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optimUMTS



Brief Characterization of Features

Input
optimUMTS works with the following input data:
  • the underlying terrain data as digital elevation data and the corresponding building clutter data
  • a set of base stations with 3D coordinates, a subset of the base stations can be fixed such that they always will appear in the site selection
  • a set of mobile users as a distribution of 3D coordinates in an area or a parameterized distribution with activation factor
  • objective Eb/N0 for uplink and downlink direction, optimUMTS handles the Rx-Tx connections independently for all mobile-to-base-station combinations
  • base frequency, noise parameters, and antenna gains, parameters of the propagation model (Xia-Bertoni)
  • activity factor of the uplink connection and orthogonality factor of the downlink connection
  • maximum transmitting power of receiver and transmitter, pilot power and maximum channel power of the base station
  • service quality (bit rate) and validation percentage, i.e., percentage of mobiles to which the service quality should be guaranteed

Simulation
  • optimUMTS is based on heuristic and randomized optimization techniques applying branch-and-bound and genetic algorithms.
  • The main optimization criterion is the reduction of the number of base stations while guaranteeing the desired service quality to all mobile users. The assignment of receivers to base stations is based on minimum power requirements.
  • optimUMTS has no restrictions in the number of base stations or in the number of receiver locations (besides the memory restrictions and affordable run times on the simulation platform).

Performance
optimUMTS is a high performance tool that computes, e.g., a complete pathloss coverage map (Xia-Bertoni propagation model) of a UMTS-cell of 4 square-kilometer with 1 m sampling distance in less than 3 minutes (on a 800 MHz PC-based platform).
Output
The principal output data of optimUMTS consist in the set of base stations being sufficient to guarantee the desired service quality to the given percentage of mobile user distributions.


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