Printing sensors and electronics over flexible substrates are an area of significant interest due to low-cost fabrication and possibility of obtaining multifunctional electronics over large areas. Over the years, a number of printing technologies have been developed to pattern a wide range of electronic materials on diverse substrates. As further expansion of printed technologies is expected in future for sensors and electronics, it is opportune to review the common features, the complementarities, and the challenges associated with various printing technologies. This paper presents a comprehensive review of various printing technologies, commonly used substrates and electronic materials. Various solution/dry printing and contact/noncontact printing technologies have been assessed on the basis of technological, materials, and process-related developments in the field. Critical challenges in various printing techniques and potential research directions have been highlighted. Possibilities of merging various printing methodologies have been explored to extend the lab developed standalone systems to high-speed roll-to-roll production lines for system level integration.

https://cris.fbk.eu/bitstream/11582/300858/1/Technologies%20for%20Printing%20Sensors%20and%20Electronics%20Over%20Large%20Flexible%20Substrates-A%20Review.pdf

Technologies for Printing Sensors and Electronics Over Large Flexible Substrates: A Review

Where you can find the array signal processing easily? Is it in the book store? On-line book store? are you sure? Keep in mind that you will find the book in this site. This book is very referred for you because it gives not only the experience but also lesson. The lessons are very valuable to serve for you, that's not about who are reading this array signal processing book. It is about this book that will give wellness for all people from many societies.

Array signal processing

This paper presents materials and designs for an ultrathin, stretchable class of device that is capable of lamination onto the surface of the skin, for wireless determination of dielectric and surface strain properties. The sensor exploits LC resonators with capacitive electrodes whose radio frequency characteristics change with variations in skin properties, and is capable of conformal and spontaneous integration with skin due to their skin-like, “epidermal”, mechanical properties. Resonance frequencies of the LC resonators can be measured wirelessly through changes in the absorption of electromagnetic energy from a coil connected to an impedance measurement setup and placed in proximity to the epidermal device. Experimental results demonstrate that the device offers a precision of 1.1 (arbitrary unit of a reference commercial hydration meter) for hydration and 1.3% for strain detection, with good stability and low drift. Measurement of simulated lymphedema using an expandable balloon with an attached sensor further demonstrates the potential for using such a sensor in monitoring skin swelling. Finite element simulation of physical deformation and associated changes in electrical properties enable quantitative interpretation of the experimental results. The results may have relevance for wireless evaluation of the skin, for applications ranging from dermatology and cosmetology to health/wellness monitoring (lymphedema, transdermal water loss, edema, and psychological stress).

Materials and Designs for Wireless Epidermal Sensors of Hydration and Strain

The estimation of the directions of arrival (DoAs) of narrow-band signals impinging on a linear antenna array is addressed within the Bayesian compressive sensing (BCS) framework. Unlike several state-of-the-art approaches, the voltages at the output of the receiving sensors are directly used to determine the DoAs of the signals thus avoiding the computation of the correlation matrix. Towards this end, the estimation problem is properly formulated to enforce the sparsity of the solution in the linear relationships between output voltages (i.e., the problem data) and the unknown DoAs. Customized implementations exploiting the measurements collected at a unique time instant (single-snapshot) and multiple time instants (multiple-snapshots) are presented and discussed. The effectiveness of the proposed approaches is assessed through an extensive numerical analysis addressing different scenarios, signal configurations, and noise conditions. Comparisons with state-of-the-art methods are reported, as well.

Directions-of-Arrival Estimation Through Bayesian Compressive Sensing Strategies

Inspired by the recent advances in deep learning, we propose a novel iterative belief propagation – convolutional neural network (BP-CNN) architecture for channel decoding under correlated noise. This architecture concatenates a trained CNN with a standard BP decoder. The standard BP decoder is used to estimate the coded bits, followed by a CNN to remove the estimation errors of the BP decoder and obtain a more accurate estimation of the channel noise. Iterating between BP and CNN will gradually improve the decoding SNR and, hence, result in better decoding performance. To train a well-behaved CNN model, we define a new loss function that involves not only the accuracy of the noise estimation but also the normality test for the estimation errors, i.e., to measure how likely the estimation errors follow a Gaussian distribution. The introduction of the normality test to the CNN training shapes the residual noise distribution and further reduces the bit error rate of the iterative decoding, compared to using the standard quadratic loss function. We carry out extensive experiments to analyze and verify the proposed framework. 1 1 Code is available at https://github.com/liangfei-info/Iterative-BP-CNN .

An Iterative BP-CNN Architecture for Channel Decoding

In antenna arrays, mutual coupling between antenna elements is well known as an undesired effect, which degrades the performance of array signal-processing algorithms. The compensation of such an undesired effect has been a popular research topic throughout the years. Various approaches for mutual-coupling compensation have been developed, and they can easily be found in the open literature. In general, the mutual-coupling problems for a transmitting and receiving array are different, even if the physical geometry of the array remains unchanged. However, it seems that antenna engineers are not well aware of such differences in the analysis of receiving antenna arrays. In this note, the mutual-coupling problems in transmitting and receiving antenna arrays are revisited. The differences between the mutual coupling and mutual impedances for transmitting and receiving antenna arrays are explained. It is concluded that the mutual-coupling problems of transmitting and receiving arrays are in general different, and hence different mutual impedances should be used for mutual-coupling analysis and compensation.

A Note on the Mutual-Coupling Problems in Transmitting and Receiving Antenna Arrays

This letter investigates the effect of antenna mutual coupling involving the unconventional concepts of transmitting and receiving mutual impedances on the multiple-input multiple-output (MIMO) channel capacity. Suitable expressions for the optimum power allocation strategy under the influence of antenna mutual coupling are derived. The undertaken numerical analysis shows a significant difference in the calculated results for the optimized average channel capacity for the cases when antenna mutual coupling is taken into account or neglected. The obtained results indicate that to obtain the correct optimum power allocation strategy antenna mutual coupling effects need to be properly taken into consideration. This claim is supported by computer simulation examples.

Optimizing MIMO Channel Capacities Under the Influence of Antenna Mutual Coupling

For a multiple-input multiple-output (MIMO) system with more antennas at the receiver than the transmitter, selecting the same number of receiver antennas as the number of transmit antennas captures most of the advantages of MIMO capacity performance and reduces the system hardware and computational cost at the same time. In this paper, a fast and global-search receive antenna selection algorithm is proposed for this MIMO array configuration. Different from many existing fast but `local' antenna selection algorithms which obtain the sub-optimal channel submatrix by adding or removing one row per step, our algorithm acquires the near-optimal channel matrix by {directly} and {rapidly} searching the maximum-volume submatrix of the original channel matrix. Due to its "globally searching" property, our antenna selection algorithm leads to a substantial improvement in the capacity optimality for moderate to high SNRs, and obtains almost the same capacity performance as that of the exhaustive-search-based optimal antenna selection algorithm. Furthermore, the computational load and memory requirement for our antenna selection method are still comparable to those of the existing sub-optimal antenna selection methods. Numerical results are provided to verify the validity of the proposed methods.

Global and Fast Receiver Antenna Selection for MIMO Systems

Based on the rank reduction theory (RARE), a decoupled method for 2D direction of arrival (DOA) estimation in the presence of elevation-dependent mutual coupling is proposed for compact uniform circular arrays (UCAs). Using a new formulation of the beamspace array manifold in the presence of mutual coupling, the azimuth estimates are decoupled from the elevation estimates and obtained with no need for the exact knowledge of mutual coupling. For the elevation estimation, a 1D parameter search in the elevation space for every azimuth estimate is performed with the elevation-dependent mutual coupling effect compensated efficiently. Though the computational load for the elevation estimation is increased compared to that of the original UCA-RARE algorithm, the 1D parameter search in our method overcomes most of the inherent shortcomings of the UCA-RARE algorithm. This enables unambiguous and paired 2D DOA estimation with the elevation-dependent mutual coupling effect being compensated for effectively. Numerical examples are presented to demonstrate the effectiveness of the proposed method.

Decoupled 2D Direction of Arrival Estimation Using Compact Uniform Circular Arrays in the Presence of Elevation-Dependent Mutual Coupling

An experimental study is performed to investigate the improvement of direction-of-arrival (DOA) estimation using the recently proposed receiving mutual impedances for mutual coupling compensation. A seven-monopole antenna array is constructed and used in DOA estimation employing the MUSIC algorithm. Comparisons are made with the case of using the conventional mutual impedances for mutual coupling compensation. All experiments are carried out inside an anechoic chamber. Results are obtained for one- and two-source experiments which indicate that the performance of DOA estimation in the presence of mutual coupling can be significantly improved when the mutual coupling effect is compensated by using the receiving mutual impedances.

Hon Tat Hui

Papers

A Note on the Mutual-Coupling Problems in Transmitting and Receiving Antenna Arrays

Optimizing MIMO Channel Capacities Under the Influence of Antenna Mutual Coupling

Global and Fast Receiver Antenna Selection for MIMO Systems

Decoupled 2D Direction of Arrival Estimation Using Compact Uniform Circular Arrays in the Presence of Elevation-Dependent Mutual Coupling

Improved DOA Estimations Using the Receiving Mutual Impedances for Mutual Coupling Compensation: An Experimental Study