Channel Modeling Approach Based on the Concept of Degradation Level Discrete-Time Markov Chain: UWB System Case Study

In this work an approach to obtain an accurate high level channel model based on Discrete-Time Markov Chain, useful in some simulation context, is provided. In particular, this model is based on the concept of error trace analysis and on the degradation level of given observation windows: an observation window is fixed and the degradation level of the link, the Packet Error Rate (PER) relative to the specific window, is evaluated. This approach is useful for any wireless transmission scheme, but in our work, we apply it to the Ultra Wideband (UWB) system. Many researchers have already treated UWB channel modeling. However, to the best of our knowledge, all the proposed channel models work at the physical level investigating only some aspects of channel interaction. It has been shown through a comparative analysis, based on the occurrence of correctly and wrongly received packets, that the degradation level approach is more accurate than the classic Gilbert-Elliot model, the 3rd order Markov model and the Markov-based Trace Analysis (MTA) model.

[1]  Qinghua Li,et al.  Multiuser detection for DS-CDMA UWB in the home environment , 2002, IEEE J. Sel. Areas Commun..

[2]  Hong Shen Wang,et al.  Finite-state Markov channel-a useful model for radio communication channels , 1995 .

[3]  Ben Y. Zhao,et al.  A Markov-Based Channel Model Algorithm for Wireless Networks , 2001, MSWIM '01.

[4]  E. Gilbert.  Capacity of a burst-noise channel , 1960 .

[5]  R. Schober,et al.  Analysis of equalization for DS-UWB systems , 2005, 2005 IEEE International Conference on Ultra-Wideband.

[6]  Rittwik Jana,et al.  Measurement and modeling of an ultra-wide bandwidth indoor channel , 2004, IEEE Transactions on Communications.

[7]  Bin Xu,et al.  On modeling the packet error statistics in bursty channels , 2002, 27th Annual IEEE Conference on Local Computer Networks, 2002. Proceedings. LCN 2002..

[8]  Andreas Willig,et al.  A new class of packet- and bit-level models for wireless channels , 2002, The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[9]  V. Tarokh,et al.  Performance evaluation of MB-OFDM and DS-UWB systems for wireless personal area networks , 2005, 2005 IEEE International Conference on Ultra-Wideband.

[10]  Don Towsley,et al.  Packet loss correlation in the MBone multicast network , 1996, Proceedings of GLOBECOM'96. 1996 IEEE Global Telecommunications Conference.

[11]  Hayder Radha,et al.  Markov-based modeling of wireless local area networks , 2003, MSWIM '03.

[12]  Sheldon M. Ross,et al.  Stochastic Processes , 2018, Gauge Integral Structures for Stochastic Calculus and Quantum Electrodynamics.

[13]  G. Boggia,et al.  A simple ON/OFF logarithmic model for frame-level errors in wireless channels applied to GSM , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[14]  Andreas F. Molisch,et al.  Ultrawideband propagation channels-theory, measurement, and modeling , 2005, IEEE Transactions on Vehicular Technology.

[15]  Robert V. Brill,et al.  Applied Statistics and Probability for Engineers , 2004, Technometrics.

[16]  Ruonan Zhang,et al.  A packet-level model for UWB channel with people shadowing process based on angular spectrum analysis , 2009, IEEE Transactions on Wireless Communications.

[17]  J. Foerster,et al.  Channel modeling sub-committee report final , 2002 .

[18]  Donald F. Towsley,et al.  Modeling frame-level errors in GSM wireless channels , 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.