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Wireless link scheduling in device-to-device (D2D) networks is an NP-hard problem. As a solution, multiple supervised deep learning (DL) models have been recently proposed, which depend on the geographical information of D2D pairs. However, such DL models require labeled training data. In this paper, we focus on unsupervised learning of scheduling. More specifically, this paper proposes using a Density-Based anti-Clustering for Scheduling D2D Communications (DBSCHedule). The proposed algorithm is a two-step approach that consists of clustering and anti-clustering. First, clustering aims at identifying the non-interfering groups of D2D pairs. Then, anti-clustering aims at identifying the maximally separated sub-groups to minimize the interference. The clustering step uses a fully-automated unsupervised density-based spectral-clustering of applications with noise (DBSCAN) and the anti-clustering uses the inverse of the objective function of the k-means clustering. Results show comparable performance with the optimal FPLinQ scheduler yet without requiring any channel information nor is there a requirement to solve a complex optimization problem. Moreover, a comparable performance to the previous attempts using DL and modified clustering is achieved while being completely adaptive and easily accommodating to changes in the network layout. [ABSTRACT FROM AUTHOR]

We present two novel methods for the generation of Fox's $H$ -function distributed random variables (RVs), which have been recently used to model fading in various wireless communication scenarios. The first proposed method is based on the use of standard normal RVs, whereas the second is based on the use of Gamma RVs. Using Monte Carlo simulations, the proposed methods are tested and are shown to provide indistinguishable results from the corresponding analytical $H$ -function probability density functions (PDFs) for a diverse set of parameters. Moreover, as an application, simulated ergodic capacity and average bit error rate results obtained using the proposed methods are compared to analytical expressions previously obtained in the literature and perfect agreement is observed. Our results also provide valuable insights into what constraints on the $H$ -function parameters are sufficient to guarantee valid $H$ -function PDFs. [ABSTRACT FROM AUTHOR]

This paper addresses throughput improvement in millimeter-wave (mmWave) mesh networks via two novel distributed scheduling algorithms. The first one uses packet aggregation and block acknowledgment (ACK) that were introduced in the IEEE Std 802.11e-2005 for WiFi. Specifically, a distributed time-division multiplexing scheduling algorithm, which targets increasing the network capacity via reserving as many contiguous slots as possible for each node, is proposed thus enabling packet aggregation. This algorithm achieves its goal when the operating signal-to-noise ratio (SNR) is significantly high. If that is not the case, the second proposed algorithm can be used. It is a distributed one that starts initially with a random feasible schedule determined cooperatively between nodes. The algorithm then tries to reach better feasible schedules via parallel and successive local searches without violating feasibility constraints. Extensive simulations show that the first algorithm improves the network throughput by almost compared to the well-known memory-guided directional medium access control (MDMAC) due to reducing the transmission overhead. The second proposed algorithm is shown to increase the number of reserved slots by about over MDMAC. Both algorithms are shown to either increase or almost maintain the same degree of fairness among the nodes as quantified by Jain's fairness index. [ABSTRACT FROM AUTHOR]

In this paper, we characterize the achievable (linear) degrees of freedom (DoFs) of the K-user single-input single-output (SISO) interference channel with blind interference alignment (BIA) using staggered antenna switching. In this scheme, each transmitter is equipped with one conventional antenna, and each receiver is equipped with one reconfigurable (multimode) antenna. Assuming that the channel is known to the receivers only, we show that by using linear BIA with staggered antenna switching at the receiver, a sum DoF of \text{2}K/(K+\text{2}) is achievable. This result implies that in using BIA, we can double the DoF achieved by orthogonal multiple-access schemes for a large number of users. Moreover, we propose a systematic algorithm to generate the transmit beamforming vectors and the reconfigurable antenna switching patterns, showing that it can achieve the \text{2}K/(K+\text{2})$ sum DoF for any K$. Finally, we apply this algorithm to the four-user SISO interference channel and demonstrate that \text{4}/\text{3} sum DoF is indeed achievable. [ABSTRACT FROM PUBLISHER]

In this paper, we introduce the exposed secondary-user (SU) problem in underlay cognitive radio systems, where both the secondary-to-primary and primary-to-secondary channels have a line-of-sight (LoS) component. Based on a Rician model for the LoS channels, we show, both analytically and numerically, that LoS interference hinders the achievable SU capacity when interference constraints are imposed at the primary user (PU) receiver. This is caused by the poor dynamic range of interference channel fluctuations when a dominant LoS component exists. To improve the capacity of such a system, we propose the use of an electronically steerable parasitic array radiator (ESPAR) antenna at the secondary terminals. An ESPAR antenna involves a single radio frequency (RF) chain and has a reconfigurable radiation pattern that is controlled by assigning arbitrary weights to $M$ orthonormal basis radiation patterns via altering a set of reactive loads. By viewing the orthonormal patterns as multiple virtual dumb antennas, we randomly vary their weights over time, creating artificial channel fluctuations that can perfectly eliminate the undesired impact of LoS interference. This scheme is termed as random aerial beamforming (RAB) and is well suited for compact and low-cost mobile terminals as it uses a single RF chain. Moreover, we investigate the exposed-SU problem in a multiuser setting, showing that LoS interference hinders multiuser interference diversity and affects the growth rate of the SU capacity as a function of the number of users. Using RAB, we show that LoS interference can, in fact, be exploited to improve multiuser diversity by boosting the effective number of users. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel framework for deriving closed-form exact expressions for the symbol error rate (SER) of $\alpha$– $\mu$ fading channels, assuming single-branch and equal-gain combining and maximal-ratio combining receivers and considering most of the commonly used modulation schemes. The proposed framework is based on Mellin transform, and the SER expressions are given in terms of the univariate and multivariate Fox $H$-functions, which have recently been extensively used in the literature. The proposed framework has the following advantages over previous frameworks: First, it is straightforward and general; therefore, it allows the derivation of the exact SER expressions for cases untreated before in the literature. Second, it enables direct derivation for the asymptotic expressions of the SER for high average signal-to-noise ratios (SNRs). To validate the obtained expressions, we compare the results of the special case of the Nakagami- $m$ fading channel with those reported in the literature. Furthermore, Monte Carlo simulations are conducted, and their results are shown to perfectly match the analytic expressions. Finally, the obtained asymptotic expressions for all the studied modulation schemes and diversity receivers are shown to match the behavior of their corresponding exact values for a wide range of SNR values that are of practical interest. [ABSTRACT FROM AUTHOR]

• A Gibbs sampling-based parameters estimation algorithm for the EGK distribution is presented. • First attempt to address ML-based estimators for the EGK distribution. • Numerical and simulation results show that the proposed method provides an efficient and mathematically tractable approach to achieve this goal. • Compared to the classical moment-matching method, the proposed method can better capture cases of heavy-tail. We present a novel approach for estimating the parameters of the extended generalized- K (EGK) distribution commonly used as a fading model in wireless and optical communications links. The proposed method is based on the Gibbs sampling technique and does not require solving nonlinear equations nor performing numerical integrations. Numerical and simulation results are presented showing that the estimated and original distributions are virtually indistinguishable and formal metrics like Kullback-Leibler (KL) divergence, the mean integrated squared bias (MISB), the mean integrated variance (MIV) and the mean integrated squared error (MISE) all show excellent agreement between the two as well. [ABSTRACT FROM AUTHOR]

We evaluate the performance of selection combining (SC) diversity in cellular systems where binary phase-shift keying (BPSK) is employed and the desired signal as well as the cochannel interferers (CCIs) is subject to Weibull fading. A characteristic function-(CF-) based approach is followed to evaluate the performance in terms of the outage probability. Two selection criteria are adopted at the diversity receiver: maximum desired signal power and maximum output signal-to-interference ratio (SIR).We study the effect of the fading parameters of the desired and interfering signals, the number of diversity branches, as well as the number of interferers on the performance. Numerical results are presented and the validity of our expressions is verified via Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

In this letter, we evaluate the performance of the dual-branch maximal ratio combining (MRC) diversity scheme in nonidentical correlated Weibull fading channels with arbitrary parameters. We first use the Padé approximation (PA) to find closed-form rational expressions for the moment generating function (MGF) of the output signal-to-noise ratio (SNR) of the MRC receiver. Different performance measures, such as the outage probability and the average symbol-error rate for different linear modulations, are then presented using the well-known MGF approach. Furthermore, the effect of the input SNRs unbalancing, the severity of fading, and the degree of correlation on the system performance are also studied. Our results are validated by comparing them with computer simulations, and we show that the PA technique is indeed a convenient tool for such performance evaluation studies. [ABSTRACT FROM AUTHOR]

We use the Padé approximation (PA) technique to obtain closed-form approximate expressions for the moment-generating function (MGF) of the Weibull random variable. Unlike previously obtained closed-form exact expressions for the MGF, which are relatively complicated as being given in terms of the Meijer G-function, PA can be used to obtain simple rational expressions for the MGF, which can be easily used in further computations. We illustrate the accuracy of the PA technique by comparing its results to either the existing exact MGF or to that obtained via Monte Carlo simulations. Using the approximate expressions, we analyze the performance of digital modulation schemes over the single channel and the multichannels employing maximal ratio combining (MRC) under the Weibull fading assumption. Our results show excellent agreement with previously published results as well as with simulations. [ABSTRACT FROM AUTHOR]

In concurrent spectrum sharing scenarios between radars and wireless communication systems, one strict approach to protect the radar from undesired interference is locating the base stations outside a guard (or exclusion) zone of the radar. As a result, users inside that zone experience bad communication coverage. This paper uses Reconfigurable Intelligent Surfaces (RISs) to improve the base station coverage of users in the radar exclusion zone. The paper shows, through analysis and simulation, that joint optimization of base station and RIS locations improves the probability of coverage in the exclusion zone over the shared spectrum without disturbing the radar operation. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the problem of optimal allocation of renewable energy resources to power base stations (BSs) in cellular networks while accounting for possible power failures in the utility grid. The allocation problem under investigation is formulated as a mixed integer non-linear programming, which is then decomposed, due to its complexity, and solved as two interdependent problems with the help of deterministic and metaheuristic techniques. We propose an allocation algorithm that jointly aims at optimizing the allocation of individualized green energy resources to simultaneously power the BSs with the grid as well as minimizing the overall system costs. Cost minimization is achieved by selecting the optimal types and sizes of the used photovoltaic (PV) panels and batteries in addition to optimally scheduling the charging and discharging of the selected batteries. This is done while limiting PV curtailment and any expected loss of cellular services at the times of power outage. Finally, the effectiveness of the proposed algorithm is demonstrated through the simulation of a sample case of a typical BS where Markov Chain Monte Carlo simulations are carried out to account for the uncertainty of the output of the PV panels and the grid failures. [ABSTRACT FROM AUTHOR]

Device-to-device communication (D2D) and massive multiple input multiple output (MIMO) systems are two emerging technologies that are being considered to improve the performance of next generation wireless cellular systems. In D2D, two mobile nodes communicate directly without traversing the base station (BS). Consequently, interference management, coordination, and/or cancellation techniques have to be adopted to target the problem of mutual interference between the D2D devices and the BS (or the normal mobiles nodes connected to the BS). In this paper, we investigate the problem of BS precoder design and D2D devices power allocation in the downlink of a single-cell network assuming existence of D2D devices as well as massive MIMO at the BS. We propose algorithms to maximize the sum of the achievable data rates of the D2D pairs while maintaining quality of service constraints on the cellular user equipment, which communicate normally with the BS. We also propose two algorithms for the precoding problem; the first is based on semi-definite programming while the second is based on gradient descent algorithms. Moreover, we investigate two solutions for the power allocation problem; the first solves an approximate convex optimization problem iteratively while the second is a suboptimal, but far less complex, heuristic. Finally, we propose a technique to apply the mentioned solutions when only partial channel state information is available at the BS. Simulation results show that the proposed solutions are superior to the conventional precoding and power allocation schemes. [ABSTRACT FROM AUTHOR]

In this paper, we derive closed-form exact and asymptotic expressions for the symbol error rate (SER) and channel capacity when communicating over Fox's $H$-function fading channel. The SER expressions are obtained for numerous practically employed modulation schemes in case of single-branch and three multiple-branch diversity receivers: maximal ratio combining (MRC), equal gain combining (EGC), and selection combining (SC). The derived exact expressions are given in terms of the univariate and multivariate Fox's $H$-functions for which we provide a portable and efficient Python code. Since Fox's $H$-function fading channel represents the most generalized fading model ever presented in the literature, the derived expressions subsume most of those previously presented for all the known simple and composite fading models. Moreover, easy-to-compute asymptotic expansions are provided to easily study the behavior of the SER and channel capacity at high values of the average signal-to-noise ratio (SNR). The asymptotic expansions are also useful in comparing different modulation schemes and receiver diversity combiners. Numerical and simulation results are also provided to support the mathematical analysis and prove the validity of the obtained expressions. [ABSTRACT FROM AUTHOR]

With the increase in the penetration of battery electric vehicles (BEVs) all over the world, utilities should start considering their increased demand as part of their electric demand. Generally, the literature lacks works that consider the impact of transportation electrification on the reliability of the power system. Thus, this paper proposes a new mechanism for reliability assessment including BEVs, with both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) modes. Three charging strategies: uncontrolled, controlled unidirectional, and controlled bidirectional are considered in this paper to model the interactions between the transportation and electric power systems. A dynamic stochastic consumption model for a fleet of BEVs is developed to be used in the reliability assessment for the distribution networks. This dynamic model takes into consideration the variability and uncertainty of different trip purposes, starting and ending trip times, as well as the corresponding battery consumption in weather conditions. Furthermore, it is composed of two sequential submodels: travel behavior and battery depletion. The first submodel considers trip-related information while the second considers battery-depleted energy. Simulation results on a benchmark test system show the negative impacts of uncontrolled charging on the power system's reliability. However, they also show that controlled charging can significantly reduce or mitigate these impacts. [ABSTRACT FROM AUTHOR]

• This work proposes a novel model for PV generation including dust and cleaning. • The model can be used for identifying the optimal investment and cleaning strategy. • The model relies on generating virtual scenarios of output power including cleaning. • Optimal cleaning results in a 23.9-36.2% added profit compared to no cleaning. • It is shown that variable cleaning frequency is more economic compared to fixed. Stochastic photovoltaic (PV) modeling that can be used for long-term planning of power systems is essential for future renewable power generation. One of the most prevalent problems that PV systems face is the accumulation of dust on the PV panel surface that negatively impacts the output power. Wind speed along with other weather variables including relative humidity, temperature, and precipitation are some of the major factors that contribute to dust accumulation. This paper presents a novel dynamic model of the PV output power profile including the dust accumulation using a Markov chain model. The proposed model incorporates the seasonal variations in ambient temperature, solar irradiance, dust accumulation, and rate of dust accumulation as well as the desired cleaning frequency, which affect the overall energy yield of the PV system. The outcome of the model is virtually generated scenarios that can be used by the investors to decide on the optimal size of the PV system and the optimal cleaning frequency for each season. The model outcome shows an error of less than 5% when compared to actual data collected from the field without cleaning. This error can be reduced by increasing the number of states, which affects the computational time. Various case studies are presented to show the effectiveness of the proposed model and its benefits. [ABSTRACT FROM AUTHOR]

Abstract: A new technique for passive doubly terminated ladder filters transformation has been proposed. The proposed technique depends on current mode realization of doubly terminated LC ladder filters instead of voltage mode realizations presented by Constantinides and Dimopoulos in . Different realizations of passive elements using new technique have been proposed. Design example of a 3rd order low-pass filter has been realized using the proposed technique and compared with the realization introduced by Rathore and Khot using current feedback operational amplifier (CFOA) as an active building block. SPICE simulations have been carried out using 0.18μ m TSMC CMOS technology and supply voltages of±0.9V. The simulation results have been demonstrated and discussed. [Copyright &y& Elsevier]