Deterministic Cramer-Rao bound for strictly non-circular sources and analytical analysis of the achievable gains

Recently, several high-resolution parameter estimation algorithms have been developed to exploit the structure of strictly second-order (SO) non-circular (NC) signals. They achieve a higher estimation accuracy and can resolve up to twice as many signal sources compared to the traditional methods for arbitrary signals. In this paper, as a benchmark for these NC methods, we derive the closed-form deterministic R-D NC Cramer-Rao bound (NC CRB) for the multi-dimensional parameter estimation of strictly non-circular (rectilinear) signal sources. Assuming a separable centro-symmetric R-D array, we show that in some special cases, the deterministic R-D NC CRB reduces to the existing deterministic R-D CRB for arbitrary signals. This suggests that no gain from strictly non-circular sources (NC gain) can be achieved in these cases. For more general scenarios, finding an analytical expression of the NC gain for an arbitrary number of sources is very challenging. Thus, in this paper, we simplify the derived NC CRB and the existing CRB for the special case of two closely-spaced strictly non-circular sources captured by a uniform linear array (ULA). Subsequently, we use these simplified CRB expressions to analytically compute the maximum achievable asymptotic NC gain for the considered two source case. The resulting expression only depends on the various physical parameters and we find the conditions that provide the largest NC gain for two sources. Our analysis is supported by extensive simulation results.Comment: submitted to IEEE Transactions on Signal Processing, 13 pages, 4 figure

R-dimensional ESPRIT-type algorithms for strictly second-order non-circular sources and their performance analysis

High-resolution parameter estimation algorithms designed to exploit the prior knowledge about incident signals from strictly second-order (SO) non-circular (NC) sources allow for a lower estimation error and can resolve twice as many sources. In this paper, we derive the R-D NC Standard ESPRIT and the R-D NC Unitary ESPRIT algorithms that provide a significantly better performance compared to their original versions for arbitrary source signals. They are applicable to shift-invariant R-D antenna arrays and do not require a centrosymmetric array structure. Moreover, we present a first-order asymptotic performance analysis of the proposed algorithms, which is based on the error in the signal subspace estimate arising from the noise perturbation. The derived expressions for the resulting parameter estimation error are explicit in the noise realizations and asymptotic in the effective signal-to-noise ratio (SNR), i.e., the results become exact for either high SNRs or a large sample size. We also provide mean squared error (MSE) expressions, where only the assumptions of a zero mean and finite SO moments of the noise are required, but no assumptions about its statistics are necessary. As a main result, we analytically prove that the asymptotic performance of both R-D NC ESPRIT-type algorithms is identical in the high effective SNR regime. Finally, a case study shows that no improvement from strictly non-circular sources can be achieved in the special case of a single source.Comment: accepted at IEEE Transactions on Signal Processing, 15 pages, 6 figure

On the SNR Variability in Noisy Compressed Sensing

Compressed sensing (CS) is a sampling paradigm that allows to simultaneously measure and compress signals that are sparse or compressible in some domain. The choice of a sensing matrix that carries out the measurement has a defining impact on the system performance and it is often advocated to draw its elements randomly. It has been noted that in the presence of input (signal) noise, the application of the sensing matrix causes SNR degradation due to the noise folding effect. In fact, it might also result in the variations of the output SNR in compressive measurements over the support of the input signal, potentially resulting in unexpected non-uniform system performance. In this work, we study the impact of a distribution from which the elements of a sensing matrix are drawn on the spread of the output SNR. We derive analytic expressions for several common types of sensing matrices and show that the SNR spread grows with the decrease of the number of measurements. This makes its negative effect especially pronounced for high compression rates that are often of interest in CS.Comment: 4 pages + reference

5G new radio physical downlink control channel reliability enhancements for multiple transmission-reception-point communications

Non-coherent transmission from multiple transmission-reception-points (TRPs), i.e., base stations, or base station panels to a user equipment (UE) is exploited in 5G New Radio (NR) to improve downlink reliability and cell-edge throughput. Ultra reliable low-latency communications (URLLC) and enhanced Mobile BroadBand (eMBB) are prominent target use-cases for multi-TRP or multi-panel transmissions. In Third-Generation Partnership Project (3GPP) Release 17 specifications, multi-TRP-based transmissions were specified for the physical downlink control channel (PDCCH) specifically to enhance its reliability and robustness. In this work, a comprehensive account of various multi-TRP reliability enhancement schemes applicable for the 5G NR PDCCH, including the ones supported by the 3GPP Release 17 specifications, is provided. The impact of the specifications for each scheme, UE and network complexity and their utility in various use-cases is studied. Their error performances are evaluated via link-level simulations using the evaluation criteria agreed in the 3GPP proceedings. The 3GPP-supported multi-TRP PDCCH repetition schemes, and the additionally proposed PDCCH repetition and diversity schemes are shown to be effective in improving 5G NR PDCCH reliability and combating link blockage in mmWave scenarios. The link-level simulations also provide insights for the implementation of the decoding schemes for the PDCCH enhancements under different channel conditions. Analysis of the performance, complexity and implementation constraints of the proposed PDCCH transmission schemes indicate their suitability to UEs with reduced-capability or stricter memory constraints and flexible network scheduling

Phase estimation of single tones next to modulated signals in the medium frequency R-mode system

Position, navigation, and timing information are critical to today’s infrastructures; as a result, the possibility of estimating ranges is being explored in more and more radio systems. One way to achieve this is to extend the modulation with time-synchronised aiding carriers and to estimate their phase at the receiver side. In this paper, we present two ways to minimise the negative influence of the modulation on the phase estimation. We show that the classical maximum likelihood estimator is still an efficient estimator for our problem, using a medium-frequency R-Mode signal as an example, and is therefore used in receiver designs. We then describe two possible ways to precondition the signal to increase the accuracy for short observations. As a first approach, we describe how window functions can positively change the signal-to-noise ratio for our estimation. As a second approach, we show the use of a narrowband bandpass filter. Finally, we show that these approaches, applied to real measurements, improve the variance of the estimate by up to two orders of magnitude

Clutter removal of near-field UWB SAR imaging for pipeline penetrating radar

Recently, ultrawideband (UWB) near-field synthetic aperture radar (SAR) imaging has been proposed for pipeline penetrating radar applications thanks to its capability in providing suitable resolution and penetration depth. Because of geometrical restrictions, there are many complicated sources of clutter in the pipe. However, this issue has not been investigated yet. In this article, we investigate some well-known clutter removal algorithms using full-wave simulated data and compare their results considering image quality, signal to clutter ratio and contrast. Among candidate algorithms, two-dimensional singular spectrum analysis (2-D SSA) shows a good potential to improve the signal to clutter ratio. However, basic 2-D SSA produces some artifacts in the image. Therefore, to mitigate this issue, we propose “modified 2-D SSA.” After developing the suitable clutter removal algorithm, wepropose a complete algorithm chain for pipeline imaging. An UWB nearfieldSARmonitoring system including anUWBM-sequence sensor and automatic positioner are implemented and the image of drilled perforations in a concrete pipe mimicking oil well structure as a case study is reconstructed to test the proposed algorithm. Compared to the literature, a comprehensive near-field SAR imaging algorithm including new clutter removal is proposed and its performance is verified by obtaining high-quality images in experimental results

Configurable pseudo noise radar imaging system enabling synchronous MIMO channel extension

In this article, we propose an evolved system design approach to ultra-wideband (UWB) radar based on pseudo-random noise (PRN) sequences, the key features of which are its user-adaptability to meet the demands provided by desired microwave imaging applications and its multichannel scalability. In light of providing a fully synchronized multichannel radar imaging system for short-range imaging as mine detection, non-destructive testing (NDT) or medical imaging, the advanced system architecture is presented with a special focus put on the implemented synchronization mechanism and clocking scheme. The core of the targeted adaptivity is provided by means of hardware, such as variable clock generators and dividers as well as programmable PRN generators. In addition to adaptive hardware, the customization of signal processing is feasible within an extensive open-source framework using the Red Pitaya ® data acquisition platform. A system benchmark in terms of signal-to-noise ratio (SNR), jitter, and synchronization stability is conducted to determine the achievable performance of the prototype system put into practice. Furthermore, an outlook on the planned future development and performance improvement is provided

Geometry-based channel modelling of MIMO channels in comparison with channel sounder measurements

In this paper we propose a flexible geometrybased propagation model for wireless communications developed at Ilmenau University of Technology. The IlmProp comprises a geometrical representation of the environment surrounding the experiment and a precise representation of the transmitting and receiving antennas. The IlmProp is capable of simulating Multi-User MIMO scenarios and includes a complete collection of tools to analyze the synthetic channels. In order to assess the potentials as well as the limits of our channel simulator we reconstruct the scenario encountered in a recent measurement campaign at Ilmenau University of Technology leading to synthetic data sets similar to the ones actually measured. The measurements have been collected with the RUSK MIMO multi-dimensional channel sounder. From the comparisons of the two channel matrices it is possible to derive useful information to improve the model itself and to better understand the physical origins of small-scale fading. In particular the effects of the different parameters on the synthetic channel have been studied in order to assess the sensibility of the model. This analysis shows that the correct positioning of a small number of scatterers is enough to achieve frequency selectiveness as well as specific traits of the channel statistics. The size of the scattering clusters, the number of scatterers per cluster, and the Rician K-factor can be modified in order to tune the channel statistics at will. To obtain higher levels of time variance, moving scatterers or time dependent reflection coefficients must be introduced

High-Precision Measurement of Sine and Pulse Reference Signals using Software-Defined Radio

This paper addresses simultaneous, high-precision measurement and analysis of generic reference signals by using inexpensive commercial off-the-shelf Software Defined Radio hardware. Sine reference signals are digitally down-converted to baseband for the analysis of phase deviations. Hereby, we compare the precision of the fixed-point hardware Digital Signal Processing chain with a custom Single Instruction Multiple Data (SIMD) x86 floating-point implementation. Pulse reference signals are analyzed by a software trigger that precisely locates the time where the slope passes a certain threshold. The measurement system is implemented and verified using the Universal Software Radio Peripheral (USRP) N210 by Ettus Research LLC. Applying standard 10 MHz and 1 PPS reference signals for testing, a measurement precision (standard deviation) of 0.36 ps and 16.6 ps is obtained, respectively. In connection with standard PC hardware, the system allows long-term acquisition and storage of measurement data over several weeks. A comparison is given to the Dual Mixer Time Difference (DMTD) and Time Interval Counter (TIC), which are state-of-the-art measurement methods for sine and pulse signal analysis, respectively. Furthermore, we show that our proposed USRP-based approach outperforms measurements with a high-grade Digital Sampling Oscilloscope.Comment: 10 pages, 15 figures, and 4 table