ABOUT BOOK

The key objective of this work was to obtain a MIMO model for a line of sight (LOS) channel component as well as the covariance matrix for a non-LOS deployment. A maximum likelihood criteria is applied to obtain a LOS spatial signature vector and a NLOS covariance matrix derived from channel measurements taken in the 2 GHz UMTS spectrum for an urban deployment in Bristol (UK). Different user equipment deployments were considered to represent both LOS and NLOS, as well as static and dynamic (motion) situations. The parameters of interest were estimated from these data and the fitness model was satisfactorily evaluated in all cases. Further, the Kronecker product between transmitter and receiver matrices was evaluated in order to simplify the model, for both, LOS and NLOS cases, including polarization diversity cases.The key objective of this work was to obtain a MIMO model for a line of sight (LOS) channel component as well as the covariance matrix for a non-LOS deployment. A maximum likelihood criteria is applied to obtain a LOS spatial signature vector and a NLOS covariance matrix derived from channel measurements taken in the 2 GHz UMTS spectrum for an urban deployment in Bristol (UK). Different user equipment deployments were considered to represent both LOS and NLOS, as well as static and dynamic (motion) situations. The parameters of interest were estimated from these data and the fitness model was satisfactorily evaluated in all cases. Further, the Kronecker product between transmitter and receiver matrices was evaluated in order to simplify the model, for both, LOS and NLOS cases, including polarization diversity cases