Publikationen

Phase-noise is a system impairment caused by the mismatch between the oscillators at the transmitter and the receiver. In OFDM systems, this induces inter-carrier-interference (ICI) by rotating the transmitted symbols. Thus it can cause severe system performance degradation. To reduce its effects, the phase-noise must be estimated or compensated. In this work, we propose a two-stage tensor-based receiver for a joint channel, phase-noise (PN), and data estimation in MIMO-OFDM systems. In the first stage, we show that the received signal at the pilot subcarriers can be modeled as a third-order PARAFAC tensor. Based on this model, we propose two algorithms for channel and phase-noise estimation at the pilot subcarriers. The first algorithm, based on the BALS (Bilinear Alternating Least Squares), is an iterative algorithm that estimates the channel gains and the phase-noise impairments. The second is a closed-form algorithm based on the LS-KRF (Least Squares - Khatri-Rao Factorization) that estimates the channel gains and the phase-noise terms through multiple rank-one factorizations. Both algorithms achieve similar performance, but in terms of computational complexity, we show that the LS-KRF becomes more attractive than the BALS as the number of receive antennas is increased. The second stage consists of data estimation, for which we propose a ZF (Zero-Forcing) receiver that capitalizes on the PARATuck tensor structure of the received signal at the data subcarriers using the Selective Kronecker Product (SKP) operator. Our numerical simulations show that the proposed receiver achieves an improved performance compared to the state-of-art receivers in terms of symbol error rate (SER) and normalized mean square error (NMSE) of the estimated channel and phase-noise matrices.

In this paper, we present a gridless channel estimation algorithm for a hybrid millimeter wave (mmWave) MIMO-OFDM system assuming a frequency-selective channel. The proposed algorithm is based on the Tensor-ESPRIT in DFT beamspace algorithm framework. First, we derive the R-dimensional (R-D) Standard/Unitary Tensor-ESPRIT in DFT beamspace framework and its analytic performance. We show that ESPRIT-type algorithms in a reduced-dimensional DFT beamspace can provide a significant performance gain over ESPRIT-type algorithms in full DFT beamspace and in element space under mild conditions. Afterwards, we develop a gridless channel estimation algorithm that is based on 3-D Tensor-ESPRIT in DFT beamspace algorithms. Numerical simulation results show that the proposed channel estimation algorithm can provide accurate channel estimates using only a few training resources.

With this paper, we present cost-effective techniques to characterize UHF RFID performance with regards to small load carriers (SLC). A self-developed turntable-positioner is used to measure the antenna pattern of tags attached to empty SLCs, as well as SLCs filled with scrap metal. With the tag-positioner we presented in a recent publication, read range degradation of various tags near dissipative and conductive electro static discharge (ESD) protective material was investigated. We also measured the sensitivity of around 80 different tags in front of an SLC made of ESD protective material and compared their performance to operation in free-space propagation. To conduct the measurements themselves, we use commercial off-the-shelf readers like the R420 from Impinj, which we control via low level reader protocol (LLRP) commands, implemented in Python.

This contribution proposes modeling methods for MIMO-TDL channel models under new evaluation method, which is non-WSSUS. V2X channels cannot be assumed to follow the WSSUS assumption due to high inherent mobility. It can be extended to non-WSSUS by employing an ON/OFF process (persistence process). An algorithm to select taps and estimate their parameters from measured data is illustrated. Meanwhile, the slow and fast fading is separated from received signal to assess the fading distribution of taps. The analysis investigates correlation coefficient among taps persistence process, as well as, among taps amplitude. Additionally, an approach is discussed to develop a time varying MIMO-TDL model, whose parameters are varying over time.

The characterization of propagation at mm-waves and THz is obtaining relevance since they are expected to be the frequency bands of the future wireless generations. Hence, measurements conducted all around the world with different equipments need to be comparable by establishing common methodologies and best-practice guidelines. As an example, all measurements are affected by noise, but its estimation and removal are not standardized. Therefore, in the present paper we define a methodology on the estimation of the noise floor and the cut-off margin for its subsequent removal. We firstly analyse the influence of the channel sounder noise floor on the estimation of different propagation parameters directly from the measured channel impulse responses (CIRs), showing the need of its removal before any processing of the measurements. Later, we introduce an algorithm to estimate the noise floor in the presence of signal, and the cut-off margin. Finally, we evaluate its performance empirically with measurements.