686 research outputs found
Iterative joint design of source codes and multiresolution channel codes
We propose an iterative design algorithm for jointly optimizing source and channel codes. The joint design combines channel-optimized vector quantization (COVQ) for the source code with rate-compatible punctured convolutional (RCPC) coding for the channel code. Our objective is to minimize the average end-to-end distortion. For a given channel SNR and transmission rate, our joint source and channel code design achieves an optimal allocation of bits between the source and channel coders. This optimal allocation can reduce distortion by up to 6 dB over suboptimal allocations for the source data set considered. We also compare the distortion of our joint iterative design with that of two suboptimal design techniques: COVQ optimized for a given channel bit-error-probability, and RCPC channel coding optimized for a given vector quantizer. We conclude by relaxing the fixed transmission rate constraint and jointly optimizing the transmission rate, source code, and channel code
The capacity region of broadcast channels with memory
We derive the two-user capacity region of a broadcast channel with memory (ISI), assuming additive white Gaussian noise (AWGN) and an input power constraint. The results can be extended to any finite number of users
Information Recovery from Pairwise Measurements
A variety of information processing tasks in practice involve recovering
objects from single-shot graph-based measurements, particularly those taken
over the edges of some measurement graph . This paper concerns the
situation where each object takes value over a group of different values,
and where one is interested to recover all these values based on observations
of certain pairwise relations over . The imperfection of
measurements presents two major challenges for information recovery: 1)
: a (dominant) portion of measurements are
corrupted; 2) : a significant fraction of pairs are
unobservable, i.e. can be highly sparse.
Under a natural random outlier model, we characterize the , that is, the critical threshold of non-corruption rate
below which exact information recovery is infeasible. This accommodates a very
general class of pairwise relations. For various homogeneous random graph
models (e.g. Erdos Renyi random graphs, random geometric graphs, small world
graphs), the minimax recovery rate depends almost exclusively on the edge
sparsity of the measurement graph irrespective of other graphical
metrics. This fundamental limit decays with the group size at a square root
rate before entering a connectivity-limited regime. Under the Erdos Renyi
random graph, a tractable combinatorial algorithm is proposed to approach the
limit for large (), while order-optimal recovery is
enabled by semidefinite programs in the small regime.
The extended (and most updated) version of this work can be found at
(http://arxiv.org/abs/1504.01369).Comment: This version is no longer updated -- please find the latest version
at (arXiv:1504.01369
The capacity region of broadcast channels with intersymbol interference and colored Gaussian noise
We derive the capacity region for a broadcast channel with intersymbol interference (ISI) and colored Gaussian noise under an input power constraint. The region is obtained by first defining a similar channel model, the circular broadcast channel, which can be decomposed into a set of parallel degraded broadcast channels. The capacity region for parallel degraded broadcast channels is known. We then show that the capacity region of the original broadcast channel equals that of the circular broadcast channel in the limit of infinite block length, and we obtain an explicit formula for the resulting capacity region. The coding strategy used to achieve each point on the convex hull of the capacity region uses superposition coding on some or all of the parallel channels and dedicated transmission on the others. The optimal power allocation for any point in the capacity region is obtained via a multilevel water-filling. We derive this optimal power allocation and the resulting capacity region for several broadcast channel models
- …