DocumentCode
915350
Title
How does a porcupine separate its quills?
Author
Landau, Henry J.
Volume
17
Issue
2
fYear
1971
fDate
3/1/1971 12:00:00 AM
Firstpage
157
Lastpage
161
Abstract
Sets of unit vectors in
-dimensional Euclidean vector space whose constituent vectors are separated one from another by at least a fixed distance
, prescribed once for all and independent of
, are of interest in theory and practice; they have fondly been called "porcupine codes." Although an elegant constructive proof of Gilbert shows that the number of vectors in a porcupine code (of given
) can increase exponentially with
, no systematic method is yet known for generating porcupine codes of this cardinality. Corresponding to a collection of
vectors, we can partition the space into maximum-likelihood regions, the
th of which consists of those vectors that lie closer to the
th than to any other element of the collection. Each maximum-likelihood region is bounded by at most
hyperplanes, and we denote by
the total number of these bounding hyperplanes. Collections for which
is small may be expected to have greater symmetry than those for which
is large. In this paper we show that, for porcupine codes,
, with
depending only on
, the minimum separation of the code vectors. Hence, for the number of vectors of a porcupine code to increase exponentially with dimension, the number of separating hyperplanes must do so as well. We conclude with, an application to the permutation codes introduced by Slepian, showing that the number of vectors of a porcupine code which is of permutation-modulation type can not increase exponentially with
.
-dimensional Euclidean vector space whose constituent vectors are separated one from another by at least a fixed distance
, prescribed once for all and independent of
, are of interest in theory and practice; they have fondly been called "porcupine codes." Although an elegant constructive proof of Gilbert shows that the number of vectors in a porcupine code (of given
) can increase exponentially with
, no systematic method is yet known for generating porcupine codes of this cardinality. Corresponding to a collection of
vectors, we can partition the space into maximum-likelihood regions, the
th of which consists of those vectors that lie closer to the
th than to any other element of the collection. Each maximum-likelihood region is bounded by at most
hyperplanes, and we denote by
the total number of these bounding hyperplanes. Collections for which
is small may be expected to have greater symmetry than those for which
is large. In this paper we show that, for porcupine codes,
, with
depending only on
, the minimum separation of the code vectors. Hence, for the number of vectors of a porcupine code to increase exponentially with dimension, the number of separating hyperplanes must do so as well. We conclude with, an application to the permutation codes introduced by Slepian, showing that the number of vectors of a porcupine code which is of permutation-modulation type can not increase exponentially with
.Keywords
Coding; maximum-likelihood (ML) decoding; Codes; Gaussian noise; Gaussian processes; Maximum likelihood detection; Multidimensional systems; Narrowband; Phase noise; Polynomials; Signal detection; Telephony;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.1971.1054601
Filename
1054601
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