53 research outputs found
Near-capacity fixed-rate and rateless channel code constructions
Fixed-rate and rateless channel code constructions are designed for satisfying conflicting design tradeoffs, leading to codes that benefit from practical implementations, whilst offering a good bit error ratio (BER) and block error ratio (BLER) performance. More explicitly, two novel low-density parity-check code (LDPC) constructions are proposed; the first construction constitutes a family of quasi-cyclic protograph LDPC codes, which has a Vandermonde-like parity-check matrix (PCM). The second construction constitutes a specific class of protograph LDPC codes, which are termed as multilevel structured (MLS) LDPC codes. These codes possess a PCM construction that allows the coexistence of both pseudo-randomness as well as a structure requiring a reduced memory. More importantly, it is also demonstrated that these benefits accrue without any compromise in the attainable BER/BLER performance. We also present the novel concept of separating multiple users by means of user-specific channel codes, which is referred to as channel code division multiple access (CCDMA), and provide an example based on MLS LDPC codes. In particular, we circumvent the difficulty of having potentially high memory requirements, while ensuring that each user’s bits in the CCDMA system are equally protected. With regards to rateless channel coding, we propose a novel family of codes, which we refer to as reconfigurable rateless codes, that are capable of not only varying their code-rate but also to adaptively modify their encoding/decoding strategy according to the near-instantaneous channel conditions. We demonstrate that the proposed reconfigurable rateless codes are capable of shaping their own degree distribution according to the nearinstantaneous requirements imposed by the channel, but without any explicit channel knowledge at the transmitter. Additionally, a generalised transmit preprocessing aided closed-loop downlink multiple-input multiple-output (MIMO) system is presented, in which both the channel coding components as well as the linear transmit precoder exploit the knowledge of the channel state information (CSI). More explicitly, we embed a rateless code in a MIMO transmit preprocessing scheme, in order to attain near-capacity performance across a wide range of channel signal-to-ratios (SNRs), rather than only at a specific SNR. The performance of our scheme is further enhanced with the aid of a technique, referred to as pilot symbol assisted rateless (PSAR) coding, whereby a predetermined fraction of pilot bits is appropriately interspersed with the original information bits at the channel coding stage, instead of multiplexing pilots at the modulation stage, as in classic pilot symbol assisted modulation (PSAM). We subsequently demonstrate that the PSAR code-aided transmit preprocessing scheme succeeds in gleaning more information from the inserted pilots than the classic PSAM technique, because the pilot bits are not only useful for sounding the channel at the receiver but also beneficial for significantly reducing the computational complexity of the rateless channel decoder
Construction of multiple-rate QC-LDPC codes using hierarchical row-splitting
In this letter, we propose an improved method called hierarchical row-splitting with edge variation for designing multiple-rate quasi-cyclic low-density parity-check (QC-LDPC) codes, which constructs lower-rate codes from a high-rate mother code by row-splitting operations. Consequently, the obtained QC-LDPC codes with various code rates have the same blocklength and can share common hardware resources to reduce the implementation complexity. Compared with the conventional row-combining-based algorithms, a wider range of code rates are supported. Moreover, each individual rate code could be separately optimized, making it easier to find a set of multiple-rate QC-LDPC codes with good performance for all different rates. Simulation results demonstrate that the obtained codes outperform the counterparts from digital video broadcasting-second generation terrestrial
Rate Compatible LDPC Neural Decoding Network: A Multi-Task Learning Approach
Deep learning based decoding networks have shown significant improvement in
decoding LDPC codes, but the neural decoders are limited by rate-matching
operations such as puncturing or extending, thus needing to train multiple
decoders with different code rates for a variety of channel conditions. In this
correspondence, we propose a Multi-Task Learning based rate-compatible LDPC
ecoding network, which utilizes the structure of raptor-like LDPC codes and can
deal with multiple code rates. In the proposed network, different portions of
parameters are activated to deal with distinct code rates, which leads to
parameter sharing among tasks. Numerical experiments demonstrate the
effectiveness of the proposed method. Training the specially designed network
under multiple code rates makes the decoder compatible with multiple code rates
without sacrificing frame error rate performance
Protograph-Based LDPC Code Design for Ternary Message Passing Decoding
A ternary message passing (TMP) decoding algorithm for low-density
parity-check codes is developed. All messages exchanged between variable and
check nodes have a ternary alphabet, and the variable nodes exploit soft
information from the channel. A density evolution analysis is developed for
unstructured and protograph-based ensembles. For unstructured ensembles the
stability condition is derived. Optimized ensembles for TMP decoding show
asymptotic gains of up to 0.6 dB with respect to ensembles optimized for binary
message passing decoding. Finite length simulations of codes from TMP-optimized
ensembles show gains of up to 0.5 dB under TMP compared to protograph-based
codes designed for unquantized belief propagation decoding
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