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Background: Measuring students' self‐regulation skills is essential to understand how they approach their learning tasks in order to identify areas where they might need additional support. Traditionally, self‐report questionnaires and think aloud protocols have been used to measure self‐regulated learning skills (SRL). However, these methods are based on students' interpretation, so they are prone to potential inaccuracy. Recently, there has been a growing interest in utilizing learning analytics (LA) to capture students' self‐regulated learning (SRL) by extracting indicators from their online trace data. Objectives: This paper aims to identify the indicators and metrics employed by previous studies to measure SRL in higher education. Additionally, the study examined how these measurements were validated. Methods: Following the protocol of Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA), this study conducted an analysis of 25 articles, published between 2015 and 2022, and sourced from major databases. Results and Conclusions: The results showed that previous research used a variety of indicators to capture learners' SRL. Most of these indicators are related to time management skills, such as indicators of engagement, regularity, and anti‐procrastination. Furthermore, the study found that the majority of the reviewed studies did not validate the proposed measurements based on any theoretical models. This highlights the importance of fostering closer collaboration between learning analytics and learning science to ensure the extracted indicators accurately represent students' learning processes. Moreover, this collaboration can enhance the validity and reliability of data‐driven approaches, ultimately leading to more meaningful and impactful educational interventions. Lay Description: What is already known about this topic?: Measuring students' self‐regulation skills is essential for understanding their learning approaches and identifying areas requiring further support.Traditionally, questionnaires and interviews have been used to measure learners' self‐regulation; however, these methods rely on students' own views, which can sometimes be unreliable.Recently, there has been more interest in using learning analytics to measure students' self‐regulation based on data extracted from their online activities. What this paper adds?: This paper systematically analyses how previous studies used learning analytics to measure students' self‐regulation in higher education.It examines how these measurements were validated. Implications for practise and/or policy: More collaboration is needed between researcher in learning science and learning analytics is essential to ensure that the metrics and methods developed are not only theoretically sound but also practically relevant. This collaboration ultimately contributes to the design of enhanced learning experiences and outcomes. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of data routing in backhaul networks using Unmanned Aerial Vehicles (UAVs) to relay data from Small Cells (SCs) to the core network. The objective is to maximize the total fulfilled demand of data to be routed, while ensuring technical requirements such as hop constraints and edge capacity. The problem is formulated using a compact mixed-integer programming model, which can solve small- and medium-sized topologies. In addition, a fast constructive heuristic based on a maximal tree is developed to solve large-scale topologies, resulting in a significant reduction in CPU time. The quality of the heuristic is evaluated by using column generation for solving the linear programming relaxation of an exponential formulation. The computational study shows the effectiveness and value of the proposed compact model and constructive heuristic for various topology sizes. Furthermore, experiments demonstrate that by keeping the network setup constant and updating the demand vector only, the computational time of the compact model can be drastically reduced for all topology sizes. [ABSTRACT FROM AUTHOR]

Housing dispersal in emerging cities should be investigated as it occurs to achieve a better understanding of future housing dispersal. In this study, housing preferences are analyzed in Doha Metropolitan Area based on Gordon's theory. Machine learning (especially the generalized adversarial network) is utilized to predict the future urban growth of the city. The housing dispersal of expatriates is visualized in the predicted urban growth map of Doha city based on an investigation of housing supply trends, household income levels, government vision, and census data. The study proves the feasibility of this approach for managing urban growth in emerging cities worldwide. It is a robust solution to the increasing imbalance in the urban morphology of metropolitan cities. The conclusions drawn from the broad-spectrum housing dispersal findings of this study will inform policymakers and planners regarding the realities of spatial patterns and future urban growth. [ABSTRACT FROM AUTHOR]

The coexistence of communication and sensing services in the next wireless communication systems, i.e., beyond 5G and 6G systems, revive the central role of interference management techniques such as interference alignment, coordinated multipoint transmission, and cell-free massive multiple-input–multiple-output (MIMO), in defeating interference and achieving the network capacity. In this article, we consider the $K$ -user single-input–single-output (SISO) X-channel and its variants ($2 \times K$ and $K \times 2$) in fast-fading environments. This can theoretically model many practical use cases for beyond 5G and 6G networks. For instance, it can model the case of having $K$ cars communicating with another $K$ cars, while former cars are sensing environment using the latter ones (in a cooperative, bistatic, and active approach) over the same time and frequency resources. We assume that the transmitters have access to synergistic alternating channel state information at the transmitter (CSIT) where it alternates between three states: perfect (P), delayed (D), and no-CSIT (N), and these states are associated with fractions of time denoted by $\lambda _{P}$ , $\lambda _{D}$ , and $\lambda _{N}$ , respectively. We develop novel degree-of-freedom (DoF) achievability schemes that exploit the synergy of the instantaneous CSIT and the delayed CSIT to retrospectively align interference in the subsequent channel uses. In particular, we show that the sum DoF of the $K$ -user SISO X-channel is at least ${2K}/{K + 1}$ , using a two-phase transmission scheme over finite symbols channel extension and under a certain distribution of the CSIT availability of $\Lambda (\lambda _{P}=({1}/{3}), \lambda _{D}= ({1}/{3}), \lambda _{N}=({1}/{3}))$. This achievability result can be considered as a tight lower bound where it coincides with the best lower bound known for the same network but with partial output feedback instead of alternating CSIT. In addition, it shows that the role of synergistically alternating CSIT with distribution $\Lambda ({1}/{3},{1}/{3},{1}/{3})$ is equivalent to the one of the partial output feedback. Moreover, we show the optimality of the proposed two-phase-based scheme using a simple combinatorial proof. This establishes a DoF lower bound, which is strictly better than the best lower bound known for the case of delayed CSI for all values of $K$. Thus, the proposed schemes offer higher DoF gain in comparison to delayed CSIT and no-CSIT. [ABSTRACT FROM AUTHOR]

A secure energy efficient approach is proposed to connect Internet of Things (IoT) sensors that operate with limited power resources. This is done by optimizing simultaneously the energy efficiency, the communication rate and the network security while limiting the potential data leakage and tracking the finite battery status evolution. The proposed model uses spatial diversity in addition to artificial jamming introduced by an intermediate device to forward the data from the sensors to the destination and to secure the communication links without draining the rechargeable batteries. The energy harvested by the source is also maximized without affecting the security level of the network. The outage secrecy capacity is derived to evaluate the security level. Furthermore, the system power stability is analyzed using Markov chains and statistical approaches to validate the efficiency of the proposed technique in maintaining the system in a self-sufficient mode and making it operate without the assistance of external power resources. [ABSTRACT FROM AUTHOR]

This study aims to visualize the future housing dispersal of expatriates, based on the predicted urban growth in emerging cities. Generalized adversarial networks (GANs) will be utilized to predict the future urban growth of Doha Metropolitan emerging city. The housing dispersal of expatriates will be visualized on the predicted urban growth map to investigate housing preferences, which will be based on Gordon's theory. This study will prove the feasibility of a process approach when practicing the management of urban growth in emerging cities worldwide. It could be a robust solution for the worsening imbalance in the urban morphology of metropolitan cities. The findings of the broad-spectrum housing dispersal guidelines could benefit the policymakers and planners for the realities of spatial patterns and future urban growth. [ABSTRACT FROM AUTHOR]

As a last resort for radio frequency communication, Terahertz bands (0.1-10 THz) are targeted thanks to their ability to provide ultra-wide bandwidth satisfying varieties of emerging applications. However, the waves propagating at THz frequencies suffer from high losses due to absorption in air molecules which forces their use into short-range links. We propose a multi-hop system to extend the range of THz links with the aid of multiple passive reconfigurable intelligent surfaces (RIS). In contrast with existing literature, we address the challenge of the over-determined system of equations arising from optimizing the phases of cascaded RISs taking into account the practical case of highly directional antennas and spatially correlated channels in THz bands. We propose an efficient method to jointly optimize the phases induced by the RISs in order to maximize the power at the receiver side. [ABSTRACT FROM AUTHOR]

Crowd management is an essential task to ensure the safety and smoothness of any event. Using novel technologies, including surveillance cameras, drones, and the communication techniques between security agents, the control of the crowd has become easier. Yet, the usage of such techniques is still not effective. This article presents an approach for crowd counting from drones' data. The proposed method exploits the dilated and scaled neural networks for feature extraction and density crowd estimation. A new dataset named ViseDrone2020 is used for training and testing of the proposed method. In order to compare the proposed method, we implemented 10 state-of-the-art methods and trained it on this dataset. The experiments show that the proposed model is more efficient for crowd counting compared with the implemented methods. Also, some of these methods give relatively accurate results in terms of estimated crowd numbers as well as the quality of estimated density maps. The proposed model was further evaluated on nondrone datasets, namely, UCF_QNRF, UCF_CC_50, and shanghaiTech_(A, B), which produced satisfying results for all the datasets. In addition, the proposed method was tested on noisy images where Gaussian noise and salt-and-pepper noise was applied to all the images of the dataset with a noise density of 0.02. The analysis showed that the quality of the density map as well as the quantity of the crowd count estimation is comparatively better than other existing methods without the presence of noise. After the acceptance, the code of the proposed method as well as 10 implemented methods will be available at: [Online]. Available: https://github.com/elharroussomar/Crowd-Conting-on-Drone-Data. [ABSTRACT FROM AUTHOR]

In this letter, the cumulative distribution function (and hence outage probability) of the r-th order signal-to-noise ratio from a set of n correlated Nakagami fading branches is studied. Numerical results are presented to illustrate the effect of fading correlation and the fading severity parameter. The accuracy of a simple exchangeable approximation is also examined. Index Terms--Correlated fading, diversity, Nakagami fading, order statistics.

In remote rural areas without continuous Internet connectivity, it is hard to envisage the use of mHealth applications for remote patient monitoring. In such areas, patients need to travel long distances to reach the nearest health center. In this article, we propose an approach that solves this problem by transmitting mHealth monitoring data, collected using IoT sensors, using DTN. Thus, buses or other vehicles acting as data mules transmit the mHealth data from remote rural areas to a medical center or hospital in the nearest urban area. The proposed approach includes methods to preserve the security of the data through encryption and secure key exchange, and to authenticate the patients through appropriate hashing of selected information. It allows preserving the privacy of the patients, and it takes into account the intermittent nature of the network by adding redundancy to avoid data loss. [ABSTRACT FROM AUTHOR]

Quickest change detection (QCD) is a fundamental problem in many applications. Given a sequence of measurements that exhibits two different distributions around a certain flipping point, the goal is to detect the change in distribution around the flipping point as quickly as possible. The QCD problem appears in many practical applications, e.g., quality control, power system line outage detection, spectrum reuse, and resource allocation and scheduling. In this letter, we focus on spectrum sensing as our application since it is a critical process for proper functionality of cognitive radio networks. Relying on the cumulative sum (CUSUM), we derive the probability of detection and the probability of false alarm of CUSUM based spectrum sensing. We show the correctness of our derivations using numerical simulations. [ABSTRACT FROM AUTHOR]

We investigate the model of a single primary-transceiver pair with multiple secondary-transceiver pairs. The secondary pairs can act as relays for the primary transmitter enabling access to its channel resources. Each secondary user (SU) is assumed to be a radio-frequency energy-harvester node. We formulate a framework that aims at specifying the optimal SU set that operates as relay nodes for the primary user (PU) data message. The set of the SUs is selected such that the SUs total throughput is maximized under a certain quality-of-service (QoS) requirement constraint on the PU target data rate. We propose both centralized and distributed approaches for solving the formulated optimization problems. The centralized approach is based on solving a convex optimization problem at the PU. On the other hand, the distributed approach leverages a Sackelberg game where all users interact to achieve the best relay-selection scheme and PU’s transmit power. We prove the uniqueness and Nash equilibrium of the considered Stackelberg game, and develop a game-theoretic relay and PU’s transmit power selection algorithm. We also introduce a fairness optimization-based scheme (FOBS) that aims at enhancing the fairness among the SUs under our proposed centralized approach. Our simulation results show the efficiency of our proposed schemes in terms of SUs total throughput. [ABSTRACT FROM AUTHOR]

eHealth and mHealth applications are gaining increasing importance with advances in the IoT and the ubiquity of sensor deployments. Measured IoT mHealth data needs to be captured, transmitted, and stored securely, without having the security measures hinder or delay the response of medical personnel in case of emergency. In this article, we present a holistic framework for data transfer from the patient to the hospital. Three tiers are identified in the proposed framework. In each tier, suitable security measures are presented for securing the data and protecting the privacy of the patients. The proposed methods range from physical layer security techniques designed for low portable sensors deployed at the patient's home or body, to combining traditional encryption methods with additional security procedures at the cloud data center where the medical records are stored. [ABSTRACT FROM AUTHOR]

The increased interest in full-duplex communication combined with spectrum utilization enhancements stemming from cognitive radio motivate research activities in full-duplex cognitive radio. Energy detection is among the simplest and most practical methods for spectrum sensing in cognitive radio networks. Energy detection spectrum sensing in full-duplex cognitive radio has been addressed in the literature; however, either due to the lack of experimental verification or for the sake of mathematical simplicity, the residual self-interference (RSI) signal has been conventionally considered as a zero-mean Gaussian signal. In this paper, we establish for the first time an accurate (realistic) mathematical framework and performance analysis for energy detection spectrum sensing in full-duplex cognitive radio under the presence of RSI signal exhibiting Rician statistical nature, as recently proven experimentally. The performance analysis results are derived in the presence of RSI after passive self-interference cancellation (SIC) scenario and after combining passive SIC with active SIC using active analog and digital cancellation (ACDC). Exact expressions for the probabilities of detection and false alarm are derived for the considered RSI cancellation scenarios and verified through simulations. The results show that the previously used conventional zero-mean Gaussian self-interference model was producing pessimistic (lower bound) performance estimates. [ABSTRACT FROM AUTHOR]

In this letter, a novel approach for physical layer security is implemented using massive cylindrical antenna arrays. A part of the arrays is used for transmitting a signal reliably from source to destination using highly directive beams. At the same time, the remaining part can be used to mitigate eavesdropping by transmitting a jamming signal through another directive beam toward the eavesdropper. In addition, the cylindrical arrays can mitigate the impact of malicious jamming by placing a null in the array pattern at the destination in the direction of the jammer. The results show that the proposed approach can lead to good jamming mitigation and high secrecy capacity in both 2D and 3D, even when there are errors in determining the location of the eavesdropper. [ABSTRACT FROM AUTHOR]

In this paper, two different patch antenna geometries are proposed for wireless sensor applications involving electromagnetic propagation from inside the jet engine to our designed relaying antenna at the rim of the inlet. First, an enhanced modified version of our earlier proposed two-element circular patch antenna array is proposed. We follow with a fresh new design based on two-element array of hybrid rectangular circular patch antenna geometry. Both antenna designs are discussed in light of basic governing equations enabling initial design calculations, intuitions behind selecting the design elements based on desired propagation characteristics, simulation results, as well as fabrication and experimental measurements. Because of the environmental constraints, the proposed antennas need to be an extremely low profile and ultrathin. The proposed relaying antennas are designed to have a dual-beam pattern, one of which is directed toward the inside of the jet engine. The antennas are simulated using HFSS as well as fabricated and measured inside an anechoic chamber. Experimental results, which sufficiently agree well with the simulation results, demonstrate the achievement of the desired characteristics by fabricated antennas for deployment on jet engines. [ABSTRACT FROM AUTHOR]

Abstract We investigate a cognitive radio network in which a primary user (PU) may cooperate with a cognitive radio user (i.e., a secondary user (SU)) for transmissions of its data packets. The PU is assumed to be a buffered node operating in a time-slotted fashion where the time is partitioned into equal-length slots. We develop two schemes which involve cooperation between primary and secondary users. To satisfy certain quality of service (QoS) requirements, users share time slot duration and channel frequency bandwidth. Moreover, the SU may leverage the primary feedback message to further increase both its data rate and satisfy the PU QoS requirements. The proposed cooperative schemes are designed such that the SU data rate is maximized under the constraint that the PU average queueing delay is maintained less than the average queueing delay in case of non-cooperative PU. In addition, the proposed schemes guarantee the stability of the PU queue and maintain the average energy emitted by the SU below a certain value. The proposed schemes also provide more robust and potentially continuous service for SUs compared to the conventional practice in cognitive networks where SUs transmit in the spectrum holes and silence sessions of the PUs. We include primary source burstiness, sensing errors, and feedback decoding errors to the analysis of our proposed cooperative schemes. The optimization problems are solved offline and require a simple 2-dimensional grid-based search over the optimization variables. Numerical results show the beneficial gains of the cooperative schemes in terms of SU data rate and PU throughput, average PU queueing delay, and average PU energy savings. [ABSTRACT FROM AUTHOR]

In this paper, we study distributed power allocation for multiflow carrier aggregation in cognitive cellular networks. Our approach differs from the conventional water filling (WF) algorithm since we deal with heterogeneous fading channels, wherein all of the Lagrange multipliers are not handled equally over the heterogeneous cells. The distributed power control solution is carried out over heterogeneous fading channels that are considered nonidentically distributed Nakagami- $m$ fading channels. We first formulate the optimization problem, and we then solve it using the alternating direction method of multipliers (ADMM), which allows the required decomposition for each channel and the required statistical learning among the different subproblem solutions. We also provide comparison with the dual decomposition method and WF solutions considered as solutions without cognition. Simulation results highlight the performance gain of ADMM in terms of the number of iterations. Furthermore, we provide a multiuser application scenario, where the analysis on the fading channel model with Nakagami- $m$ distribution is carried out. We distinguish into the synchronous and the asynchronous ADMM implementations tackling the asynchronous user updates that can be found in a heterogeneous network deployment. The simulation results are obtained to highlight the impact of the partial barrier and the bounded delay in the asynchronous use case. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of sub-channel selection for carrier aggregation (CA) systems is examined. CA enables the achievement of high data rate links via simultaneous transmissions over multiple component carriers. A CA system usually occupies only a limited number of sub-channels $M$ of these components due to limitations on the maximum permitted number of sub-channels per system. From an information theoretic point of view, a CA system should detect and employ the $M$ -best sub-channels out of the $N$ available ones. To that end, such a system probes a subset of sub-channels during each coherence time via pilot transmission. Then, for the best $M$ sub-channels, one-bit feedback information is transmitted in order to prohibit the transmission through sub-channels with gain below a threshold. The aim is to derive tractable forms via employing the extreme value theory for the sum rate (lower bound on ergodic capacity) achieved by the system under Rayleigh fading and then, to optimize jointly the training length and power, the number of the probed sub-channels (probing bandwidth size) and the feedback threshold such that the sum rate is maximized by considering the sub-channel estimation error. The accuracy of the theoretical analysis is verified by numerical results. [ABSTRACT FROM PUBLISHER]

In this paper, we introduce a secure multiple access scheme, which exploits the multipath structure of the channel to create a multi-user interference environment. The generated interference enables legitimate users to share time and frequency resources over spatially secure communication links. Utilizing directional modulation, we ensure secrecy for legitimate users against eavesdropping while preserving mutual confidentiality between the legitimate users themselves. Moreover, we introduce a complementary scheme for covering the non-selective channel case. The scheme uses directional modulation in coordinated multi-point transmission to provide location-specific secure communication to legitimate users. We characterize the achievable performance using a newly defined metric called vulnerable region. We provide analysis for the achievable secrecy rate, secrecy outage probability, and channel correlation effect on the secrecy performance for the proposed scheme. Furthermore, the effect of the channel spatial diversity, channel estimation error, and the number of legitimate users on the secrecy performance is studied. [ABSTRACT FROM PUBLISHER]

In this paper, a collaborative energy-harvesting cognitive radio (CR) network is considered such that the transmitter of the secondary user (SU) is allowed to harvest signal energy of the primary user (PU) when the presence of the PU is detected. The harvested energy is converted to electrical power in order to supply the sensing and transmission energy of SUs. The time frame (time slot) is divided into two phases allocated to sensing (divided into two durations: spectrum sensing and results reporting) and transmission, respectively. The time spanned by the results reporting duration depends on the number of collaborative sensing users, while the time spent on spectrum sensing duration controls the number of sensing samples. A constrained convex optimization problem of the overall probability of error is formulated incorporating constraints on time and energy resources along with PU interference protection presented as a threshold on probability of collision. We use a soft decision rule scheme while considering two energy harvesting scenarios namely, energy surplus and energy deficit. In each scenario, the convexity of the optimization problem is established analytically and the global optimal solution is obtained. Simulation results are provided to demonstrate the impact of the different parameters on the overall system performance as well as to verify the deduced analytical results. [ABSTRACT FROM PUBLISHER]

This paper considers the problem of analytically assessing the maximum achievable rates (capacity) of orthogonal frequency division multiplexing (OFDM) transmissions when the receiver, for complexity reasons, only accounts for the common phase error (CPE) effect due to phase noise impairments with inter-carrier interference (ICI) treated as noise. By recognizing that the functional form of the CPE with respect to the phase noise realization is actually a free design parameter, determination of the capacity is posed as a functional optimization problem with respect to the, so-called, CPE function. A simple lower bound of the capacity is obtained, revealing the performance degradation due to the unknown CPE at the receiver, as well as the suboptimal performance achieved in severe phase noise conditions by the conventional CPE function that is routinely employed in previous works. The existence of an optimal number of subcarriers that balances the effects of the (unknown) CPE and ICI is highlighted and critical system design/operation issues, such as selection of the CPE function and effect of unknown channel on the achievable rate, are discussed. The analysis in this paper can be employed for determining the suitability of OFDM in phase noise channels and provides a tractable utility function for resource allocation purposes. [ABSTRACT FROM PUBLISHER]

In this paper, we characterize the total degrees of freedom (DoFs) of the full-duplex asymmetric multiple-input multiple- output (MIMO) three-way channel. Each node has a separate-antenna full-duplex MIMO transceiver with a different number of antennas, where each antenna can be configured for either signal transmission or reception. We study this system under two message configurations; the first configuration is when each node has two unicast messages to be delivered to the two other nodes, while the second configuration is when each node has two unicast messages as well as one broadcast message to be delivered to the two other nodes. For each configuration, we first derive upper bounds on the total DoF of the system. Cut-set bounds in conjunction with genie-aided bounds are derived to characterize the achievable total DoF. Afterward, we analytically derive the optimal number of transmit and receive antennas at each node to maximize the total DoF of the system, subject to the total number of antennas at each node. Finally, the achievable schemes for each configuration are constructed. The proposed schemes are mainly based on zero-forcing and null-space transmit beamforming. We show that the derived outer and inner bounds on the total DoF are tight for each message configuration. [ABSTRACT FROM PUBLISHER]

Estimating the number of sources is a key task in many array signal processing applications. Conventional algorithms such as Akaike's information criterion (AIC) and minimum description length (MDL) suffer from underestimation and overestimation errors. In this study, the authors propose four algorithms to estimate the number of sources in white Gaussian noise. The authors' proposed algorithms are categorised into two main categories; namely, sample correlation matrix (CorrM) based and correlation coefficient matrix (CoefM) based. Their proposed algorithms are applied on the CorrM and CoefM eigenvalues. They propose to use two decision statistics, which are the moving increment and the moving standard deviation of the estimated eigenvalues as metrics to estimate the number of sources. For their two CorrM based algorithms, the decision statistics are compared to thresholds to decide on the number of sources. They show that the conventional process to estimate the threshold is mathematically tedious with high computational complexity. Alternatively, they define two threshold formulas through linear regression fitting. For their two CoefM based algorithms, they re‐define the problem as a simple maximum value search problem. Results show that the proposed algorithms perform on par or better than AIC and MDL as well as recently modified algorithms at medium and high signal‐to‐noise ratio (SNR) levels and better at low SNR levels and low number of samples, while using a lower complexity criterion function. [ABSTRACT FROM AUTHOR]

The ever-increasing demand for mobile Internet and high-data-rate applications poses unique challenging requirements for 5G mobile networks, including spectrum limitations and massive connectivity. Cognitive radio and carrier aggregation (CA) have recently been proposed as promising technologies to overcome these challenges. In this paper, we investigate joint relay selection and optimal power allocation in an underlay cooperative cognitive radio with CA, taking into account the availability of multiple carrier components in two frequency bands, subject to outage probability requirements for primary users (PUs). The secondary user network employs relay selection, where the relay that maximizes the end-to-end sum rate is selected, assuming both decode-and-forward and amplify-and-forward relaying. The resulting optimization problems are optimally solved using convex optimization tools, i.e., dual decomposition and an efficient iterative method, allowing their application in practical implementations. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom efficiently to maximize the SU rate, while meeting the PU average outage probability constraints. [ABSTRACT FROM PUBLISHER]

The problem of multiple antenna spectrum sensing in cognitive radio (CR) networks is studied in this paper. We propose two new invariant constant false-alarm rate eigenvalue-based (EVB) detectors, using the higher order moments of the sample covariance matrix eigenvalues, by exploiting the separating function estimation test framework. We find closed-form expressions for the false-alarm and detection probabilities of the proposed detectors by providing moment-based approximations of their statistical distributions. The accuracy of the obtained closed-form expressions is validated by Monte Carlo simulations. In addition, we compare the performance of the proposed detectors with that of their two counterparts, i.e., John’s and the arithmetic to geometric mean (AGM) detectors, in terms of the asymptotic relative efficiency. This comparison enables us to demonstrate the superiority of our proposed detectors over those detectors within the typical range of signal-to-noise ratio in CR application. The comparative simulation results also illustrate the superiority of the proposed detectors over John’s and the AGM detectors as well as some other state-of-the-art EVB algorithms given in the literature. [ABSTRACT FROM PUBLISHER]

This paper presents an improved propagation channel model for the visible light in indoor environments. We employ this model to derive an enhanced positioning algorithm using on the relation between the time-of-arrivals (TOAs) and the distances for two cases either by assuming known or unknown transmitter and receiver vertical distances. We propose two estimators, namely the maximum likelihood estimator and an estimator by employing the method of moments. To have an evaluation basis for these methods, we calculate the Cramer-Rao lower bound (CRLB) for the performance of the estimations. We show that the proposed model and estimations result in a superior performance in positioning when the transmitter and receiver are perfectly synchronized in comparison to the existing state-of-the-art counterparts. Moreover, the corresponding CRLB of the proposed model represents almost about 20 dB reduction in the localization error bound in comparison with the previous model for some practical scenarios. [ABSTRACT FROM AUTHOR]

Analyzing electromagnetic propagation inside jet engine turbines is a challenging and important research topic due to its potential applications in both civil and military fields. Electromagnetic modeling of such complex cavities is very difficult due to their complex geometry and the harsh surrounding environment, as well as the rotating metallic parts they contain. In addition, it is extremely difficult to extract the field values from arbitrarily shaped model geometries having large sizes, complex terminations, and cross-section variations. [ABSTRACT FROM PUBLISHER]

This paper investigates the maximum throughput of a rechargeable secondary user (SU) sharing the spectrum with a primary user (PU). The SU is assumed to be an energy harvesting node, which harvests energy packets from the environmental energy sources (e.g. solar, wind and acoustics) with a certain harvesting rate. The PU is equipped with a data buffer to store the randomly arrived data packets at its receiver. In addition to its own data buffer, the SU is equipped with another data buffer for storing the unsuccessfully decoded packets at the primary destination in a given time slot due to channel fading. Moreover, it has an energy buffer for storing the energy packets harvested from the environment. We propose a new cooperative cognitive relaying protocol that allows the SU to gain channel access when it relays a fraction of the undelivered primary packets. We consider an interference channel model [or a multipacket reception (MPR) channel model], where simultaneous transmissions can be decoded correctly at the corresponding destinations with certain decoding probabilities characterised by the complement of channel outages under interference. Our proposed protocol exploits the PU's data burstiness because of the random and sporadic packet arrival at its queue. Moreover, the proposed protocol takes advantage of the receivers' MPR capabilities. In addition, it efficiently expends the secondary energy packets under the objective of secondary throughput maximisation. Our numerical results show the benefits of cooperation, receivers' MPR capabilities and secondary energy queue arrival rate on the system's performance from a network layer standpoint. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The vast majority of existing secret key generation protocols exploit the inherent randomness of the wireless channel as a common source of randomness. However, independent noise added at the receivers of the legitimate nodes affects the reciprocity of the channel. In this paper, we propose a new simple technique to generate the secret key that mitigates the effect of noise. Specifically, we exploit the estimated channel to generate a secondary random process (SRP) that is common between the two legitimate nodes. We compare the estimated channel gain and phase to a preset threshold. The moving differences between the locations at which the estimated channel gain and phase exceed the threshold are the realization of our SRP. We study the properties of our generated SRP and derive a closed form expression for the probability mass function of the realizations of our SRP. We simulate an orthogonal frequency division multiplexing system and show that our proposed technique provides a drastic improvement in the key bit mismatch rate between the legitimate nodes when compared with the techniques that exploit the estimated channel gain or phase directly. In addition to that, the secret key generated through our technique is longer than that generated by conventional techniques. Moreover, we compute the conditional probabilities used to estimate the secret key capacity. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the impact of cooperation between a secondary transmitter–receiver pair and a primary transmitter on the maximum stable throughput of the primary–secondary network. Each transmitter, either primary or secondary, has a buffer for storing its own traffic. In addition to its own buffer, the secondary transmitter has a buffer for storing a fraction of the undelivered primary packets due to channel impairments. Moreover, the secondary destination has a relaying queue (buffer) for storing a fraction of the undelivered primary packets. In our proposed cooperative system, the secondary transmitter and the secondary destination increase the spectrum availability for the secondary packets by relaying the unsuccessfully transmitted packets of the primary transmitter. We consider two multiple-access strategies to be used by the secondary transmitter and the secondary destination to utilize the silence sessions of the primary transmitter. Numerical results demonstrate the gains of our proposed cooperative system over the noncooperation case and the systems when the secondary transmitter is the only cooperating node in the network. [ABSTRACT FROM AUTHOR]

Within the paradigm of physical layer security, a physical layer characteristic is used as a common source of randomness to generate the secret key. This key is then used to encrypt the data to hide information from eavesdroppers. In this paper, we survey the most recent common sources of randomness used to generate the secret key. We present the steps used to extract the secret key from the estimated common source of randomness. We describe the metrics used to evaluate the strength of the generated key. We follow that with a qualitative comparison between different common sources of randomness along with a proposed new direction which capitalizes on hybridization of sources of randomness. We conclude by a discussion about current open research problems in secret key generation. [ABSTRACT FROM AUTHOR]

This work is devoted to the study of dispersed spectrum cognitive radio (CR) systems over independent and nonidentically distributed (i.n.i.d.) generalized fading channels. More specifically, this is performed in terms of the high-order statistics (HOS) of the channel capacity over \eta-\mu fading channels. A generic analytic expression is derived for the corresponding $n$th statistical moment, which is subsequently employed for deducing exact closed-form expressions for the first four moments. Using these expressions, important statistical metrics, such as the amount of dispersion, amount of fading, skewness, and kurtosis, are derived in closed form and can be efficiently used in providing insights on the performance of dispersed CR systems. The obtained numerical results reveal interesting outcomes that could be useful for the channel selection, either for sharing or aggregation in heterogeneous networks, which is the core structure of future wireless communication systems. [ABSTRACT FROM AUTHOR]

In this paper, we consider a cognitive scenario where an energy harvesting secondary user shares the spectrum with a primary user. The secondary source helps the primary source in delivering its undelivered packets during periods of silence of the primary source. The primary source has a queue for storing its data packets, whereas the secondary source has two data queues: a queue for storing its own packets and the other for storing the fraction of the undelivered primary packets accepted for relaying. The secondary source is assumed to be a battery-based node, which harvests energy packets from the environment. In addition to its data queues, the secondary user has an energy queue to store the harvested energy packets. The secondary energy packets are used for primary packets decoding and data packets transmission. More specifically, if the secondary energy queue is empty, the secondary source can neither help the primary source nor transmit a packet from the data queues. The energy queue is modeled as a discrete-time queue with Markov arrival and service processes. Because of the interaction of the queues, we provide inner and outer bounds on the stability region of the proposed system. We investigate the impact of the energy arrival rate on the stability region. Numerical results show the significant gain of cooperation.Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We address the problem of spectrum sensing in cognitive radios (CRs) when the secondary user (SU) is equipped with a multiantenna receiver. We consider scenarios with correlation between the received channels at different antennas and unequal per-antenna noise variances to accommodate calibration errors. First, we derive the exact as well as the asymptotic performance of the genie-aided (benchmark) detector with perfect knowledge of the antenna correlation coefficients, the primary user (PU) signal power and the noise covariance matrix. Then, we consider the sensing problem in which the SU is non-cognizant of the per-antenna noise variances, the PU signal power and the correlation of channel gains, starting with a specific treatment of the two-antenna case. For a general multiantenna receiver, we propose combining the derived test statistics among all antenna pairs. The related optimization problem to obtain the optimum combination weights is analyzed, which requires the analytical performance characterization of the constituent two-antenna detector. Thus, we compute the exact performance of the proposed detector in a special case (a particular case of the Hadamard ratio test) in terms of its detection and false alarm probabilities. Performance analyses are verified with simulations, showing that the proposed detector outperforms several recently-proposed multiantenna detectors for CR in the scenarios considered. [ABSTRACT FROM PUBLISHER]

A recent investigation on the medium access control (MAC) layer in cognitive radio networks (CRNs) proposed the primary packet relaying by the secondary node maintaining an extra queue used for this particular addable functionality. Nevertheless, relaying of primary packets may introduce delays on secondary packets called secondary delay and may require an additional power budget to forward the primary packets. Power budget is particularly crucial when a type of sensor network is deployed using devices of limited power resources. In this paper, admission control is employed to efficiently manage this packet-wise relaying process in cognitive radio sensor networks (CRSNs). To be specific, we assume a cognitive packet-relaying scenario with two pairs of primary and secondary users, i.e., transmitter and receiver. We analyze and formulate the secondary delay and the required power budget of the secondary sensor node in relation to the acceptance factor (i.e., admission control parameter) that indicates whether the primary packets are admitted for relaying or not. Having defined the above, we present a tradeoff between the secondary delay and the required power budget by tuning the acceptance factor, which can be tailored to specific chosen values. Based on this behavior, we formulate an optimization problem to minimize the secondary delay over the admission control parameter subject to a limit on the required power budget. Additionally, the constraints related to the stabilities of all individual queues at the primary and secondary networks are taken into account in the proposed optimization problem, due to their interdependence relations. The solution of this problem is provided using iterative decomposition methods, i.e., dual and primal decompositions, using Lagrange multipliers that simplify the original complicated problem and result in a final equivalent dual problem that includes the initial Karush–Kuhn–Tucker (KKT) conditions. We obtain the optimal acceptance factor, while in addition, we highlight the opportunities for extra delay minimization that is provided by relaxing the initial constraints through changing the values of the Lagrange multipliers. Finally, we present the behavior of the secondary delay, assuming infinite and finite queues and assessing thereby the overflow and blocking probabilities, respectively. [ABSTRACT FROM AUTHOR]

A blind (non-data-aided) SNR estimator using the statistical moments of the received signal is proposed. The proposed envelope-based non-data-aided estimator works for any time-domain Gaussian-distributed signal (e.g., OFDM signals). A closed-form expression for the estimated SNR as a function of the moments of the received signal and the Nakagami- $m$ parameter, is derived. Interestingly, the obtained expression shows that the proposed estimator operation and performance is independent of the constellation of the received signal. Moreover, the existence of the closed-form expression results in lower implementation complexity. Furthermore, to enable theoretical performance analysis, a general mathematical expression is derived for the even moments of the received signal in terms of SNR and the Nakagami- $m$ parameter. The performance of the proposed estimator is evaluated based on the mean-squared-error, under different conditions of the channel. An extension of our SNR estimation method into multiple antennas configurations is provided. Our results reveal that the proposed estimator works better in low SNR conditions, which is attractive to applications such as cognitive radio spectrum sharing scenarios. [ABSTRACT FROM PUBLISHER]

A relay network composed of a source, a set of relays, and a destination is considered. A queueing framework is proposed, in which each node maintains a buffer to store its incoming traffic. An optimization-based formulation is proposed to maximize the mean service rate of the source queue. The relay selection technique is based on the statistics of the system parameters. Three packet decoding strategies at the relays are investigated and their performance is compared. The proposed decoding strategies, which do not require the channel state information at the transmitters, can outperform the max-max relay selection strategy. [ABSTRACT FROM PUBLISHER]