Uplink Load in CDMA Cellular Systems

Cellular mobile systems designed to handle multimedia services are currently being developed. The primary goal for any mobile system is to provide a satisfactory quality of service, both to operators and customers. Providing good quality of service while maintaining system stability requires accurate knowledge of the system load. In particular, it is important to be able to predict how a resource management decision will affect the stability of the network. This thesis addresses the problem of characterizing and estimating the uplink load in a cellular system using CDMA (Code Division Multiple Access) in the radio interface.Uplink load can be related directly to the uplink power control problem of finding transmitter powers to support the users' quality of service requirements. This yields a rather theoretical view. Another way of looking at uplink load is to relate it to the total received power users induce in the base station antennas. Both of these views are handled and relations between them are established in this thesis.The literature survey on uplink load provided in this work concludes that practical estimates of the uplink load are generally what can be referred to as decentralized estimates; they use information gathered only in the immediate vicinity of the estimates' host node. As an alternative to these estimates, a number of centralized estimates based on information readilyavailable to the system are proposed. The usage of information from several cells makes them more sensitive to the soft capacity inherent in all CDMA cellular systems.Extensive simulations in an advanced WCDMA (Wideband Code Division Multiple Access) simulator show that the estimates statistically perform well and the performance is insensitive to non uniform traffic load.In the time domain, the load approximation can be described as oscillations superimposed on a slowly varying bias. If occasional high loads can be accepted, a non-oscillative signal representing the uplink load can be used to further increase the utilization of the resources. An algorithm is proposed to estimate the bias and a prediction of it.

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