Robust Transmission Research Articles

Performance of Unslotted ALOHA With Capture and Multiple Collisions in LoRaWAN

This paper explores the capacity limits and the tradeoff between the antagonistic means of enabling reliable data delivery in a loaded LoRaWAN cell. In fact, channel attenuation and variability call for robust transmission settings but the associated load increase causes more collisions between frames. In addition to the physical layer parameters of the LoRa modulation, this paper considers the benefits and tuning of inter-packet Error Correction Codes (ECC), which also trades transmission redundancy for reliability. We thus start by proposing a refined Packet Delivery Ratio (PDR) model that improves the ones found in the literature in that, first, it takes into account the dependency between overcoming ambient noise and dominating colliding frames, and second, it considers the sum of interference powers when multiple colliding frames are present, even if the interference preexists. Moreover, the model extends to the case of a gateway with receiver diversity. In a second step, the model allows to set out the level of redundancy at which ECC is the most effective without hindering capacity: a coding rate of one third. When this is fixed, it allows to define the transmission parameters allocation within a cell and thus the size of the cell. We finally develop an ad-hoc Python discrete-event simulator, freely accessible, to complement the model for assessing the effect of inter-SF and near-far interference and to show the benefits of power control in this respect.

Versatile biomimetic catalyst functionalized nanozymes for electrochemical sensing

Electrochemical sensors face challenges in the readily accessible versatile sensing materials, robust signal transmission and selective detection of analytes in complex systems. Herein, we report a simple one-pot approach using commercially available materials to synthesize versatile biomimetic catalyst functionalized nanozymes for multifunctional electrochemical sensors. Nanoenzymes were synthesized by in situ polymerization of 3,4-ethylenedioxythiophene (EDOT) on graphene (GR) while integrating biomimetic catalysts into nanosheets. The resulting nanozymes exhibited stable and efficient catalysis activity and interfacial signal transmission through electrostatic and π-π interactions, as well as charge transfer at the active centers. By virtue of excellent electron transfer and favorable cascade catalysis effect, the biosensor based on sulfonated cobalt phthalocyanine functionalized nanozymes (CoPcNS) and acetylcholinesterase (AChE) exhibited superior catalytic activity and robust stability. This one-pot method was also used to prepare nanozymes with diverse biomimetic catalysts (metallophthalocyanine and metalloporphyrin), achieving specific detection of various biomolecules (H2O2, NO, etc.). A portable biosensing device based on a screen-printed electrode was developed, featuring a low limit of detection, ultralow working potential, high anti-interference capability, and good applicability for the rapid detection of organophosphorus pesticides (OPs) in real samples. Our research presents a promising guide for the rational fabrication of versatile biomimetic catalyst-functionalized nanozymes, advancing the development of electrochemical sensors in environmental and biological fields.

Asymmetric responses of equity returns to changes in exchange rates at different market volatility levels

Our study aims to explore interactions between equity market returns and exchange rates at different market risk zones proxied by the Chicago Board Options Exchange Volatility Index (VIX). We analyze comovements between daily S&P 500 returns and three different USD exchange rates: the Federal Reserve's Nominal Broad U.S. Dollar Index, the Nominal Advanced Foreign Economies U.S. Dollar Index, and the USD in euro. The comovements are examined at three VIX zones (low, intermediate, and high) that we identify by employing the self-exciting threshold autoregressive SETAR(2,p) tests on daily data from January 03, 2006 to January 23, 2023. We subsequently employ VAR and conditional least square tests for S&P 500 returns and log changes in USD exchange rates with all showing the most robust transmission of shocks between equity returns and exchange rates in the high VIX zone. We further run Markov switching tests to identify specific jump periods from low to high responsiveness of equity returns to the USD exchange rate. Our tests show that interactions between equity returns and exchange rates are asymmetric, i.e., the exchange rate elasticity of equity returns is pronounced during periods of high market volatility and indiscernible at periods of low volatility. These findings may be useful for forecasting equity returns, exchange rates, as well as for asset pricing and portfolio diversification.

Control of wave scattering for robust coherent transmission in a disordered medium

Control of wave scattering for robust coherent transmission in a disordered medium

Simulating Generalised Locational Marginal Pricing for Power Markets in East Africa

There is an enormous opportunity for adopting a wholesale electricity market under locational marginal pricing. Besides ensuring competition and accounting for network congestion, the price signal reflects a space-time electricity economy. This paper examines the prospects of introducing a single East African electricity market in five selected partner states. It reports on a pioneering effort to simulate the coupling of power markets, estimate locational marginal prices, and determine the economic benefits of cross-border power trade and competition across these five countries. The nodes representing the primary power systems in these five countries are simulated in an optimal power flow model using optimisation software GAMS. The total welfare of electric power market integration is estimated at $ 4.8 million/hr, representing a welfare gain of $ 2.6 million/hr, thus, net total welfare increases by 118%. The simulation also investigates the implications for locational prices and power flows under constrained and unconstrained scenarios. To secure the benefits of an integrated electricity market, it is vital to pursue significant institutional restructuring, a robust transmission infrastructure, and the harmonisation of energy policies.

Spatial multiplexing for robust optical vortex transmission with optical nonlinearity

Optical vortex beams, with phase singularity characterized by a topological charge (TC), introduces a new dimension for optical communication, quantum information, and optical light manipulation. However, the evaluation of TCs after beam propagation remains a substantial challenge, impeding practical applications. Here, we introduce vortices in lateral arrays (VOILA), a novel spatial multiplexing approach that enables simultaneous transmission of a lateral array of multiple vortices. Leveraging advanced learning techniques, VOILA effectively decodes TCs, even in the presence of strong optical nonlinearities simulated experimentally. Notably, our approach achieves substantial improvements in single-shot bandwidth, surpassing single-vortex scheme by several orders of magnitude. Furthermore, our system exhibits precise fractional TC recognition in both linear and nonlinear regimes, providing possibilities for high-bandwidth communication. The capabilities of VOILA promise transformative contributions to optical information processing and structured light research, with significant potential for advancements in diverse fields.

A Flexibility-oriented robust transmission expansion planning approach under high renewable energy resource penetration

High penetrations of renewable energy sources incorporated into transmission systems pose a substantial challenge to transmission expansion planning operations due to both the strong uncertainty of these sources and their high variability. However, most current robust transmission expansion planning studies focus exclusively on the issue of uncertainty, and neglect to optimize system flexibility in an effort to cope with the high variability of these sources. The present work addresses this critical issue by proposing a flexibility-oriented robust transmission expansion planning method developed according to the unit commitment characteristics of coal-fired and gas-fired generation units that fully considers the short-term flexibility requirements of electric power systems while maintaining high robustness to the uncertainties of RES outputs in long-term transmission expansion planning problems. The proposed complex model with unit commitment constraints containing massive binary variables is solved by first reducing the number of binary variables via the application of clustering techniques to identify generator units with similar generation properties, and then decreasing the complexity of the model further by relaxing the integer variables in the unit-clustered model. Finally, we develop generalized column-and-constraint generation algorithms that can solve the clustered model and the relaxed simplified model with greatly enhanced efficiency. Comparisons of the numerical results obtained by the proposed approach with existing state-of-the-art methods when applied to a simple Garver 6-node system and a realistically-sized power system demonstrate that the proposed method produces optimal RTEP solutions that account for both the uncertainty and variability of RES outputs. Moreover, the total cost of the proposed approach is 2.22×106$ less than that of the other state-of-the-art methods considered, which is of great significance in guiding practical transmission expansion planning applications.

Coordinated Multi-Beam Transmissions for Reliable Millimeter-Wave Communications With Independent and Correlated Blockages

Millimeter-Wave (mmWave) communication has been considered as one of enabling technologies for the sixth generation (6G) network and beyond to boost the system throughput, which however is hard to provide robust and reliable transmissions since it is easy to be blocked. Coordinated multi-beam transmission has emerged as an effective way to overcome this challenge. In this paper, we first define an incomplete blockage probability and a correlated blockage probability for each user equipment (UE) to measure the robustness and reliability in coordinated multi-beam transmissions, and then formulate the coordinated multi-beam selection and transmission power allocation problem to maximize the sum rate of all UEs in consideration of the independent blockage probability and dependent blockage probability constraints of each UE in mmWave networks. To solve the considered problem efficiently, we reformulate it as a hierarchical game model and design a decentralized algorithm to search the Nash Equalibriums (NEs) of the games. Finally, we present extensive simulation results to demonstrate the effectiveness of the proposed scheme.

Enhancing Packet Reliability in Wireless Multimedia Sensor Networks using a Proposed Distributed Dynamic Cooperative Protocol (DDCP) Routing Algorithm

Wireless Multimedia Sensor Networks (WMSNs) are being extensively utilized in critical applications such as environmental monitoring, surveillance, and healthcare, where the reliable transmission of packets is indispensable for seamless network operation. To address this requirement, this work presents a pioneering Distributed Dynamic Cooperation Protocol (DDCP) routing algorithm. The DDCP algorithm aims to enhance packet reliability in WMSNs by prioritizing reliable packet delivery, improving packet delivery rates, minimizing end-to-end delay, and optimizing energy consumption. To evaluate its performance, the proposed algorithm is compared against traditional routing protocols like Ad hoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR), as well as proactive routing protocols such as Optimized Link State Routing (OLSR). By dynamically adjusting the transmission range and selecting optimal paths through cooperative interactions with neighboring nodes, the DDCP algorithm offers effective solutions. Extensive simulations and experiments conducted on a wireless multimedia sensor node testbed demonstrate the superior performance of the DDCP routing algorithm compared to AODV, DSR, and OLSR, in terms of packet delivery rate, end-to-end delay, and energy efficiency. The comprehensive evaluation of the DDCP algorithm against multiple routing protocols provides valuable insights into its effectiveness and efficiency in improving packet reliability within WMSNs. Furthermore, the scalability and applicability of the proposed DDCP algorithm for large-scale wireless multimedia sensor networks are confirmed. In summary, the DDCP algorithm exhibits significant potential to enhance the performance of WMSNs, making it a suitable choice for a wide range of applications that demand robust and reliable data transmission.

Robust Energy-Efficient Transmission for Cell-Free Massive MIMO Systems with Imperfect CSI

In this paper, we investigate a long-term power minimization problem of cell-free massive multiple-input multiple-output (MIMO) systems. To address this issue and to ensure the system queue stability, we formulate a dynamic optimization problem aiming to minimize the average total power cost in a time-varying system under imperfect channel conditions. The problem is then converted into a real-time weighted sum rate maximization problem for each time slot using the Lyapunov optimization technique. We employ approximation techniques to design robust sparse beamforming, which enables energy savings of the network and mitigates channel uncertainty. By applying direct fractional programming (DFP) and alternating optimization, we can obtain a locally optimal solution. Our DFP-based algorithm minimizes the average total power consumption of the network while satisfying the quality of service requirements for each user. Simulation results demonstrate the rapid convergence of the proposed algorithm and illustrate the tradeoff between average network power consumption and queue latency.

Expansion planning of the transmission network with high penetration of renewable generation: A multi-year two-stage adaptive robust optimization approach

This paper addresses the multi-year two-stage expansion planning of the transmission network of a power system with high penetration of renewable generation modeling long-term uncertainty by using adaptive robust optimization. The multi-year nature of the problem is modeled by considering a comprehensive view of the planning horizon. A cardinality-constrained uncertainty set is used to model the future worst-case uncertainty realization of the peak power consumption of loads, along with the capacity and marginal production cost of generating units. Unlike previous works, we model certain features of the operation that are typically ignored in multi-year robust transmission network expansion planning problems, namely, the operational variability of renewable generating units, the operational flexibility of conventional generating units, and the non-convex operational feasibility sets of storage facilities. The solution procedure employed for this multi-year two-stage robust problem, which is formulated as a three-level problem, is based on the combination of the nested column-and-constraint generation algorithm with two exact acceleration techniques. We analyze the performance of the proposed model through the use of the IEEE 24-bus Reliability Test System and the IEEE 118-bus Test System. Numerical results show that the use of the multi-year approach leads to reductions in the total worst-case cost of up to 7% in comparison with the static and sequential static procedures. Moreover, an underestimation of the total worst-case cost of more than 8% is attained when ignoring certain operational constraints of conventional generating units and storage facilities. Lastly, a sensitivity analysis is presented in order to illustrate the impact of the maximum deviations of the uncertain parameters on the total worst-case cost.

Robust Max-Min Fairness Transmission Design for IRS-Aided Wireless Network Considering User Location Uncertainty

In this paper, we propose a robust max-min fairness transmission design for intelligent reflecting surface (IRS)-aided wireless network in the presence of user location uncertainty. In particular, the non-isotropic reflection property for the IRS element is considered. We investigate the joint design of the active transmit beamformer at the base station (BS) and the passive phase shift matrix along with the deployment orientation (facing/pointing direction) of the IRS for maximizing the worst-case minimum signal-to-interference-plus-noise ratio (SINR) received by the users. In order to show the potential gains obtained by adjusting the deployment orientation of the IRS, a single-input-single-output (SISO) system is studied where a closed-form signal-to-noise ratio (SNR) of the user is obtained. For the multi-user case, to solve the resulting non-convex problem, an inexact-alternating-optimization algorithm consisting of a double-loop iteration is proposed. Specifically, in the inner loop, an optimization problem with semi-infinite constraints needs to be solved to increase the worst-case min-SINR compared to the given SINR reference value. We first transform the semi-infinite constraints into linear matrix inequality (LMI) constraints with finite form by applying the Taylor expansion approximation method, the general S-procedure, and the general sign-definiteness lemma. Then an efficient alternating optimization (AO) algorithm based on the two-dimensional search method, negative square penalty (NSP) method, and successive convex approximation (SCA) technique is proposed. While in the outer loop, we update the given SINR reference value as the worst-case minimum SINR obtained after each inner loop iteration. The whole algorithm terminates when the updated SINR reference values converge. Simulation results demonstrate the effectiveness of the proposed algorithm, and also show the additional system performance gain brought by the optimization of the IRS deployment orientation compared to its counterpart with fixed IRS deployment orientation, especially for a smaller IRS element number and a more prominent non-isotropic reflection property of the IRS element.

Robust Downlink Transmission Design in IRS-Assisted Cognitive Satellite and Terrestrial Networks

Cognitive satellite and terrestrial network (CSTN) is considered as a promising technology to provide ubiquitous connectivity for various users within wide-coverage. This paper proposes a robust downlink transmission scheme for multiple intelligent reflecting surfaces (IRSs) assisted CSTN. Here, the satellite network adopts multigroup multicast transmission scheme to serve many earth stations, while the terrestrial network exploits space division multiple access and multi-IRS-enhanced non-orthogonal multiple access technology to communicate with many terrestrial users. By assuming that these two networks share the same frequency band having only the angular information based imperfect channel state information of each user, we formulate an optimization problem to minimize the total transmit power subject to the constraints of quality-of-service requirement for each user, per-antenna transmit power budgets of satellite and BS, and unit-modulus requirement for each reflecting element. To tackle this mathematically intractable problem, we then employ angular discretization together with the successive convex approximation method to obtain the active beamforming (BF) vectors of satellite and BS, the passive BF vector of IRS, and the power allocation coefficients. Moreover, we propose a generalized zero forcing BF and alternative optimization to obtain the suboptimal solutions of the optimization problem with low computational complexity. Finally, simulation results are given to demonstrate the effectiveness and superiority of the proposed two schemes over the benchmarks.

Transmission of Vortex Solitons in Three-Dimensional χ(2) Helical-Periodically Poled Ferroelectric Crystals

It is well known that bright vortex solitons are unstable in the χ2 nonlinear media due to the strong azimuthal modulation instability. To solve this problem, a quadratic (χ2) LiNbO3 ferroelectric crystal with a special kind of helical-periodically poled structure is proposed. The proposed structure is designed by embedding topological charges into the crystal with a quasi-phase matching technique. Simulation results indicate that vortex solitons containing fundamental-frequency and second-harmonic waves can robustly propagate over a distance. Two types of vortex states are obtained: double vortices state and vortex–antivortex state. The dependence of effective area, propagation constants, and maximum light intensity on the control parameters are presented. These results provide a new solution for robust transmission of bright vortex solitons in a χ2 nonlinear media.

SDN-IoT: SDN-based efficient clustering scheme for IoT using improved Sailfish optimization algorithm.

The Internet of Things (IoT) includes billions of different devices and various applications that generate a huge amount of data. Due to inherent resource limitations, reliable and robust data transmission for a huge number of heterogenous devices is one of the most critical issues for IoT. Therefore, cluster-based data transmission is appropriate for IoT applications as it promotes network lifetime and scalability. On the other hand, Software Defined Network (SDN) architecture improves flexibility and makes the IoT respond appropriately to the heterogeneity. This article proposes an SDN-based efficient clustering scheme for IoT using the Improved Sailfish optimization (ISFO) algorithm. In the proposed model, clustering of IoT devices is performed using the ISFO model and the model is installed on the SDN controller to manage the Cluster Head (CH) nodes of IoT devices. The performance evaluation of the proposed model was performed based on two scenarios with 150 and 300 nodes. The results show that for 150 nodes ISFO model in comparison with LEACH, LEACH-E reduced energy consumption by about 21.42% and 17.28%. For 300 ISFO nodes compared to LEACH, LEACH-E reduced energy consumption by about 37.84% and 27.23%.

Effect of Doping with Zinc Oxide on The Structural, Surface, and Optical Properties of Titanium Dioxide Thin Films

Titanium oxide thin films that are both undoped and doped with zinc have been produced in rates of (0, 2 and 4) %. The titanium oxide films doped with zinc were made by combining cadmium acetate with zinc acetate in a solution of titanium acetate with (0.2 M). X-ray diffraction tests showed that the films of undoped TiO2 and (TiO2: Zn) are polycrystalline with (121) orientation. Additionally, the crystallization of films rises as zinc doping level rises. With zinc doping concentration, the grain size of the deposited films is around (15.55-17.91) nm, while the strain (%) parameter decreases from 22.29 to 19.35 with zinc. The grain size was in the range of (90.9), (67.8), and (37.7) nm for the (Ti O2, TiO2: 2% Zn, and TiO2:4% Zn) accordingly in Atomic Force Macroscopy pictures of the film surface morphology. Surface roughness and rms values for the deposited films for undoped TiO2 and TiO2:2% Zn, and TiO2:4%Zn were (6.72, 3.34, and 2.034) nm and (8.80, 8.03, and 4.24), respectively. The spectrum of absorbance and transmission was used to study the optical characteristics. The investigation revealed that the films have robust transmission throughout the visible spectrum and that this transmission decreases with increased doping with zinc content. In addition, the edge of the films' absorbance changes to high wavelengths, which supports a drop in energy gap values. Also computed and discovered to vary with increased doping with zinc concentration were the absorption coefficient, refractive index, and extinction coefficient.

Compact topological polarization beam splitter based on all-dielectric fishnet photonic crystals.

Conventional polarization beam splitters (PBSs) suffer energy loss and signal distortion due to backscattering caused by disturbances. Topological photonic crystals provide backscattering immunity and anti-disturbance robustness transmission owing to the topological edge states. Here, we put forward a kind of dual-polarization air hole-type fishnet valley photonic crystal with a common bandgap (CBG). The Dirac points at the K point formed by different neighboring bands for transverse magnetic and transverse electric polarizations are drawn closer via changing the filling ratio of the scatterer. Then the CBG is constructed by lifting the Dirac cones for dual polarizations within a same frequency range. We further design a topological PBS using the proposed CBG via changing the effective refractive index at the interfaces which guide polarization-dependent edge modes. Based on these tunable edge states, the designed topological PBS (TPBS) achieves efficient polarization separation and is robust against sharp bends and defects, verified by simulation results. The TPBS's footprint is approximately 22.4 × 15.2 μ m 2, allowing high-density on-chip integration. Our work has potential application in photonic integrated circuits and optical communication systems.

Robust Beamforming Design for IRS-Aided Secure Communication Systems Under Complete Imperfect CSI

We investigate the performance of an intelligent reflecting surface (IRS) aided secure communication system which operates in a complete imperfect channel state information (CSI) regime. By jointly considering the imperfect CSI of both IRS-Bob and IRS-Eve channels, we propose a robust transmission scheme which is based upon a joint optimization of the continuous transmit beamforming at Alice and the discrete phase shifts at the IRS. To deal with this mixed integer non-convex optimization problem, novel lower- and upper-bounding techniques are used to transform it in a more tractable form for which a solution based upon the derivation of a quantization-based alternative optimization (AO) algorithm is presented. More specifically, on the one hand, a successive convex approximation (SCA) algorithm is proposed to optimize the continuous transmit beamforming. On the other hand, by applying a SCA, penalty convex-concave procedure (PCCP), and quantization-based algorithm, the discrete phase shifts are obtained. Various performance evaluation results obtained by means of computer simulations have shown that the proposed robust transmission scheme guarantees a minimum quality of service (QoS) while simultaneously limits Eve's maximum eavesdropping rate.

Robust Beamforming Design for RIS-Aided NOMA Secure Networks With Transceiver Hardware Impairments

Integrating reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) provides a promising solution to support large-scale secure communications. However, reducing the impact of transceiver hardware impairments (HWI) on the performance of RIS-aided NOMA secure networks remains a challenge. In this paper, we propose a robust transmission scheme for RIS-aided NOMA secure networks with transceiver HWI under two proposed eavesdropping scenarios and two artificial noise methods. A closed-form expression for the distortion noise power caused by transceiver HWI in NOMA networks is derived to quantify transceiver HWI. The sum secrecy rate of NOMA users with imperfect successive interference cancellation (SIC) is maximized under distortion noise for more robust security. Further, to tackle the resulting non-convex problem, we decompose it into two sub-problems. Both of them are converted into convex problems using the multi-dimensional quadratic transform (MDQT) method, semi-definite relaxation (SDR) technique, and the successive convex approximation (SCA) algorithm, and then employing the alternate optimization (AO) algorithm solve them. Numerical results demonstrate that the proposed scheme has superior security performance over orthogonal multiple access (OMA) networks, time division multiple access (TDMA) networks, and traditional NOMA networks, achieving more robust performance than the conventional scheme that ignores HWI and imperfect SIC.

Topological rainbow based on coupling of topological waveguide and cavity.

Topological photonics and topological photonic states have opened up a new frontier for optical manipulation and robust light trapping. The topological rainbow can separate different frequencies of topological states into different positions. This work combines a topological photonic crystal waveguide (topological PCW) with the optical cavity. The dipole and quadrupole topological rainbows are realized through increasing cavity size along the coupling interface. The flatted band can be obtained by increasing cavity length due to interaction strength between the optical field and defected region material which is extensively promoted. The light propagation through the coupling interface is built on the evanescent overlapping mode tails of the localized fields between bordering cavities. Thus, the ultra-low group velocity is realized at a cavity length more than the lattice constant, which is appropriate for realizing an accurate and precise topological rainbow. Hence, this is a novel release for strong localization with robust transmission and owns the possibility to realize high-performance optical storage devices.