Chapter Two Mobile Radio Channel Modelling & Mitigations 2.2 Mitigation Techniques for Fading Wireless Channels By : Amare Kassaw
Chapter Two
Mobile Radio Channel Modelling & Mitigations
2.2 Mitigation Techniques for Fading Wireless Channels
By : Amare Kassaw
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,
Lecture Outlines
� Introduction
� Equalization Techniques
� Diversity Techniques
� Coding Techniques
� Summery
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
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
� 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
� 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
� 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
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.
�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.
�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.
� 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.
� 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.
� 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.
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
� 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
� 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
� 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
�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
�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
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
� 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
� 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
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
�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
�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
� 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
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
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
� 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
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
� 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)
� 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.
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
� 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