Search

The successive cancellation flip (SC Flip) decoding algorithm was recently suggested for decoding polar codes, which could improve the performance of the frame error rate (FER). The performance of the SC Flip (SCF) decoding algorithm is strong, and its computational complexity tends to be the same as that of the SC decoder at medium to high signal‐to‐noise ratios (SNRs). However, the decoding latency of the SCF decoding algorithm is large. In this paper, a new method for detecting whether or not the flipped bit is correct is proposed. The proposed method makes a decision according to the changing log likelihood ratio (LLR) value caused by the flipped bit to ensure that the decoding process can be terminated in advance and the decoding latency is reduced. The simulation results show that the proposed Latency‐Reduced SCF decoding algorithm can decrease computational complexity and decoding latency, while also achieving similar decoding performance compared to its counterpart. [ABSTRACT FROM AUTHOR]

Sparse code multiple access (SCMA) is a promising candidate air interface of the next generation mobile networks. However, the decoding complexity of current message passing algorithm for SCMA is very high. In this study, the authors map SCMA constellation to q-order Galois field (GF(q)) and introduce a trellis representation to SCMA. Based on the trellis representation, they propose low-complexity decoding algorithms for SCMA by using truncated messages, which is referred as extended max-log (EML) algorithm. As the truncated length of EML is unitary for each user, they further propose a channel-adaptive EMLalgorithm to truncate the messages with a rule that can be adaptive to the channel state. Simulation results show that the proposed schemes obtain a low computational complexity with only a slight performance degradation when the truncated length is selected appropriately. [ABSTRACT FROM AUTHOR]

For iterative detection and decoding (IDD) in multiple-input multiple-output systems, the maximum a posteriori probability (MAP) detector would be ideal in terms of the performance. However, due to its high computational complexity, various suboptimal low-complexity approximate MAP detectors have been studied. In this study, a lattice reduction (LR)-based detector is considered for a near-optimal performance for IDD. The authors improve further the performance by employing a partial bit-wise minimum mean square error (MMSE) approach with randomised sampling, which has a lower complexity than that of the full bit-wise MMSE method. Moreover, the list of candidate vectors obtained by randomised sampling is extended using a MAP-aided integer perturbation algorithm for a better performance with low additional complexity. Through simulation results, it is shown that a near-optimal performance can be obtained which is better than that of the LR-based randomised successive interference cancellation and the full bit-wise MMSE methods. [ABSTRACT FROM AUTHOR]

Spectral efficiency of turbo code can be improved by use of coded modulation methods such as bit-interleaved coded modulation (BICM) with iterative decoding (BICM-ID). On the other hand, the performance of the turbo-BICM can be further improved by iteratively exchanging information between a decoder and a demodulator within a receiver and this scheme is known as the turbo-BICM-ID. Unfortunately, the required complexity of the turbo-BICM-ID is much higher than that of the turbo bit-interleaved coded modulation with iterative decoding turbo-BICM-ID. In this study, the authors propose a complexity reduced turbo-BICM-ID by optimising the mapping of coded bits to modulation symbols and the amount of information fed back from the decoder to the demodulator. [ABSTRACT FROM AUTHOR]

In this study, a new weighted bit-flipping (WBF) algorithm called mixed modified WBF (MM-WBF) decoding is proposed for low-density parity-check codes. The new algorithm is built by mixing two WBF algorithms, one acting as the main decoding algorithm and the other acting as the auxiliary. Simulation results show that the new algorithm achieves a notable performance gain over reliability ratio-based WBF, improved M-WBF and low-complexity WBF algorithms with almost the same computational complexity. Compared with some belief-propagation-based algorithms, MM-WBF also provides an appealing performance against complexity trade-off. [ABSTRACT FROM AUTHOR]