相关论文: A Cognitive Sub-Nyquist MIMO Radar Prototype
In this paper, we consider the downlink of a massive multiple-input-multiple-output (MIMO) single user transmission system operating in the millimeter wave outdoor narrowband channel environment. We propose a novel receive spatial…
Radar for deep learning-based human identification has become a research area of increasing interest. It has been shown that micro-Doppler ($\mu$-D) can reflect the walking behavior through capturing the periodic limbs' micro-motions. One…
We present a sub-Nyquist analog-to-digital converter of wideband inputs. Our circuit realizes the recently proposed modulated wideband converter, which is a flexible platform for sampling signals according to their actual bandwidth…
Beamforming techniques are proposed for a joint multi-input-multi-output (MIMO) radar-communication (RadCom) system, where a single device acts both as a radar and a communication base station (BS) by simultaneously communicating with…
Partial feedback in multiple-input multiple-output (MIMO) communication systems provides tremendous capacity gain and enables the transmitter to exploit channel condition and to eliminate channel interference. In the case of severely…
Recent years have witnessed growing interest in reduced cost radar systems operating with low power. Multiple-input multiple-output (MIMO) radar technology is known to achieve high performance sensing by probing with multiple orthogonal…
In this paper, we consider a reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output communication system with multiple antennas at both the base station (BS) and the user. We plan to maximize the achievable rate…
Because optical systems have huge bandwidth and are capable of generating low noise short pulses they are ideal for undersampling multi-band signals that are located within a very broad frequency range. In this paper we propose a new scheme…
Reconfigurable intelligent surface (RIS) is a new paradigm that has great potential to achieve cost-effective, energy-efficient information modulation for wireless transmission, by the ability to change the reflection coefficients of the…
Accurate reconstruction of static and rapidly moving targets demands three-dimensional imaging solutions with high temporal and spatial resolution. Radar sensors are a promising sensing modality because of their fast capture rates and their…
Joint estimation of carrier frequency and direction of arrival (DOA) for multiple signals has been found in many practical applications such as Cognitive Radio (CR). However, Nyquist sampling mechanism is costly or implemented due to wide…
Recently, several array radar structures combined with sub-Nyquist techniques and corresponding algorithms have been extensively studied. Carrier frequency and direction-of-arrival (DOA) estimations of multiple narrow-band signals received…
We consider a radar architecture where an illuminator composed of few sources is used as a feeder for a (passive) reconfigurable intelligent surface (RIS), so as to mimic the behavior of a multiple-input multiple-output (MIMO) radar…
Hybrid Reconfigurable Intelligent Surfaces (HRISs) constitute a new paradigm that redefines smart metasurfaces, not only offering tunable reflections of incoming signals, but also incorporating signal reception and processing capabilities.…
A stylized compressed sensing radar is proposed in which the time-frequency plane is discretized into an N by N grid. Assuming the number of targets K is small (i.e., K much less than N^2), then we can transmit a sufficiently "incoherent"…
Multiple-input multiple-output (MIMO) radars offer higher resolution, better target detection, and more accurate target parameter estimation. Due to the sparsity of the targets in space-velocity domain, we can exploit Compressive Sensing…
This paper considers efficient sampling of simultaneously sparse and correlated (S$\&$C) signals. Such signals arise in various applications in array processing. We propose an implementable sampling architecture for the acquisition of…
While machine learning (ML)-based receiver algorithms have received a great deal of attention in the recent literature, they often suffer from poor scaling with increasing spatial multiplexing order and lack of explainability and…
This paper addresses the design of transmit precoder and receive combiner matrices to support $N_{\rm s}$ independent data streams over a time-division duplex (TDD) point-to-point massive multiple-input multiple-output (MIMO) channel with…
In this paper, the problem of optimal power allocation in Cognitive Radio (CR) Multiple Input Multiple Output (MIMO) systems is treated. The focus is on providing limited feedback solutions aiming at maximizing the secondary system rate…