Location and Positioning (L&P) techniques which utilize wireless broadband networks are often considered by the wireless communications industries to be a means for improving overall system performance and providing value added services. Conventional L&P methods rely on the availability of base station (BS) locations as well as the mitigation of propagation effects. It is known that location estimation accuracy suffers in poor geometric dilution of precision (GDOP) caused by BS location as conventional location algorithms generate large GDOP values which correspond to poor geometrical topology. In addition, non line of sight (NLOS) effects cause large errors in time of arrival (TOA) readings, which affecting mobile station (MS) estimation accuracy. In this thesis a new concept of virtual BS (VirBS) utilizing multiple input multiple output (MIMO) technology has been introduced and successfully applied to improve L&P accuracy. The performance of the proposed algorithm has been evaluated via computer simulations. The simulation results demonstrate that the proposed algorithm increased L&P accuracy without additional expenditure on network architecture. Furthermore, a new hybrid algorithm enhancement of mobile station (MS) location estimation by using a single MIMO base station (SMBS) with the virtual base station has been introduced. The SMBS algorithm with virtual base station utilizes both AOA and AOD measurement parameter (SMVirBS). The developed algorithm includes the effect of the geometric dilution of precision (GDOP) to assist with the location estimation accuracy. Simulation results show that the proposed technique outperforms the linear least square (LLS) algorithm in terms of estimated location accuracy
