MULTIUSER DETECTION AND INTERFACE DETECTION

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MULTIUSER DETECTION

AND INTERFACEDETECTION

PRESENTED BY:DISHANT KHOSLAM.TECH(1`st Year)ECE

ROLL NO.11092025


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INTRODUCTION

The idea of MUD was proposed by Sergio Verdu in theearly 1980s.

Modern wireless communication systems are required toaccommodate many users simultaneously, while providinghigh data rates and on-demand data transfers. The multiusercommunication system consists of many users attempting tocommunicate with a single receiver over a common set ofchannel resources.

The primary idea of Multi User Detection (MUD)

techniques is to cancel the interference caused by otherusers. This is done by exploiting the available sideinformation of the interfering users, rather than ignoring the

presence of other users like in Single User Detection (SUD)techniques.


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Example of a Multiuser Wireless MultipleAccess Communication System


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Multiuser Detection

Multiuser detection considers all users as signals for each other ->joint detection

Reduced interference leads to capacity increase

Alleviates the near/far problem

MUD can be implemented in the BS or mobile, or both In a cellular system, base station (BS) has knowledge of all the chip

sequences

Size and weight requirement for BS is not stringent

Therefore MUD is currently being envisioned for the uplink (mobileto BS)


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MUD Features

It has the capability to reject the interference created by thenarrow band

Capable to achieve diversity in frequency

It tremendously reduces the complexity and it increases the

spectral efficiency

Robustness to multipath fading

The use of modern DSP makes MC-CDMA implementationfeasible and attractive

MC-CDMA translates the time operations to the frequencydomain

Effect of ISI and delay spread is mitigated


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The Evolution Path to 3G

Systems


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CDMA System Model

Data of User 1Data of User 1

Spreading SequenceSpreading Sequence

of user 1of user 1

Chip shapingChip shaping

filterfilter 1X



of user 2of user 2


filterfilter 2X



of user Kof user K


filterfilter KX

AWGNAWGN


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Types of SS communication

system


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Anti-jamming (AJ) propertyof DS-SS system


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Near-Far Effect


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Near-Far Effect

Factors causing near-far effect (unequal RxSignal powers from different users) incellular CDMA

Distance loss Shadow loss

Multipath fading (Most detrimental. Dynamicrange of fade power variations: about 60 dB)

Two common approaches to combat near-far effect Transmit Power Control

Near-far Resistant Multiuser Detectors


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Types of multiple access

communications


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Synchronous CDMA System


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MUD Algorithms

Optimal

MLSE

Decorrelator MMSE

Linear

Multistage Decision-feedback Successiveinterference

cancellation

Non-linear

Suboptimal

Multiuser

Receivers

Linear detectors apply

linear transformations tomatched filter outputs to

minimize MAI. Simple to

implement but can get

complex.

Non-Linear detectors are

more complex calculation

wise than linear detectors

due to nonlinearity, however

they perform better under

severe conditions


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Linear Algorithms Practical Linear Algorithms:

- Decorrelating Detector

- Minimum-mean squared error (MMSE)

- Blind (adaptive non-adaptive) techniques


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Adaptive Minimum Mean Squared

Error (MMSE) Detector


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Adaptive MMSE Detector


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Blind Adaptive MMSE Detector Blind adaptive detector characteristics:

The detector doesnt require the training sequence inorder to calculate the channel impulse response

Requires the knowledge of the signature waveforms andtiming information of the desired user

The limitation is that it works only for short codes The major disadvantage of the adaptive MMSE detector

over the blind adaptive MMSE is that it requires thetraining sequences this results on a waste of the bandwidthwhich is populated with signals that do not carry anycommunication data. Therefore for the Blind adaptive we

have a clear benefit when it is compared to other detectorssince it does not require any training sequence thats why iscalled blind.

Adaptive MMSE detectors also are advantageous over othernon-adaptive detectors because they can adapt to unknownand time-varying channel conditions


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Non-Linear Algorithms

Non-Linear Algorithms:Estimate the interference caused by each user on theothers, re-spread and cancel from the received signal. This

is done through multitude of stages.

Practical Non-Linear Detectors: Multistage Detector Decision Feedback Detector

Subtractive Interference cancellation Successive Interference Cancellation (SIC) Parallel Interference Cancellation (PIC) Selective Parallel Interference Cancellation


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Optimal MLSE Detector


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Decision-Feedback Detectors


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Decision-Feedback Detectors


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Successive Interference Cancellers The SIC detectors start to subtract off the

strongest remaining signals in a

successive fashion from the rest of thesignals

By canceling the strongest signalfrom the rest we gain most of thebenefit and it is the most reliablecancellation

The other similar alternative is the PICmethod. This starts to simultaneouslysubtract off all of the users signals fromall of the others unlike the serialcancellation that starts with the strongestsignal user .

It works better than SIC when all ofthe users are received with equalstrength since it is much easier todetect them and hence decreases theprobability of error


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The main advantages are:

1) The weakest user will see atremendous signal gain from theMAI reduction since all of theinterfering channel will add up assignals to the weakest user. Hence

every user is on a win-win situation.2) For severe conditions if we remove the

strongest user the rest of weakerusers will benefit hence the signalcan be recovered

3) Can recover from near-far effects

The main disadvantages are:

1) If the strongest estimate is not highlyreliable it results on performance

degradation

2) As the power profile changes the

signals must be reordered

3) Every stage introduces a delay

1) More vulnerable to

near-far issues2) Complicated circuitry

1) Because of the

parallel nature no

delays/stage required!

2) Simpler than otherlinear detectors

SuccessiveInterference Cancellers

VS. Parallel InterferenceCancellers


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BENEFITS OF MULTIUSER

DETECTION

Significant capacity improvement

Reduced MAI and near-far effect

More efficient power utilization


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LIMITATION OF MULTIUSER

DETECTION

Potential capacity improvements in cellular systems are not

enormous but certainly nontrivial (2.8x upper bound)

Capacity improvements only on the uplink would only bepartly used anyway in determining overall system capacity

Cost of doing MUD must be as low as possible so that there

is a performance/cost tradeoff advantage

If the neighboring cells are not included interference

cancellation efficiency is greatly reduced.


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CONCLUSION AND FUTURE

WORK

It has been shown that CDMA systems suffer fromsevere multiuser interference. Although strong errorcontrol coding is able to ensure reliable transmissions formedium system loads, it is beneficial to apply multiuser

detection especially for high system loads. . MUD research is still in a phase that would not justify

making it a mandatory feature for 3G WCDMA standards.

Currently other techniques such as smart antenna seemto be more promising.

Though MUD has not been a mandatory feature of the

wireless standards so far, the rapid advances in DSParchitectures promise the evolution of MUD asintegrated feature of future wireless standards toprovide better capacity and data rates.

Feasible VLSI implementations for Mobiles


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REFERENCES

Multi user detection using CDMA by Sergio

Verdu.

www. Wikipedia.com


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THANKS

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MULTIUSER DETECTION AND INTERFACE DETECTION