be sampled and the best

one sent to a single demodulation

� Simple to implement but does not use all of the possible

branches

Page 33: Chapter Two Mitigation Techniques

� Generalized receiver block diagram for selection diversity

Example: See Handout

Page 34: Chapter Two Mitigation Techniques

Maximum Ratio Combining

� The received signals are weighted with respect to their SNR

and then summed

� Principle: Combine all the signals from all of the M branches

in a co-phased and weighted manner so as to have the highest

SNR at the receiver at all timesSNR at the receiver at all times

� The control algorithms for setting the gains and phases for

MRC are similar to those required in equalizer

� Need time to converge & performance is as good as the

channel

Page 35: Chapter Two Mitigation Techniques

� Generalized receiver block diagram for MRC

Page 36: Chapter Two Mitigation Techniques

Equal Gain Combining:

�In equal gain combining

� The branch weights are all set to unity but the signals from

each are co-phased to provide equal gain combining diversity

� Co-phased signals are then add together

� All the received signals are summed coherently.� All the received signals are summed coherently.

� This allows the receiver to exploit signals that are

simultaneously received on each branch

� In certain cases, it is not convenient to provide for the variable

weighting capability as in MRC

Page 37: Chapter Two Mitigation Techniques

� The probability of producing an acceptable signals from a

number of unacceptable inputs is still retained

� The performance is marginally inferior to maximal ratio

combining and superior to selection combining

Figure : Equal Gain Combining

Page 38: Chapter Two Mitigation Techniques

Channel Coding Techniques

� It is used by the Rx to detect or correct some (or all) of the errors

introduced by the channel (Post detection technique)

� It improves mobile communication link performance by adding

redundant data bits in the transmitted message

� Mainly for error control and classified as block or convolutional

codescodes

� Block Codes: examples

• FEC codes, Hamming Codes, Hadamard Codes

• Golay Codes, Cyclic Codes, BCH cyclic, Reed-Solomon Codes

Page 39: Chapter Two Mitigation Techniques

� Convolutional codes: Here the output of the FEC encoder can

be viewed as the convolution of the input bit stream and the

impulse response of the encoder. Which is a time invariant

polynomial.

� A convolutional code is described by a set of rules by which the

encoding of k data bits into n-coded data (n, k)encoding of k data bits into n-coded data (n, k)

Page 40: Chapter Two Mitigation Techniques

� The ratio of k/n is typically called the code rate, this ratio

determines the amount of additional redundancy inserted into the

code word.

� The smaller the code rate the more parity bits are inserted into the

data stream.

Page 41: Chapter Two Mitigation Techniques

Conclusion

� Equalizers attempt to make the discrete time impulse response of

the channel ideal

� Channels act as filters that cause both amplitude and phase

distortion of signals

� Transmitters and receivers can be designed as filters to compensate

for non-ideal channel behaviour

� Training sequences can be used to adapt equalizer weights

� Multiple techniques are available for setting filter tap weights

�Zero forcing

� Least mean squares

� Recursive least squares

Page 42: Chapter Two Mitigation Techniques

� Diversity is one technique to combat fading in wireless channel

� Time diversity: Used when channels spacing is greater than the

coherence time of the channel

� Repeating transmission in time correlated channel brings

little advantage

� Good with fast fading channels� Good with fast fading channels

� Frequency diversity: used when channels frequency separation

is greater than the coherence bandwidth of the channel

� Spatial diversity requires multiple antennas

� E.g., MIMO and virtual antenna systems

� Finally channel coding is mainly used for error control