| 1. |
- Basharat, S., et al.
(författare)
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Reconfigurable Intelligent Surfaces : Potentials, Applications, and Challenges for 6G Wireless Networks
- 2021
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Ingår i: IEEE wireless communications. - : Institute of Electrical and Electronics Engineers Inc.. - 1536-1284 .- 1558-0687.
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Tidskriftsartikel (refereegranskat)abstract
- Reconfigurable intelligent surfaces (RISs), with the potential to realize smart radio environments, have emerged as an energy-efficient and a cost-effective technology to support the services and demands foreseen for coming decades. By leveraging a large number of low-cost passive reflecting elements, RISs introduce a phase-shift in the impinging signal to create a favorable propagation channel between the transmitter and the receiver. In this article, we provide a tutorial overview of RISs for sixth-generation (6G) wireless networks. Specifically, we present a comprehensive discussion on performance gains that can be achieved by integrating RISs with emerging communication technologies. We address the practical implementation of RIS-assisted networks and expose the crucial challenges, including the RIS reconfiguration, deployment and size optimization, and channel estimation. Furthermore, we explore the integration of RIS and non-orthogonal multiple access (NOMA) under imperfect channel state information (CSI). Our numerical results illustrate the importance of better channel estimation in RIS-assisted networks and indicate the various factors that impact the size of RIS. Finally, we present promising future research directions for realizing RIS-assisted networks in 6G communication. IEEE
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| 2. |
- Minhaj, Syed Usama, et al.
(författare)
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How SIC-enabled LoRa Fares under Imperfect Orthogonality?
- 2021
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Ingår i: IWCMC 2021. - : IEEE. - 9781728186160 ; , s. 729-734
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Konferensbidrag (refereegranskat)abstract
- With the increase of connected Internet-of-things (IoT) devices, the need for low-power wide-area networks (LP-WANs) is imminent, and LoRaWAN is one such technology that offers an elegant solution to the problem of long-range communication and battery consumption. A parameter of special interest in LoRaWAN is the spreading factor (SF), and it is often assumed that communication between different SFs is independent of each other. However, this claim has been practically debunked by many works, proving that SFs have imperfect orthogonality. To maximize connectivity and throughput, several techniques have been introduced, such as non-orthogonal-multiple-access (NOMA) and dynamic resource allocation. NOMA is getting a lot of attention recently, especially for IoT networks, because it embraces interference and tries to obtain desired information packets from corrupted ones. Furthermore, NOMA can be easily implemented on the base-station side by using the principle of successive interference cancellation (SIC). In this paper, we investigate how SIC, under the assumption of imperfect orthogonality of SF channels, can be used to increase the performance of the system. We find the expressions for success and coverage probability considering various SF allocation schemes and found the most efficient scheme for different scenarios.
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| 3. |
- Minhaj, Syed Usama, et al.
(författare)
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Intelligent Resource Allocation in LoRaWAN Using Machine Learning Techniques
- 2023
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Ingår i: IEEE Access. - 2169-3536. ; 11, s. 10092-10106
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Tidskriftsartikel (refereegranskat)abstract
- With the ubiquitous growth of Internet-of-things (IoT) devices, current low-power wide-area network (LPWAN) technologies will inevitably face performance degradation due to congestion and interference. The rule-based approaches to assign and adapt the device parameters are insufficient in dynamic massive IoT scenarios. For example, the adaptive data rate (ADR) algorithm in LoRaWAN has been proven inefficient and outdated for large-scale IoT networks. Meanwhile, new solutions involving machine learning (ML) and reinforcement learning (RL) techniques are shown to be very effective in solving resource allocation in dense IoT networks. In this article, we propose a new concept of using two independent learning approaches for allocating spreading factor (SF) and transmission power to the devices using a combination of a decentralized and centralized approach. SF is allocated to the devices using RL for contextual bandit problem, while transmission power is assigned centrally by treating it as a supervised ML problem. We compare our approach with existing state-of-the-art algorithms, showing a significant improvement in both network level goodput and energy consumption, especially for large and highly congested networks.
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| 4. |
- Nadeem, Aamir, et al.
(författare)
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Thermally stable and anti-corrosive polydimethyl siloxane composite coatings based on nanoforms of boron nitride
- 2024
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Ingår i: Inorganic Chemistry Communications. - : Elsevier. - 1387-7003 .- 1879-0259. ; 168
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Tidskriftsartikel (refereegranskat)abstract
- Coating technology has been emerged as a recognized and cost-effective approach in regard to mitigating issues that are linked to corrosion. We employed in-house synthesized boron nitride nanosheets (BNNS-CVD) and commercially available nanosized boron nitride (BN-nano) as fillers in this study to fabricate composite coatings with enhanced thermal stability and corrosion resistance. These fillers were dispersed in polydimethylsiloxane (PDMS) resin to develop composite coatings. The Fourier-transform infrared spectroscopy (FTIR), UV-visible spectroscopy, field emission scanning electron microscopy (FESEM), thermogravimetric analysis (TGA), and electrochemical impedance spectroscopy (EIS) were employed to characterize the prepared composite coatings. The FTIR analysis revealed a prominent absorption band around 1350 cm(-1) that is indication of the distinctive BN in-plane bending vibrations characteristic of boron nitride (BN). The FESEM images simultaneously confirmed the sheet-like morphology of both BN-nano and BNNS-CVD, which both found to be uniformly dispersed in the PDMS matrix. The EIS revealed that the composite films based on BNNS-CVD exhibited superior corrosion resistance compared to those based on BN-nano when exposed to a 3.5 wt% NaCl solution. Further, TGA profiles indicated that the composite films maintained their structural integrity up to 200 degree celsius without degradation. Therefore, thermally stable and corrosion resistant coatings can be valuable for various new technology applications that involve corrosion issues.
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| 5. |
- Ullah, Syed Ali, et al.
(författare)
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Deep RL-assisted Energy Harvesting in CR-NOMA Communications for NextG IoT Networks
- 2022
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Ingår i: 2022 IEEE GLOBECOM Workshops, GC Wkshps 2022 - Proceedings. - : IEEE conference proceedings. - 9781665459754 ; , s. 74-79
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Konferensbidrag (refereegranskat)abstract
- Zero-energy radios in energy-constrained devices are envisioned as key enablers to realizing the next-generation Internet-of-things (NG-IoT) networks for ultra-dense sensing and monitoring. This paper presents analytical modeling and analysis of the energy-efficient uplink transmission of an energyconstrained secondary sensor operating opportunistically among several primary sensors. The considered scenario assumes that all primary sensors transmit in a round-robin, time division multiple access-based schemes, and the secondary sensor is admitted in the time slot of each primary sensor using a nonorthogonal multiple access technique, inspired by cognitive radio. The energy efficiency of the secondary sensor is maximized by exposing it to a deep reinforcement learning-based algorithm, recognized as a deep deterministic policy gradient (DDPG). Our results demonstrate that the DDPG-based transmission scheme outperforms the conventional random and greedy algorithms in terms of energy efficiency at different operating conditions.
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| 6. |
- Ullah, Syed Asad, et al.
(författare)
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DRL-Driven Optimization of a Wireless Powered Symbiotic Radio With Nonlinear EH Model
- 2024
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Ingår i: IEEE Open Journal of the Communications Society. - : IEEE. - 2644-125X. ; 5, s. 5232-5247
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Tidskriftsartikel (refereegranskat)abstract
- Given the rising demand for low-power sensing, integrating additional devices into an existing wireless infrastructure calls for innovative energy-and spectrum-efficient wireless connectivity strategies. In this respect, wireless-powered or energy-harvesting symbiotic radio (EHSR) is gaining attention for establishing the secondary relationship with the primary wireless systems in terms of RF EH and opportunistically sharing the spectrum or schedule. In this paper, assuming the commensalistic relationship with the primary system, we consider the energy-efficient optimization of such an EHSR by intelligently making EH and transmission decisions under the inherent nonlinearity of the EH circuitry and dynamics of pre-scheduled primary devices. We present a state-of-the-art deep reinforcement learning (DRL)-engineered, energy-efficient transmission strategy, which intelligently orchestrates EHSR’s uplink transmissions, leveraging the cognitive radio-inspired non-orthogonal multiple access (CR-NOMA) scheme. We first formulate the energy efficiency (EE) optimization metric for EHSR considering the nonlinear EH model, and then we decompose the inherently complex, non-convex problem into two optimization layers. The strategy first derives the optimal transmit power and time-sharing coefficient parameters, using convex optimization. Subsequently, these inferred parameters are substituted in the subsequent layer, where the optimization problem with continuous action space is addressed via a DRL framework, named modified deep deterministic policy gradient (MDDPG). Simulation results reveal that, compared to the baseline DDPG algorithm, our proposed solution provides a 6% EE gain with the linear EH model and approximately a 7% EE gain with the non-linear EH model.
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| 7. |
- Zeb, Shah, et al.
(författare)
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NOMA Enhanced Backscatter Communication for Green IoT Networks
- 2019
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Ingår i: 16th International Symposium on Wireless Communication Systems (ISWCS). - : VDE Verlag GmbH. ; , s. 640-644
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Konferensbidrag (refereegranskat)abstract
- Backscatter communication has recently emerged as a promising technology to enable passive sensing-based Internet-of-things (IoT) applications. In a backscatter communication network, uplink transmissions of multiple nodes are usually multiplexed in time- or frequency-domain to avoid collisions, yet it is desirable to improve the uplink capacity further. In this paper, we study a wireless-powered backscatter communication system, where the sensors use a hybrid channel access scheme by combining time division multiplexing access(TDMA) with power-domain non-orthogonal multiple access(PD-NOMA) to enhance the system performance in terms of outage probability and throughput. Our analysis shows that the proposed PD-NOMA increases both the spectrum efficiency and the throughput of the system.
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| 8. |
- Zeb, Shah, et al.
(författare)
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Towards defining industry 5.0 vision with intelligent and softwarized wireless network architectures and services : A survey
- 2024
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Ingår i: Journal of Network and Computer Applications. - : Elsevier. - 1084-8045 .- 1095-8592. ; 223
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Forskningsöversikt (refereegranskat)abstract
- Industry 5.0 vision, a step toward the next industrial revolution and enhancement to Industry 4.0, conceives the new goals of resilient, sustainable, and human-centric approaches in diverse emerging applications such as factories-of-the-future and digital society. The vision seeks to leverage human intelligence and creativity in nexus with intelligent, efficient, and reliable cognitive collaborating robots (cobots) to achieve zero waste, zero-defect, and mass customization-based manufacturing solutions. However, it requires merging distinctive cyber–physical worlds through intelligent orchestration of various technological enablers, e.g., cognitive cobots, human-centric artificial intelligence (AI), cyber–physical systems, digital twins, hyperconverged data storage and computing, communication infrastructure, and others. In this regard, the convergence of the emerging computational intelligence (CI) paradigm and softwarized next-generation wireless networks (NGWNs) can fulfill the stringent communication and computation requirements of the technological enablers of the Industry 5.0, which is the aim of this survey. In this article, we address this issue by reviewing and analyzing current emerging concepts and technologies, e.g., CI tools and frameworks, network-in-box architecture, open radio access networks, softwarized service architectures, potential enabling services, and others, elemental and holistic for designing the objectives of CI-NGWNs to fulfill the Industry 5.0 vision requirements. Furthermore, we outline and discuss ongoing initiatives, demos, and frameworks linked to Industry 5.0. Finally, we provide a list of lessons learned from our detailed review, research challenges, and open issues that should be addressed in CI-NGWNs to realize Industry 5.0.
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| 9. |
- Zulfiqar, Shumaila, et al.
(författare)
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Whole exome sequencing identifies novel variant underlying hereditary spastic paraplegia in consanguineous Pakistani families
- 2019
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Ingår i: Journal of clinical neuroscience. - : Elsevier BV. - 0967-5868 .- 1532-2653. ; 67, s. 19-23
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Tidskriftsartikel (refereegranskat)abstract
- Hereditary Spastic paraplegias (HSPs) are heterogeneous group of degenerative disorders characterized by progressive weakness and spasticity of the lower limbs, combined with additional neurological features. This study aimed to identify causative gene variants in two nonrelated consanguineous Pakistani families segregating HSP. Whole exome sequencing (WES) was performed on a total of five individuals from two families including four affected and one phenotypically normal individual. The variants were validated by Sanger sequencing and segregation analysis. In family A, a novel homozygous variant c.604G > A (p.Glu202Lys) was identified in the CYP2U1 gene with clinical symptoms of SPG56 in 3 siblings. Whereas, a previously reported variant c.5769delT (p.Ser1923Argfs*28) in the SPG11 gene was identified in family B manifesting clinical features of SPG11 in 3 affected individuals. Our combined findings add to the clinical and genetic variability associated with CYP2U1 and SPG11 variants highlighting the complexity of HSPs. These findings further emphasize the usefulness of WES as a powerful diagnostic tool.
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| 10. |
- Abazajian, Kevork, et al.
(författare)
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CMB-S4 : Forecasting Constraints on Primordial Gravitational Waves
- 2022
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Ingår i: Astrophysical Journal. - : American Astronomical Society. - 0004-637X .- 1538-4357. ; 926:1
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Tidskriftsartikel (refereegranskat)abstract
- CMB-S4—the next-generation ground-based cosmic microwave background (CMB) experiment—is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the universe. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semianalytic projection tool, targeted explicitly toward optimizing constraints on the tensor-to-scalar ratio, r, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2–3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments, given a desired scientific goal. To form a closed-loop process, we couple this semianalytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for r > 0.003 at greater than 5σ, or in the absence of a detection, of reaching an upper limit of r < 0.001 at 95% CL.
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