S. E. D. Habib

Bio: S. E. D. Habib is an academic researcher from Cairo University. The author has contributed to research in topics: Video tracking & Field-programmable gate array. The author has an hindex of 13, co-authored 60 publications receiving 500 citations. Previous affiliations of S. E. D. Habib include University of Toronto & Kuwait University.

An integrated high-level hardware/software partitioning methodology

Abstract: Embedded systems are widely used in many sophisticated applications. To speed the time-to-market cycle, the hardware and software co-design has become one of the main methodologies in modern embedded systems. The most important challenge in the embedded system design is partitioning; i.e. deciding which modules of the system should be implemented in hardware and which ones in software. Finding an optimal partition is hard because of the large number and different characteristics of the modules that have to be considered. In this article, we develop a new high-level hardware/software partitioning methodology. Two novel features characterize this methodology. Firstly, the Particle Swarm Optimization (PSO) technique is introduced to the Hardware/Software partitioning field. Secondly, the hardware is modeled using two extreme implementations that bound different hardware scheduling alternatives. Our methodology further partitions the design into hardware and software modules at the early Control-Data Flow Graph (CDFG) level of the design; thanks to improved modeling techniques using intermediate-granularity functional modules. A new restarting technique is applied to PSO to avoid quick convergence. This technique is called Re-Excited PSO. Our numerical results prove the usefulness of the proposed technique. The target technology is Field Programmable Gate Arrays (FPGAs). We developed FPGA-based estimation techniques to evaluate the costs of implementing the design components. These costs are the area, delay, latency, and power consumption for both the hardware and software implementations. Hardware/software communication is also taken into consideration. The aforementioned methodology is embodied in an integrated CAD tool for hardware/software co-design. This tool accepts behavioral, un-timed, algorithmic-level, VHDL, design representation, and outputs a valid hardware/software partition and schedule for the design subject to a set of area/power/delay constraints. This tool is code named CUPSHOP for (Cairo University PSo-based Hardware/sOftware Partitioning tool). Finally, a JPEG-encoder case study is used to validate and contrast our partitioning methodology against the prior-art methodologies.

Efficient FPGA Implementation of MIMO Decoder for Mobile WiMAX System

Abstract: In this paper, we present a FPGA prototyping of the MIMO Decoder for the IEEE 802.16e WiMAX mobile systems. The IEEE 802.16e standard supports three types of MIMO space time codes (STC), referred to in the standard by matrix A, B, and C, that achieve different levels of throughput and diversity depending on the quality of the MIMO channels. In particular, the STC matrix A achieves full diversity by employing the Alomuti coding, while the STC matrix B achieves full rate by employing spatial multiplexing and the STC matrix C achieves full rate and diversity by employing the Golden code. In this paper, we present a FPGA architecture of MIMO decoder based on the fixed sphere decoder (FSD) algorithm that achieves close-to ML BER performance with a reduced computational complexity and fixed throughput. We show how a single FSD can be used to decode the different STC by adaptively processing the received signal according to the STC type prior to be fed to the FSD. The FPGA design is incorporated with a QR decomposition of the channel matrix. The proposed FSD achieves fixed and high throughput required for the WiMAX systems. The FPGA implementation is incorporated with a MATLAB simulation model of an FUSC OFDMA-based WiMAX 2x2 MIMO system to validate the hardware design.

Hardware Software Partitioning using Particle Swarm Optimization Technique

Abstract: In this paper the authors investigate the application of the particle swarm optimization (PSO) technique for solving the hardware/software partitioning problem. The PSO is attractive for the hardware/software partitioning problem as it offers reasonable coverage of the design space together with O(n) main loop's execution time, where n is the number of proposed solutions that will evolve to provide the final solution. The authors carried out several tests on a hypothetical, relatively-large hardware/software partitioning problem using the PSO algorithm as well as the genetic algorithm (GA), which is another evolutionary technique. The authors found that PSO outperforms GA in the cost function and the execution time. For the case of unconstrained design problem, the authors tested several hybrid combinations of PSO and GA algorithm; including PSO then GA, GA then PSO, GA followed by GA, and finally PSO followed by PSO. We found that a PSO followed by GA algorithm gives small or no improvement at all, while a GA then PSO algorithm gives the same results as the PSO alone. The PSO algorithm followed by another PSO round gave the best result as it allows another round of domain exploration. The second PSO round assign new randomized velocities to the particles, while keeping best particle positions obtained in the first round. The paper proposes to name this successive PSO algorithm as the re-excited PSO algorithm

When group-III nitrides go infrared: New properties and perspectives

Abstract: Wide-band-gap GaN and Ga-rich InGaN alloys, with energy gaps covering the blue and near-ultraviolet parts of the electromagnetic spectrum, are one group of the dominant materials for solid state lighting and lasing technologies and consequently, have been studied very well. Much less effort has been devoted to InN and In-rich InGaN alloys. A major breakthrough in 2002, stemming from much improved quality of InN films grown using molecular beam epitaxy, resulted in the bandgap of InN being revised from 1.9 eV to a much narrower value of 0.64 eV. This finding triggered a worldwide research thrust into the area of narrow-band-gap group-III nitrides. The low value of the InN bandgap provides a basis for a consistent description of the electronic structure of InGaN and InAlN alloys with all compositions. It extends the fundamental bandgap of the group III-nitride alloy system over a wider spectral region, ranging from the near infrared at ∼1.9 μm (0.64 eV for InN) to the ultraviolet at ∼0.36 μm (3.4 eV for GaN...

Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

Abstract: This paper presents a comprehensive review of emerging technologies for the internet of things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and describing emergent technologies for the agricultural IoT, such as unmanned aerial vehicles, wireless technologies, open-source IoT platforms, software defined networking (SDN), network function virtualization (NFV) technologies, cloud/fog computing, and middleware platforms. We also provide a classification of IoT applications for smart agriculture into seven categories: including smart monitoring, smart water management, agrochemicals applications, disease management, smart harvesting, supply chain management, and smart agricultural practices. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward supply chain management based on the blockchain technology for agricultural IoTs. Furthermore, we present real projects that use most of the aforementioned technologies, which demonstrate their great performance in the field of smart agriculture. Finally, we highlight open research challenges and discuss possible future research directions for agricultural IoTs.

Design of Nanostructured Solar Cells Using Coupled Optical and Electrical Modeling - eScholarship

Abstract: Design of Nanostructured Solar Cells Using Coupled Optical and Electrical Modeling Michael G. Deceglie † , Vivian E. Ferry ‡ , A. Paul Alivisatos ‡ , and Harry A. Atwater* ,† Thomas J. Watson Laboratories of Applied Physics, California Institute of Technology, Pasadena, California 91125, United States Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States Abstract: Nanostructured light trapping has emerged as a promising route toward improved efficiency in solar cells. We use coupled optical and electrical modeling to guide optimization of such nanostructures. We study thin-film n-i-p a-Si:H devices and demonstrate that nanostructures can be tailored to minimize absorption in the doped a-Si:H, improving carrier collection efficiency. This suggests a method for device optimization in which optical design not only maximizes absorption, but also ensures resulting carriers are efficiently collected. Keywords: Thin film solar cells, plasmon, nanophotonic, light trapping, simulation, device physics, silicon, photovoltaics In order to maximize solar cell efficiency, it is necessary to optimize both the electrical device physics and the optical absorption of the device. Typically, these two problems are treated separately,