We address wideband direct coherent localization of a radio transmitter by a distributed antenna array in a multipath scenario with spatially-coherent line-of-sight (LoS) signal components. Such a signal scenario is realistic in small cells, especially indoors in the mmWave range. The system model considers collocated time and phase synchronized receiving front-ends with antennas distributed in 3D space at known locations connected to the front-ends via calibrated coaxial cables or analog radio frequency over fiber links. The signal model assumes spherical wavefronts. We propose two ML-type algorithms (for known and unknown transmitter waveforms) and a subspace-based SCM-MUSIC algorithm for wideband direct coherent position estimation. We demonstrate the performance of the methods by Monte Carlo simulations. The results show that even in multipath environments, it is possible to achieve localization accuracy that is much better (by two to three orders of magnitude) than the carrier wavelength. They also suggest that the methods that do not exploit knowledge of the waveform have mean-squared errors approaching the Cramér–Rao bound.

In this paper, we propose a massive MIMO (multiple-input-multiple-output) architecture with distributed steerable phased antenna subarrays for position estimation in the mmWave range. We also propose localization algorithms and a multistage/multiresolution search strategy that resolve the problem of high side lobes, which is inherent in spatially coherent localization. The proposed system is intended for use in line-of-sight indoor environments. Time synchronization between the transmitter and the receiving system is not required, and the algorithms can also be applied to a multiuser scenario. The simulation results for the line-of-sight-only and specular multipath scenarios show that the localization error is only a small fraction of the carrier wavelength and that it can be achieved under reasonable system parameters including signal-to-noise ratios, antenna number/placement, and subarray apertures. The proposed concept has the potential of significantly improving the capacity and spectral/energy efficiency of future mmWave massive MIMO systems.

Some experimental results of the concept development and practical implementation of an Orthogonal Frequency Division Multiplexing (OFDM) based secondary cognitive link are presented in this paper. The secondary link is realized using Universal Software Radio Peripheral (USRP) N210 platforms. For communication with USRP, we use MATLAB toolbox. Several algorithms are used to overcome transmission problems. Time-synchronization is achieved using a method based on auto-correlation of two sliding windows. Frequency offset estimation is performed using a phase offset between samples in a signal header, comprised of a sinusoid. A channel is estimated using predefined symbols inserted at the beginning of every frame, which enables channel equalization. Also, the cognitive feature of spectrum sensing and changing transmission parameters is implemented. A least-mean-square adaptive filter is introduced to offer time-synchronization error estimation as well as an alternative option for channel equalization.

A new concept development and practical implementation of OFDM based secondary cognitive link are presented in this paper. Coexistence of secondary user employing Orthogonal Frequency Division Multiplexing (OFDM) and primary user employing Frequency Hopping (FH) is achieved. Secondary and primary links are realized using Universal Software Radio Peripheral (USRP) N210 platforms. Cognitive features of spectrum sensing and changing transmission parameters are implemented. Some experimental results are presented.

Abstract. This paper deals with estimation of time difference of arrival (TDOA)