Electromagnetic spectrum is a scarce resource. Spectrum licensing is estimated to consume about 20% of cellular operators' capital expenditure (CAPEX). One important measure of spectrum use is “spectral efficiency” (SE), which is the amount of data bandwidth that a specific technology can extract from a certain amount of radio spectrum and is measured in bits per second per Hz (bps/Hz). Using data from 4 different mobile operators, we show that spectral efficiency as the measure of bits per second per Hz correlates poorly with users' performance on cellular networks. Applying spectral efficiency directly in network performance monitoring or in network planning can provide misleading diagnostics and poorly targeted expansion plans. We propose a new spectral efficiency metric that combines the raw bit per second per Hz measurement with user perceived performance. We show that this new metric correlates well with measured user throughput and is superior metric for network planning and performance monitoring in real networks. We present a number of applications of our new metric on network management and capacity planning tasks. Our implementation of this approach has been used in operational networks for over 8 years and has provided sound basis for CAPEX decision making.

In performance testing of ATM switches and networks of switches a variety of connection configurations is needed. In most of the cases, these configurations require one traffic generator and/or analyzer for each switch port. Since this equipment is rather expensive, it is desirable to define scalable configurations that can be used with a limited number of generators. In this paper we present a methodology for the implementation of scalable connection configurations. The methodology is simple and offers a general solution to generate scalable connection configurations. Several examples of scalable configurations illustrate the methodology. The application of this methodology helps users to repeat easily performance tests under the same traffic load conditions.

This paper analyzes implementations of automatic code gapping (ACG) in intelligent network service control points (SCPs). The objective is to identify ACG controls that provide high call throughput while protecting the network from overloads. To achieve this we emphasize the need for careful engineering of vendors' control implementations (for example, the proper choice and use of internal SCP measurements) within the constraints of present ACG requirements. We use simulation and find that algorithms that use a combination of processor utilization measurements and measurements of excessive response times can yield reasonable call throughput. Shortening the measurement intervals to speed up the rate at which the SCP can change the rate at which traffic arrives to it further improves the call throughput. Finally, making the sizes of the rate changes smaller refines the granularity of the control and leads to better results.