Congress & Conference Contributions

The statistical study of target detectability is crucial in radar system design. In this regard, signal-to-noise ratio (SNR) of the received signal at the radars receiver is a key parameter and therefore every influence on SNR should be taken into account. One of the main influences is the fluctuation of the target scattering/reflectivity to the incident electromagnetic wave. Consequently, the target fluctuation models and their accuracy become important. For monostatic radar system, various models can be found in the literature. In contrast, this paper studies a case of vehicular sensing scenario with multistatic configuration for an urban crossroad and proposes a modelling method of the target fluctuation by taking into account the target information, such as size, shape and composed materials, and the wave information, such as polarizations and aspect angles. Furthermore, the derived target fluctuation models are then applied directly to the formulation of the probability of detection for multistatic radar system. These probabilities of detection are also compared to that of monostatic radar system.

In this work, we propose a two-stage tensor-based receiver for joint channel, phase-noise (PN), and data estimation in MIMO-OFDM systems. First, we cast the received signal at the pilot subcarriers as a third-order PARAFAC model. Based on this model, we propose 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. From the estimated channel, the second stage of the receiver consists of data estimation based on a ZF (Zero-Forcing) receiver that capitalizes on the tensor structure of the received signal at the data subcarriers via a Selective Kronecker Product (SKP) approach. Our numerical simulations show that the proposed receiver achieves an improved performance compared to the state-of-art receivers.

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.