Comparison between unitary ESPRIT and SAGE for 3-D channel sounding

The detailed knowledge of the directional characteristics of the mobile radio channel is required to develop directional channel models and to design efficient smart antenna concepts for future mobile radio systems. In this paper, we examine the applicability and performance of two popular high-resolution parameter estimation schemes for directional channel sounding, namely subspace-based unitary ESPRIT and the maximum-likelihood-based SAGE algorithm. To this end, an investigation of the resolution capability using a synthetic scenario is carried out for both schemes by means of Monte-Carlo simulations. The performance is also compared to the Cramer-Rao lower bound (CRLB). Moreover, we apply both parameter estimation schemes to propagation data generated by a ray-tracing model. This model is based on indoor channel measurements generated by the wideband channel sounding system ECHO 24. The channel measurements were taken inside a radio frequency shielded room (RFSR), an environment dominated by severe specular multipath and, therefore, can be considered a worst case scenario.