Predicting the Demand for Spectrum Allocation through Auctions (PREPRINT)

Abstract

The projected rare resource spectrum generates high profits if utilized efficiently. The current static allocation lead the spectrum to underutilized with fixed income. Predicting the user requirement for spectrum and auctioning the spectrum helps to better serve the customers and at the same time increases the income. In this research we use the automated collaborative filtering model for predicting the customer requirement and then allocate the spectrum through auctions (bidding for spectrum in open market). Genetic algorithm is used for optimization of the spectrum bidding problem and concluded that the spectrum will be used efficiently while generating more revenue by bidding for spectrum in the market.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2010
Accession Number
ADA523859

Entities

People

  • Y. B. Reddy

Organizations

  • Grambling State University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Air Force Research Laboratories
  • Algorithms
  • Channel Allocation
  • Cognitive Radio
  • Computations
  • Computer Programming
  • Computer Science
  • Evolutionary Algorithms
  • Filtration
  • Frequency
  • Game Theory
  • Genetic Algorithms
  • Linear Programming
  • Mathematics
  • Optimization

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Government Contracting/Procurement.
  • Life Cycle Cost Analysis

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks
  • Biotechnology