Simple Antenna Diversity with inherit directional information for SDMA operation

1. Simple Antenna Diversity with inherit directional information for SDMA operation Project group 997: Julien Gonidec Thibaut Ingrain François Net Mauro Pelosi Aurélie Villemont Supervisors: Patrick Eggers Chenguang Lu Censor: Jesper Ø. Nielsen

2. Introduction Why diversity techniques ?

3. Introduction Why WLAN ? • A widespread technology • Problems of security • New localisation services • Convergence of technlogies

4. 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

5. 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

6. Jitter part 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

7. 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

8. 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

9. 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

10. Jitter part Transfer function • At each realisation all beam’s orientation are performed • Discrete transfer function • Influence of the environment width on the fades

11. 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 • Reference direction θrefk is found at the kth step • is compared to and • The orientation of the maximum value is chosen θpathk • is the whole the collected h module

12. Jitter part JRDA results

13. Jitter part Standard deviation of the JDRA

14. 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 Jitter part Total power gain of the JRDA

15. 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 Jitter part Diversity gain of the JRDA (1) • Diversity gain at the 1% level of probability : • Definition of the normalised power :

16. Jitter part Diversity gain of the JRDA (2)

17. 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 Jitter part Diversity gain of the JRDA (3) • To better understand the tendencies of the diversity gain we introduce the following ratio: