5,858 research outputs found
Grassmannian Frames with Applications to Coding and Communication
For a given class of uniform frames of fixed redundancy we define
a Grassmannian frame as one that minimizes the maximal correlation among all frames . We first analyze
finite-dimensional Grassmannian frames. Using links to packings in Grassmannian
spaces and antipodal spherical codes we derive bounds on the minimal achievable
correlation for Grassmannian frames. These bounds yield a simple condition
under which Grassmannian frames coincide with uniform tight frames. We exploit
connections to graph theory, equiangular line sets, and coding theory in order
to derive explicit constructions of Grassmannian frames. Our findings extend
recent results on uniform tight frames. We then introduce infinite-dimensional
Grassmannian frames and analyze their connection to uniform tight frames for
frames which are generated by group-like unitary systems. We derive an example
of a Grassmannian Gabor frame by using connections to sphere packing theory.
Finally we discuss the application of Grassmannian frames to wireless
communication and to multiple description coding.Comment: Submitted in June 2002 to Appl. Comp. Harm. Ana
An Upper Bound to Zero-Delay Rate Distortion via Kalman Filtering for Vector Gaussian Sources
We deal with zero-delay source coding of a vector Gaussian autoregressive
(AR) source subject to an average mean squared error (MSE) fidelity criterion.
Toward this end, we consider the nonanticipative rate distortion function
(NRDF) which is a lower bound to the causal and zero-delay rate distortion
function (RDF). We use the realization scheme with feedback proposed in [1] to
model the corresponding optimal "test-channel" of the NRDF, when considering
vector Gaussian AR(1) sources subject to an average MSE distortion. We give
conditions on the vector Gaussian AR(1) source to ensure asymptotic
stationarity of the realization scheme (bounded performance). Then, we encode
the vector innovations due to Kalman filtering via lattice quantization with
subtractive dither and memoryless entropy coding. This coding scheme provides a
tight upper bound to the zero-delay Gaussian RDF. We extend this result to
vector Gaussian AR sources of any finite order. Further, we show that for
infinite dimensional vector Gaussian AR sources of any finite order, the NRDF
coincides with the zero-delay RDF. Our theoretical framework is corroborated
with a simulation example.Comment: 7 pages, 6 figures, accepted for publication in IEEE Information
Theory Workshop (ITW
Cyclic-Coded Integer-Forcing Equalization
A discrete-time intersymbol interference channel with additive Gaussian noise
is considered, where only the receiver has knowledge of the channel impulse
response. An approach for combining decision-feedback equalization with channel
coding is proposed, where decoding precedes the removal of intersymbol
interference. This is accomplished by combining the recently proposed
integer-forcing equalization approach with cyclic block codes. The channel
impulse response is linearly equalized to an integer-valued response. This is
then utilized by leveraging the property that a cyclic code is closed under
(cyclic) integer-valued convolution. Explicit bounds on the performance of the
proposed scheme are also derived
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