IEEE 802.11 WPP SG - Optimization Parallels with CDMA Cellular/PCS Industry

1. IEEE 802.11 WPP SG - Optimization Parallels with CDMA Cellular/PCS Industry Dong-Jye Shyy, Ph.D. djshyy@mitre.org MITRE Craig J. Stanziano, Founder craig.stanziano@distributed-wireless.com DWG Dong-Jye Shyy, MITRE

2. The experience of wireless subscribers service is a direct result of RF design guidelines, deployment realities, and optimization solutions RF Design Guidelines Optimization Solutions Deployment Realities Dong-Jye Shyy, MITRE

3. Purpose Investigate the applicability of optimization solutions in the CDMA Cellular/PCS industry to WLAN deployments. Switch/Cell Translations Drive Testing Antenna Manipulation Dong-Jye Shyy, MITRE

4. Optimization Solutions • Background • Traditionally, CDMA Cellular/PCS deployment has focused on macro cell level deployment (large areas, >1 mile radius) solutions. Recent applications of micro cell (small areas, < ½ mile radius) solutions indicate there is a trend towards even smaller area deployment such as pico cell (< ¼ mile radius). This is the domain of WLAN. • This trend is attributed to wireless subscribers demands for “LAN like” performance from the service providers. • This trend has forced the optimization process to become more granular in its analysis. The area requiring to be optimized is decreasing although dependency to its neighboring cells is increasing • The first step in system optimization is to have an understanding of subscriber usage patterns. Dong-Jye Shyy, MITRE

5. Optimization Solutions • Subscriber Usage Patterns • Similar to vehicular traffic in the CDMA networks, office environment also has predefined routes. • In an office environment, we need to address both mobility and stationary user scenarios. • For the mobility users, it would be desirable if they can transition areas of service with as few handoffs as possible to minimize performance degradation. • For the stationary users, it would be desirable if they can receive maximum throughput with no degradation from neighboring users. This can be achieved by service delineation between stationary users and mobility users. • One solution to achieve the above objectives is to properly position antennas to dedicate their service based on the usage patterns. Dong-Jye Shyy, MITRE

6. Optimization Solutions • Subscriber Usage Patterns No MobilityPeriodic MobilityHigh Mobility Dong-Jye Shyy, MITRE

7. Optimization Solutions Access Point Deployment Solution • Subscriber Usage Patterns No MobilityPeriodic MobilityHigh Mobility Dong-Jye Shyy, MITRE

8. Optimization Solutions • Drive (Walk) Testing • Routes are derived to access the network performance • Define the overall coverage boundaries through thorough investigation of all useable areas • Define cell specific routes to benchmark performance and evaluate trends over time • Define major routes across cells • Drive testing is also needed to evaluate the effect of parameter adjustment • Switch/Cell parameters modification would require re-drive/walk to determine effect of change • Similarly, once the antenna placement is changed (to meet coverage conditions), drive testing needs to be re-performed Dong-Jye Shyy, MITRE

9. Optimization Solutions Drive routes are used to bench mark the performance of the network • Drive Testing No MobilityPeriodic MobilityHigh Mobility Dong-Jye Shyy, MITRE

10. OptimizationSolutions • Switch/Cell Translations • Frequency/PN (Pseudo random Noise) Offset Re-Use Planning • Minimize co-channel & adjacent channel interference through spatial separation that maximizes signal level differentials • In CDMA the entire network is co-channel so re-use planning is purely based on effective PN Offset (512 values divided by a typical increment factor of 4) strategies. The results of which (128 discrete PN Offsets) have to eliminate occurrences where same PN Offsets are considered for simultaneous use. • 802.11 is a pure frequency (11 channels in 11b) plan to ensure co-channel and adjacent channel is minimized. Dong-Jye Shyy, MITRE

11. Optimization Solutions 3 Carrier Access Point Frequency Plan Solution • Switch/Cell Translations 11 6 1 11 1 11 1 11 6 6 1 6 11 1 11 No MobilityPeriodic MobilityHigh Mobility Dong-Jye Shyy, MITRE

12. Optimization Solutions • Antenna Manipulation • Antenna pattern discrimination is applied to improve network performance • Omni directional patterns to maximize distribution of service to all areas around cell site • Directional patterns to amplify signal levels to a specific area or remove service from another area. • Deployment of a combination of both antenna patterns are effective solutions for various usage environments Dong-Jye Shyy, MITRE

13. Optimization Solutions Poor Antenna Solution • Antenna Manipulation 11 6 1 11 1 11 1 11 6 6 1 6 11 1 11 No MobilityPeriodic MobilityHigh Mobility Dong-Jye Shyy, MITRE

14. Optimal Antenna Solution • Antenna Manipulation 11 6 1 11 1 11 1 11 6 6 1 11 6 11 1 No MobilityPeriodic MobilityHigh Mobility Dong-Jye Shyy, MITRE

15. Conclusion • Propose to include the presented methodology in the “Recommended Practice for Wireless Performance Prediction” Dong-Jye Shyy, MITRE