On Channel State Inference and Prediction Using Observable Variables in 802.11b Network
Karande, S.
Khayam, S.A.
Yongju Cho
Misra, K.
Radha, H.
Jaegon Kim
Jin-Woo Hong
Michigan State Univ., East Lansing;
This paper appears in: Communications, 2007. ICC '07. IEEE International Conference on
Publication Date: 24-28 June 2007
On page(s): 4554-4559
Location: Glasgow,
ISBN: 1-4244-0353-7
INSPEC Accession Number: 9875441
Digital Object Identifier: 10.1109/ICC.2007.752
Current Version Published: 2007-08-13
Abstract
Performance of cross-layer protocols that recommend the relay of corrupted packets to higher layers can be improved significantly by accurately inferring/predicting the bit error rate (BER) in the packets. In practice, higher layers observe the bits only after some hard decision. Hence physical layer link-quality indications, such as the signal strength of each individual bit, are not observable at higher layers. Therefore, it is essential to identify practically observable variables, which can be used for reasonably robust channel state inference/prediction (CSI/CSP). Here, inference specifically refers to estimating the BER in an already received packet, while prediction refers to anticipating the BER in a future packet. In this paper, we note that, in practical 802.11b devices, it is possible to acquire a Signal to Silence Ratio (SSR) indication and measure the background traffic intensity (p ) on a per packet basis. This paper, thus presents a measurement-based study that analyzes the utility of SSR and p as side-information for CSI/CSP. In this work, we exploit the method of types to measure the robustness of the observable side-information. Our analysis and simulations based on an extensive set of actual 802.11b traces exhibit the practical utility of the considered observable variables.
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
