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See detailEnergy-Efficient Backscatter Aided Uplink NOMA Roadside Sensor Communications under Channel Estimation Errors
Ihsan, Asim; Chen, Wen; Khan, Wali Ullah UL et al

in IEEE Transactions on Intelligent Transportation Systems (2023)

This work presents non-orthogonal multiple access (NOMA) enabled energy-efficient alternating optimization framework for backscatter aided wireless powered uplink sensors communications for beyond 5G ... [more ▼]

This work presents non-orthogonal multiple access (NOMA) enabled energy-efficient alternating optimization framework for backscatter aided wireless powered uplink sensors communications for beyond 5G intelligent transportation system (ITS). Specifically, the transmit power of carrier emitter (CE) and reflection coefficients of backscatter aided roadside sensors are optimized with channel uncertainties for the maximization of the energy efficiency (EE) of the network. The formulated problem is tackled by the proposed two-stage alternating optimization algorithm named AOBWS (alternating optimization for backscatter aided wireless powered sensors). In the first stage, AOBWS employs an iterative algorithm to obtain optimal CE transmit power through simplified closed-form computed through Cardano’s formulae. In the second stage, AOBWS uses a noniterative algorithm that provides a closed-form expression for the computation of optimal reflection coefficient for roadside sensors under their quality of service (QoS) and a circuit power constraint. The global optimal exhaustive search (ES) algorithm is used as a benchmark. Simulation results demonstrate that the AOBWS algorithm can achieve near-optimal performance with very low complexity, which makes it suitable for practical implementations. [less ▲]

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See detailA Survey on STAR-RIS: Use Cases, Recent Advances, and Future Research Challenges
Abdul, Wahid; Ahmed, Manzoor; Laique, Sayed Shariq et al

E-print/Working paper (2023)

The recent development of metasurfaces, which may enable several use cases by modifying the propagation environment, is anticipated to have a substantial effect on the performance of 6G wireless ... [more ▼]

The recent development of metasurfaces, which may enable several use cases by modifying the propagation environment, is anticipated to have a substantial effect on the performance of 6G wireless communications. Metasurface elements can produce essentially passive sub-wavelength scattering to enable a smart radio environment. STAR-RIS, which refers to reconfigurable intelligent surfaces (RIS) that can transmit and reflect concurrently (STAR), is gaining popularity. In contrast to the widely studied RIS, which can only reflect the wireless signal and serve users on the same side as the transmitter, the STAR-RIS can both reflect and refract (transmit), enabling 360-degree wireless coverage, thus serving users on both sides of the transmitter. This paper presents a comprehensive review of the STAR-RIS, with a focus on the most recent schemes for diverse use cases in 6G networks, resource allocation, and performance evaluation. We begin by laying the foundation for RIS (passive, active, STARRIS), and then discuss the STAR-RIS protocols, advantages, and applications. In addition, we categorize the approaches within the domain of use scenarios, which includes increasing coverage, enhancing physical layer security (PLS), maximizing sum rate, improving energy efficiency (EE), and reducing interference. Next, we will discuss the various strategies for resource allocation and measures for performance evaluation. We aimed to elaborate, compare, and evaluate the literature in terms of setup, channel characteristics, methodology, and objectives. In conclusion, we examine the open research problems and potential future prospects in this field. [less ▲]

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See detailIntegration of NOMA with Reflecting Intelligent Surfaces: A Multi-cell Optimization with SIC Decoding Errors
Khan, Wali Ullah UL; Lagunas, Eva UL; Mahmood, Asad UL et al

E-print/Working paper (2023)

Reflecting intelligent surfaces (RIS) has gained significant attention due to its high energy and spectral efficiency in next-generation wireless networks. By using low-cost passive reflecting elements ... [more ▼]

Reflecting intelligent surfaces (RIS) has gained significant attention due to its high energy and spectral efficiency in next-generation wireless networks. By using low-cost passive reflecting elements, RIS can smartly reconfigure the signal propagation to extend the wireless communication coverage. On the other hand, non-orthogonal multiple access (NOMA) has been proven as a key air interface technique for supporting massive connections over limited resources. Utilizing the superposition coding and successive interference cancellation (SIC) techniques, NOMA can multiplex multiple users over the same spectrum and time resources by allocating different power levels. This paper proposes a new optimization scheme in a multi-cell RIS-NOMA network to enhance the spectral efficiency under SIC decoding errors. In particular, the power budget of the base station and the transmit power of NOMA users while the passive beamforming of RIS is simultaneously optimized in each cell. Due to objective function and quality of service constraints, the joint problem is formulated as non-convex, which is very complex and challenging to obtain the optimal global solution. To reduce the complexity and make the problem tractable, we first decouple the original problem into two sub-problems for power allocation and passive beamforming. Then, the efficient solution of each sub-problem is obtained in two-steps. In the first-step of For power allocation sub-problem, we transform it to a convex problem by inner approximation method and then solve it through a standard convex optimization solver in the second-step. Accordingly, in the first-step of passive beamforming, it is transformed to a standard semidefinite programming problem by successive convex approximation and different of convex programming methods. Then, penalty based method is used to achieve a Rank-1 solution for passive beamforming in second-step. Numerical results demonstrate the benefits of the proposed optimization scheme in the multi-cell RIS-NOMA network. [less ▲]

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See detailErgodic Performance Analysis of Double Intelligent Reflecting Surfaces-Aided NOMA–UAV Systems with Hardware Impairment
Nguyen, Minh-Sang Van; Do, Dinh-Thuan; Phan, Van-Duc et al

in Drones (2022)

In this work, we design an intelligent reflecting surface (IRS)-assisted Internet of Things (IoT) by enabling non-orthogonal multiple access (NOMA) and unmanned aerial vehicles (UAV) approaches. We pay ... [more ▼]

In this work, we design an intelligent reflecting surface (IRS)-assisted Internet of Things (IoT) by enabling non-orthogonal multiple access (NOMA) and unmanned aerial vehicles (UAV) approaches. We pay attention to studying the achievable rates for the ground users. A practical system model takes into account the presence of hardware impairment when Rayleigh and Rician channels are adopted for the IRS–NOMA–UAV system. Our main findings are presented to showcase the exact expressions for achievable rates, and then we derive their simple approximations for a more insightful performance evaluation. The validity of these approximations is demonstrated using extensive Monte Carlo simulations. We confirm the achievable rate improvement decided by main parameters such as the average signal to noise ratio at source, the position of IRS with respect to the source and destination and the number of IRS elements. As a suggestion for the deployment of a low-cost IoT system, the double-IRS model is a reliable approach to realizing the system as long as the hardware impairment level is controlled. The results show that the proposed scheme can greatly improve achievable rates, obtain optimal performance at one of two devices and exhibit a small performance gap compared with the other benchmark scheme. [less ▲]

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See detailA Learning Based Framework for Enhancing Physical Layer Security in Cooperative D2D Network
Ahmad, Noman; Sardar Sidhu, Guftaar Ahmad; Khan, Wali Ullah UL

in Electronics (2022)

Next-generation wireless communication networks demand high spectrum efficiency to serve the requirements of an enormous number of devices over a limited available frequency spectrum. Device-to-device ... [more ▼]

Next-generation wireless communication networks demand high spectrum efficiency to serve the requirements of an enormous number of devices over a limited available frequency spectrum. Device-to-device (D2D) communication with spectrum reuse offers a potential solution to spectrum scarcity. On the other hand, non-orthogonal multiple access (NOMA) as a multiple-access approach has emerged as a key technology to re-use a spectrum among multiple users. A cellular users (CUs) can share their spectrum with D2D users (DUs) and in response, the D2D network can help relay the CU signal to achieve better secrecy from an eavesdropper. Power optimization is known to be a promising technique to enhance system performance in challenging communication environments. This work aimed to enhance the secrecy rate of the CUs where the D2D transmitter (DT) helps in relaying the CU’s message under the amplify and forward (AF) protocol. A power optimization problem is considered under the quality of service constraints in terms of minimum rate requirements at the receivers and maximum power budgets at the transmitters. The problem is a non-convex complex optimization. A deep learning-based solution is proposed and promising results are obtained in terms of the secrecy rate of CU and the rate of D2D users. [less ▲]

See detailMULTI-OMICS ANALYSIS OF DIFFERENTIATING DOPAMINERGIC NEURONS IDENTIFIES NOVEL FACTORS NECESSARY FOR LINEAGE SPECIFICATION
Gomez Ramos, Borja UL

Doctoral thesis (2022)

Midbrain dopaminergic neurons (mDANs) control voluntary movement, cognition, and reward behavior and are implicated in human diseases such as Parkinson’s disease (PD). Many transcription factors (TFs ... [more ▼]

Midbrain dopaminergic neurons (mDANs) control voluntary movement, cognition, and reward behavior and are implicated in human diseases such as Parkinson’s disease (PD). Many transcription factors (TFs) controlling human mDAN differentiation have been described but much of the regulatory landscape remains undefined. The location and the low number of these cells in the brain have limited the application of epigenomic assays, as they usually require a high number of cells. Thanks to the emergence of induced pluripotent stem cell (iPSC) technology, differentiation protocols for the derivation of mDANs were developed, making access to this neuronal subtype easier, facilitating its study. However, current protocols for the differentiation of human iPSC towards mDANs produce a mixture of developmentally immature and incompletely specified cells together with more physiological cells. Differentiation protocols are based on the developmental knowledge generated from animal studies and the translation of this knowledge to humans appears not to be completely compatible. Therefore, a better understanding of human development is needed, encouraging the use of human-based models. A proper understanding of the epigenetic landscape of human mDAN differentiation will have direct implications for uncovering gene regulatory mechanisms, disease-associated variants (as most of them are in the non-coding regions of the genome), and cell identity. In this study, a human tyrosine hydroxylase (TH) reporter line of iPSC was used for the generation of time series transcriptomic and epigenomic profiles from differentiating mDANs. TH is the rate-limiting enzyme for dopamine production and therefore a specific marker for mDANs. In the reporter line, mCherry was expressed under the control of the TH promoter, which allowed to isolate mDANs from the cultures by FACS. Integration of time-point-specific chromatin accessibility and associated TF binding motifs with paired transcriptome profiles across 50 days of differentiation was performed using an adapted version of the EPIC-DREM pipeline. Time-point-specific gene regulatory interactions were obtained and served to identify putative key TFs controlling mDAN differentiation. Low-input ChIP-seq for histone H3 lysine 27 acetylation (H3K27ac) was performed to identify and prioritize key TFs controlled by super-enhancer regions. LBX1, NHLH1, and NR2F1/2 were found to be necessary for mDAN differentiation. Overexpression of either LBX1 or NHLH1 was also able to increase mDAN numbers. LBX1 was found to regulate cholesterol biosynthesis and translation possibly via mTOR signaling. NHLH1 was found to be necessary for the induction of miR-124, a potent neurogenic microRNA. Interestingly, miR-124 and NHLH1 appear to be part of a positive feedback loop. Thus, the results from this study provide novel insights into the regulatory landscape of human mDAN differentiation. In addition, as the identified candidates from EPIC-DREM did not show selective expression in mDANs, the data produced was further explored for the identification of novel expression selective TFs in these cells. ZFHX4 was selected as a relevant TF for mDANs that was also downregulated in PD patients. It presented a high and specific expression during development and in adult mDANs from human brains. Depletion of ZFHX4 during differentiation affected mDAN neurogenesis. However, CRISPR-mediated overexpression of ZFHX4 during differentiation did not affect mDAN numbers. Transcriptomic analysis revealed a role of ZFHX4 in controlling cell cycle and cell division on mDANs. ZFHX4 seems to be regulating cell cycle control by interaction with E2F TFs and the NuRD complex, as these proteins have also been associated with this function and appeared in the analysis performed. Overall, the present study provides a novel profile of mDANs during differentiation that can be used for many other applications apart from the one presented here, like the identification of disease-associated variants affecting these neurons. Incorporating epigenetic information into the current transcriptomic knowledge increased the understanding of this neuronal subtype and uncovered important pathways involved in the biology of these cells and most probably with implications to disease. [less ▲]

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See detailNOMA-Enabled Optimization Framework for Next-Generation Small-Cell IoV Networks Under Imperfect SIC Decoding
Khan, Wali Ullah UL; Li, Xingwang; Ihsan, Asim et al

in IEEE Transactions on Intelligent Transportation Systems (2022)

To meet the demands of massive connections, diverse quality of services (QoS), ultra-reliable and low latency in the future sixth-generation (6G) Internet-of-vehicle (IoV) communications, we propose non ... [more ▼]

To meet the demands of massive connections, diverse quality of services (QoS), ultra-reliable and low latency in the future sixth-generation (6G) Internet-of-vehicle (IoV) communications, we propose non-orthogonal multiple access (NOMA)-enabled small-cell IoV network (SVNet). We aim to investigate the trade-off between system capacity and energy efficiency through a joint power optimization framework. In particular, we formulate a nonlinear multi-objective optimization problem under imperfect successive interference cancellation (SIC) detecting. Thus, the objective is to simultaneously maximize the sum-capacity and minimize the total transmit power of NOMA-enabled SVNet subject to individual IoV QoS, maximum transmit power and efficient signal detecting. To solve the nonlinear problem, we first exploit a weighted-sum method to handle the multi-objective optimization and then adopt a new iterative Sequential Quadratic Programming (SQP)-based approach to obtain the optimal solution. The proposed optimization framework is compared with Karush-Kuhn-Tucker (KKT)-based NOMA framework, average power NOMA framework, and conventional OMA framework. Monte Carlo simulation results unveil the validness of our derivations. The presented results also show the superiority of the proposed optimization framework over other benchmark frameworks in terms of system sum-capacity and total energy efficiency. [less ▲]

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See detailOn reliability in the performance analysis of cognitive radio networks
Khan, Abd Ullah; Tanveer, Muhammad; Khan, Wali Ullah UL

in Journal of King Saud University - Computer and Information Sciences (2022)

Satisfying the quality of service (QoS) requirements of users in the form of channel availability and service retainability within the resource limited environment has been a major problem in cognitive ... [more ▼]

Satisfying the quality of service (QoS) requirements of users in the form of channel availability and service retainability within the resource limited environment has been a major problem in cognitive radio networks. In this connection, several research studies have been carried out in the literature to improve the QoS of users by proposing dynamic channel reservation algorithms. However, the studies have a number of limitations in their conceptual and mathematical modeling of channel availability and service retainability, which render their performance evaluation unreliable. In this paper, we address these limitations for leading to more realistic, reliable, and practically valid modeling. For conceptual modeling, we use connection availability in place of channel availability, motivated by the fact that the latter does not necessarily lead to a successful establishment of connection and, thus, is not a suitable performance indicator. For instance, obtaining a channel for transmission is of no avail if the intended receiver is inaccessible. Similarly, we consider service retainability with accessibility/inaccessibility of the intended receiver incorporated. For mathematical modeling, we use CTMC and the resultant closed from expressions to include all the required states of channel availability yet unsuccessful connection establishment. Additionally, we derive closed form equations for channel availability and service retainability that are in exact conformance with the CTMC model. Results confirm that considering the impact of receiver’s accessibility leads to performance difference for the channel availability and service retainability presented in the sate-of-the-art. [less ▲]

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See detailMARL based resource allocation scheme leveraging vehicular cloudlet in automotive-industry 5.0
Ahmed, Manzoor; Liu, Jinshi; Mirza, Muhammad Ayzed et al

in Journal of King Saud University - Computer and Information Sciences (2022)

Automotive-Industry 5.0 will use Beyond Fifth-Generation (B5G) communications to provide robust, abundant computation resources and energy-efficient data sharing among various Intelligent Transportation ... [more ▼]

Automotive-Industry 5.0 will use Beyond Fifth-Generation (B5G) communications to provide robust, abundant computation resources and energy-efficient data sharing among various Intelligent Transportation System (ITS) entities. Based on the vehicle communication network, the Internet of Vehicles (IoV) is created, where vehicles’ resources, including processing, storage, sensing, and communication units, can be leveraged to construct Vehicular Cloudlet (VC) to realize resource sharing. As Connected and Autonomous Vehicles (CAV) onboard computing is becoming more potent, VC resources (comprising stationary and moving vehicles’ idle resources) seems a promising solution to tackle the incessant computing requirements of vehicles. Furthermore, such spare computing resources can significantly reduce task requests’ delay and transmission costs. In order to maximize the utility of task requests in the system under the maximum time constraint, this paper proposes a Secondary Resource Allocation (SRA) mechanism based on a dual time scale. The request service process is regarded as M/M/1 queuing model and considers each task request in the same time slot as an agent. A Partially Observable Markov Decision Process (POMDP) is constructed and combined with the Multi-Agent Reinforcement Learning (MARL) algorithm known as QMix, which exploits the overall vehicle state and queue state to reach effective computing resource allocation decisions. There are two main performance metrics: the system’s total utility and task completion rate. Simulation results reveal that the task completion rate is increased by 13%. Furthermore, compared with the deep deterministic policy optimization method, our proposed algorithm can improve the overall utility value by 70% and the task completion rate by 6%. [less ▲]

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See detailNon-stationary 3-D GBSM channel model for V2Vcommunications
Xu, Yan; Saleem, Asad; Asif, Muhammad et al

in IET Communications (2022)

The spatial characteristics of the propagation channel have a considerable impact onthe applicability of multi-antenna systems. In this paper, a non-stationary 3-D GBSMvehicle-to-vehicle channel model is ... [more ▼]

The spatial characteristics of the propagation channel have a considerable impact onthe applicability of multi-antenna systems. In this paper, a non-stationary 3-D GBSMvehicle-to-vehicle channel model is proposed in the tunnel environment based on massivemultiple-input multiple-output antenna arrays. Instead of the plane wavefront assumptionsutilized in traditional multiple-input multiple-output systems, the proposed channel modelfor vehicle-to-vehicle communications uses spherical wavefront assumptions. Initially, thechannel impulse response and closed-form expression for the probability density func-tion of angle-of-departure and angle-of-arrival are derived in the elevation and azimuthplanes. Following that, due to the mobility of transmitting and receiving antenna arrays,expressions for the delay spread (DS), Doppler power spectrum density, temporal cross-correlation function, and channel capacity are extracted by examining line of sight andthe non line of sight propagation paths. The influence of numerous model parameterson the temporal cross-correlation function is also investigated, including antenna arrayspacing,K-factor, movement velocity, and time separation. The proposed 3-D model’s sta-tistical characteristics are verified through measurements, simulations, and analytical results,revealing its adaptability and effectiveness in the high-speed-train environment. [less ▲]

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See detailLearning-Based Resource Allocation for Backscatter-Aided Vehicular Networks
Khan, Wali Ullah UL; Nguyen, Tu N.; Jameel, Furqan et al

in IEEE Transactions on Intelligent Transportation Systems (2022)

Heterogeneous backscatter networks are emerging as a promising solution to address the proliferating coverage and capacity demands of next-generation vehicular networks. However, despite its rapid ... [more ▼]

Heterogeneous backscatter networks are emerging as a promising solution to address the proliferating coverage and capacity demands of next-generation vehicular networks. However, despite its rapid evolution and significance, the optimization aspect of such networks has been overlooked due to their complexity and scale. Motivated by this discrepancy in the literature, this work sheds light on a novel learning-based optimization framework for heterogeneous backscatter vehicular networks. More specifically, the article presents a resource allocation and user association scheme for large-scale heterogeneous backscatter vehicular networks by considering a collaboration centric spectrum sharing mechanism. In the considered network setup, multiple network service providers (NSPs) own the resources to serve several legacy and backscatter vehicular users in the network. For each NSP, the legacy vehicle user operates under the macro cell, whereas, the backscatter vehicle user operates under small private cells using leased spectrum resources. A joint power allocation, user association, and spectrum sharing problem has been formulated with an objective to maximize the utility of NSPs. In order to overcome challenges of high dimensionality and non-convexity, the problem is divided into two subproblems. Subsequently, a reinforcement learning and a supervised deep learning approach have been used to solve both subproblems in an efficient and effective manner. To evaluate the benefits of the proposed scheme, extensive simulation studies are conducted and a comparison is provided with benchmark techniques. The performance evaluation demonstrates the utility of the presented system architecture and learning-based optimization framework. [less ▲]

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See detailEfficient Matching-Based Parallel Task Offloading in IoT Networks
Malik, Usman Mahmood; Javed, Muhammad Awais; Frnda, Jaroslav et al

in Sensors (2022)

Fog computing is one of the major components of future 6G networks. It can provide fast computing of different application-related tasks and improve system reliability due to better decision-making ... [more ▼]

Fog computing is one of the major components of future 6G networks. It can provide fast computing of different application-related tasks and improve system reliability due to better decision-making. Parallel offloading, in which a task is split into several sub-tasks and transmitted to different fog nodes for parallel computation, is a promising concept in task offloading. Parallel offloading suffers from challenges such as sub-task splitting and mapping of sub-tasks to the fog nodes. In this paper, we propose a novel many-to-one matching-based algorithm for the allocation of sub-tasks to fog nodes. We develop preference profiles for IoT nodes and fog nodes to reduce the task computation delay. We also propose a technique to address the externalities problem in the matching algorithm that is caused by the dynamic preference profiles. Furthermore, a detailed evaluation of the proposed technique is presented to show the benefits of each feature of the algorithm. Simulation results show that the proposed matching-based offloading technique outperforms other available techniques from the literature and improves task latency by 52% at high task loads. [less ▲]

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See detailA Reusable Structural System Fit for Geometrical Standardisation and Serial Production
Odenbreit, Christoph UL; Yang, Jie UL; Romero, Alfredo UL et al

in ce/papers (2022, August 31)

A series of demountable connections for reusable composite flooring systems and a standardized adjustable steel connection have been developed and tested, to facilitate circular economy as well as the ... [more ▼]

A series of demountable connections for reusable composite flooring systems and a standardized adjustable steel connection have been developed and tested, to facilitate circular economy as well as the serial production of structural elements and the suitability to be added into BIM or other digital tools. Demountable beam and floor elements and adjustable steel con-nections form the basis of a Lego-liked ‘plug and play’ circular framed structural system. This paper presents the proposed circular system, the results from experiments and finite element analyses and indicates the analysing methods for structural engineers to open a path way for fully implementation of the structures ‘as built’ into digital tools, fabrication and construction. [less ▲]

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See detailNumerical Investigation of Steel-LVL Timber Composite Beams
Romero, Alfredo UL; Yang, Jie UL; Hanus, François et al

in ce/papers (2022, August 31)

In the last years, new connectors of steel-concrete composite flooring systems have been developed and investigated to enhance the circularity and standardisation of building components. Recent studies ... [more ▼]

In the last years, new connectors of steel-concrete composite flooring systems have been developed and investigated to enhance the circularity and standardisation of building components. Recent studies showed that timber can be used as an alternative to the concrete slab in hybrid structures. However, the knowledge in steel-timber composite flooring systems is still very limited. This contribution presents numerical investigations of steel-LVL timber composite beams. The load deformation behaviour was determined through 3D finite element models. The design resistance of the composite beams was estimated analytically through a strain-controlled approach. The results of this study show that the resistances obtained in the numerical models and the strain-controlled approach are in good agreement. Moreover, obtained deflections and slip values were given at ultimate load. [less ▲]

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See detailInvestigations on the lateral-torsional buckling of an innovative U-shaped steel beam in construction stage of composite beam
Turetta, Maxime; Odenbreit, Christoph UL; Khelil, Abdelouahab et al

in Structures (2022), 44

Structural elements of building have to meet a multitude of requirements. Besides the static load bearing capacity, common requirements are the structural integrity and efficiency during the construction ... [more ▼]

Structural elements of building have to meet a multitude of requirements. Besides the static load bearing capacity, common requirements are the structural integrity and efficiency during the construction stage and sufficient fire resistance. Within the French CIFRE research project COMINO, an innovative type of composite beam was developed for buildings beams with a span of 6 -12m, which need fire resistance until 2 hours with no additional supports at construction stage. The developed solution is composed of a steel U-section acting as a formwork in construction stage for a reinforced concrete part that provides the fire resistance. In the exploitation stage, the steel and the reinforced concrete are acting together as a composite beam. In construction stage, when the concrete is not hardened and thus the stabilizing effect is not present, the steel beam, is subjected to Lateral-Torsional Buckling. In order to investigate the structural behaviour of the new developed steel section in construction stage, a single full-scale test has been carried out at the Laboratory of Structural Engineering of the University of Luxembourg. This article focuses on the stability of the steel beam made of thin-walled steel parts without considering any stabilizing effect. The test results are then compared to the results of numerical investigations and to the analytical solutions of EN 1993. [less ▲]

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See detailEnergy Efficient Transmission Design for NOMA Backscatter-Aided UAV Networks with Imperfect CSI
AlJubayrin, Saad; Al-Wesabi, Fahd N.; Alsolai, Hadeel et al

in Drones (2022)

The recent combination of ambient backscatter communication (ABC) with non-orthogonal multiple access (NOMA) has shown great potential for connecting large-scale Internet of Things (IoT) in future ... [more ▼]

The recent combination of ambient backscatter communication (ABC) with non-orthogonal multiple access (NOMA) has shown great potential for connecting large-scale Internet of Things (IoT) in future unmanned aerial vehicle (UAV) networks. The basic idea of ABC is to provide battery-free transmission by harvesting the energy of existing RF signals of WiFi, TV towers, and cellular base stations/UAV. ABC uses smart sensor tags to modulate and reflect data among wireless devices. On the other side, NOMA makes possible the communication of more than one IoT on the same frequency. In this work, we provide an energy efficient transmission design ABC-aided UAV network using NOMA. This work aims to optimize the power consumption of a UAV system while ensuring the minimum data rate of IoT. Specifically, the transmit power of UAVs and the reflection coefficient of the ABC system are simultaneously optimized under the assumption of imperfect channel state information (CSI). Due to co-channel interference among UAVs, imperfect CSI, and NOMA interference, the joint optimization problem is formulated as non-convex, which involves high complexity and makes it hard to obtain the optimal solution. Thus, it is first transformed and then solved by a sub-gradient method with low complexity. In addition, a conventional NOMA UAV framework is also studied for comparison without involving ABC. Numerical results demonstrate the benefits of using ABC in a NOMA UAV network compared to the conventional UAV framework. [less ▲]