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Title page for ETD etd-03302006-145659


Type of Document Dissertation
Author Hutchinson, Ryan Durward
Author's Email Address ryandh2000@yahoo.com
URN etd-03302006-145659
Title Generic Properties of Convolutional Codes
Degree Doctor of Philosophy
Department Mathematics
Advisory Committee
Advisor Name Title
Joachim Rosenthal Committee Chair
Keywords
  • MDS convolutional codes
  • partial realization problem
  • superregular matrices
  • maximum distance profile
  • Quot scheme
Date of Defense 2006-03-24
Availability unrestricted
Abstract
In this dissertation, convolutional codes possessing the maximum distance profile (MDP) and strongly maximum distance separable (sMDS) properties are studied. More specifically, ideas from linear systems theory and algebraic geometry are used to

1. give an affirmative answer to the conjecture in~cite{gl03r} that

convolutional codes possessing both the MDP and sMDS properties exist for arbitrary code parameters over finite fields of every prime characteristic

and

2. show that the set of such codes may be seen as a generic set in a certain Quot scheme.

In order to think of all points of the aforementioned scheme as somehow representing

convolutional codes of the same degree, we associate so-called homogeneous convolutional codes to them. We introduce this

notion, develop a body of results similar to those that exist in the traditional (nonhomogeneous)

setting, generalize the notions of MDP and

sMDS to these codes, and prove existence

and genericity results analogous to those mentioned above for nonhomogeneous codes.

Finally, the topic of superregular matrices is addressed. Superregular matrices

arise when one considers the problem of constructing codes having the MDP

property. After introducing superregular matrices, we consider group actions

preserving the property of superregularity. We then derive an upper bound on the smallest

size a finite field can have in order that a superregular matrix of a given size can

exist over that field.

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