1 / 21

Joseph Camp, Edward Knightly ACM MobiCom 2008

Modulation Rate Adaptation in Urban and Vehicular Environments: Cross-Layer Implementation and Experimental Evaluation. Joseph Camp, Edward Knightly ACM MobiCom 2008. Background. Why need modulation rate adaptation? Time-varying link quality – Mobility of sender, receiver, or obstacles

anne
Download Presentation

Joseph Camp, Edward Knightly ACM MobiCom 2008

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Modulation Rate Adaptation in Urban and Vehicular Environments: Cross-Layer Implementation and Experimental Evaluation Joseph Camp, Edward Knightly ACM MobiCom 2008

  2. Background • Why need modulation rate adaptation? • Time-varying link quality • – Mobility of sender, receiver, or obstacles • – Multiple paths existing • Ideal modulation rate for channel condition Ideal rate

  3. For Protocol Designer • Use available information (loss, SNR, …) to track ideal modulation rate Rate Selection Protocol Rate choice SNR, loss, …

  4. Problem • ALL existing rate adaptation algorithms fail to track the ideal rate • Urban propagation environment ( ex: multi-path ) • Even with non-mobile sender and receiver • Result becomes loss and under-utilization Select rate

  5. Propose • Understand the origins of the failure to track link variation • Compare the result in in-door (lab) and out-door (urban or downtown )

  6. Propose (cont) • Unified Implementation Platform • Implement multiple algorithms on a common platform • Extract General Rate Adaptation Principles • Evaluate rate selection accuracy packet-by-packet • Compare against ideal rate found via exhaustive search • Use repeatable controlled channels • Accurately measured outdoor channels • Design core mechanisms to track real-world link variation

  7. WARP - Wireless Open-Access Research Platform • Limits of Off-the-shelf platforms • Programmability and observability • WARP is clean-slate MAC and PHY • Needed to implement CSMA/CA (802.11-like MAC) • Cross-layer rate adaptation framework • Core mechanisms for rate selection protocols • Channel measurements • Evaluation of selected rate versus ideal rate

  8. Core Mechanisms for Rate Adaptation • Loss-triggered Rate Adaptation • Consecutive-Packet Decision • Historical-Decision • Collision/Fading Differentiation • SNR-triggered Rate Adaptation • Equal Air-time Assurance

  9. Rate Adaptation Accuracy Matrices • Ideal rate found via exhaustive search of channel condition • Consider case where at least one modulation rate succeeds Ideal Rate Channel Condition

  10. Rate Adaptation Accuracy Matrices (cont) • Rate Selection Accuracy Categories • Over-selection (loss) • Accurate (achieving optimal rate) • Under-selection (under-utilization) Over-selection Accurate Ideal Rate Under-selection Channel Condition

  11. In-door (lab) experiments • Impact of Coherence Time • Increase fading of the channel to evaluate if rate adaptation can track

  12. In-door (lab) experiments (cont) • Similar performance with long coherence of channel • SNR: high overhead penalty • Equal Air-time Assurance: overcomes overhead penalty • Dissimilar performance at short coherence of channel

  13. Rate Choice Inaccuracies • Consecutive low due to under-selection • SNR: extremely low throughput due to over-selection

  14. SNR-based Coherence Time Sensitivity • Fast to slow channel fading • Accurate at long coherence • Over-select at <1ms • Over-selection caused by coherence time sensitivity of SNR-rate relationship 1 ms accurate

  15. Coherence Time Training for SNR • Consider different SNR thresholds according to coherence time

  16. Consideration of SNR and Coherence Time • Consider different SNR thresholds according to coherence time • Ideal rate = f(SNR, CT) • Retrain SNR-based decision (for the same protocol) • Joint consideration of SNR and coherence time provides large gains

  17. Residential Urban and Downtown Scenarios • Residential Urban (TFA) • Single-family residential, dense foliage • Coherence Time: 100 ms on average • Driven to 15 ms with mobility of scatterers (in static topology) • Downtown Houston • Both sides of street lined with tall buildings (strong multipath) • Coherence Time: 80 ms on average • Driven to 300 us with mobility of scatterers (in static topology)

  18. Rate adaptation accuracy in outdoor • Residential urban • Inaccurate in outdoor settings for loss-triggered • Consecutive-decision due to the mobility of scatters • Historical-decision due to different modulation rate selection

  19. Rate adaptation accuracy in outdoor (cont) • Downtown - strong multipath • Force loss-based to under-select • SNR: over and under-select with low coherence time

  20. Static Sender to Mobile Receiver -Urban • SNR protocols are able to plateau for >4 sec • Per-packet decision • Loss-based protocols are only able to spike to suboptimal rate choices • Loss sensitivity prevents protocol from tracking mobile static

  21. Summary • Loss-based core mechanisms under-select with • Fast-fading, interference, competing links (even with collision/fading differentiation), and mobile environments • SNR-based mechanisms over-select with fast-fading but have • Large gains from considering SNR and coherence time jointly • Robustness to interference, competing links, and mobility • Despite use of 4-way handshake, SNR-based protocols outperform loss-based protocols in practical environments

More Related