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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