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Recent Submissions

  • Photoelectrochemical and crystalline properties of a GaN photoelectrode loaded with α-Fe2O3 as cocatalyst.

    Velazquez-Rizo, Martin; Iida, Daisuke; Ohkawa, Kazuhiro (Scientific reports, Springer Science and Business Media LLC, 2020-07-30) [Article]
    Nitrides are of particular interest in energy applications given their suitability to photocatalytically generate H2 from aqueous solutions. However, one of the drawbacks of nitrides is the decomposition they suffer when used in photoelectrochemical cells. Here, we report the improvement of the catalytic performance and chemical stability of a GaN electrode when it is decorated with Fe2O3 particles compared with an undecorated electrode. Our results show a higher reaction rate in the Fe2O3/GaN electrode, and that photocorrosion marks take more than 20 times longer to appear on it. We also characterized the crystalline properties of the Fe2O3 particles with transmission electron microscopy. The results show that the Fe2O3 particles keep an epitaxial relationship with GaN that follows the Fe2O3[Formula: see text]GaN[Formula: see text] and Fe2O3[Formula: see text]GaN[Formula: see text] symmetry constraints. We also characterized an Fe2O3 (thin film)/GaN electrode, however it did not present any catalytic improvement compared with a bare GaN electrode. The epitaxial relationship found between the Fe2O3 thin film and GaN exhibited the Fe2O3[Formula: see text]GaN[Formula: see text] and Fe2O3[Formula: see text]GaN[Formula: see text] symmetry constraints.
  • Multi-source ambient energy harvester based on RF and thermal energy: Design, testing, and IoT application

    Bakytbekov, Azamat; Nguyen, Thang Q.; Li, Weiwei; Lee Cottrill, Anton; Zhang, Ge; Strano, Michael S.; Salama, Khaled N.; Shamim, Atif (Energy Science & Engineering, Wiley, 2020-07-29) [Article]
    Billions of wireless sensing devices must be powered for IoT applications. Collecting energy from the ambient environment to power sensor nodes is a promising solution. Solar energy has been one of the main sources of ambient energy due to its availability, higher power density, and the maturity of the solar photovoltaic industry. However, there are many scenarios (indoor environment, outdoor environment during nighttime, poor weather conditions, underground, etc) where ambient solar energy is either not available or not sufficient for practical applications. For such scenarios, other renewable sources of energy must be sought. Typically, not enough power is collected from one ambient source to charge sensor nodes for continuous operation. In this work, we present a multi-source energy harvester that collects RF and thermal energy (both available 24 hours) from the ambient environment simultaneously. The RF energy harvester is multi-band and collects power from GSM (900, 1800 MHz) and 3G (2100 MHz). The thermal harvester converts diurnal temperature fluctuations to electrical energy using high thermal effusivity phase change material. Extensive field testing has been performed in three different conditions—outdoors, indoors, and buried underground—to highlight the usefulness of the multi-source energy harvester in all these environments. When one source is disabled, the harvester still generates energy from the remaining active source and can enable continuous operation of futuristic IoT sensors. As a proof of concept, a real-world IoT application is demonstrated, where temperature and humidity sensors are powered by the multi-source energy harvester. Continuous robust operation of the sensors and wireless data transmission after each 3.7 seconds are expected when both harvesters operate in full mode. Scenarios, where only single thermal energy harvester or only single RF energy harvester operates, are also demonstrated and data transmission with average time intervals of 30 seconds and 9 minutes is achieved, respectively.
  • Biofunctionalization of Magnetic Nanomaterials

    Alsharif, Nouf; Merzaban, Jasmeen; Kosel, Jürgen (Journal of Visualized Experiments, MyJove Corporation, 2020-07-17) [Article]
    Magnetic nanomaterials have received great attention in different biomedical applications. Biofunctionalizing these nanomaterials with specific targeting agents is a crucial aspect to enhance their efficacy in diagnostics and treatments while minimizing the side effects. The benefit of magnetic nanomaterials compared to non-magnetic ones is their ability to respond to magnetic fields in a contact-free manner and over large distances. This allows to guide or accumulate them, while they can also be monitored. Recently, magnetic nanowires (NWs) with unique features were developed for biomedical applications. The large magnetic moment of these NWs enables a more efficient remote control of their movement by a magnetic field. This has been utilized with great success in cancer treatment, drug delivery, cell tracing, stem cell differentiation or magnetic resonance imaging. In addition, the NW fabrication by template-assisted electrochemical deposition provides a versatile method with tight control over the NW properties. Especially iron NWs and iron-iron oxide (core-shell) NWs are suitable for biomedical applications, due to their high magnetization and low toxicity. In this work, we provide a method to biofunctionalize iron/iron oxide NWs with specific antibodies directed against a specific cell surface marker that is overexpressed in a large number of cancer cells. Since the method utilizes the properties of the iron oxide surface, it is also applicable to superparamagnetic iron oxide nanoparticles. The NWs are first coated with 3-aminopropyl-tri-ethoxy-silane (APTES) acting as a linker, which the antibodies are covalently attached to. The APTES coating and the antibody biofunctionalization are proven by electron energy loss spectroscopy (EELS) and zeta potential measurements. In addition, the antigenicity of the antibodies on the NWs is tested by using immunoprecipitation and western blot. The specific targeting of the biofunctionalized NWs and their biocompatibility are studied by confocal microscopy and a cell viability assay.
  • Growth of large-scale MoS2 nanosheets on double layered ZnCo2O4 for real-time in situ H2S monitoring in live cells.

    Mani, Veerappan; Selvaraj, Shanthi; Jeromiyas, Nithiya; Huang, Sheng-Tung; Ikeda, Hiroya; Hayakawa, Yasuhiro; Ponnusamy, Suru; Muthamizhchelvan, Chellamuthu; Salama, Khaled N. (Journal of materials chemistry. B, Royal Society of Chemistry (RSC), 2020-07-16) [Article]
    There is an urgent need to develop in situ sensors that monitor the continued release of H2S from biological systems to understand H2S-related pathology and pharmacology. For this purpose, we have developed a molybdenum disulfide supported double-layered zinc cobaltite modified carbon cloth electrode (MoS2-ZnCo2O4-ZnCo2O4) based electrocatalytic sensor. The results of our study suggest that the MoS2-ZnCo2O4-ZnCo2O4 electrode has excellent electrocatalytic ability to oxidize H2S at physiological pH, in a minimized overpotential (+0.20 vs. Ag/AgCl) with an amplified current signal. MoS2 grown on double-layered ZnCo2O4 showed relatively better surface properties and electrochemical properties than MoS2 grown on single-layered ZnCo2O4. The sensor delivered excellent analytical parameters, such as low detection limit (5 nM), wide linear range (10 nM-1000 μM), appreciable stability (94.3%) and high selectivity (2.5-fold). The practicality of the method was tested in several major biological fluids. The electrode monitors the dynamics of bacterial H2S in real-time for up to 5 h with good cell viability. Our research shows that MoS2-ZnCo2O4-ZnCo2O4/carbon cloth is a robust and sensitive electrode to understand how bacteria seek to adjust their defense strategies under exogenously induced stress conditions.
  • High-performance solar flow battery powered by a perovskite/silicon tandem solar cell.

    Li, Wenjie; Zheng, Jianghui; Hu, Bo; Fu, Hui-Chun; Hu, Maowei; Veyssal, Atilla; Zhao, Yuzhou; He, Jr-Hau; Liu, T Leo; Ho-Baillie, Anita; Jin, Song (Nature materials, Springer Science and Business Media LLC, 2020-07-15) [Article]
    The fast penetration of electrification in rural areas calls for the development of competitive decentralized approaches. A promising solution is represented by low-cost and compact integrated solar flow batteries; however, obtaining high energy conversion performance and long device lifetime simultaneously in these systems has been challenging. Here, we use high-efficiency perovskite/silicon tandem solar cells and redox flow batteries based on robust BTMAP-Vi/NMe-TEMPO redox couples to realize a high-performance and stable solar flow battery device. Numerical analysis methods enable the rational design of both components, achieving an optimal voltage match. These efforts led to a solar-to-output electricity efficiency of 20.1% for solar flow batteries, as well as improved device lifetime, solar power conversion utilization ratio and capacity utilization rate. The conceptual design strategy presented here also suggests general future optimization approaches for integrated solar energy conversion and storage systems.
  • Correction to “Optimal Joint Channel Estimation and Data Detection for Massive SIMO Wireless Systems: A Polynomial Complexity Solution”

    Xu, Weiyu; Alshamary, Haider Ali Jasim; Al-Naffouri, Tareq Y.; Zaib, Alam (IEEE Transactions on Information Theory, Institute of Electrical and Electronics Engineers (IEEE), 2020-07-15) [Article]
    By exploiting large antenna arrays, massive MIMO (multiple input multiple output) systems can greatly increase spectral and energy efficiency over traditional MIMO systems. However, increasing the number of antennas at the base station (BS) makes the uplink joint channel estimation and data detection (JED) challenging in massive MIMO systems. In this paper, we consider the JED problem for massive SIMO (single input multiple output) wireless systems, which is a special case of wireless systems with large antenna arrays. We propose exact Generalized Likelihood Ratio Test (GLRT) optimal JED algorithms with low expected complexity, for both constantmodulus and nonconstant-modulus constellations. We show that, despite the large number of unknown channel coefficients, the expected computational complexity of these algorithms is polynomial in channel coherence time (T ) and the number of receive antennas (N), even when the number of receive antennas grows polynomially in the channel coherence time (N = O(T 11) suffices to guarantee an expected computational complexity cubic in T and linear in N). Simulation results show that the GLRT-optimal JED algorithms achieve significant performance gains (up to 5 dB improvement in energy efficiency) with low computational complexity.
  • Janus Monolayers of Magnetic Transition Metal Dichalcogenides as an All-in-One Platform for Spin-Orbit Torque

    Smaili, Idris; Laref, Slimane; Garcia, Jose H.; Schwingenschlögl, Udo; Roche, Stephan; Manchon, Aurelien (arXiv, 2020-07-15) [Preprint]
    We theoretically predict that vanadium-based Janus dichalcogenide monolayers constitute an ideal platform for spin-orbit-torque memories. Using first principles calculations, we demonstrate that magnetic exchange and magnetic anisotropy energies are higher for heavier chalcogen atoms, while the broken inversion symmetry in the Janus form leads to the emergence of Rashba-like spin-orbit coupling. The spin-orbit torque efficiency is evaluated using optimized quantum transport methodology and found to be comparable to heavy nonmagnetic metals. The coexistence of magnetism and spin-orbit coupling in such materials with tunable Fermi-level opens new possibilities for monitoring magnetization dynamics in the perspective of non-volatile magnetic random access memories.
  • BAlN alloy for enhanced two-dimensional electron gas characteristics of GaN/AlGaN heterostructures

    Lin, Rongyu; Liu, Xinwei; Liu, Kaikai; Lu, Yi; Liu, Xinke; Li, Xiaohang (Journal of Physics D: Applied Physics, IOP Publishing, 2020-07-10) [Article]
    The emerging wide bandgap BAlN alloys have potentials for improved III-nitride power devices including high electron mobility transistor (HEMT). Yet few relevant studies have been carried. In this work, we have investigated the use of the B0.14Al0.86N alloy as part or entirety of the interlayer between the GaN buffer and the AlGaN barrier in the conventional GaN/AlGaN heterostructure. The numerical results show considerable improvement of the two-dimensional electron gas (2DEG) concentration with small 2DEG leakage into the ternary layer by replacing the conventional AlN interlayer by either the B0.14Al0.86N interlayer or the B0.14Al0.86N/AlN hybrid interlayer. Consequently, the transfer characteristics can be improved. The saturation current can be enhanced as well. For instance, the saturation currents for HEMTs with the 0.5 nm B0.14Al0.86N/0.5 nm AlN hybrid interlayer and the 1 nm B0.14Al0.86N interlayer are 5.8% and 2.2% higher than that for the AlN interlayer when VGS-Vth= +3 V.
  • Learning Heat Diffusion for Network Alignment

    Qu, Sisi; Xu, Mengmeng; Ghanem, Bernard; Tegner, Jesper (arXiv, 2020-07-10) [Preprint]
    Networks are abundant in the life sciences. Outstanding challenges include how to characterize similarities between networks, and in extension how to integrate information across networks. Yet, network alignment remains a core algorithmic problem. Here, we present a novel learning algorithm called evolutionary heat diffusion-based network alignment (EDNA) to address this challenge. EDNA uses the diffusion signal as a proxy for computing node similarities between networks. Comparing EDNA with state-of-the-art algorithms on a popular protein-protein interaction network dataset, using four different evaluation metrics, we achieve (i) the most accurate alignments, (ii) increased robustness against noise, and (iii) superior scaling capacity. The EDNA algorithm is versatile in that other available network alignments/embeddings can be used as an initial baseline alignment, and then EDNA works as a wrapper around them by running the evolutionary diffusion on top of them. In conclusion, EDNA outperforms state-of-the-art methods for network alignment, thus setting the stage for large-scale comparison and integration of networks.
  • Functionalization of Magnetic Nanowires for Active Targeting and Enhanced Cell Killing Efficacy

    Alsharif, Nouf; Aleisa, Fajr A; Liu, Guangyu; Ooi, Boon S.; Patel, Niketan Sarabhai; Ravasi, Timothy; Merzaban, Jasmeen; Kosel, Jürgen (ACS Applied Bio Materials, American Chemical Society (ACS), 2020-07-08) [Article]
    Conventional chemotherapy and radiation therapy are often insufficient in eliminating cancer and are accompanied by severe side effects, due to a lack in the specificity of their targeting. Magnetic iron nanowires have made a great contribution to the nanomedicine field because of their low toxicity and ease of manipulation with the magnetic field. Recently, they have been used in magnetic resonance imaging, wireless magneto-mechanical, and photothermal treatments. The addition of active targeting moieties to these nanowires thus creates a multifunctional tool that can boost therapeutic efficacies through the combination of different treatments towards a specific target. Colon cancer is the third most commonly occurring cancer, and 90±2.5% of colon cancer cells express the glycoprotein CD44. Iron nanowires with an iron oxide surface are biocompatible, multifunctional materials that can be controlled by magnetic fields and heated by laser irradiation. Here, they were functionalized with anti-CD44 antibodies and used for in a combination therapy that included magneto-mechanical and photothermal treatments on colon cancer cells. The functionalization resulted in a threefold increase of nanowire internalization in colon cancer cells compared to control cells and did not affect the antigenicity and magnetic properties. It also increased the efficacy of killing from 35±1% to more than 71±2%, whereby the combination therapy was more effective than individual therapies alone.
  • Coherent Free-Space Optical Communication Using Non-mode-Selective Photonic Lantern

    Zhang, Bo; Yuan, Renzhi; Sun, Jianfeng; Cheng, Julian; Alouini, Mohamed-Slim (arXiv, 2020-07-03) [Preprint]
    A coherent free-space optical communication system based on non-mode-selective photonic lantern is studied. Based on simulation of photon distribution, the power distribution at single-mode fiber end of the photonic lantern is quantitatively described as a truncated Gaussian distribution over a simplex. The signal-to-noise and the outage probability are analyzed for the communication system using photonic lantern based receiver with equal-gain combining, and they are compared with those of the single-mode fiber receiver and multimode fiber receiver. The scope of application of the communication system is provided. It is shown that the signal-to-noise ratio gain of the photonic lantern based receiver over single-mode fiber receiver and multimode fiber receiver can be greater than 7 dB. The integral solution, series lower bound solution and asymptotic solution are presented for bit-error rate of photonic lantern based receiver, single-mode fiber receiver and multimode fiber receiver over the Gamma-Gamma atmosphere turbulence channels. Simulation results show that for the considered system the power distribution of the photonic lantern has limited influence on the outage probability and the bit-error rate performance.
  • Prism-based tunable InGaN/GaN self-injection locked blue laser diode system: study of temperature, injection ratio, and stability

    Khan, Mohammed Zahed Mustafa; Mukhtar, Sani; Holguin Lerma, Jorge Alberto; Alkhazragi, Omar; Ashry, Islam; Ng, Tien Khee; Ooi, Boon S. (Journal of Nanophotonics, SPIE-Intl Soc Optical Eng, 2020-07-02) [Article]
    A quasicontinuously wavelength tuned self-injection locked blue laser diode system employing a prism is presented. A rigorous analysis of the injection ratio (IR) in the form of three systems, namely high (HRS, ∼ − 0.7 dB IR), medium (MRS, ∼ − 1.5 dB IR), and low (LRS, ∼ − 3.0 dB IR) reflection systems, showed a direct relationship with the wavelength tunability whereas the usable system power exhibited an inverse correlation. In particular, MRS configuration demonstrated a concurrent optimization of tuning window and system power, thus emerging as a highly attractive candidate for practical realization. Moreover, a comprehensive investigation on two distinct MRS configurations employing different commercially available InGaN/GaN blue lasers, i.e., MRS-1 and MRS-2, displayed a wavelength tunability (system power) of ∼8.2 nm (∼7.6 mW) and ∼6.3 nm (∼11.6 mW), respectively, at a low injection current of 130 mA. In addition, both MRS configurations maintained high-performance characteristic with corresponding average optical linewidths of ∼80 and ∼58 pm and a side-mode-suppression-ratio of ≥12 dB. Lastly, a thorough stability analysis of HRS and MRS configurations, which are more prone to system instabilities due to elevated IRs, is performed at critical operation conditions of a high injection current of ≥260 mA and a temperature of 40°C, showing an extended stable performance of over 120 min, thus further substantiating the promising features of the prism-based systems for practical applications.
  • Giant magnetoelectric effect in perpendicularly magnetized Pt/Co/Ta ultrathin films on a ferroelectric substrate

    Chen, Aitian; Huang, Haoliang; Wen, Yan; Liu, Wenyi; Zhang, Senfu; Kosel, Jürgen; Sun, Weideng; Zhao, Yonggang; Lu, Yalin; Zhang, Xixiang (Materials Horizons, Royal Society of Chemistry (RSC), 2020-07-01) [Article]
    <p>We demonstrate a giant magnetoelectric effect in perpendicularly magnetized Pt/Co/Ta ultrathin films on a ferroelectric substrate.</p>
  • An in-field integrated capacitive sensor for rapid detection and quantification of soil moisture

    Surya, Sandeep Goud; Yuvaraja, Saravanan; Varrla, Eswaraiah; Baghini, Maryam Shojaei; Palaparthy, Vinay S.; Salama, Khaled N. (Sensors and Actuators B: Chemical, Elsevier BV, 2020-06-29) [Article]
    The development of in-situ soil moisture sensors (SMS) with advanced materials is the requirement of the future autonomous agriculture industry. However, an open challenge for these sensors is to control changes in the capacitance rather than resistance while attaining reliability, high performance, scalability and stability. In this work, a series of materials such as Graphite oxide (GO), Molybdenum disulfide (MoS2), Vanadium oxide (V2O5), and Molybdenum oxide (MoO3) are tested in realizing a receptor layer that can efficiently sense soil moisture. Here, we found that MoS2 offers the sensitivity, which is nearly three times higher (1200 pF) than in the case of V2O5 for any given range of soil-moisture content outperforming both GO and MoO3 materials. The corresponding increase in the sensitivities for MoO3, GO, MoS2, and V2O5 are ∼13%, ∼11%, ∼30%, and ∼9% respectively, for a variety of temperature up to 45 °C. A temperature variation of 25 °C to 50 °C showed a minimal increase in the sensitivity response for all the devices. We further demonstrated a record sensitivity of 540% with MoS2 in black soil and the corresponding response time was 65 sec. Finally, the recovery time for the MoS2 sensor is 27 s, which is quite fast.
  • Photonics based perfect secrecy cryptography: Toward fully classical implementations

    Mazzone, Valerio; Falco, Andrea Di; Cruz, Al; Fratalocchi, Andrea (Applied Physics Letters, AIP Publishing, 2020-06-29) [Article]
    Developing an unbreakable cryptography is a long-standing question and a global challenge in the internet era. Photonics technologies are at the frontline of research, aiming at providing the ultimate system with capability to end the cybercrime industry by changing the way information is treated and protected now and in the long run. Such a perspective discusses some of the current challenges as well as opportunities that classical and quantum systems open in the field of cryptography as both a field of science and engineering.
  • Towards Efficient Neuromorphic Hardware: Unsupervised Adaptive Neuron Pruning

    Guo, Wenzhe; Yantir, Hasan Erdem; Fouda, Mohamed E.; Eltawil, Ahmed; Salama, Khaled N. (Electronics, MDPI AG, 2020-06-29) [Article]
    To solve real-time challenges, neuromorphic systems generally require deep and complex network structures. Thus, it is crucial to search for effective solutions that can reduce network complexity, improve energy efficiency, and maintain high accuracy. To this end, we propose unsupervised pruning strategies that are focused on pruning neurons while training in spiking neural networks (SNNs) by utilizing network dynamics. The importance of neurons is determined by the fact that neurons that fire more spikes contribute more to network performance. Based on these criteria, we demonstrate that pruning with an adaptive spike count threshold provides a simple and effective approach that can reduce network size significantly and maintain high classification accuracy. The online adaptive pruning shows potential for developing energy-efficient training techniques due to less memory access and less weight-update computation. Furthermore, a parallel digital implementation scheme is proposed to implement spiking neural networks (SNNs) on field programmable gate array (FPGA). Notably, our proposed pruning strategies preserve the dense format of weight matrices, so the implementation architecture remains the same after network compression. The adaptive pruning strategy enables 2.3× reduction in memory size and 2.8× improvement on energy efficiency when 400 neurons are pruned from an 800-neuron network, while the loss of classification accuracy is 1.69%. And the best choice of pruning percentage depends on the trade-off among accuracy, memory, and energy. Therefore, this work offers a promising solution for effective network compression and energy-efficient hardware implementation of neuromorphic systems in real-time applications.
  • Efficient Acceleration of Stencil Applications through In-Memory Computing

    Yantir, Hasan Erdem; Eltawil, Ahmed; Salama, Khaled N. (Micromachines, MDPI AG, 2020-06-29) [Article]
    The traditional computer architectures severely suffer from the bottleneck between the processing elements and memory that is the biggest barrier in front of their scalability. Nevertheless, the amount of data that applications need to process is increasing rapidly, especially after the era of big data and artificial intelligence. This fact forces new constraints in computer architecture design towards more data-centric principles. Therefore, new paradigms such as in-memory and near-memory processors have begun to emerge to counteract the memory bottleneck by bringing memory closer to computation or integrating them. Associative processors are a promising candidate for in-memory computation, which combines the processor and memory in the same location to alleviate the memory bottleneck. One of the applications that need iterative processing of a huge amount of data is stencil codes. Considering this feature, associative processors can provide a paramount advantage for stencil codes. For demonstration, two in-memory associative processor architectures for 2D stencil codes are proposed, implemented by both emerging memristor and traditional SRAM technologies. The proposed architecture achieves a promising efficiency for a variety of stencil applications and thus proves its applicability for scientific stencil computing.
  • Stochastic Geometry-based Analysis of LEO Satellite Communication Systems

    Talgat, Anna; Kishk, Mustafa Abdelsalam; Alouini, Mohamed-Slim (arXiv, 2020-06-28) [Preprint]
    This letter studies the performance of a low-earth orbit (LEO) satellite communication system where the locations of the LEO satellites are modeled as a binomial point process (BPP) on a spherical surface. In particular, we study the user coverage probability for a scenario where satellite gateways (GWs) are deployed on the ground to act as a relay between the users and the LEO satellites. We use tools from stochastic geometry to derive the coverage probability for the described setup assuming that LEO satellites are placed at n different altitudes, given that the number of satellites at each altitude ak is Nk for all k. To resemble practical scenarios where satellite communication can play an important role in coverage enhancement, we compare the performance of the considered setup with a scenario where the users are solely covered by a fiber-connected base station (referred to as anchored base station or ABS in the rest of the paper) at a relatively far distance, which is a common challenge in rural and remote areas. Using numerical results, we show the performance gain, in terms of coverage probability, at rural and remote areas when LEO satellite communication systems are adopted. Finally, we draw multiple system-level insights regarding the density of GWs required to outperform the ABS, as well as the number of LEO satellites and their altitudes.
  • Automating Analogue AI Chip Design with Genetic Search

    Krestinskaya, Olga; Salama, Khaled N.; James, Alex P. (Advanced Intelligent Systems, Wiley, 2020-06-25) [Article]
    Optimization of analogue neural circuit designs is one of the most challenging, complicated, time-consuming, and expensive tasks. Design automation of analogue neuromemristive chips is made difficult by the need to design chips at low cost, ease of scaling, high-energy efficiency, and small on-chip area. The rapid progress in edge AI computing applications generates high demand for developing smart sensors. The integration of high-density analogue computing AI chips as coprocessing units to sensors is gaining popularity. This article proposes a hardware–software codesign framework to speed up and automate the design of analogue neuromemristive chips. This work uses genetic algorithms with objective functions that take into account hardware nonidealities such as limited precision of devices, the device-to-device variability, and device failures. The optimized neural architectures and hyperparameters successfully map with the library of relevant neuromemristive analogue hardware blocks. The results demonstrate the advantage of proposed automation to speed up the analogue circuit design of large-scale neuromemristive networks and reduce overall design costs for AI chips.
  • On Integrated Access and Backhaul Networks: Current Status and Potentials

    Madapatha, Charitha; Makki, Behrooz; Fang, Chao; Teyeb, Oumer; Dahlman, Erik; Alouini, Mohamed-Slim; Svensson, Tommy (arXiv, 2020-06-25) [Preprint]
    In this paper, we introduce and study the potentials and challenges of integrated access and backhaul (IAB) as one of the promising techniques for evolving 5G networks. We study IAB networks from different perspectives. We summarize the recent Rel-16 as well as the upcoming Rel-17 3GPP discussions on IAB, and highlight the main IAB-specific agreements on different protocol layers. Also, concentrating on millimeter wave-based communications, we evaluate the performance of IAB networks in both dense and suburban areas. Using a finite stochastic geometry model, with random distributions of IAB nodes as well as user equipments (UEs) in a finite region, we study the service coverage rate defined as the probability of the event that the UEs' minimum rate requirements are satisfied. We present comparisons between IAB and hybrid IAB/fiber-backhauled networks where a part or all of the small base stations are fiber-connected. Finally, we study the robustness of IAB networks to weather and various deployment conditions and verify their effects, such as blockage, tree foliage, rain as well as antenna height/gain on the coverage rate of IAB setups, as the key differences between the fiber-connected and IAB networks. As we show, IAB is an attractive approach to enable the network densification required by 5G and beyond.

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