Title page for ETD etd-04202010-202823


Type of Document Master's Thesis
Author Deaton, Juan D
Author's Email Address deatjd@vt.edu
URN etd-04202010-202823
Title Evaluation of Dynamic Channel and Power Assignment Techniques for Cognitive Dynamic Spectrum Access Networks
Degree Master of Science
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
DaSilva, Luiz A. Committee Chair
MacKenzie, Allen B. Committee Member
Reed, Jeffrey Hugh Committee Member
Keywords
  • Mobile Adhoc Networks
  • Dynamic Channel and Power Assignment
  • Cognitive Networks
  • Dynamic Spectrum Access
Date of Defense 2010-05-04
Availability restricted
Abstract
This thesis provides three main contributions with respect to the Dynamic Channel and

Power Assignment (DCPA) problem. DCPA refers to the allocation of transmit power and

frequency channels to links in a cognitive dynamic spectrum network so as to maximize the

total number of feasible links while minimizing the aggregate transmit power. In order to

provide a method to compare related, yet disparate, work, the first contribution of this thesis

is a unifying optimization formulation to describe the DCPA problem. This optimization

problem is based on maximizing the number of feasible links and minimizing transmit power

of a set of communications links in a given communications network. Using this optimization

formulation, this thesis develops its second contribution: a evaluation method for comparing

DCPA algorithms. The evaluation method is applied to five DPCA algorithms representative

of the DCPA literature . These five algorithms are selected to illustrate the tradeoffs

between control modes (centralized versus distributed) and channel/power assignment

techniques. Initial algorithm comparisons are done by analyzing channel and power assignment

techniques and algorithmic complexity of five different DCPA algorithms. Through

simulations, algorithm performance is evaluated by the metrics of feasibility ratio and average

power per link. Results show that the centralized algorithm Minimum Power Increase

Assignment (MPIA) has the overall best feasibility ratio and the lowest average power per

link of the five algorithms we investigated. Through assignment by the least change in

transmit power, MPIA minimizes interference and increases the number of feasible links.

However, implementation of this algorithm requires calculating the inverse of near singular

matrices, which could lead to inaccurate results. The third contribution of this thesis is a

proposed distributed channel assignment algorithm, Least Interfering Channel and Iterative

Power Assignment (LICIPA). This distributed algorithm has the best feasibility ratio and

lowest average power per link of the distributed algorithms. In some cases, LICIPA achieves

90% of the feasibility ratio of MPIA, while having lower complexity and overall lower average

run time.

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