Fading Research Articles

Dispersive FSO Performance Estimation with Gaussian Pulses and Laplace Modeled Time Jitter

FSO communications tend to be one of most convenient, wireless, high-data-rate communications technologies of global telecom networking, and they are implemented and operated with low-cost resources. Despite their advantages, FSO systems’ performance is delimited by several physical phenomena, which act on propagating signal beams through the atmospheric path. Among other effects, chromatic dispersion and time jitter affect the shape and the detection instant of the incoming optical pulse, respectively. This results in signal fading and probable misdetections, and the signal fades along the propagation path due to power losses. Particularly, chromatic dispersion affects the width of the longitudinal information pulse, while the stochastic nature of the time jitter effect is treated with the use of a statistical model for the instantly received irradiance of the detecting pulse at the corresponding time slot. In this study, the symmetrical Laplace distribution was chosen for weak time jitter effect emulation because of its symmetry in pulse detection before or after the center of the specific timeslot. Thus, the joint influence of all three effects could considered, including all the parameters involved. Moreover, new-closed-form mathematical expressions were derived in order to accurately estimate the availability and the reliability of the FSO links under consideration. Next, using the derived mathematical forms, performance outcomes were presented for typical parameter values for realistic FSO links.

Waving Effect Characterization for Water-to-Air Optical Wireless Communication

In this paper, we establish and experimentally verify a water-to-air (W2A) visible light communication (VLC) system through dynamic air-water interface. Considering the complexity of waves in real environments, we divide waves into largescale wave and small-scale wave. Monte Carlo simulation and experimental results show that small-scale wave mainly affects the energy distribution of the light spot on the receiving plane and the variation frequency of link gain, while largescale wave mainly affects the coverage of the light spot. In the W2A-VLC system based on light-emitting diode (LED), the statistical characteristics of variation time and link gain are mainly related to the small-scale wave, and the effect of large-scale wave can be treated as slow fading. In order to design a reliable communication system, a large-divergence-angle LED array and avalanche photodiode (APD) array are used under dynamic water surface. We investigate three cases, namely single-input multiple-output (SIMO), multiple-input single-output (MISO) and multiple-input multiple-output (MIMO). In the SIMO or MISO systems, the correlation coefficient of channel gain decreases with the inter-receiver or inter-transmitter distance. A significant transmission performance enhancement can be achieved by deploying more transmitters or receivers and increasing the distance between the transmitters or receivers. A MIMO structure can effectively increase the achievable rate. We further establish a W2A-VLC link in a deep wave pool to verify our research in the real environment. The results show that more intensive small-scale wave yields higher bit error rate (BER), and the diversity scheme can improve the transmission stability and decrease BER.

Carbon confined GeO2 hollow spheres for stable rechargeable Na ion batteries.

Germanium (Ge) based nanomaterials are regarded as promising high-capacity anode materials for Na ion batteries, but suffer fast capacity fading problems caused by the alloying/de-alloying reactions of Na-Ge. Herein, we report a new method for preparing highly dispersed GeO2 by using molecular-level ionic liquids (ILs) as carbon sources. In the obtained GeO2@C composite material, GeO2 exhibits hollow spherical morphology and is uniformly distributed in the carbon matrix. The as-prepared GeO2@C exhibits improved Na ion storage performances including high reversible capacity (577 mA h g-1 at 0.1C), rate property (270 mA h g-1 at 3C), and high capacity retention (82.3% after 500 cycles). The improved electrochemical performance could be attributed to the unique nanostructure of GeO2@C, the synergistic effect between GeO2 hollow spheres and the carbon matrix ensures the anode material effectively alleviates the volume expansion and the particle agglomeration problems.

Approaching high-performance lithium storage materials of CoNiO2 microspheres wrapped coal tar pitch-derived porous carbon.

Ternary transition metal oxides (TMOs) are deemed as promising anode materials of Li-ion batteries (LIBs) owing to their large theoretical capacity and rich redox reaction. Nevertheless, the inherent semiconductor characteristic and enormous volume variation of TMOs during cycling bring about sluggish reaction kinetics, fast capacity fading, and poor rate capability. In this study, three-dimensional (3D) porous CoNiO2@CTP architectures, i.e., CoNiO2 microspheres combined with coal tar pitch-derived porous carbon, were designed and synthesized through a one-step hydrothermal method followed by a heat treatment process for the first time. The microsphere morphology increases the contact area between the anode and electrolyte, shortens the transport distance of Li+ ions, and reduces the agglomeration. The existence of the CTP layer provides rich charge transmission paths, improves the electronic conductivity of CoNiO2 and provides abundant active sites for Li+ storage. Owing to the synergistic effect of porous carbon and microsphere morphology of CoNiO2, the CoNiO2@CTP (10.0 wt%) anode shows remarkable electrochemical performance with a high charge capacity (1437.5 mA h g-1 at 500 mA g-1), good rate performance (839.76 mA h g-1 even at 1 A g-1), and remarkable cycle durability (741.4 mA h g-1 after 1000 cycles at 1 A g-1), which is significantly better than pristine CoNiO2. This study not only provides a simple strategy for high-value utilization of CTP but also offers cost-effective CoNiO2@CTP architectures for high-performance LIBs.

Secrecy Performance Evaluation of Scalable Cell-Free Massive MIMO Systems: A Stochastic Geometry Approach

This paper presents the first performance analysis of physical layer downlink secure transmissions in a scalable cell-free massive MIMO (SCF-mMIMO) system. A stochastic geometry approach is used to model the locations of the access points (APs), user equipments (UEs) and eavesdroppers (Eves) as independent homogeneous Poisson point processes (HPPPs). In addition to applying maximum ratio transmission (MRT) to send the confidential messages, null-space artificial noise is also injected for secrecy enhancement. We analytically characterize the secrecy performance in terms of both the outage-based secrecy transmission rate (STR) and the ergodic secrecy rate (ESR), appropriate for slow quasi-static fading channels and fast block-fading channels, respectively. By utilizing moment matching and Gil-Pelaez inversion theorem, we are able to obtain mathematically tractable approximations for the performance metrics. These approximations are shown to have high accuracy as compared to simulation results. Our numerical results reveal useful design insights that cannot be inferred from existing studies. These insights answer important questions such as whether it is best to deploy as many APs each with fewer antennas and to what extent the artificial noise insertion is beneficial.

An Improved Hybrid Indoor Positioning Algorithm via QPSO and MLP Signal Weighting

Accurate location or positioning of people and self-driven devices in large indoor environments has become an important necessity The application of increasingly automated self-operating moving transportation units, in large indoor spaces demands a precise knowledge of their positions. Technologies like WiFi and Bluetooth, despite their low-cost and availability, are sensitive to signal noise and fading effects. For these reasons, a hybrid approach, which uses two different signal sources, has proven to be more resilient and accurate for the positioning determination in indoor environments. Hence, this paper proposes an improved hybrid technique to implement a fingerprinting based indoor positioning, using Received Signal Strength information from available Wireless Local Area Network access points, together with the Wireless Sensor Networks technology. Six signals were recorded on a regular grid of anchor points, covering the research space. An optimization was performed by relative signal weighting, to minimize the average positioning error over the research space. The optimization process was conducted using a standard Quantum Particle Swarm Optimization, while the position error estimate for all given sets of weighted signals was performed using a Multilayer Perceptron (MLP) neural network. Compared to our previous research works, the MLP architecture was improved to three hidden layers and its learning parameters were finely tuned. These experimental results led to the 20% reduction of the positioning error when a suitable set of signal weights was calculated in the optimization process. Our final achieved value of 0.725 m of the location incertitude shows a sensible improvement compared to our previous results.

LoRa and Rotating Polarization Wave: Physical Layer Principles and Performance Evaluation

Link reliability and enhanced coverage are the primitive concerns of Low-Power Wide-Area Networks (LPWANs) for suitability to critical Internet of Things (IoT) applications. Reliability is limited by the destructive multipath propagation, data rate and sensitivity, that ultimately limits the coverage range. LoRa by far is the predominant LPWAN operating on unlicensed spectrum. Despite its robust Chirp Spread Spectrum (CSS) modulation, there is a severe degradation in its error performance particularly in hostile propagation environments, and an excessive reduction in coverage. Rotating Polarization Wave (RPW) is a potential LPWAN recently emerged to achieve a highly reliable IoT and Machine-to-Machine (M2M) communication. This is the first paper to provide comprehensive error performance comparison between LoRa and RPW. Okumura-Hata model is used for median path loss calculation. Shadowing and fast fading margins of RPW and LoRa are estimated. Effective gain of RPW is computed from error performance. Results have shown that LoRa offers a sensitivity of 23 dB higher than RPW under AWGN conditions. However, under fading conditions, RPW exhibits a sensitivity of 15 dB higher than LoRa. At a reference distance of 100 m, the maximum received signal strength of RPW is -39 dBm, which is 29 dB above LoRa. The maximum coverage distance attained by RPW is 15 km, which is 1.5 times of LoRa.

Chekhov’s Gull

Chekhov’s Gull

Opportunities and Challenges in the Development of Layered Positive Electrode Materials for High-Energy Sodium Ion Batteries: A Computational Perspective

In recent years, high-energy-density sodium ion batteries (SIBs) have attracted enormous attention as a potential replacement for LIBs due to the chemical similarity between Li and Na, high natural abundance, and low cost of Na. Despite the promise of high energy, SIBs with layered cathode materials face several challenges including irreversible capacity loss, voltage hysteresis, voltage decay, irreversible TM migrations that lead to fast capacity fading, and structural degradation. However, their electrochemical performance can be improved by introducing reversible anionic redox along with conventional cationic redox. This Perspective systematically summarizes different factors that trigger the irreversible anionic redox in Na-based cathode materials. Additionally, this Perspective highlights the mechanistic understanding and key challenges for reversible anionic redox and proposes plausible solutions to overcome these limitations. The overview of various existing experimental and theoretical approaches presented here could provide a futuristic pathway to design Na-based cathode materials for high-energy-density SIBs.

Embedding the high entropy alloy nanoparticles into carbon matrix toward high performance Li-ion batteries

The alloying type materials have been proposed to be served as the alternative anode for lithium ion batteries (LIBs) owing to their much higher capacity than graphite. However, those elementary alloying substances still suffer large volume expansion, resulting in much Li-irreversibility of low initial coulombic efficiency (ICE<75%) and fast capacity fading. Herein, inspired by the high entropy concept, we extend the simple elements into the high entropy alloy (HEA) system by rational designing Li-active and high conductive components. Interestingly, one kind atomic disorder HEA composed of Ge-Sn-Sb-Si-Fe-Cu-P is successfully synthesized for the first time, which is surprisingly found delivered ultra-high reversibility (e.g. ICE=91%) for LIBs, combining with suitable plateau (∼0.5 V) and large discharge capacity (1448 mAh/g) as well. Furthermore, such formed HEA nanoparticles are greatly emdedded and encapsulated into carbon matrix to form a dragon-fruit-like HEA/C composite. Benefitted from above unique structural design, the HEA/C composite exhibits superior cyclability (>1600 h operation) and excellent rate performances (787 mAh/g and 63% retention at 2000 mA/g). This successful implement of high entropy concept into alloying type anode materials may open a new avenue to developing series high entropy alloys toward advanced energy storage.

DRL-Based Dependent Task Offloading Strategies with Multi-Server Collaboration in Multi-Access Edge Computing

Many applications in Multi-access Edge Computing (MEC) consist of interdependent tasks where the output of some tasks is the input of others. Most of the existing research on computational offloading does not consider the dependency of the task and uses convex relaxation or heuristic algorithms to solve the offloading problem, which lacks adaptability and is not suitable for computational offloading in the dynamic environment of fast fading channels. Therefore, in this paper, the optimization problem is modeled as a Markov Decision Process (MDP) in multi-user and multi-server MEC environments, and the dependent tasks are represented by Directed Acyclic Graph (DAG). Combined with the Soft Actor–Critic (SAC) algorithm in Deep Reinforcement Learning (DRL) theory, an intelligent task offloading scheme is proposed. Under the condition of resource constraint, each task can be offloaded to the corresponding MEC server through centralized control, which greatly reduces the service delay and terminal energy consumption. The experimental results show that the algorithm converges quickly and stably, and its optimization effect is better than existing methods, which verifies the effectiveness of the algorithm.

Enhanced Cyclability of LiNi0.6Co0.2Mn0.2O2 Cathodes by Integrating a Spinel Interphase in the Grain Boundary.

Nickel-rich layered oxides are promising cathode materials for high-energy-density lithium-ion batteries. Unfortunately, the interfacial instability and intergranular cracks result in fast capacity fading and voltage fading during battery cycling. To address these issues, a coherent spinel interphase in the grain boundary of LiNi0.6Co0.2Mn0.2O2 (NCM) was successfully constructed via solution infusion and heat treatment. The results showed that the spinel (LiMn2O4) interphase could significantly reduce the formation of intergranular cracks during cycling. Meanwhile, the spinel structure on the primary particles effectively suppressed surface degradation, realizing the reduction of interface charge-transfer resistance and electrochemical polarization. As a result, the spinel-modified NCM cathode materials display superior electrochemical cyclability. The 1 wt % spinel phase-modified NCM delivers a discharge capacity of 154.1 mAh g-1 after 300 cycles (1 C, 3-4.3 V) with an excellent capacity retention of 93%.

EVALUATION OF THE MULTIPATH EFFECT ON THE QUALITY OF RADIO COMMUNICATION IN THE TECHNOLOGICAL RANGE IEEE 802.11xx

Background. As a result of the rays’ reflection from buildings, from the surface of the Earth or from horizontal boundaries between different layers of the atmosphere, occur multipath effects that cause fast fading, which degrades the quality of service.&#x0D; Objective. The purpose of the paper is to determine the multipath effect on the signal-to-noise ratio in a wireless communication channel. Compare the results obtained for a communication channel at operating frequencies of the IEEE 802.11xx standard: 5 GHz and 2.4 GHz.&#x0D; Methods. The useful signal powers and the total interference powers for a communication channel with multipath are calculated. The signal-to-noise ratio for such a channel is compared at operating frequencies of 5 GHz and 2.4 GHz.&#x0D; Results. The results of the study showed that the higher the frequency of the carrier of the wireless radio link, the less pronounced the effect of multipath is.&#x0D; The frequency rating significantly affects the quality of communication in multipath conditions. In this case, lowering the frequency significantly improves the reception condition outside of multipath effect. However, it deteriorates significantly due to the effects of rays reflected from the Earth's surface.&#x0D; In the considered case, the useful signal power in the 2.4 GHz band is 4.2 times higher; at the same time, the power of reflected interference is 19 times higher than in the 5 GHz band.&#x0D; Conclusions. Suggested model makes it possible to determine the effect of interference power in the ranges traditionally assigned in IEEE 802.11xx technology, specifically 2.4 GHz and 5 GHz.

High-performance MoS2 quantum dots/graphene functionalized separator and its failure analysis under high sulfur loading

Although functionalized separators have been proved to effectively mitigate the shuttle of lithium polysulfides (LiPSs), the capacity degradation of lithium-sulfur (Li-S) batteries with functionalized separators under high sulfur loading still hasn’t been detailed investigated totally. Herein, the synergistic inhibition effect of ultralight MoS2 quantum dots decorated nitrogen doped reduction of graphene oxides composites (MoS2 QDs-NRGO) modified separator on polysulfides shuttling is achieved. The Li-S batteries with this functional separator exhibit an impressive drop in cycle performance under high sulfur loading that the capacity retention at 71.5 % under sulfur loading of 2 mg cm−2, and only 53.1 % under 6 mg cm−2. Through the in-situ/ex-situ Raman spectroscopy investigation, kinetics analysis and electrochemical performance test, we discover that the inhomogeneous deposition of Li2S is seriously on the separator modified layer under high sulfur loading, which blocks the lithium-ion diffusion kinetics in the separator and increases the reaction between Li2S and lithium anode, leading to the fast capacity fading of Li-S batteries. Afterward, we find an appropriate area-loading of the modified layer can effectively mitigate the deposition of the Li2S, thereby improving the cycling stability of Li-S batteries under the high sulfur loading.

Optimization of NixCo1-x-yMnySe2 composition for efficient sodium storage

Due to the low cost and the abundance of Na resources, sodium-ion batteries (SIBs) have emerged as leading candidates for next-generation energy storage devices. For Se-based anodes, large volume expansion during cycling leads to poor structural reversibility and fast capacity fade. To overcome it, the heterostructured Ni1/3-xCo1/3-yMn1/3-zSe2/MnSe2 is constructed via tuning metal ratio with good controllability, in which the functionalities of heterostructure in realizing high-performance SIBs is comprehensively studied. Benefiting from the synergistic effect of element ratio optimization and heterostructure construction, Ni1/3-xCo1/3-yMn1/3-zSe2/MnSe2 simultaneously realizes high capacity, fast Na+ storage performance, and long-cycling durability. Remarkably, it exhibits a specific capacity of around 400 mAh g−1 at 2 A g−1, and achieves a capacity retention as high as ∼ 99.9 % after 2000 cycles, outperforming most Se-based anodes. Therefore, this work not only demonstrates the significance of heterostructure engineering in a cubic NixCo1-x-yMnySe2 anode, but also opens a new avenue for achieving high-performance electrode materials based on heterostructure construction.

Orchestrating multiple cobalt compounds via a unique dual-templating design towards enhanced sulfur conversion kinetics

The intrinsic polysulfide shuttling and sluggish redox kinetics plague lithium-sulfur (Li-S) batteries with fast capacity fading and poor rate capability. Doping heteroatoms and embedding polar motifs into carbonaceous materials have been reckoned highly effective to promote both polysulfide trapping and catalytic sulfur conversion. Herein, we report polyaniline (PANi)-derived hierarchical carbon capsule co-doped with Co, S, N, F (MHCC) as the sulfur host, synthesized through a dual-template strategy exploiting Escherichia coli as the primary bio-template and ordered mesoporous silica as the secondary pore-forming template. The resulting capsular composite comprises a hollow core surrounded by a mesoporous shell, expressing a variety of active sites including Co-Nx, Co9S8, and CoF2 that synergistically boost the redox kinetics via strong chemisorption and catalytic effects. The Li-S cell with the sulfur/MHCC cathode delivers a high initial discharge capacity of 1331 mAh g−1 at 0.2 C and a long-term lifespan of 700 cycles at 2 C. Moreover, an areal capacity of 8.2 mAh cm−2 is achieved at a high sulfur loading of 8 mg cm−2. This study paves the way for the deployment of green Li-S batteries based on natural products through hierarchical structure design and catalytic engineering.

Stochastic modeling of q-Lognormal fading channels over Tsallis' entropy: Evaluation of channel capacity and higher order moments

In wireless communication systems (WCSs), fading and shadowing of signals are the most frequently encountered phenomena which lead to degradation in the performance of communication channels. Several multipath distribution models like Weibull, Rayleigh, and Nakagami-m models have been extensively used for statistically capturing the fading signals in large-scale propagation scenarios. Several studies have emphasized on exploiting the log-normal model which efficiently characterizes the shadowing signals, or large-scale effects of the propagation channel. However, the conventional log-normal model suffers through some limitations, due to the lack of mathematical tractability in its analytical expression for characterizing shadowed multipath fading signals. In this perspective, the present work proposes a novel adaptive generalized stochastic differential equation (SDE) in context to Tsallis non-extensive sense, which leads to q-Lognormal distribution under a suitable initial condition corresponding to Fokker-Planck equation for effectively capturing the rapid fluctuations in composite signals. The closed form expressions corresponding to the probability density function (PDF) and cumulative distribution function (CDF) are obtained in terms of Gauss-Hypergeometric function F12[a,b,c;z] for the proposed distribution model. Finally, several performance measures like average channel capacity, higher order moments, and coefficient of variation (CV) are estimated for proposed q-Lognormal model by employing extensive Monte-Carlo simulations. The corresponding results obtained by using the above techniques are presented to understand the applicability of the proposed model for modeling WCS and multipath composite signals.

Signal-stabilized Al2O3:C-OSL dosimeter “checking chip” for correcting OSL reader sensitivity variation

Since an OSL reader sensitivity varies 15% over two years, the sensitivity variation should be corrected for every measurement. Conventionally, the OSL reader sensitivity is corrected by either preparing a new reference OSL dosimeter or reusing a reference OSL dosimeter previously used for calibration with corrections for signal depletion and fading effect. To facilitate the correction of the OSL reader sensitivity, a signal-stabilized Al2O3:C-OSL dosimeter “checking chip” was developed in this study. The checking chip has small signal depletion and fading effect, and can correct the OSL reader sensitivity without any corrections. The checking chip was prepared through the following steps. (a) The commercial OSL dosimeter was irradiated with approximately 100 Gy. (b) The irradiated dosimeter was partially bleached by exposing visible light at 30 s to decrease the effect of signal depletion. (c) The partially bleached dosimeter was stored at 50 °C for 30 d to stabilize signal regeneration. To evaluate the usability of the checking chip, dose measurements in a high-energy photon beam were performed for half a year. The absorbed dose to water in a high-energy photon beam was determined by the calibrated ionization chamber and the OSL dosimeter. The sensitivity variation of the OSL reader was corrected by reading the checking chip on every measurement day. The signal stability of the checking chip related to multiple readings and day elapsing were −0.013% per reading and within ±0.5% at 100 d, respectively. The relative standard uncertainty of dose determination with the OSL reader sensitivity correction was 1.7%. The OSL signal of the checking chip was sufficiently stable as a reference signal source and the OSL reader sensitivity variation can be more easily corrected by using the checking chip with the same uncertainty as the conventional method.

A Residual CNN-Based Denoiser for Reliable Recovery of Bit Stream With Applications to Soft Channel Decoding

The noise existent in practical systems degrades reliability performances, especially when delivering data over fast fading channels with the correlated noise. To address this issue, we propose a residual convolutional neural network aided denoiser (ResCNND) to suppress the noise for more reliable information recovery. The intelligent ResCNND is composed by convolutional layers, batch normalization layers and nonlinear activation functions. The ResCNND aided denoiser is then integrated with different types of channel decoders, and we propose a data preprocessing module to embed the statistical characteristics of channel conditions in terms of channel state information (CSI) as inputs to the neural network. Additionally, we propose the loss function by combining the mean square error loss and the normality test loss to simultaneously reduce the noise power and preserve the Gaussian distribution of residual noises. Then the well trained ResCNND can be used to suppress the noise in real time. In simulations, three types of channel codes, including LDPC, Polar and Turbo codes, are considered. The results demonstrate that the proposed ResCNND-aided receiver can effectively improve the signal-to-noise ratio and bit error rate performances with no requirement of perfect CSI, thereby achieving better reliability and robustness performances than benchmark schemes.

Regularized artificial fast fading designs for secure transmission in multi-user MIMO wiretap channels

In this paper, we investigate a regularized artificial fast fading (AFF) design for multi-user multi-input multi-output (MIMO) wiretap channels. To solve the effective channel gain reduction issue in conventional zero-forcing (ZF) based approaches, we propose a regularized AFF beamforming method by applying the minimum mean squared error (MMSE) problem and Lagrangian dual analysis. Finally, simulation results show that the proposed MMSE based AFF scheme improves the error performance of the legitimate user compared to the conventional ZF AFF method while achieving the same low probability of interception at the eavesdropper for multi-user MIMO secure transmission systems.