Search

The paper introduces two decoding techniques based on grouping for symbol flipping non-binary LDPC codes. Firstly, a new technique of adaptive grouping of variable nodes in each iteration using bit reliability and majority voting of each received symbol is presented. Grouping of variable nodes and the subsequent decoding are based on individual symbol reliability and majority voting. To form groups adaptively, the cumulative density of variable nodes is used where a high priority group is considered to contain the most unreliable variable nodes and is decoded while the second priority group contains variable nodes having a second level of reliability and so on. Secondly, a fixed grouping technique is applied to symbol flipping decoding of non-binary LDPC codes. In the fixed grouping decoding, each group contains an equal number of variable nodes, and selected symbols in each group are flipped according to pre-defined flipping criteria. Numerical results and analysis show that the proposed group-based hard decision symbol flipping decoding algorithms have the advantage of reduced computational complexity and show better performance. Therefore, the proposed algorithms can be considered for applications like data storage and mobile communication.

This paper addresses the problem of decoding non-binary low density parity check codes(LDPC) over finite field $GF(q)$ using symbol flipping approach. To achieve low complexity reliable communication, three new algorithms for improving the bit error rate performance of the non-binary LDPC decoder are presented. The first type is the symbol flipping decoding algorithm using a flipping function based on the channel reliability to identify the least reliable symbol position. In this algorithm, if the predicted symbol value satisfies the check sum, then the value is declared as correct otherwise the value is adjusted and sent back to the QAM detector. Algorithms 2 in this paper is an improvement to iterative joint detection-decoding algorithm by using the method of iterative hard decision based majority logic to select the new candidate symbol value. The feedback value to the QAM detector is adjusted by using Euclidean distance between the current symbol and the newly selected symbol value. Algorithm 3 is a low complexity version of Algorithm 2 which is derived by applying a majority voting scheme. In the majority voting scheme, symbols are short listed first by voting and all the computation are carried out only for the short listed least reliable symbols which significantly lowers the processing complexity. Numerical results and complexity analysis show that the proposed methods have good bit error rate versus complexity trade-off for various applications when compared with some existing algorithms.

A simplified version of the enhanced serial generalized bit-flipping algorithm is proposed in this brief. This new algorithm reduces the quantity of information that is stored with a negligible performance loss of 0.05 dB compared with previous proposals. In addition, the algorithm allows us not only to save memory, but also to reduce the number of arithmetic resources needed. In addition, a new initialization of the algorithm avoids using techniques to control data growth without any performance degradation, reduces routing, increasing the maximum frequency achievable, and saves logic. The decoder derived from the simplified algorithm requires almost half the area of previous architectures, with a throughput of 716 Mbps on a 90-nm CMOS process for the (837, 723) nonbinary code over GF(32) at ten iterations. [ABSTRACT FROM AUTHOR]