Name
Abstract | ||
|---|---|---|
This paper presents a systematic design methodology for block Markov superposition transmission (BMST) systems to approach the channel capacity at any given target bit-error-rate (BER) of interest. To simplify the design, we choose the basic code as the Cartesian product of a short block code. The encoding memory is then inferred from the genie-aided lower bound according to the performance gap of the short block code to the corresponding Shannon limit at the target BER. In addition to the sliding-window decoding algorithm, we propose to perform one more phase decoding to remove residual (rare) errors. A new technique that assumes a noisy genie is proposed to upper bound the performance. Under some assumptions, these genie-aided bounds can be used to predict the performance of the proposed two-phase decoding algorithm in the extremely low BER region. Using the Cartesian product of a repetition code as the basic code, we construct a BMST system with an encoding memory 30 whose performance at the BER of 10-15 can be predicted over the binary-input additive white Gaussian noise channel (BI-AWGNC). |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ISTC.2014.6955092 | ISTC |
Keywords | Field | DocType |
awgn channels,markov processes,block codes,channel capacity,error statistics,ber targeting,bi-awgnc,bmst system,cartesian product,binary-input additive white gaussian noise channel,bit-error-rate,block markov superposition transmission system,block code,encoding memory,genie-aided bound,phase decoding,residual errors removal,sliding-window decoding algorithm,systematic design methodology | Binary symmetric channel,Concatenated error correction code,Sequential decoding,Repetition code,Computer science,Low-density parity-check code,Block code,Algorithm,Theoretical computer science,Decoding methods,List decoding | Conference |
Citations | PageRank | References |
1 | 0.35 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chulong Liang | 1 | 103 | 12.50 |
| Xiao Ma | 2 | 487 | 64.77 |
| Qiutao Zhuang | 3 | 44 | 3.56 |
| Baoming Bai | 4 | 353 | 63.90 |