Title: CSI-SF: Estimating Wireless Channel State
1CSI-SF Estimating Wireless Channel State Using
CSI Sampling Fusion
Riccardo Crepaldi, Jeongkeun Lee, Raul Etkin,
Sung-Ju Lee, Robin Kravets University of
Illinois at Urbana-Champaign Hewlett-Packard
Laboratories
Improving Performance in High Speed Wireless
Channel Quality Metrics
- How do systems describe the channel quality?
- Pros
- Finer granularity compared to SNR
- Fading and phase shift information for each
subcarrier - Tighter bound with channel performance
Halperin10 - Cons
- PHY Layer enhancements
- MIMO technology
- OFDM
- Channel Bonding
- Adaptive protocols for
- Rate adaptation
- Channel selection
- Optimal antenna scheme selection
- Best AP selection
- Choices based on
- Channel quality
N Input streams
M spatial streams
Signal-to-Noise Ratio (SNR) One scalar value per
packet Accurate only for narrow-band channel
Channel State Information (CSI) M x N x W
complex matrix W Number of OFDM
subcarriers Current 802.11n devices M3, N3
W56 (20MHz) or W114 (40MHz)
Why CSI?
CSI Matrix Combining
- CSI-SF enables estimation of uninvestigated
channel configurations
- A real networking problem Rate Adaptation
- Metrics SNR, effective SNR, estimated effective
SNR - Whats a good metric?
- Small or no gaps
- Monotonic behavior
CSI
- Ex Estimate of a 2x3 configuration using two 1x3
received packets
2x3 20MHz
Large gaps
Non-monotonic beavior
2x3 40MHz
3x3 20MHz
eSNR (effective SNR based on real samples)
e2SNR (effective SNR based on CSI-SF estimates)
- SNR is not a good metric, eSNR and e2SNR are
better - Compared to standard eSNR, e2SNR uses estimates
instead of real samples thus limiting the overhead
- Example of CSI-SF combining two 1x3 packets in a
2x3 packets
Packet 1 1x3 Ant B
CSI-SF Reduces Overhead
- Hypoyetical channel variation
- Overhead required to rate control to converge
using different metrics
Packet 3 2x3 Ant AB
Real CSI
Estimated CSI
Hewlett Packard LaboratoriesUniversity of
Illinois _at_ Urbana-Champaign, Department of
Computer Science Mobicom 2011