Optimal MAC state switching for cdma2000 networks

This paper deals with the performance modeling of the various MAC states as defined by the cdma2000 protocol. Our method uses a composite performance metric which has the capability of proportionally combining three basic parameters: channel utilization, waiting time and the saving in the signalling overhead. The scheduler at the base station is not only responsible for admitting new services into the system but also for switching the MAC states of a service depending on its activity. Since the true nature of the wireless data traffic is yet unknown, we use a mix of Poisson-distributed voice packets and Pareto-distributed data packets. We derive analytical expressions and also conduct simulation experiments to study the nature of the performance curve and thus compute the optimal values of expiration timers at which the MAC states should be switched such that the system performance is maximized. We show how our model can be made suitable for different systems by tuning the scaling functions (or weights) for each of the three performance parameters considered.

[1]  Bruno O. Shubert,et al.  Random variables and stochastic processes , 1979 .

[2]  Sidney C. Port,et al.  Probability, Random Variables, and Stochastic Processes—Second Edition (Athanasios Papoulis) , 1986 .

[3]  H. Saunders,et al.  Probability, Random Variables and Stochastic Processes (2nd Edition) , 1989 .

[4]  W. C. Y. Lee,et al.  Overview of cellular CDMA , 1991 .

[5]  Murad S. Taqqu,et al.  On the Self-Similar Nature of Ethernet Traffic , 1993, SIGCOMM.

[6]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[7]  A. Viterbi CDMA: Principles of Spread Spectrum Communication , 1995 .

[8]  Sally Floyd,et al.  Wide area traffic: the failure of Poisson modeling , 1995, TNET.

[9]  Azer Bestavros,et al.  Self-similarity in World Wide Web traffic: evidence and possible causes , 1996, SIGMETRICS '96.

[10]  Jack M. Holtzman,et al.  Access control of data in integrated voice/data CDMA systems: benefits and tradeoffs , 1997, Proceedings of ICC'97 - International Conference on Communications.

[11]  Azer Bestavros,et al.  Self-similarity in World Wide Web traffic: evidence and possible causes , 1997, TNET.

[12]  Sanjiv Nanda,et al.  Evolution of wireless data services: IS-95 to cdma2000 , 1998, IEEE Commun. Mag..

[13]  Quinn Li,et al.  cdma2000: A third-generation radio transmission technology , 1998, Bell Labs Technical Journal.

[14]  Erik Dahlman,et al.  UMTS/IMT-2000 based on wideband CDMA , 1998, IEEE Commun. Mag..

[15]  Ramjee Prasad,et al.  A survey on CDMA: evolution towards wideband CDMA , 1998, 1988 IEEE 5th International Symposium on Spread Spectrum Techniques and Applications - Proceedings. Spread Technology to Africa (Cat. No.98TH8333).

[16]  Hyoung-Kee Choi,et al.  A behavioral model of Web traffic , 1999, Proceedings. Seventh International Conference on Network Protocols.

[17]  A. Kripalani,et al.  cdma2000 mobile radio access for IMT 2000 , 1999, 1999 IEEE International Conference on Personal Wireless Communications (Cat. No.99TH8366).

[18]  Matthias Grossglauser,et al.  On the relevance of long-range dependence in network traffic , 1999, TNET.

[19]  Z. Hadzi-Velkov,et al.  Performance of the IEEE 802.11 wireless LANs under influence of hidden terminals and Pareto distributed packet traffic , 1999, 1999 IEEE International Conference on Personal Wireless Communications (Cat. No.99TH8366).

[20]  Giridhar D. Mandyam,et al.  1 XTREME : A Step Beyond 3 G , 2000 .

[21]  Maria Huhtala,et al.  Random Variables and Stochastic Processes , 2021, Matrix and Tensor Decompositions in Signal Processing.