7 research outputs found

    Polar Codes with Dynamic Frozen Symbols and Their Decoding by Directed Search

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    A novel construction of polar codes with dynamic frozen symbols is proposed. The proposed codes are subcodes of extended BCH codes, which ensure sufficiently high minimum distance. Furthermore, a decoding algorithm is proposed, which employs estimates of the not-yet-processed bit channel error probabilities to perform directed search in code tree, reducing thus the total number of iterations.Comment: Accepted to ITW201

    Finite-Length Scaling of Polar Codes

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    Consider a binary-input memoryless output-symmetric channel WW. Such a channel has a capacity, call it I(W)I(W), and for any R<I(W)R<I(W) and strictly positive constant PeP_{\rm e} we know that we can construct a coding scheme that allows transmission at rate RR with an error probability not exceeding PeP_{\rm e}. Assume now that we let the rate RR tend to I(W)I(W) and we ask how we have to "scale" the blocklength NN in order to keep the error probability fixed to PeP_{\rm e}. We refer to this as the "finite-length scaling" behavior. This question was addressed by Strassen as well as Polyanskiy, Poor and Verdu, and the result is that NN must grow at least as the square of the reciprocal of I(W)−RI(W)-R. Polar codes are optimal in the sense that they achieve capacity. In this paper, we are asking to what degree they are also optimal in terms of their finite-length behavior. Our approach is based on analyzing the dynamics of the un-polarized channels. The main results of this paper can be summarized as follows. Consider the sum of Bhattacharyya parameters of sub-channels chosen (by the polar coding scheme) to transmit information. If we require this sum to be smaller than a given value Pe>0P_{\rm e}>0, then the required block-length NN scales in terms of the rate R<I(W)R < I(W) as N≥α(I(W)−R)μ‾N \geq \frac{\alpha}{(I(W)-R)^{\underline{\mu}}}, where α\alpha is a positive constant that depends on PeP_{\rm e} and I(W)I(W), and μ‾=3.579\underline{\mu} = 3.579. Also, we show that with the same requirement on the sum of Bhattacharyya parameters, the block-length scales in terms of the rate like N≤β(I(W)−R)μ‾N \leq \frac{\beta}{(I(W)-R)^{\overline{\mu}}}, where β\beta is a constant that depends on PeP_{\rm e} and I(W)I(W), and μ‾=6\overline{\mu}=6.Comment: In IEEE Transactions on Information Theory, 201
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