Communication at millimeter wave (mmWave) frequencies is defining a new era of wireless communication. The mmWave band offers higher bandwidth communication channels versus those presently used in commercial wireless systems. The applications of mmWave are immense: wireless local and personal area networks in the unlicensed band, 5G cellular systems, not to mention vehicular area networks, ad hoc networks, and wearables. Signal processing is critical for enabling the next generation of mmWave communication. Due to the use of large antenna arrays at the transmitter and receiver, combined with radio frequency and mixed signal power constraints, new multiple-input multiple-output (MIMO) communication signal processing techniques are needed. Because of the wide bandwidths, low complexity transceiver algorithms become important. There are opportunities to exploit techniques like compressed sensing for channel estimation and beamforming. This article provides an overview of signal processing challenges in mmWave wireless systems, with an emphasis on those faced by using MIMO communication at higher carrier frequencies.

An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems

The last 20 years have seen ever-increasing research activity in the field of human activity recognition. With activity recognition having considerably matured, so has the number of challenges in designing, implementing, and evaluating activity recognition systems. This tutorial aims to provide a comprehensive hands-on introduction for newcomers to the field of human activity recognition. It specifically focuses on activity recognition using on-body inertial sensors. We first discuss the key research challenges that human activity recognition shares with general pattern recognition and identify those challenges that are specific to human activity recognition. We then describe the concept of an Activity Recognition Chain (ARC) as a general-purpose framework for designing and evaluating activity recognition systems. We detail each component of the framework, provide references to related research, and introduce the best practice methods developed by the activity recognition research community. We conclude with the educational example problem of recognizing different hand gestures from inertial sensors attached to the upper and lower arm. We illustrate how each component of this framework can be implemented for this specific activity recognition problem and demonstrate how different implementations compare and how they impact overall recognition performance.

A tutorial on human activity recognition using body-worn inertial sensors

A Tutorial on Human Activity Recognition Using Body-Worn

This tutorial presents an overview of the technological advances in millimeter-wave (mm-wave) circuit components, antennas, and propagation that will soon allow 60-GHz transceivers to provide multigigabit per second (multi-Gb/s) wireless communication data transfers in the consumer marketplace. Our goal is to help engineers understand the convergence of communications, circuits, and antennas, as the emerging world of subterahertz and terahertz wireless communications will require understanding at the intersections of these areas. This paper covers trends and recent accomplishments in a wide range of circuits and systems topics that must be understood to create massively broadband wireless communication systems of the future. In this paper, we present some evolving applications of massively broadband wireless communications, and use tables and graphs to show research progress from the literature on various radio system components, including on-chip and in-package antennas, radio-frequency (RF) power amplifiers (PAs), low-noise amplifiers (LNAs), voltage-controlled oscillators (VCOs), mixers, and analog-to-digital converters (ADCs). We focus primarily on silicon-based technologies, as these provide the best means of implementing very low-cost, highly integrated 60-GHz mm-wave circuits. In addition, the paper illuminates characterization techniques that are required to competently design and fabricate mm-wave devices in silicon, and illustrates effects of the 60-GHz RF propagation channel for both in-building and outdoor use. The paper concludes with an overview of the standardization and commercialization efforts for 60-GHz multi-Gb/s devices, and presents a novel way to compare the data rate versus power efficiency for future broadband devices.

http://faculty.poly.edu/~tsr/wp-content/uploads/publications/abstract17.pdf

State of the Art in 60-GHz Integrated Circuits and Systems for Wireless Communications

Using electromyogram (EMG) signals to control upper-limb prostheses is an important clinical option, offering a person with amputation autonomy of control by contracting residual muscles. The dexterity with which one may control a prosthesis has progressed very little, especially when control- ling multiple degrees of freedom. Using pattern recognition to discriminate multiple degrees of freedom has shown great promise in the research literature, but it has yet to transition to a clinically viable option. This article describes the pertinent issues and best practices in EMG pattern recognition, identifies the major challenges in deploying robust control, and advocates research directions that may have an effect in the near future.

Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use.

The authors present a new versatile circuit building block called a differential difference current conveyor (DDCC). An IC technique for implementing the DDCC is also presented. The DDCC-based frequency-selective circuits and nonlinear building blocks such as multiplier, squarer and square rooter are developed. Experimental results are given to demonstrate the feasibility of the proposed techniques, and they show that DDCC-based circuits offer a competitive design choice to CCII-based and DDA-based circuits.

/pdf/cmos-differential-difference-current-conveyors-and-their-3dmi0gt50s.pdf

CMOS differential difference current conveyors and their applications

The Letter describes the design of a versatile analogue building block, termed an operational transresistance amplifer (OTRA). An operational transresistance amplifier has two low-input-impedance terminals and one low-output-impedance terminal. It is found to have a constant bandwidth indpendent of the gain in most closed-loop configurations. Simulation results are presented to demonstrate the constant-bandwidth performance. As an application example this amplifier is used to implement a MOSFET-C differentiator, of which analysis and simulation results are also presented.

Operational transresistance amplifier using CMOS technology

A new technique for classifying patterns of movement via electromyographic (EMG) signals is presented. Two methods (conventional autoregressive (AR) coefficients and cepstral coefficients) for extracting features from EMG signals and three classification algorithms (Euclidean Distance Measure (EDM), Weighted Distance Measure (WDM), and Maximum Likelihood Method (MLM)) for discriminating signals representative of broad classes of movements are described and compared. These three classifiers are derived from Bayes classifier with some assumptions, the relationship among them is discussed. The conventional MLM is modified to avoid heavy matrix inversion. Six able-bodied subjects with two pairs of surface electrodes located on bilateral sternocleidomastoid and upper trapezius muscles were studied in the experiment. The EMG signals of 20 repetitions of 10 motions were analyzed for each subject. Experimental results showed that mean recognition rate of the cepstral coefficients was at least 5% superior to that of the AR coefficients. The improvement achieved by the cepstral method was statistically significant for all the three classifiers. Reasons for the superiority of cepstral features were investigated from the feature space and frequency domain, respectively. The cepstral coefficients owned better cluster separability in feature space and they emphasized the more informative part in the frequency domain. The discrimination rate of the MLM was the highest among three classifiers. Incorporation of the cepstral features with the MLM could reduce the misclassification rate by 10.6% when compared with the combination of AR coefficients and EDM. Proper choice of five of ten motions could further raise the recognition rate to more than 95%. >

The application of cepstral coefficients and maximum likelihood method in EMG pattern recognition [movements classification]

A parasitic-capacitance-insensitive MOSFET-C integrator and differentiator using operational transresistance amplifiers are proposed and experimental results demonstrated. The bandwidths of these circuits are also independent of their gains. The required capacitances are smaller than those in previous work. Two new configurations of universal current-mode biquad filters based on these circuits are presented. A second-order bandpass filter constructed using universal biquad filters and another third-order Chebyshev lowpass filter with 0.1 dB passband ripple are breadboarded and the measured results presented.

Parasitic-capacitance-insensitive current-mode filters using operational transresistance amplifiers

This paper describes a design of time-to-digital converter (TDC) using a two-level conversion scheme. The first level is accomplished by a multi-phase sampling technique with the aid of delay-locked loop (DLL). Then the input signal and its adjacent sampling clock are manipulated and sent into a vernier delay line (VDL) sampling circuit at the second level. The proposed TDC can provide high resolution with less hardware compared to one level VDL sampling circuit with the same dynamic range. A new architecture of dual DLL circuit is also implemented to stabilize delay control against process and ambient variations. A test chip is designed and fabricated in 0.35-/spl mu/m logic technology. With an input reference clock within 130 to 160 MHz, the TDC achieves 24 to 30 ps resolution. The DNL is less than /spl plusmn/0.55 LSB and INL is within +1 to -1.5 LSB.

/pdf/a-high-precision-time-to-digital-converter-using-a-two-level-3s4bhqeh7e.pdf

Hen-Wai Tsao

Papers

CMOS differential difference current conveyors and their applications

Operational transresistance amplifier using CMOS technology

The application of cepstral coefficients and maximum likelihood method in EMG pattern recognition [movements classification]

Parasitic-capacitance-insensitive current-mode filters using operational transresistance amplifiers

A high-precision time-to-digital converter using a two-level conversion scheme