The continuous demand for mobile communications leads to the development of new cellular networks for transmission of data, voice and video sequences. Already established GSM mobile cellular networks, a great economic success of the last decade, will be slowly upgraded to and eventually replaced by the new, third generation, cellular networks according to the UMTS standard. On the other hand, local wireless data networks according to the IEEE 802.11 standard will extend the classic LAN computer networks beyond building boundaries and lead to the creation of local communication islands. Both cases imply high requirements in respect to the communication bandwidth and quality of service. Very efficient use of the frequency spectrum and a very accurate knowledge of the communication channel properties are needed to satisfy these requirements. Statistical communication channel models allow a general classification of the propagation environment properties. In addition to the statistical modeling, deterministic channel models provide very accurate predictions of the radiowave propagation in a scenario of a particular geometry. Deterministic channel modeling is computationally very intensive, contrary to virtually any statistical channel model, and thus applications has been limited to a set of simplified geometries of rather small extents. Together with measurements, deterministic channel models can be used for parameter extraction in new statistical channel models in the process of evaluation and optimization of future communication systems. A new parallel and adaptive method for the deterministic communication channel modelling has been developed in the context of this work. The method is based on the construction of propagation paths between transmitters and receivers by means of a ray tracing technique together with additional sources taking edge diffraction and rough surface scattering into account. A new fast algorithm based on modified binary space partitioning trees has been deployed for the ray/object intersection test. The construction of nearly optimal binary space partitioning trees for arbitrary geometries has been realized by heuristics, the simulated annealing method and genetic algorithms. A novel ray density normalization algorithm based on tagged rays has been developed to quickly identify new propagation paths. The ray density is adapted locally to the scene geometry to minimize the total number of rays required for the spatial sampling of the geometry. The combination of the classic ray launching method with the source imaging technique allows the precise computation of the shortest propagation paths while maintaining constant local ray density and short simulation runtimes. It allows the accurate computation of the frequency selective properties of the communication channel. Source imaging over multiple arbitrary oriented diffraction edges according to the extension of the Fermat's principle has been solved with the Newton-Raphson iteration and a Simulated Annealing technique. Scattering on rough fractal surfaces has been modelled by the method of moments. Further substantial acceleration of the ray tracing solution of complex electromagnetic wave propagation problems has been achieved through the parallelization of the algorithm. Parallel implementations on symmetric multiprocessors with shared memory and on distributed memory parallel computers are presented together with a new hybrid method for distributed/shared memory architectures. Theoretical limits and achieved speedup of the computation are discussed. The physical propagation model is validated with analytical models and channel sounder measurements. Finally some applications of the deterministic model are presented, among these the radio network planning of the Transrapid track in Shanghai and an EMC computation of a radar facility
