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PERFORMANCE ANALYSIS OF MULTICARRIER CDMA MULTIUSERDECTECTION WITH CHANNEL MISMATCH

Under Guidance of

Mrs.GNANAPRASANNA

BY

M.Nagarchita P.Sruthi

P.Sahithya I.Silpa

M.Joys chandra priya G.Sudhamani

Department of Electronics & Communications

Intellectual Institute of Technology,ATP


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ABSTRACT Using the replica method originally developed for statistical physics, we provide asymptotic

(large- system limit ) solutions to the output signal-to-interference ratio(SNR)Of multi user

detection (MUDs) with channel mismatch in MC-CDMA systems.

Among system performances of the MUDs, we have several models i.e., detectors for MUD

that include Linear multi-user detectors like Decorrelating detector ,Linear minimum mean-

square error (LMMSE)detector,Maximum-likelihood sequence estimation(MLSE),Linear

decorrelator (LDD) ,Matched filter (MF) detector and Non linear detector such as SuccessiveInterfernece Cancellation,Parallel interference cancellation,Decision feedback. Here we

proposed low complexity algorithm Log Likelyhood Ratio(LLR)

In this paper we also cover methods to reduce the multiple access interference based on

power control,by reducing cross-correalation in spread spectrum systems and capacity

improvement with CDMA antenna arrays inorder to achieve higher capacities and importance

of processing gain ,relation between system capacity and processing gain.

Finally we emphasize fading which is severe in mobile communications and proving racian

fading will be good in future.


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INTRODUCTION

The performance analysis of the MUD algorithms in statistical systems are not easy sincetheir behaviors are described by a set of random variables.

MC-CDMA was first proposed as a MULTIPLE ACCESS MODULATION TECHNIQUEwhich combines the addition of OFDM and DS-CDMA.

In this paper ,we provide the performance of MC-CDMA systems with channel mismatchacross multiple sub carriers .

The analytical carriers include previous results as special cases .As will be shown bycomputer simulations ,with channel mismatch ,the analytical BER performances of boththe optimum MUDS and suboptimum linear MUDs in MC-CDMA systems exhibit excellentagreement to the simulated BER results.


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WIRELESS MIGRATION


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COMPARISON OF GENERATIONS

1G 2G 3G

System Analogue Digital Digital

Major Systems AMPS,NMT,TACS GSM,CDMA,TDMAWCDMA,CDMA2000,

TD-SCDMA

Application VoiceVoice + little Circuit

switch-data

Voice + Packet-

switch-data

Local Subscriber Less than 500k About 5.9 MillionMore than 5Million

(estimated)

SpeedDepends on

Analogue Signal9.6kbps to 14.4kbps

144kbps for mobile to

2Mbps for stationary

Properties

Unstable,

incomplete coverage

and poor sound

quality

More secure data

services available,

broader coverage,

more stable, allow

more users, better

sound quality

Multimedia data,

positioning capability,

connection to

internet, always

connected


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FDMA

In FDMA ,the available band width of the common channel is divided into bands thatare separated by guard bands.


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TDMA

In TDMA ,the bandwidth is just one channel that is time shared between differentstations


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DRAWBACKS OF FDMA AND TDMA In both FDMA and TDMA only one subscriber at a time is assigned to a channel.

No other conversation can access this channel until the subscribers channel is finished or

until that original call to handed off to a different channel by the system .

Voice channel tends to be burst in nature .So much of the time ,no data is being sent overthe channel.

This inefficiency tends to limit the capacity of the system.

The above drawbacks are overcome in CDMA technique in which the users are spreadacross both frequency and time in the same. channel.


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CDMA

In CDMA communication system ,a communication channel with a given bandwidth isaccessed by all users simultaneously. CDMA is hybrid combination of FDMA andTDMA.


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SPREAD SPECTRUM TECHNOLOGY

Spread-Spectrum communication system Spread Spectrum Mechanism


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TYPES OF SPREAD SPECTRUMThere are two types of spread spectrum. They are

Direct sequence spread spectrum.

Frequency hopping spread spectrum


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FREQUENCY HOPPING SPREAD SPECTRUM


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FREQUENCY-HOP SPREAD SPECTRUM (FHSS)


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FREQUENCY SELECTION IN FHSS


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FDMA & FHSS


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MULTI USER INTERFACE IN CDMA SYSTEM

In CDMA system, each user data is spread by a pseudorandom code.

All user then transmit in the same frequency band and are distinguished at the

receiver by the user specific spreading code. All other signal are not dispreadbecause they use different codes. These signal appear as interference to the desireduser because of non zero cross co-relation values between the spreading codes.

As the number of user increases , the signal to interference ratio (SIR) decrease untilthe resulting performance is no longer acceptable. thus, this multiuser interferencemust be reduced to achieve higher capacities.


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MC-CDMA


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RELATION BETWEEN SYSTEM GAIN AND PROCESSING GAIN The capacity of a system is approximated by:

Processing Gain:

:


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MC-CDMA TRANSMITTER AND RECEIVER


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CONCEPT OF MULTI-USER DETECTION Multi-user Signal Processing:

Multi-user signal processing techniques can be broadly classified into twocategories

Multi-user Detection:

These are receiver based schemes in which the bulk of the processing is carriedat receiver end.

Multi-user Transmission:

These schemes involve some pre-processing at the transmitter with the aim ofkeeping the receiver simple. The low computational burden at the receiver makes themgood candidates for deployment in the downlink of mobile wireless systems.


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MUD ALGORITHMSDecorrelator.

MMSE

Maximum Likelihood.

Multistage.

Decision Feedback.

Successive Interference Cancellation.


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CONCEPT OF MUD

0ikkkkk iTtsicixtu

T

dttstsr0

21

Simplified system model (BPSK):

K

k

k tztuty1

Base band signal for the kth user is:

Knumber of users

z(t) is the complex AWGN

xk(i) is the ith input symbol of the kth user

ck(i) is the real, positive channel gain

k(t) is the signature waveform containing the PN sequence

kis the transmission delay; for synchronous CDMA, k=0 for all users

Received signal at base band


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CONCEPT OF MUD ( 2) Sampled output of the matched filter

for the kthuser:

K

kj

T T

kjkjjkk

T

kk

dttztsdttstscxxc

dttstyy

0 0

0

T

dttstsr0

21

1st term - desired information 2nd term - MAI 3rd term - noise Assume two-user case (K=2), and


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CONCEPT OF MUD(3) Outputs of matched filter are:

211222122111 zxrcxcyzxrcxcy

kk yx sgn Detected symbol for user k:

If user 1 is much stronger than user 2 (the near/far problem), the MAI term rc1x1 present in the signal ofuser 2 is very large Successive Interference Cancellation decision is made for the stronger user 1:subtractthe estimate of MAI from the signal of the weaker user.

211122

1122

sgn

sgn

zxxrcxc

xrcyx

All MAI can be subtracted from user 2 signal provided estimate is correct MAI is reduced and near/far problem is alleviated


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PERFORMANCE OF MUD

BER vs. no. of users under ideal power control (asynchronous).


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PERFORMANCE OF MUD(2)

BER vs. no. of active users under Rayleigh fading(asynchronous).


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LIMITATIONS OF MUD Processing complexity

Processing delay

Sensitivity and robustness

Potential capacity improvements in cellular systems are not enormous but certainlynontrivial (2.8x upper bound)

Capacity improvements only on the uplink would only be partly used anyway indetermining overall system capacity

Cost of doing MUD must be as low as possible so that there is a performance/costtradeoff advantage.


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FADING

Fading means variation in the strength of receivedradio signals due to variations in the conditions of thetransmission medium.

In wireless communications, signal fading is causedby multi-path effect. Multi-path effect means that asignal transmitted from a transmitter may have

multiple copies traversing different paths to reach areceiver.

Thus, at the receiver, the received signal should bethe sum of all these multi-path signals. Because thepaths traversed by these signals are different; someare longer and some are shorter.

The one at the direction of LOS should be the

shortest. These signals interact with each other.signals are in phase, they would intensify the resultantsignal; otherwise, the resultant signal is weakeneddue to out of phase.


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FADING ON CDMA CHANNEL


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ADDITIVE WHITE GAUSSIAN NOISE A basic and generally accepted model

for thermal noise in communicationchannel is the set of assumptions that:

The noise is additive .

The noise is white.

The noise samples have a Gaussiandistribution..

Mostly it is also assumed that thechannel is Linear and Time Invariant.

The most basic results further assumethat it is also frequency non-selective.

Optimal signal detection in AWGN LTI channel


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RAYLEIGH FADING In a radio link, the RF signal from the transmitter

may be reflected from objects such as hills,buildings, or vehicles. This gives rise to multipletransmission paths at the receiver.

Rayleigh fading is caused by multipath reception.The mobile antenna receives a large number,

say N, reflected and scattered waves.

Because of wave cancellation effects, theinstantaneous received power seen by a movingantenna becomes a random variable, dependenton the location of the antenna.


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RACIAN FADING Racian fading is observed when, in addition

to multipath components there exists adirect path between transmitter and receiver.

The dominant wave can be a phasor sum oftwo or more dominant signals, e.g. the line-of-site, plus a ground reflection. Thiscombined signal is then mostly treated as a

deterministic (fully predictable) process, andthat

The dominant wave can also be subject toshadow attenuation. This is a popularassumption in the modeling of satellitechannels.

Besides the dominant component, the

mobile antenna receives a large number ofreflected and scattered waves.


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EXPERIMENTAL RESULT AND DISCUSSION

0 5 10 15

10-10

10-8

10-6

10-4

10-2

100

10*log10SNR

Average

ErrorProbability

AWGN

Rayleigh

K=0 Rician

K=10 Rician

0 5 10 15

10-5

10-4

10-3

10-2

10-1

100

10*log10SNR

Average

ErrorProbability

M=8 Rayleigh

M=64 Rayleigh

M=128 Rayleigh

COMPARISION OF AWGN,RAYLEIGN, RICIAN Number of Users in Rayleigh


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0 5 10 1510

-2

10-1

100

10*log10SNR

Average

ErrorP

robability

N=64 Rayleigh

N=128 Rayleigh

N=256 Rayleigh

0 5 10 1510

-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

100

10*log10SNR

Average

Error

Probability

M=8 Rician

M=64 Rician

M=128 Rician

0 5 10 1510

-5

10-4

10-3

10-2

10-1

100

10*log10SNR

Average

ErrorProbability

M=64 Rician

M=128 Rician

M=256 Rician

Number of sub carriers in Rayleigh Number of Users in Rician

Number of Users in Rician


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FEATURE SCOPE A study of the key theoretical foundations of MUD is carried out. A trade off between

complexity, performance and assumption about what is know is studied. A new lowcomplexity algorithm for MUD is also described. Simulation results show the performancegains of various schemes.

A more general analysis of the proposed algorithm needs to be carried out to find out theperformance in the case of fading environment and asynchronous transmission. The effectof using Gauss Seidal iteration as the first step of proposed algorithm has to be evaluated.An attempt can be made to find out the bound for error probability for the proposedscheme. Also, a general validity of the approximation used for calculating LLR needs to bestudied.

A further generalization can be in the direction of modifying such schemes for a MIMOsystem.


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CONCULSION The performance of this system in AWGN ,Rayleigh Fading ,and Rician Fading channel is

analyzed by analytical equations ,and compared to single-carrier system intuitively. Bysimulation result, BER in AWGN channel out performs other channels as SNR isincreased.

The performance of Rician fading channel is better than that of Rayleigh fading channel,because of LOS path . BER depends on the number of users and subcarriers in Rayleighfading and Rician fading channel .

The performance is degraded by the number of users and improved by the numbers ofsubcarriers .whenever we compare to single-carrier system ,the multicarrier systemoutperforms single-carrier system, the multicarrier system outperforms single-carriersystem expect that the bandwidth of interference covers the entire bandwidth BW.


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REFERENCES

T. Tanaka, A statistical-mechanics approach to large-systemanalysis of CDMA multiuser detectors,IEEE Trans. Inform., vol.48, pp. 28882910, Nov. 2002.

T. Tanaka, Performance analysis of optimum multiuser detector

under phase mismatch, in Proceedings 2004 IEEE InternationalSymposium on Information Theory, Chicago, USA, Jun. 2004, p.317.

Cellular and Mobile Communication 2nd edition McGraw Hill byWilliam Y C Lee.

www.WirelessCommunication.NL


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THANK YOU !!!!

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