3D Location Accuracy Estimation of Radio Emission Sources for Beamforming in UltraDense Radio Networks Accurate location estimation of Radio Emission Sources (RES) is very important for locationbased applications in 5G radio networks. Multiple Input Multiple Output (MIMO), millimeter Wave (mmWave) and Ultra Dense Networks (UDN) are among emerging technologies to increase not only communication performance, but also positioning accuracy and vice versa. In addition to leverage coverage and capacity new technologies give rise to beamforming techniques with successful implementation of simultaneous transmission and reception by means of preliminary location of neighboring stations. Contribution of the current research is 3D location accuracy limits estimation for positioning of radio emission sources using Time Difference of Arrival (TDOA), Angle of Arrival (AOA) and their combination TDOAAOA. Resulting accuracy limits, such as CramerRao Lower Bound (CRLB) ellipsoid and Spherical Error Probable (SEP) contour were analyzed and visualized to confirm spatial splitting possibility of neighboring RES for shortrange communications thus enabling location aware beamforming.

Direct position determination of multiple radio signals The most common methods for position determination of radio signal emitters such as communications or radar transmitters are based on measuring a specified parameter such as angle of arrival (AOA) or time of arrival (TOA) of the signal. The measured parameters are then used to estimate the transmitteru0027s location. Since the measurements are done at each base station independently, without using the constraint that the AOATOA estimates at different base stations should correspond to the same transmitteru0027s location, this is a suboptimal location determination technique. Further, if the number of array elements at each base station is M, and the signal waveforms are unknown, the number of cochannel simultaneous transmitters that can be localized by AOA is limited to M  1. Also, most AOA algorithms fail when the sources are not well angularly separated. We propose a technique that uses exactly the same data as the common AOA methods but the position determination is direct. The proposed method can handle more than M  1 cochannel simultaneous signals. Although there are many stray parameters, only a twodimensional search is required for a planar geometry. The technique provides a natural solution to the measurements sources association problem that is encountered in AOAbased location systems. In addition to new algorithms, we provide analytical performance analysis, CramerRao bounds and Monte Carlo simulations. We demonstrate that the proposed approach frequently outperforms the traditional AOA methods for unknown as well as known signal waveforms.