Theoretical Foundations of Wireless Networks

Abstract

The goal of this project is to develop a formal theory of wireless networks providing a scientific basis to understand their fundamental properties and guide their design. Our technical approach is to rely on two aspects that are somewhat inherent to these networks: randomness and optimality. Randomness, in the form of fading, is a defining characteristic of wireless networks. Optimality is a suitable design specification. Wireless network optimization problems are notoriously difficult to analyze and solve. The incorporation of fading randomness leads to more complex formulations. However, it is frequently the case that these more complex formulations are in fact simpler to analyze. Randomness introduces structure making it often possible to infer properties of large-scale stochastic systems even if analogous deterministic counterparts are intractable. In light of the former comments, it should not come as a surprise if random wireless networks exhibit more regular structure than deterministic networks. The research undertaken in the context of this project aims at exploiting randomness to devise solution methodologies for optimal wireless networking problems.

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Document Details

Document Type
Technical Report
Publication Date
Jul 22, 2015
Accession Number
ADA625733

Entities

People

  • Alejandro Ribeiro

Organizations

  • University of Pennsylvania

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Communication Networks
  • Frequency Division Multiple Access
  • Mesh Networks
  • Multiple Access
  • Network Science
  • Numerical Analysis
  • Operations Research
  • Probability
  • Probability Distributions
  • Sensor Networks
  • Signal Processing
  • Social Networks
  • Students
  • Wireless Communications
  • Wireless Networks
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Mathematical Modeling and Probability Theory.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms