Last edited by Jurr
Monday, May 11, 2020 | History

1 edition of Design and analysis of parallel algorithms for distributed in-situ array beamforming found in the catalog.

Design and analysis of parallel algorithms for distributed in-situ array beamforming

by Keonwook Kim

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Published .
Written in English

    Subjects:
  • Computer algorithms,
  • Parallel processing (Electronic computers),
  • Signal processing,
  • Array processors m,
  • Digital techniques,
  • Design and construction

  • Edition Notes

    Statementby Keonwook Kim
    The Physical Object
    Paginationxi, 116 leaves :
    Number of Pages116
    ID Numbers
    Open LibraryOL25902707M
    OCLC/WorldCa48222043

    Editor's Note: This multi-part are on parallel algorithm design is based on the book Designing and Building Parallel Programs by Ian Foster. Designing and Building Parallel Programs promotes a view of parallel programming as an engineering discipline, in which programs are developed in a methodical fashion and both cost and performance are considered in a design.   In most applications that are using beamforming algorithms such as Least Mean Square and Recursive Least Square beamforming algorithms, the elements of the antenna array are assumed to be point sources and practically the antennas array elements in the linear and planar array have dimensions so mutual coupling must be : Sarah EL-Issawi, Wael Abd El latiff, Mohammed Omar.

    Beamforming Techniques for Large-N Aperture Arrays K. Zarb-Adami, A. Faulkner, J.G. Bij de Vaate, G.W. Kant and Abstract—Beamforming is central to the processing function of all phased arrays and becomes particularly challenging with a large number of . Distributed nullforming specifically poses challenges that call for special attention. Here, we develop a set of scalable algorithms for beamforming and nullforming using distributed transmitters by forming a virtual antenna array and overcome the involved challenges in a purely distributed fashion.

    Parallel Algorithm Analysis and Design CPS Parallel and High Performance Computing Spring CPS (Parallel and HPC) Parallel Algorithm Analysis and Design Spring 1/65 split cube into a 1-D array of slices (each slice is 2-D,coarse granularity) (Parallel and HPC) Parallel Algorithm Analysis and Design Spring 11/ Analysis of parallel algorithms is usually carried out under the assumption that an unbounded number of processors is available. This is unrealistic, but not a problem, since any computation that can run in parallel on N processors can be executed on p by letting each processor execute multiple units of work.


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Design and analysis of parallel algorithms for distributed in-situ array beamforming by Keonwook Kim Download PDF EPUB FB2

Click here to view the University of Florida catalog recordPages: Design and analysis of parallel algorithms for distributed in-situ array beamforming. By Keonwook Kim. Abstract (Thesis) Thesis (Ph.D.)--University of Florida, (Bibliography) Includes bibliographical references (leaves )(Statement of Responsibility) by Keonwook Kim Author: Keonwook Kim.

The Design and Analysis of Parallel Algorithms Selim G. Akl Queen's U nioersity Kingston, Ontario, Canada Prentice Hall, Englewood Cliffs, New Jersey File Size: 5MB.

which is performed by a centralized antenna array, distributed beamforming is performed by a virtual antenna array composed of randomly located sensor nodes, each of which has an independent oscillator. Implementing parallel beamforming algorithms in situ on distributed array systems holds the potential to provide increased performance and fault tolerance at a lower cost.

The basic idea is to have many distributed antennas that are transmitting phase-coherently to the receiving user. In other words, the antennas’ signal components add constructively at the location of the user, just as when using a compact array for beamforming.

PARALLEL IMPLEMENTATIONS OF BEAMFORMING DESIGN AND FILTERING FOR MICROPHONE ARRAY APPLICATIONS Jorge Lorente1, Gema Piner~ o1, Antonio M. Vidal2, Jose Antonio Belloch1, Alberto Gonzalez1 1 Institute of Telecommunications and Multimedia Applications (iTEAM) 2 Interdisciplinary Group of Computer and Communications (INCO2) Universitat Polit ecnica de Val encia.

MODELLING AND ANALYSIS OF DIGITAL BEAMFORMING ALGORITHM SMART ANTENNA BASICS Smart antenna refers to a system of antenna arrays with smart signal processing algorithm which is used to calculate beam forming vectors, to track and direct the beam towards the mobile user (Jeffrey Reed ).

The array is configured using a given number of antennas or through a selection of subset of antennas from a larger available set, leading to a sparse array in both cases.

The bounds on the highest achievable SINR for a given number of antennas are formulated and used to offer new insights into open-loop adaptive beamforming.

by building “parallel” computers – computers that perform multiple operations in a single step. In order to solve a problem efficiently on a parallel machine, it is usually necessary to design an algorithm that specifies multiple operations on each step, i.e., a parallel algorithm.

Abstract: For a large-scale adaptive array, the heavy computational load and the high-rate data transmission are two challenges in the implementation of an adaptive digital beamforming system.

An efficient parallel digital beamforming (DBF) algorithm based on the least mean square algorithm (PLMS) is proposed. An appropriate method is found to partition the least mean square (LMS) algorithm.

Design and Analysis of Parallel Algorithms Murray Cole e-mail: mic room: Informatics Forum Design and Analysis of Parallel Algorithms. 1 What. Devising algorithms which allowmany processorsto work collectively to solve the same problems, butfaster bigger/more re nedproblems in the same time how it is distributed.

Brent’s theorem. Design and Analysis of Algorithm is very important for designing algorithm to solve different types of problems in the branch of computer science and information technology. This tutorial introduces the fundamental concepts of Designing Strategies, Complexity analysis of Algorithms, followed by problems on Graph Theory and Sorting methods.

Parallel and Distributed Algorithms ABDELHAK BENTALEB (AH), LEI YIFAN (AE), JI XIN (AR), DILEEPA FERNANDO (AB), ABDELRAHMAN KAMEL (AX).

Beamforming (BF) design for large-scale antenna arrays with limited radio frequency chains and the phase-shifter-based analog BF architecture, has been recognized as a key issue in millimeter wave communication systems.

It becomes more challenging with imperfect channel state information (CSI). In this letter, we propose a deep learning based BF design approach and develop. The execution times, parallel efficiencies, and memory requirements of each parallel algorithm are presented and analyzed. The results of these analyses demonstrate that parallel in-array processing holds the potential to meet the needs of future advanced sonar beamforming algorithms.

SCALABLE ALGORITHMS FOR DISTRIBUTED BEAMFORMING AND NULLFORMING by Amy Kumar A thesis submitted in partial ful llment of the requirements for the Doctor of Philosophy degree in Electrical and Computer Engineering in the Graduate College of The University of Iowa May Thesis Supervisors: Associate Professor Raghuraman Mudumbai Professor.

Parallel Algorithms UNIT 1 PARALLEL ALGORITHMS Structure Page Nos. Introduction 5 Objectives 6 Analysis of Parallel Algorithms 6 Time Complexity Asymptotic Notations Number of Processors Overall Cost Different Models of Computation 8 Combinational Circuits.

Parallel Reduction Complexity • log(n) parallel steps, each step S does n/2. independent ops • Step Complexity is O(log n) • Performs n/2 + n/4 + + 1 = n-1 operations • Work Complexity is O(n)—it is work-efficient • i.e.

does not perform more operations than a sequential algorithm • With p threads physically in parallel (p. Explore a preview version of Design and Analysis of Algorithms right now. O’Reilly members get unlimited access to live online training experiences, plus.

YAO et al.: RANDOMLY DISTRIBUTED SENSOR ARRAY SYSTEM Fig. 1. Beamforming with three randomly distributed sensors and L taps. array-weight vector is denoted by (4) Now, assume the objective of the sensor array is to detect the presence of the strongest source which emits the signal in an otherwise relatively quiet environment.

The sensor.speaker. A prerequisite for using beamforming techniques is to equip the hand-held devices with multiple microphones (omnidirectional or directional) and proper signal processing techniques, e.g., source localization or source tracking, source separation, and beamforming algorithms.must be performed upon the CSDM with each iteration of beamforming.

Many fine-grained algorithms exist for parallel matrix inversion However, like systolic array algorithms, these algorithms generally require too much communication to be feasible on a distributed system. The distributed method for parallel adaptive beamforming presented.