Approximation of geometry based stochastic channel models

A geometry-based stochastic channel model discussed in this paper was developed in IST-WINNER I, WINNER II, and WINNER+ projects. The model is based on the same principles as, e.g., 3GPP SCM and ITU-R IMT-advanced channel models, and the results are applicable to them as well. The complexity of the channel model has been under discussion within ITU-R working groups as well as in industry planning to perform system level simulations. The complexity reduction (approximation, simplification) is one key task to improve the model usability. However, the complexity reduction should be made without reducing the model accuracy and generality too much. When application of the model is known, more approximation can often be done. Therefore, this paper studies first application independent and then application dependent approximation. Approximation of an accurate model is always possible, and the methods are known, but doing vice versa is impossible without additional information. This paper proposes a number of approximation steps, and shows the impact of some steps on the outage capacity and semi-analytical BER. The results show that only very little approximation can be done when application is unknown, but much more approximation is possible for narrowband single-input single-output (SISO) systems.