A Novel 3D Analytical Scattering Model for Air-to-Ground Fading Channels

A geometry-based three-dimensional (3D) novel stochastic channel model for air-to-ground (A2G) and ground-to-air (G2A) radio propagation environments is proposed. The vicinity of a ground station (GS) is modelled as surrounded by effective scattering points; whereas the elevated air station’s (AS) vicinity is modelled as a scattering-free region. Characterization of the Doppler spectrum, dispersion in the angular domain and second order fading statistics of the A2G/G2A radio communication channels is presented. Closed-form analytical expressions for joint and marginal probability density functions (PDFs) of Doppler shift, power and angle of arrival (AoA) are derived. Next, the paper presents a comprehensive analysis on the characteristics of angular spread on the basis of shape factors (SFs) for A2G/G2A radio propagation environments independently in both the azimuth and elevation planes. The analysis is further extended to second order statistics of the fading channel; where the behaviour of the level crossing rate (LCR), average fade duration (AFD), auto-covariance and coherence distance for the A2G/G2A radio propagation environment is studied. Finally, the impact of physical channel parameters, such as the mobility of AS, the height of AS, the height of GS and the delay of the longest propagation path, on the distribution characteristics of Doppler shift, angular spread and second order statistics is thoroughly studied

A Combined Deep Learning and Ensemble Learning Methodology to Avoid Electricity Theft in Smart Grids

Electricity is widely used around 80% of the world. Electricity theft has dangerous effects on utilities in terms of power efficiency and costs billions of dollars per annum. The enhancement of the traditional grids gave rise to smart grids that enable one to resolve the dilemma of electricity theft detection (ETD) using an extensive amount of data formulated by smart meters. This data are used by power utilities to examine the consumption behaviors of consumers and to decide whether the consumer is an electricity thief or benign. However, the traditional data-driven methods for ETD have poor detection performances due to the high-dimensional imbalanced data and their limited ETD capability. In this paper, we present a new class balancing mechanism based on the interquartile minority oversampling technique and a combined ETD model to overcome the shortcomings of conventional approaches. The combined ETD model is composed of long short-term memory (LSTM), UNet and adaptive boosting (Adaboost), and termed LSTM–UNet–Adaboost. In this regard, LSTM–UNet–Adaboost combines the advantages of deep learning (LSTM-UNet) along with ensemble learning (Adaboost) for ETD. Moreover, the performance of the proposed LSTM–UNet–Adaboost scheme was simulated and evaluated over the real-time smart meter dataset given by the State Grid Corporation of China. The simulations were conducted using the most appropriate performance indicators, such as area under the curve, precision, recall and F1 measure. The proposed solution obtained the highest results as compared to the existing benchmark schemes in terms of selected performance measures. More specifically, it achieved the detection rate of 0.92, which was the highest among existing benchmark schemes, such as logistic regression, support vector machine and random under-sampling boosting technique. Therefore, the simulation outcomes validate that the proposed LSTM–UNet–Adaboost model surpasses other traditional methods in terms of ETD and is more acceptable for real-time practices

Location-aware and Superimposed-Pilot based Channel Estimation of Sparse HAP Radio Communication Channels

A superimposed (arithmetically added) Pilot (SiP) sequence based channel estimation method for beamforming assisted multi-antenna High Altitude Platform (HAP) land mobile radio communication systems is proposed, which exploits the prior available information of users' spatial location, density of users, and beam-width of HAP directional antenna. A thorough characterization of HAP sparse multipath radio propagation channels' is presented in first part of the paper, where mathematical relationship of HAP antenna beam-width with channel's delay span and optimal length of SiP base sequence are presented. Further, a location information aided and low- power SiP sequence based Stage-wise Orthogonal Match Pursuit (StOMP) algorithm is proposed for estimation of channels from single-antenna user terminals to beamforming assisted large scale multiple-antenna HAP. A thorough analysis on the basis of Normalized Channel Mean Square Error (NCMSE) and Bit Error Rate (BER) performance of proposed method is presented; where the effect of channels' sparsity level, Pilot-to-Information power Ratio (PIR), beam-width of HAP's directional antenna, amount of HAP antenna elements, density of interfering users, and spatial location of active user terminal are thoroughly studied. A comparison of the proposed method with a notable reference technique available in the literature is also presented

Angle and Time of Arrival Characteristics of 3D Air-to-Ground Radio Propagation Environments

A three dimensional (3D) geometric channel model is proposed for ground-to-air (G2A) and air-toground (A2G) communication links. A low-elevated ground station (GS) and a high-elevated air station (AS) are taken at foci points of a virtual bounding ellipsoid corresponded from known knowledge of delay of longest propagation path. The effective region of scatterers around the GS is designed on the basis of this ellipsoid truncated by the average rooftop level (or average height of sea waves) and ground plane. Closedform expressions for joint and marginal probability density functions (PDFs) of angle of arrival (AoA) observed at AS and GS in correspondence with azimuth and elevation angles are derived. Furthermore, closed-form expressions for density of energy with respect to the delay of arriving multipath waves corresponded from both the elevation and azimuth AoA are derived independently when observed from either end of the communication link. Moreover, effect of different physical parameters of the channel on distribution of energy in angular and temporal domains is presented. The comparison of analytical results with results of a notable model is also presented. In order to verify the derived analytical expressions, a comparison of analytical results with the performed simulation results is presented, which shows a good match

Massive-MIMO Sparse Uplink Channel Estimation Using Implicit Training and Compressed Sensing

Massive multiple-input multiple-output (massive-MIMO) is foreseen as a potential technology for future 5G cellular communication networks due to its substantial benefits in terms of increased spectral and energy efficiency. These advantages of massive-MIMO are a consequence of equipping the base station (BS) with quite a large number of antenna elements, thus resulting in an aggressive spatial multiplexing. In order to effectively reap the benefits of massive-MIMO, an adequate estimate of the channel impulse response (CIR) between each transmit–receive link is of utmost importance. It has been established in the literature that certain specific multipath propagation environments lead to a sparse structured CIR in spatial and/or delay domains. In this paper, implicit training and compressed sensing based CIR estimation techniques are proposed for the case of massive-MIMO sparse uplink channels. In the proposed superimposed training (SiT) based techniques, a periodic and low power training sequence is superimposed (arithmetically added) over the information sequence, thus avoiding any dedicated time/frequency slots for the training sequence. For the estimation of such massive-MIMO sparse uplink channels, two greedy pursuits based compressed sensing approaches are proposed, viz: SiT based stage-wise orthogonal matching pursuit (SiT-StOMP) and gradient pursuit (SiT-GP). In order to demonstrate the validity of proposed techniques, a performance comparison in terms of normalized mean square error (NCMSE) and bit error rate (BER) is performed with a notable SiT based least squares (SiT-LS) channel estimation technique. The effect of channels’ sparsity, training-to-information power ratio (TIR) and signal-to-noise ratio (SNR) on BER and NCMSE performance of proposed schemes is thoroughly studied. For a simulation scenario of: 4 × 64 massive-MIMO with a channel sparsity level of 80 % and signal-to-noise ratio (SNR) of 10 dB , a performance gain of 18 dB and 13 dB in terms of NCMSE over SiT-LS is observed for the proposed SiT-StOMP and SiT-GP techniques, respectively. Moreover, a performance gain of about 3 dB and 2.5 dB in SNR is achieved by the proposed SiT-StOMP and SiT-GP, respectively, for a BER of 10 − 2 , as compared to SiT-LS. This performance gain NCME and BER is observed to further increase with an increase in channels’ sparsity

Preliminary Work Towards Finding Proteins as Potential Vaccine Candidates for <i>Vibrio cholerae</i> Pakistani Isolates through Reverse Vaccinology

Background and Objective: Vibrio cholerae continues to emerge as a dangerous pathogen because of increasing resistance to a number of antibiotics. This paper provides a solution to emerging antibiotic resistance by introducing novel proteins as vaccine candidates against cholera. Materials and Methods: Vibrio cholerae genome versatility is a hurdle for developing a vaccine to combat diarrhoeal infection, so its core gene information was used to determine a potential vaccine candidate. Whole genome sequence data of more than 100 Vibrio cholerae strains were used simultaneously to get core genome information. The VacSol pipeline based on reverse vaccinology was selected to address the problem of safe, cheap, temperature-stable, and effective vaccine candidates which can be used for vaccine development against Vibrio cholerae. VacSol screens vaccine candidates using integrated, well-known, and robust algorithms/tools for proteome analysis. The proteomes of the pathogens were initially screened to predict homology using BLASTp. Proteomes that are non-homologous to humans are then subjected to a predictor for localization. Helicer predicts transmembrane helices for the protein. Proteins failing to comply with the set parameters were filtered at each step, and finally, 11 proteins were filtered as vaccine candidates. Results: This selected group of vaccine candidates consists of proteins from almost all structural parts of Vibrio cholerae. Their blast results show that this filtered group includes flagellin A protein, a protein from the Zn transporter system, a lipocarrier outer membrane protein, a peptidoglycan-associated protein, a DNA-binding protein, a chemotaxis protein, a tRNA Pseuriudine synthase A, and two selected proteins, which were beta lactamases. The last two uncharacterized proteins possess 100% similarity to V. albensis and Enterobacter, respectively. Tertiary structure and active site determination show a large number of pockets on each protein. Conclusions: The most interesting finding of this study is that 10 proteins out of 11 filtered proteins are introduced as novel potential vaccine candidates. These novel vaccine candidates can result in the development of cost-effective and broad-spectrum vaccines which can be used in countries where cholera is a major contributor to diarrheal disease

A 3-D Propagation Model for Emerging Land Mobile Radio Cellular Environments

<div><p>A tunable stochastic geometry based Three-Dimensional (3-D) scattering model for emerging land mobile radio cellular systems is proposed. Uniformly distributed scattering objects are assumed around the Mobile Station (MS) bounded within an ellipsoidal shaped Scattering Region (SR) hollowed with an elliptically-cylindric scattering free region in immediate vicinity of MS. To ensure the degree of expected accuracy, the proposed model is designed to be tunable (as required) with nine degrees of freedom, unlike its counterparts in the existing literature. The outer and inner boundaries of SR are designed as independently scalable along all the axes and rotatable in horizontal plane around their origin centered at MS. The elevated Base Station (BS) is considered outside the SR at a certain adjustable distance and height w.r.t. position of MS. Closed-form analytical expressions for joint and marginal Probability Density Functions (PDFs) of Angle-of-Arrival (AoA) and Time-of-Arrival (ToA) are derived for both up- and down-links. The obtained analytical results for angular and temporal statistics of the channel are presented along with a thorough analysis. The impact of various physical model parameters on angular and temporal characteristics of the channel is presented, which reveals the comprehensive insight on the proposed results. To evaluate the robustness of the proposed analytical model, a comparison with experimental datasets and simulation results is also presented. The obtained analytical results for PDF of AoA observed at BS are seen to fit a vast range of empirical datasets in the literature taken for various outdoor propagation environments. In order to establish the validity of the obtained analytical results for spatial and temporal characteristics of the channel, a comparison of the proposed analytical results with the simulation results is shown, which illustrates a good fit for 10⁷ scattering points. Moreover, the proposed model is shown to degenerate to various notable geometric models in the literature by an appropriate choice of a few parameters.</p></div

Effect of <i>θ</i>_<i>i</i> on azimuth and elevation marginal PDF of AoA observed from BS.

<p>(<i>a</i>_<i>o</i> = 120m, <i>b</i>_<i>o</i> = 70m, <i>c</i>_<i>o</i> = 50m, <i>a</i>_<i>i</i> = 40m, <i>b</i>_<i>i</i> = 20m, <i>θ</i>_<i>o</i> = 0^<i>o</i>, <i>h</i>_<i>b</i> = 80m, and <i>d</i> = 130m).</p

Definition of Symbols.

<p>Definition of Symbols.</p

Joint PDF of ToA and azimuth AoA observed from MS.

<p>(<i>a</i>_<i>o</i> = 100m, <i>b</i>_<i>o</i> = 70m, <i>c</i>_<i>o</i> = 50m, <i>θ</i>_<i>i</i> = <i>θ</i>_<i>o</i> = 0^<i>o</i>, <i>h</i>_<i>b</i> = 100m, and <i>d</i> = 200m).</p