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Cross-Layer Modeling of Wireless Channels: An Overview of Basic Principles

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Abstract

To optimize performance of applications running over wireless channels, state-of-the-art technologies incorporate a number of channel adaptation mechanisms at different layers of the protocol stack. These mechanisms affect the way communication is performed and their joint effect is often difficult to predict. Recently, to evaluate joint operation of these mechanisms, a number of cross-layer performance models have been proposed. These models abstract functionality of layers providing channel adaptation and characterize performance of information transmission at higher layers, where it is usually standardized. While cross-layer performance models differ in some details, most of them are similar in the way they approach the problem. In this paper we identify similarities between these models, formulate step-by-step cross-layer modeling procedure and discuss its basic components.

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References

  1. Srivastava V., Motani M. (2005) Cross-layer design: a survey and the road ahead. IEEE Computer Communications 43(12): 112–119

    Article  Google Scholar 

  2. Lin X., Shroff N., Srikant R. (2006) A tutorial on cross-layer optimization in wireless networks. IEEE JSAC 24(8): 1452–1463

    Google Scholar 

  3. Lucas D., Mendes P., Rodrigues J. (2011) A survey on cross-layer solutions for wireless sensor networks. Elsevier J. Netw. Comput. Appl. 34(2): 523–534

    Google Scholar 

  4. Zhou L., Wang H., Lian Y., Vasilakos A., Jing W. (2011) Availability-aware multimedia scheduling in heterogeneous wireless networks. IEEE Trans. Veh. Tech. 60(3): 1161–1170

    Article  Google Scholar 

  5. Wang, W., Chen, W., & Cao, Z. (2012). A cross-layer design for rateless coding with optimal packet size over block fading channels. Wireless Personal Communications doi:10.1007/s11277-012-0687-X, March 2012.

  6. Pack, S., Kim, K., Kim, W., Song, T., & Min, S. (2012). A cross-layer approach to reduce channel access delay jitter in IEEE 802.11 WLANs. Wireless Personal Communications, doi:10.1007/s11277-012-0639-X, March 2012.

  7. Simon M., Alouini M. (2005) Digital communication over fading channels (2nd ed.). Wiley-Interscience, New York

    Google Scholar 

  8. Halunga S., Vizireanu D. (2010) Performance evaluation for conventional and MMSE multiuser detection algorithms in imperfect reception conditions. Digital Signal Processing 20(1): 166–178

    Article  Google Scholar 

  9. Bai, H., & Atiquzzaman, M. (2003). Error modeling schemes for fading channel in wireless communications: a survey. IEEE Communications Surveys, 2–9, Fourth Quarter.

  10. Wang H.-S., Moayeri N. (1995) Finite-state Markov channel—A useful model for wireless communications channels. IEEE Transactions on Vehicular Technology 44(1): 163–171

    Article  Google Scholar 

  11. Gilbert E. (1960) Capacity of a burst-noise channel. Bell Systems Technical Journal 39: 1253–1265

    Article  Google Scholar 

  12. Elliott, E. (1963). Estimates of error rates for codes on burst-noise channel. Bell Systems Technical Journal, 42, 1977–1997.

    Google Scholar 

  13. Fritchman B. (1967) A binary channel characterization using partitioned Markov chain. IEEE Transactions on Information Theory 13: 221–227

    Article  MATH  Google Scholar 

  14. Swarts, J., & Ferreira, H. (1999). On the evaluation and application of Markov channel models in wireless communications. In Proceedings of the VTC, pp. 117–121.

  15. Lui, Q., Zhou, S., & Ganniakis, G. (2003). Cross-layer combining of queuing with adaptive modulation and coding over wireless links. In IEEE MILCOMM, pp. 717–722.

  16. Lui Q., Zhou S., Ganniakis G. (2004) Cross-layer combining of adaptive modulation and coding with truncated ARQ over wireless links. IEEE Transactions on Wireless Communications 3(5): 1746–1755

    Article  Google Scholar 

  17. Moltchanov D. (2010) Performance models for wireless channels. Computer Science Review 4(3): 153–184

    Article  Google Scholar 

  18. Tang, J., Zhang, X. (2005). Capacity analysis for integrated multiuser and antenna diversity over Nakagami-m fading channels in mobile wireless networks. In Proceedings of the CISS’05, pp. 16–18.

  19. Lui, Q., Zhou, S., & Ganniakis, G. (2003). Combining adpative modulation and coding with truncated ARQ enhances throughput. In IEEE workshop on signal processing, pp. 110–114.

  20. Elwalid A.I. (1993) Effective bandwidth of general markovian traffic sources and admission control of high speed networks. IEEE/ACM Transactions on Network 1(3): 329–343

    Article  Google Scholar 

  21. Zhang X., Tang J., Chen H.-H., Ci S., Guizani M. (2006) Cross-layer-based modeling for quality of service guarantees in mobile wireless networks. IEEE Communications Magazine 44: 100–106

    Article  Google Scholar 

  22. Wu D., Negi R. (2003) Effective capacity: A wireless link model for support of quality of service. IEEE Transactions on Vehicular Technology 2(4): 630–643

    Google Scholar 

  23. Wu D., Negi R. (2004) Downlink scheduling in a cellular network for quality-of-service assurance. IEEE Transactions on Vehicular Technology 53(5): 1547–1557

    Article  Google Scholar 

  24. Wu D., Negi R. (2005) Utilizing multiuser diversity for efficient support of quality of service over a fading channel. IEEE Transactions on Vehicular Technology 54(3): 1198–1206

    Article  Google Scholar 

  25. Moltchanov D., Koucheryavy Y., Harju J. (2006) Loss performance model for wireless channels with autocorrelated arrivals and losses. Computer Communications 29(13–14): 2646–2660

    Article  Google Scholar 

  26. Lui Q., Zhou S., Ganniakis G. (2005) Queuing with adaptive modulation and coding over wireless links: Cross-layer analysis and design. IEEE Transactions on Wireless Communications 4(3): 1142–1153

    Article  Google Scholar 

  27. Moltchanov, D. (2008). The effect of data-link layer reliability on performance of wireless channels. In Proceedings of the IEEE PIMRC, Cannes, France, pp. 1–6.

  28. Stochastic modeling and simulation of the TCP protocol. PhD thesis, Uppsala University, 2003.

  29. Padhye J., Firoiu V., Towsley D., Kurose J. (2000) Modeling TCP reno performance: A simple model and its empirical validation. IEEE Transactions on Network 8(2): 133–145

    Article  Google Scholar 

  30. Mathis M., Semke J., Mahdavi J. (1997) The macroscopic behavior of the TCP congestion avoidance algorithm. Computer Communications Review 27(3): 67–82

    Article  Google Scholar 

  31. Misra A., Ott T., & Baras J. (1999). The window distribution of multiple TCPs with random loss queues. In Proceedings of the GLOBECOM, pp. 1714–1726.

  32. Kassa, S., & Wittevrongel, S. (2006). Convergence of the fixed point algorithm of analytical models of reliable internet protocols (TCP). In Proceedings of the 13th GI/ITG MMECCS, pp. 65–72.

  33. Bianchi G. (2000) Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on Selected Areas in Communications 18(3): 535–547

    Article  Google Scholar 

  34. Firoiu, V., & Borden, M. A study of active queue management for congestion control. In Proceedings of the INFOCOM, pp. 1435–1444.

  35. Casetti C., Meo M. (2001) An analytical framework for the performance evaluation of TCP reno connections. Computer Network 37(5): 669–682

    Article  Google Scholar 

  36. Ziouva E., Antonakopoulos T. (2002) CSMA/CA performance under high traffic conditions: throughput and delay analysis. Computer Communications 25: 313–321

    Article  Google Scholar 

  37. Ozdemir, M., & McDonald, A. B. (2004). An M/MMGI/1/K queuing model for IEEE 802.11 ad hoc networks. In Proceedings of the ACM MSWiM, pp. 107–111.

  38. Ozdemir, M., & McDonald, A. B. (2005). A queuing theoretic model of ad hoc wireless LANs. In Proceedings of the WiMob, pp. 131–137.

  39. Park, C.-G., Jung, H.-S., & Han, D.-H. (2006). Queuing analysis of IEEE 802.11 MAC protocol in wireless LAN. In Proceedings of the IEEE ICNICONSMCL’2006.

  40. Hadzi-Velkov, Z., & Spasenovski, B. (2003). Saturation throughput—delay analysis of ieee 802.11 DCF in fading channel. In Proceedings of the IEEE ICC, pp. 121–126.

  41. Moltchanov D. (2012) A study of TCP performance in wireless environment using fixed-point approximation. Computer Network 56(4): 1263–1285

    Article  Google Scholar 

  42. Blondia C. (1993) A discrete-time batch Markovian arrival process as B-ISDN traffic model. Belgian Journal of Operations Research 32(3,4): 3–23

    Google Scholar 

  43. Arauz J., Krishnamurthy P. (2004) Discrete Rayleigh fading channel modeling. Wireless Communications and Mobile Computing Journal 4: 413–425

    Article  Google Scholar 

  44. Moltchanov D., Koucheryavy Y., Harju J. (2006) Cross-layer modeling of wireless channels for IP layer performance evaluation of delay-sensitive applications. Computer Communications 29(7): 827–841

    Article  Google Scholar 

  45. Moltchanov, D., & Dunaytsev R. (2008). Modeling TCP performance over wireless channels with a semi-reliable data-link layer. In Proceedings of the IEEE ICSS.

  46. Moltchanov, D., Dunaytsev, R., & Koucheryavy, Y. (2008) Cross-layer modeling of TCP SACK performance over wireless channels with completely reliable ARQ/FEC. In Proceedings of the WWIC, pp. 13–26.

  47. Gemignani, L. (1995). Efficient and stable solutions of structured Hessenberg linear systems arising from difference equations. Technical report, Departments of Mathematics, University of Pisa.

  48. Meine, B. (1997). Fast algorithms for the numerical solutions of structured Markov chains. Technical report, Departments of Mathematics, University of Pisa.

  49. Akar, N., & Sohraby, K. (1998). Matrix-geometric solutions of M/G/1 type Markov chains: A unifying generalized state-space approach. Technical report, University of Missouri, Kansas.

  50. Kim N., Chang S., Chae K. (2002) On the relationships among queue length at arrival, departure, and random epochs in the discrete-time queue with D-BMAP arrivals. Operations Research Letters 30: 25–32

    Article  MATH  MathSciNet  Google Scholar 

  51. Herrmann C. (2001) The complete analysis of the discrete-time finite D-BMAP/G/1/N queue. IEEE Performance Evaluation 43: 95–121

    Article  MATH  Google Scholar 

  52. Raisinghani V., Lyer S. (2004) Cross-layer design optimizations in wireless protocol stacks. IEEE Computer Communications 27: 720–724

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Communication Engineering, Tampere University of Technology, P.O.Box 553, Tampere, Finland

    D. Moltchanov & Y. Koucheryavy

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  1. D. Moltchanov
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  2. Y. Koucheryavy
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Correspondence to D. Moltchanov.

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Moltchanov, D., Koucheryavy, Y. Cross-Layer Modeling of Wireless Channels: An Overview of Basic Principles. Wireless Pers Commun 74, 23–44 (2014). https://doi.org/10.1007/s11277-012-0896-8

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