Simple Antenna Diversity with inherit directional information for SDMA operation

Simple Antenna Diversity with inherit directional information for SDMA

operation

Project group 997:Julien GonidecThibaut IngrainFrançois NetMauro PelosiAurélie Villemont

Supervisors: Patrick Eggers

Chenguang Lu

Censor: Jesper Ø. Nielsen

Why diversity techniques ?

Introduction

Why WLAN ?

A widespread technology Problems of security New localisation services Convergence of technlogies

Introduction

Choices made

802.11G standard Open office environments Jitter diversity Implementation of diversity techniques only

at the base station Algorithm will provide directionnal information

Introduction

Experiment process

Apply the Jitter Diversity algorithm to deduce tendencies

Model a more realistic channel model and apply the jitter diversity on it

Study the gain provided by the diversity See how the algorithm can provide

directionnal information

Introduction

Jitter diversity simulation in a simplified environment

Steps of the simulation

Modelling a simplified indoor channel Generation of an ideal antenna pattern Jitter process description Results and tendencies

Monte-Carlo simulations

the user’s location is randomly defined at each step

Jitter part

Environment implementation (1)

Clustered scattering Investigations concentrated on rays from an unique cluster AOA power distribution approximated by a Laplacian

distribution PowerLaplace_a(θAOA)

Environment response

Where The amplitude is defined by

The phase is defined by

,, , . er AOAj xAOA er AOAer x x e

_

1

., . 1 ,

1 ,R

R Laplace a AOAk

er i AOAk i AOAkN

n AOAkn

N Px temp x

temp x

, 2 . 2 ,er AOA AOAx temp x

Jitter part

Environment implementation (2)

“a“ parameter controls the shape of the environment

10-6 < a < 10-1

BWenv: half-power width of the mean environment response

Simulation of various type of environment by varying the a parameter

Jitter part

Antenna pattern

Choice of an ideal beam pattern (no side and back lobes)

Amplitude of the pattern

“α“ parameter controls the antenna beamwidth

sin,

0AOA BO AOA BO

AOA BO

ifa

otherwise

Jitter part

Transfer function

At each realisation all beam’s orientation are performed

Discrete transfer function

Influence of the environment width on the fades

1

, , . ,AOAN

BO AOAn AOAn BOn

h x er x a

Jitter part

Jitter process

We want to compare 3 different algorithms: JRDA (Jitter with respect to the Reference Direction Algorithm) BPP (best possible process algorithm) FB (fixed beam algorithm) as a reference

Explanation of the JRDA process

1. Reference direction θrefk is found at the kth step

2. is compared to and

3. The orientation of the maximum value is chosen θpathk

4. is the whole the collected h module

,k refkh x ,k refk jitth x

,k refk jitth x

, pathh x

Jitter part

JRDA results

Jitter part

Standard deviation of the JDRA

Jitter part

Total power gain of the JRDA

Total power gain at the 1% level of probability:

We define the total power gain at the 1% level of probability as the difference between the cumulative density values of

and at the 1% level of probability

( , )path dBh x ( , )FB dB

h x

_1%JRDATPG

Jitter part

Diversity gain at the 1% level of probability : Definition of the normalised power :

_( , ) ( , ) ( , )path path pathdB norm dB dBh x h x h x We define the diversity gain at the 1% level

of probability as the difference between the cumulative density values of and at the 1% level of probability

_( , )path dB normh x

_( , )FB dB normh x

Diversity gain of the JRDA (1)

Jitter part

Diversity gain of the JRDA (2)

Jitter part

antW

env

BWR

BW

To better understand the tendencies of the diversity gain we introduce the following ratio:

Diversity gain of the JRDA (3)

Median power gain at the 50% level of probability :

We define the median power gain at the 50% level of probability as the difference between the cumulative density values of and at the 50% level of probability

_ 50%JRDAMPG

_( , )path dB normh x

_( , )FB dB normh x

Jitter part