Current medical imaging technologies allow visualization of tissue anatomy in the human body at resolutions ranging from 100 micrometers to 1 millimeter. These technologies are generally not sensitive enough to detect early-stage tissue abnormalities associated with diseases such as cancer and atherosclerosis, which require micrometer-scale resolution. Here, optical coherence tomography was adapted to allow high-speed visualization of tissue in a living animal with a catheter-endoscope 1 millimeter in diameter. This method, referred to as "optical biopsy," was used to obtain cross-sectional images of the rabbit gastrointestinal and respiratory tracts at 10-micrometer resolution.

In Vivo Endoscopic Optical Biopsy with Optical Coherence Tomography

The ever-increasing demand for higher data rates in wireless communications in the face of limited or underutilized spectral resources has motivated the introduction of cognitive radio. Traditionally, licensed spectrum is allocated over relatively long time periods and is intended to be used only by licensees. Various measurements of spectrum utilization have shown substantial unused resources in frequency, time, and space [1], [2]. The concept behind cognitive radio is to exploit these underutilized spectral resources by reusing unused spectrum in an opportunistic manner [3], [4]. The phrase cognitive radio is usually attributed to Mitola [4], but the idea of using learning and sensing machines to probe the radio spectrum was envisioned several decades earlier (cf., [5]).

Spectrum Sensing for Cognitive Radio : State-of-the-Art and Recent Advances

Time-Frequency Analysis.

The future of mobile communications looks exciting with the potential new use cases and challenging requirements of future 6th generation (6G) and beyond wireless networks. Since the beginning of the modern era of wireless communications, the propagation medium has been perceived as a randomly behaving entity between the transmitter and the receiver, which degrades the quality of the received signal due to the uncontrollable interactions of the transmitted radio waves with the surrounding objects. The recent advent of reconfigurable intelligent surfaces in wireless communications enables, on the other hand, network operators to control the scattering, reflection, and refraction characteristics of the radio waves, by overcoming the negative effects of natural wireless propagation. Recent results have revealed that reconfigurable intelligent surfaces can effectively control the wavefront, e.g., the phase, amplitude, frequency, and even polarization, of the impinging signals without the need of complex decoding, encoding, and radio frequency processing operations. Motivated by the potential of this emerging technology, the present article is aimed to provide the readers with a detailed overview and historical perspective on state-of-the-art solutions, and to elaborate on the fundamental differences with other technologies, the most important open research issues to tackle, and the reasons why the use of reconfigurable intelligent surfaces necessitates to rethink the communication-theoretic models currently employed in wireless networks. This article also explores theoretical performance limits of reconfigurable intelligent surface-assisted communication systems using mathematical techniques and elaborates on the potential use cases of intelligent surfaces in 6G and beyond wireless networks.

Wireless Communications Through Reconfigurable Intelligent Surfaces

Transmission through reconfigurable intelligent surfaces (RISs), which control the reflection/scattering characteristics of incident waves in a deliberate manner to enhance the signal quality at the receiver, appears as a promising candidate for future wireless communication systems. In this paper, we bring the concept of RIS-assisted communications to the realm of index modulation (IM) by proposing RIS-space shift keying (RIS-SSK) and RIS-spatial modulation (RIS-SM) schemes. These two schemes are realized through not only intelligent reflection of the incoming signals to improve the reception but also utilization of the IM principle for the indices of multiple receive antennas in a clever way to improve the spectral efficiency. Maximum energy-based suboptimal (greedy) and exhaustive search-based optimal (maximum likelihood) detectors of the proposed RIS-SSK/SM schemes are formulated and a unified framework is presented for the derivation of their theoretical average bit error probability. Extensive computer simulation results are provided to assess the potential of RIS-assisted IM schemes as well as to verify our theoretical derivations. Our findings also reveal that RIS-based IM, which enables high data rates with remarkably low error rates, can become a potential candidate for future wireless communication systems in the context of beyond multiple-input multiple-output (MIMO) solutions.

Reconfigurable Intelligent Surface-Based Index Modulation: A New Beyond MIMO Paradigm for 6G

This paper considers mutual interference mitigation (MIM) for frequency modulated continuous wave (FMCW) automotive radar. Particularly, we exploit distinguished features of target and interference components in the fast-time-frequency (fTF) representation and, as opposed to existing fast-time MIM methods on nulling the interference component, propose to directly recover the underwhelmed target component via the fast-time-frequency mode retrieval (fTFMR). This is achieved by utilizing the Fourier synchrosqueezed transform (FSST) and introducing robust ridge detection that, in combination, guarantees that the recovered fast-time errors of the target signal are bounded at separable time intervals. Comprehensive performance comparison with a list of baseline methods shows that the proposed MIM method yields higher output signal-to-interference-noise ratios (SINRs) at both the range and velocity domains and reduces the false alarm.

Automotive Radar Interference Mitigation with Fast-Time-Frequency Mode Retrieval

We report the first experimental results on the linear encoder based on a resonant-tunneling-diode (RTD) and a periodic linear array of carbon-fiber reinforced plastic (CFRP) plates as a scale. By using polarization dependent reflection signal, we were able to detect the incremental position in a non-contact manner.

Terahertz Polarimetric Sensing for Linear Encoder Based on a Resonant-Tunneling-Diode and CFRP polarizing plates

We consider the problem of channel estimation for millimeter wave (mmWave) systems, where, to minimize the hardware complexity and power consumption, an analog transmit beamforming and receive combining structure with only one radio frequency (RF) chain at the base station (BS) and mobile station (MS) is employed. Most existing works for mmWave channel estimation exploit sparse scattering characteristics of the channel. In addition to sparsity, mmWave channels may exhibit angular spreads over the angle of arrival (AoA), angle of departure (AoD), and elevation domains. In this paper, we show that angular spreads give rise to a useful low-rank structure that, along with the sparsity, can be simultaneously utilized to reduce the sample complexity, i.e. the number of samples needed to successfully recover the mmWave channel. Specifically, to effectively leverage the joint sparse and low-rank structure, we develop a two-stage compressed sensing method for mmWave channel estimation, where the sparse and low-rank properties are respectively utilized in two consecutive stages, namely, a matrix completion stage and a sparse recovery stage. Our theoretical analysis reveals that the proposed two-stage scheme can achieve a lower sample complexity than a direct compressed sensing method that exploits only the sparse structure of the mmWave channel. Simulation results are provided to corroborate our theoretical results and to show the superiority of the proposed two-stage method.

Millimeter Wave Channel Estimation via Exploiting Joint Sparse and Low-Rank Structures

Methods are provided for determining properties of an anisotropic formation (including both fast and slow formations) surrounding a borehole. A logging-while-drilling tool is provided that is moveable through the borehole. The logging-while drilling tool has at least one dipole acoustic source spaced from an array of receivers. During movement of the logging- while-drilling tool, the at least one dipole acoustic source is operated to excite a time-varying pressure field in the anisotropic formation surrounding the borehole. The array of receivers is used to measure waveforms arising from the time- varying pressure field in the anisotropic formation surrounding the borehole. The waveforms are processed to determine a parameter value that represents shear directionality of the anisotropic formation surrounding the borehole.

Methods and systems for determining fast and slow shear directions in an anisotropic formation using a logging while drilling tool

This paper introduces a terahertz (THz)-based absolute positioning system with a single THz transceiver as the read head and a multi-level pseudo-random reflectance pattern (e.g., multi-level m-sequences) as the high-resolution scale in a compressed scanning mode. One of key technical challenges here is to computationally recover the multi-level pseudo-random reflectance pattern from compressed measurements. To this end, we develop a variational Bayesian approach to exploit the finite alphabet of reflectance levels and enable a pixel-wise iterative inference for fast recovery. Numerical results confirm the effectiveness of the proposed method.

Pu Wang

Papers

Automotive Radar Interference Mitigation with Fast-Time-Frequency Mode Retrieval

Terahertz Polarimetric Sensing for Linear Encoder Based on a Resonant-Tunneling-Diode and CFRP polarizing plates

Millimeter Wave Channel Estimation via Exploiting Joint Sparse and Low-Rank Structures

Methods and systems for determining fast and slow shear directions in an anisotropic formation using a logging while drilling tool

Terahertz Imaging of Multi-Level Pseudo-Random Reflectance