6 research outputs found
LT Code Design for Inactivation Decoding
We present a simple model of inactivation decoding for LT codes which can be
used to estimate the decoding complexity as a function of the LT code degree
distribution. The model is shown to be accurate in variety of settings of
practical importance. The proposed method allows to perform a numerical
optimization on the degree distribution of a LT code aiming at minimizing the
number of inactivations required for decoding.Comment: 6 pages, 7 figure
Fountain Capacity
Fountain codes are currently employed for reliable and efficient transmission of information via erasure channels with unknown erasure rates. This correspondence introduces the notion of fountain capacity for arbitrary channels. In contrast to the conventional definition of rate, in the fountain setup the definition of rate penalizes the reception of symbols by the receiver rather than their transmission. Fountain capacity measures the maximum rate compatible with reliable reception regardless of the erasure pattern. We show that fountain capacity and Shannon capacity are equal for stationary memoryless channels. In contrast, Shannon capacity may exceed fountain capacity if the channel has memory or is not stationary
Fountain Capacity
Fountain codes are currently employed for reliable and efficient transmission of information via erasure channels with unknown erasure rates. This correspondence introduces the notion of fountain capacity for arbitrary channels. In contrast to the conventional definition of rate, in the fountain setup the definition of rate penalizes the reception of symbols by the receiver rather than their transmission. Fountain capacity measures the maximum rate compatible with reliable reception regardless of the erasure pattern. We show that fountain capacity and Shannon capacity are equal for stationary memoryless channels. In contrast, Shannon capacity may exceed fountain capacity if the channel has memory or is not stationary
Design Principles for Raptor Codes
In this paper we describe some practical aspects of the design process of good Raptor codes for finite block lengths over arbitrary binary input symmetric channels. In particular we introduce a simple model for the finite-length convergence behavior of the iterative decoding algorithm based on density evolution, and propose a practical design procedure. We report simulation results for some example codes