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doi:10.1016/j.peva.2006.06.001 
Copyright © 2006 Elsevier Ltd All rights reserved.
Markov and multifractal wavelet models for wireless MAC-to-MAC channels
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Syed A. Khayam
, a, 
, Hayder Radhaa, , Selin Aviyentea, and J.R. Deller, Jr.a,
Received 4 January 2005;
Abstract
Statistical understanding of bit-errors above the physical layer facilitates the design and verification of wireless protocols and applications. In this paper, we provide analysis and modeling of bit-errors at the 802.11b MAC layer. We show that MAC-to-MAC bit-errors at 2 and 5.5 Mbps are Markov, whereas those at 11 Mbps are long-range dependent (LRD). For the 2 and 5.5 Mbps channels, we observe that low-complexity hierarchical and hidden Markov models cannot characterize the bit-error processes, and consequently high-order full-state Markov chains are employed for accurate channel characterization. A multifractal wavelet model is employed to accurately capture the LRD 11 Mbps bit-error process.
Keywords: Channel model; Bit-errors; 802.11b networks; Long-range dependence; Markov chains
Article Outline
- 1. Introduction
- 2. Related work
- 3. Background
- 3.1. Autocorrelation of random processes
- 3.2. Long-range dependent processes
- 3.3. The multifractal wavelet model
- 3.4. Data collection
- 3.5. Performance evaluation measure
- 4. Analysis of bit-errors
- 4.1. Throughput analysis
- 4.2. Autocorrelation analysis
- 4.3. Preliminary analysis of FSM chains
- 4.4. Scaling behavior of the 11 Mbps bit-error process
- 5. Bit-error modeling at 5.5 Mbps
- 5.1. Hierarchical Markov models for the 5.5 Mbps bit-error process
- 5.2. Hidden Markov models for the 5.5 Mbps bit-error process
- 5.3. FSM chains for the 5.5 Mbps bit-error process
- 6. Bit-error modeling at 2 Mbps
- 7. Bit-error modeling at 11 Mbps
- 7.1. ENK-based performance evaluation
- 7.2. Performance in capturing the energy at different scales
- 7.3. Performance in capturing the variance–time characteristics
- 8. Conclusions
- References
- Vitae
