University of Notre Dame
Browse

File(s) under permanent embargo

Design and Implementation of Sequence Detection Algorithms for Dynamic Spectrum Access Networks

thesis
posted on 2010-04-15, 00:00 authored by Zhanwei Sun
Spectrum sensing is a critical function for enabling dynamic spectrum access (DSA) in a cognitive radio system. In DSA networks, unlicensed secondary users can gain access to a licensed spectrum band as long as they do not cause harmful interfere to the primary users. Although existing research has demonstrated the utility of a Markov chain for modeling the spectrum access pattern of primary users over time, little effort has been directed toward spectrum sensing based upon such models. In this thesis, we develop several sequence detection algorithms for spectrum sensing in DSA networks. We assign different costs for missed detections and false alarms and show that a suitably modified forward-backward sequence detection algorithm is optimal in minimizing the detection risk. Two advanced sequence detection algorithms, the complete forward algorithm and the complete forward partial backward algorithm are introduced. Along the way, we observe new fundamental limitations that we call the risk floor and the window length limitation of traditional physical layer detection schemes that arise from their mismatch with the primary user’s channel access pattern. We also report results from preliminary experiments in which we implement and compare different detectors using a software-defined radio platform.

History

Date Modified

2017-06-02

Research Director(s)

J. Nicholas Laneman

Committee Members

Martin Haenggi Yih-Fang Huang

Degree

  • Master of Science in Electrical Engineering

Degree Level

  • Master's Thesis

Language

  • English

Alternate Identifier

etd-04152010-035106

Publisher

University of Notre Dame

Program Name

  • Electrical Engineering

Usage metrics

    Masters Theses

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC