26 research outputs found
Network error correction with unequal link capacities
This paper studies the capacity of single-source single-sink noiseless
networks under adversarial or arbitrary errors on no more than z edges. Unlike
prior papers, which assume equal capacities on all links, arbitrary link
capacities are considered. Results include new upper bounds, network error
correction coding strategies, and examples of network families where our bounds
are tight. An example is provided of a network where the capacity is 50%
greater than the best rate that can be achieved with linear coding. While
coding at the source and sink suffices in networks with equal link capacities,
in networks with unequal link capacities, it is shown that intermediate nodes
may have to do coding, nonlinear error detection, or error correction in order
to achieve the network error correction capacity
Approximate Capacity of Gaussian Relay Networks
We present an achievable rate for general Gaussian relay networks. We show
that the achievable rate is within a constant number of bits from the
information-theoretic cut-set upper bound on the capacity of these networks.
This constant depends on the topology of the network, but not the values of the
channel gains. Therefore, we uniformly characterize the capacity of Gaussian
relay networks within a constant number of bits, for all channel parameters.Comment: This paper is submited to 2008 IEEE International Symposium on
Information Theory (ISIT 2008) -In the revised format the approximation gap
(\kappa) is sharpene