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GUIDE
K.B. Pavan Kumar Prof.R.S.RaoM.Tech(DECS) Dept. of ECE
Roll no:10121D3805 SVEC
(Autonomous)
Sree Sainathnagar, A.Rangampet, Tirupathi-517102
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OUTLINE
Objective
Introduction
OFDM
OFDM Transceiver
Principles of operation
PAR reduction methodsAdaptive Active Constellation Extension Method
Summary of proposed algorithm
Gradient step size
AACE Algorithm model Simulation results
Optimization Problem
References
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OBJECTIVE
For PAR reduction in OFDM systems, the clipping based
Active Constellation Extension (ACE) technique issimple and attractive for practical implementation.
However, we observe it cannot achieve the minimumPAR when the target clipping level is set below aninitially unknown optimum value.
To overcome this low clipping ratio problem, we proposea novel ACE algorithm with adaptive clipping control.Simulation results demonstrate that our proposedalgorithm can reach the minimum PAR for severely low
clipping ratios. In addition, we present the tradeoff between PAR and the
loss in /
over an AWGN channel in terms of theclipping ratio.
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INTRODUCTION
Among various peak-to-average ratio (PAR) reduction
techniques, the active constellation extension (ACE)
technique is attractive for use in the down-link.
The reason is that ACE allows the reduction of high-
peak signals by extending some modulation constellation
points toward the outside of the constellation without any
loss of data rate.
The basic principle of clipping-based ACE (CB-ACE)
algorithms involves switching between the time domain
and the frequency domain.
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CONT
Filtering and applying the ACE constraint in the
frequency domain, after clipping in the time domain,
both require iterative processing to suppress the
subsequent re-growth of the peak power.
CB-ACE algorithms have a low clipping ratio problem in
that they cannot achieve the minimum PAR when the
target clipping level is set below an initially unknown
optimum value.
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ORTHOGONAL FREQUENCY DIVISION
MULTIPLEXING ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING (OFDM) is a
method of encoding digital data on multiple carrier frequencies.
Its is a hybrid of FDMA and TDMA
Users are dynamically assigned subcarriers (FDMA) in different time slots (TDMA)
In OFDM the entire bandwidth is divided among many MS's in the cell. Each MS
using only a small subset of subcarriers. Thus each MS transmits with a lower PAR
The advantages of OFDM starts with the advantage of single-user OFDM in terms
of robust multipath suppression and frequency diversity
It can accommodate many users with widely varying applications, data rates, and
QOS requirements
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OFDM TRANSCEIVER
Figure: OFDM Transceiver
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PRINCIPLESOFOPERATION
1. Orthogonality
Conceptually, OFDM is a specialized FDM, the
additional constraint being: all the carrier signals are
orthogonal to each other.
In OFDM, the sub-carrier frequencies are chosen so
that the sub-carriers are orthogonal to each other, sothat cross-talk between the sub-channels is eliminated
and inter-carrier guard bands are not required.
This greatly simplifies the design of both
the transmitter and the receiver; unlikeconventional FDM, a separate filter for each sub-
channel is not required.
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2. Guard interval
One key principle of OFDM is that since low symbol
rate modulation schemes suffer less from
intersymbol interference caused by multipath
propagation, it is advantageous to transmit a
number of low-rate streams in parallel instead of a
single high-rate stream.
Since the duration of each symbol is long, it is
feasible to insert a guard interval between the
OFDM symbols, thus eliminating the inter-symbol
interference. The guard interval also eliminates the need for
a pulse-shaping filter, and it reduces the sensitivity
to time synchronization problems.
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PAR REDUCTION METHODS
Clipping and filtering and non-linear distortion
Multiple signal representation
Partial transmit signalling
Selected mapping
Interleaving
Constellation optimization
Tone Reservation
Tone injection
Active constellation extension
Coding
Receiver-side clipping noise compensation
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ADAPTIVEACTIVECONSTELLATION
EXTENSIONMETHOD (AACE) Make constellations more flexible:
There are many or infinite points which can be used totransmit
Find a good or best representation with PAR as the cost
function.
Allowable Extensions do NOT change ML decision regions
Extensions cannot change minimum distance properties
Generally, this means only outside constellation points can bemoved
Very simple for the case of QAM constellations
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CONT
Key idea: move constellation points, but dont change
receiver decision boundaries i.e. maintain or increase
margin
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GRADIENTSTEPSIZE We can use a preselected step size, but convergence will be
slower.
We can determine a step size for each ACE application.
Signals are complex, so it may be difficult to determine anoptimal step size that minimizes the PAR at each level.
Solution: Linearize the optimal step size with a safe, simple,
and intuitive assumptionsvalid while the PAR has not been
reduced a lot already.
Assumption breaks down after about four ACE iterations, butmost gains are achieved within the first two or three iterations.
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AACE ALGORITHMMODEL
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X=1
Y=11.53
SIMULATION RESULTS
INITIAL PAR
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SIMULATION RESULTS
X=6
Y=7.423
PAR from Adaptive
CB-ACE
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SIMULATION RESULTS
X=14
Y=0.155
.X=14.5
Y=0.025
X=12
Y=0.025
.
.X=11.5Y=0.003
SIMULATION RESULTS
PAR of originalsignal
CB-ACE;
Gamma=0Db
CB-ACE;
Gamma=2Db
CB-ACE;
Gamma=4Db
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PARAMETERS USED FOR CLIPPING &
FILTERING
PARAMETERS VALUES
Band width 1 MHz
Sampling frequency 8 MHz
Carrier frequency 2MHz
FFT size(N) 128
Number of guard interval samples 32
Modulation order QAM
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COMPARISONOFPAR REDUCTIONDistortion less Power Increase Data loss rate
Clipping & Filtering NO NO NO
Coding YES NO YES
Partial Transmit
Signaling
YES NO YES
Selected Mapping YES NO YES
Interleaving YES NO YES
Tone Reservation YES YES YES
Tone Injection YES YES NO
ACE YES YES NO
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OPTIMIZATION PROBLEMS
Rate Maximization Maximize the total rate subject to a power budget.
Margin Maximization Minimize the total power to meet a target total rate.
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G. Andrews and Edward J. Powers, Adaptive Active Constellation Extension
Algorithm for Peak-to-Average Ratio Reduction in OFDM, in Proc. IEEE Veh.
Technology Conf., Sep. 2010, pp. 3941.
L. Wang and C. Tellambura, An adaptive-scaling algorithm for OFDM PAR
reduction using active constellation extension, in Proc. IEEE Veh. Technology
Conf., Sep. 2006, pp. 15.
J. Tellado, Multicarrier Modulation with Low PAR: Applications to DSL and
Wireless. Boston: Kluwer Academic Publishers, 2000.
E. Van der Ouderaa, J. Schoukens, and J. Renneboog, Peakfactor minimization
using a time-frequency domain swapping algorithm,IEEE Trans. Instrum.
Meas., vol. 37, no. 1, pp. 145-147, Mar. 1988.
Y. Kou, W.-S. Lu, and A. Antoniou, New peak-to-average power-ratio
reduction algorithm for multicarrier communication,IEEE Trans. Circuits and
Syst., vol. 51 no. 9, pp. 1790-1800, Sep. 2004. E. Van der Ouderaa, J. Schoukens, and J. Renneboog, Peakfactor minimization
using a time-frequency domain swapping algorithm,IEEE Trans. Instrum.
Meas., vol. 37, no. 1, pp. 145147, Mar. 1988.
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THANK
YOU