Blocking rates in large CDMA networks via a spatial Erlang formula

This paper builds upon the scalable admission control schemes for CDMA networks developed in F. Baccalli et al. (2003, December 2004). These schemes are based on an exact representation of the geometry of both the downlink and the uplink channels and ensure that the associated power allocation problems have solutions under constraints on the maximal power of each station/user. These schemes are decentralized in that they can be implemented in such a way that each base station only has to consider the load brought by its own users to decide on admission. By load we mean here some function of the configuration of the users and of their bit rates that is described in the paper. When implemented in each base station, such schemes ensure the global feasibility of the power allocation even in a very large (infinite number of cells) network. The estimation of the capacity of large CDMA networks controlled by such schemes was made in these references. In certain cases, for example for a Poisson pattern of mobiles in an hexagonal network of base stations, this approach gives explicit formulas for the infeasibility probability, defined as the fraction of cells where the population of users cannot be entirely admitted by the base station. In the present paper we show that the notion of infeasibility probability is closely related to the notion of blocking probability, defined as the fraction of users that are rejected by the admission control policy in the long run, a notion of central practical importance within this setting. The relation between these two notions is not bound to our particular admission control schemes, but is of more general nature, and in a simplified scenario it can be identified with the well-known Erlang loss formula. We prove this relation using a general spatial birth-and-death process, where customer locations are represented by a spatial point process that evolves over time as users arrive or depart. This allows our model to include the exact representation of the geometry of inter-cell and intra-cell interferences, which play an essential role in the load indicators used in these cellular network admission control schemes.

[1]  C. Preston Spatial birth and death processes , 1975, Advances in Applied Probability.

[2]  D. Stoyan,et al.  Stochastic Geometry and Its Applications , 1989 .

[3]  Kishor S. Trivedi,et al.  Loss formulas and their application to optimization for cellular networks , 2001, IEEE Trans. Veh. Technol..

[4]  François Baccelli,et al.  Downlink admission/congestion control and maximal load in CDMA networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[5]  D. Everitt,et al.  On the teletraffic capacity of CDMA cellular networks , 1999 .

[6]  Moshe Sidi,et al.  New call blocking versus handoff blocking in cellular networks , 1996, Proceedings of IEEE INFOCOM '96. Conference on Computer Communications.

[7]  Andrew J. Viterbi,et al.  Erlang Capacity of a Power Controlled CDMA System , 1993, IEEE J. Sel. Areas Commun..

[8]  Andreas Brandt,et al.  Marked Point Processes on the Real Line: The Dynamical Approach , 1995 .

[9]  Zhao Liu,et al.  SIR-based call admission control for DS-CDMA cellular systems , 1994, IEEE J. Sel. Areas Commun..

[10]  R. Serfozo Introduction to Stochastic Networks , 1999 .

[11]  François Baccelli,et al.  Up- and Downlink Admission/Congestion Control and Maximal Load in Large Homogeneous CDMA Networks , 2004, Mob. Networks Appl..

[12]  Tomás̆ Novosad,et al.  Radio Network Planning and Optimisation for Umts , 2006 .

[13]  Kenneth Mitchell,et al.  An analysis of the effects of mobility on bandwidth allocation strategies in multi-class cellular wireless networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[14]  Andrew J. Viterbi,et al.  On the capacity of a cellular CDMA system , 1991 .

[15]  Xiaotao Huang,et al.  Spatial Queueing Processes , 1999, Math. Oper. Res..

[16]  D. Everitt,et al.  Effective bandwidth-based admission control for multiservice CDMA cellular networks , 1999 .

[17]  Don Towsley,et al.  Personal & wireless communications: digital technology & standards , 1997, MOCO.

[18]  R. Serfozo,et al.  Reversible Markov Processes on General Spaces: Spatial Birth-Death and Queueing Processes , 2002 .