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Interferometric synthetic aperture radar (InSAR) is a radar technique widely used in geodesy and remote sensing applications, e.g., topography reconstruction and subsidence estimation. Phase unwrapping (PU) is one of the key procedures of InSAR signal processing. Artificial intelligence (AI) techniques have proven to be potentially powerful in many fields and have been introduced into the PU domain

Synthetic aperture radar (SAR) images are affected by a spatially correlated and signal-dependent noise called speckle, which is very severe and may hinder image exploitation. Despeckling is an important task that aims to remove such noise so as to improve the accuracy of all downstream image processing tasks. The first despeckling methods date back to the 1970s, and several model-based algorithms

In past years, we have witnessed the fields of geosciences and remote sensing and artificial intelligence (AI) become closer. Thanks to the massive availability of observational data, improved simulations, and algorithmic advances, these disciplines have found common objectives and challenges to help advance the modeling and understanding of the Earth system. Despite such great opportunities, we have

We discuss best practices for developing multilanguage remote sensing training. Our discussion is based on the approach developed by the NASA-funded Applied Remote Sensing Training (ARSET) program for Spanish-speaking countries. Best practices include incorporating Spanish language at all phases of the training cycle, from outreach activities to program evaluation, and full integration of Spanish-speaking

In this era of environmental challenges, such as global climate change and local and regional air pollution, it is increasingly important that students develop skills to understand and address interdisciplinary scientific issues related to atmospheric studies. Involving students in optical remote sensing research projects is a high-impact educational strategy that can foster student interest and persistence

Reports on GRSS society summer schools in 2020.

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Structural similarity (SSIM)-based distortion $\text {D}_{\text {SSIM}}$ is more consistent with human perception than the traditional mean squared error $\text {D}_{\text {MSE}}$ . To achieve better video encoding quality, many studies on optimal bit allocation (OBA) used $\text {D}_{\text {SSIM}}$ as the distortion metric. However, the MSE-based rate distortion optimization (RDO) was still used in

The physical process used in CCD cameras for image formation makes it imperative to simultaneously upsample and deblur the captured images. In this paper, we provide an efficient scheme to solve this problem through a nonlinear end-to-end mapping carried out by a novel deep light-weight residual neural network. The proposed network is designed based on two main modules, namely, image upsampling and

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We would like to welcome the readers to the second issue of the IEEE Communications Surveys and Tutorials in 2021. This issue includes 21 articles covering different aspects of communication networks. In particular, these articles survey and tutor various issues in “Wireless Communications,” “Vehicular and Sensor Communications,” “IoT and M2M,” “Network Security,” “Multimedia Communications,” “Internet

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged

Joint radar and communication (JRC) has recently attracted substantial attention. The first reason is that JRC allows individual radar and communication systems to share spectrum bands and thus improves the spectrum utilization. The second reason is that JRC enables a single hardware platform, e.g., an autonomous vehicle or a UAV, to simultaneously perform the communication function and the radar function

Internet of Things (IoT) is an emerging technology that makes people’s lives smart by conquering a plethora of diverse application and service areas. In near future, the fifth-generation (5G) wireless networks provide the connectivity for this IoT ecosystem. It has been carefully designed to facilitate the exponential growth in the IoT field. Network slicing is one of the key technologies in the 5G

Recently, there has been an increase in studies relating to the Internet of Things (IoT) in various fields, such as smart cities, smart homes, smart factories, and healthcare. In an IoT environment, several entities, including users, devices, and information resources, are interconnected and interworked with services. Therefore, interoperability between different entities is essential to accomplish

In the above article [1] , the references in Tables V – IX were incorrectly assigned. The corrected tables are provided here.

In mobile speech communication, speech signals can be severely corrupted by background noise when the far-end talker is in a noisy acoustic environment. To suppress background noise, speech enhancement systems are typically integrated into mobile phones, in which one or more microphones are deployed. In this study, we propose a novel deep learning based approach to real-time speech enhancement for

The use of deep neural networks (DNNs) has dramatically elevated the performance of speech enhancement over the last decade. However, to achieve strong enhancement performance typically requires a large DNN, which is both memory and computation consuming, making it difficult to deploy such speech enhancement systems on devices with limited hardware resources or in applications with strict latency requirements

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In this letter, we study data-aided sensing (DAS) for distributed detection in wireless sensor networks (WSNs) when sensors’ measurements are correlated. In particular, we derive a node selection criterion based on the J-divergence in DAS for reliable decision subject to a decision delay constraint. Based on the proposed J-divergence based DAS, the nodes can be selected to rapidly increase the log-likelihood

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This letter investigates the resource allocation problem for multiple Unmanned Aerial Vehicles (UAVs)-served Machine-to-Machine (M2M) communications. Our goal is to maximize the sum-rate of UAVs-served M2M communications by jointly considering the transmission power, transmission mode, frequency spectrum, relay selection and the trajectory of UAVs. In order to model the uncertainty of stochastic environments

Conventional hybrid precoding and combining based transceivers require a large number of high-resolution radio frequency (RF) phase shifters (PSs), which impose prohibitive hardware costs and power consumption. To address the above issue, both partially connected RF PSs and low-resolution PSs have been proposed. However, the performance limits of these low-cost designs have not been investigated theoretically

This letter proposes a novel time-asynchronous non-orthogonal multiple access (TA-NOMA) in downlink multicarrier systems. TA-NOMA applies an intentional time offset to control interference between multi-users and to improve spectral efficiency. We first propose a transceiver design for TA-NOMA, and analyze a novel type of interference caused by the intentional time offset. Based on the analysis, a

Millimeter wave (mmWave) relaying has been introduced recently as a solution to extend the coverage of mmWave communication systems and to deal with the blockage problem as well. In order for the relay probing process to identify the most suitable relays, we should maintain an intelligent trade-off between the number of probed relays and the overhead due to beamforming training (BT). This letter leverages

Unmanned aerial vehicle (UAV) can work as mobile edge computing (MEC) server in the sky to provide communication and computation services to ground terminals (GTs), due to its high mobility. However, UAV might work in complicated environment, where UAV-GT links being frequently blocked by ground obstacles, then leading to a poor quality of service (QoS) on task latency. To this problem, reconfigurable

Over-the-air computation (AirComp) leveraging the superposition property of wireless multiple-access channel (MAC), is a promising technique for effective data collection and computation of large-scale wireless sensor measurements in Internet of Things applications. Most existing work on AirComp only considered computation of spatial-and-temporal independent sensor signals, though in practice different

Age of Information (AoI) is a critical metric in status update systems as these systems require the fresh updates. This letter investigates the uplink of an Internet-of-Thing (IoT) network where ${L}$ nodes transmit their information packets to a base station. The effects of the arrival rate of packets at the nodes, the number of nodes in the system, and queue length of each node have been studied

A novel coding strategy is proposed for a broadcast setting with two transmitter (TX) antennas and two single-antenna receivers (RX). The strategy consists of using space-time block coding to send a common message (to be decoded by both RXs) across the two TX antennas, while each TX antenna also sends a private message to one of the RXs. The relative weight of the private and common messages from each

Coherent light fidelity (LiFi) systems which uses coherent detection at the receiver are attracting more and more interest as they provide many advantages over the conventional intensity modulation / direct detection (IM/DD) LiFi systems. Recent efforts to boost the performance of IM/DD LiFi systems include the usage of multiple-input-multiple-output (MIMO) technology, among which spatial multiplexing

This paper studies an intelligent reflecting surface (IRS) aided wireless powered sensor network (WPSN). Specifically, a power station (PS) provides wireless energy to multiple internet of thing (IoT) devices which supports them to deliver their own messages to an access point (AP). Moreover, we deploy an IRS to enhance the performance of the WPSN by intelligently adjusting the phase shift of each

This paper presents a part of our ground-breaking work on evaluation of buildings in terms of wireless friendliness at the building-design stage. The main goal is to devise building design practices that provide for a good performance of wireless networks deployed in buildings. In this paper, the interference gain (IG) and power gain (PG) are defined as two figures of merit (FoM) of the wireless performance

Detecting ever increasing anomalous signals is critical to effective spectrum management. In this letter, we present a radio anomaly detection algorithm based on modified generative adversarial network (GAN). Firstly, short time fourier transform (STFT) is applied to obtain the spectrogram image from the received signal. Then, a novel encoder-GAN (E-GAN) structure is proposed by incorporating an encoder

The meta distribution (MD) of the signal to interference ratio (SIR) extends stochastic geometry analysis from spatial averages to reveals find-grained information about the network performance. There have been several efforts to establish the MD framework for the Poisson point process (PPP) and other ergodic point processes. However, the MD analysis for finite point processes is overlooked. In this

In this letter, we propose a deep learning-based dual mode orthogonal frequency division multiplexing with index modulation (DM-OFDM-IM) detector called DeepDM, which is close to optimal bit error rate (BER) performance with low computational complexity. DeepDM adopts a concatenation of convolutional neural network (CNN) and deep neural network (DNN) to detect index bits and carrier bits separately

This letter first investigates the effects of inter-frame interference (IFI) on the recent eigendecomposition-precoded (EVD) non-orthogonal frequency-division multiplexing (NOFDM) transmission scheme, where subcarrier spacing is set smaller than that of orthogonal frequency-division multiplexing (OFDM). More specifically, the system model of EVD-NOFDM is generalized to support multi-frame transmission