Biblio

Double differential phase shift keying(DDPSK) modulation is an efficient method to compensate the Doppler shifts, whereas the phase noise will be amplified which results in the signal-to-noise ratio (SNR) loss. In this paper, we propose a novel receiver architecture for underwater acoustic DSSS communications with Doppler shifts. The proposed method adopts not only the DDPSK modulation to compensate the Doppler shifts, but also the improved bit-interleaved coded modulation with iterative decoding (BICM-ID) algorithm for DDPSK to recover the SNR loss. The improved DDPSK demodulator adopts the multi-symbol estimation to track the channel variation, and an extended trellis diagram is constructed for DDPSK demodulator. Theoretical simulation shows that our system can obtain around 10.2 dB gain over the uncoded performance, and 7.4 dB gain over the hard-decision decoding performance. Besides, the experiment conducted in the Songhua Lake also shows that the proposed receiver can achieve lower BER performance when Doppler shifts exists.

Ze the quality of channels into either completely noisy or noieseless channels. This paper presents extrinsic information transfer (EXIT) analysis for iterative decoding of Polar codes to reveal the mechanism of channel transformation. The purpose of understanding the transformation process are to comprehend the placement process of information bit and frozen bit and to comprehend the security standard of Polar codes. Mutual information derived based on the concept of EXIT chart for check nodes and variable nodes of low density parity check (LDPC) codes and applied to Polar codes. This paper explores the quality of the polarized channels in finite blocklength. The finite block-length is of our interest since in the fifth telecommunications generation (5G) the block length is limited. This paper reveals the EXIT curve changes of Polar codes and explores the polarization characteristics, thus, high value of mutual informations for frozen bit are needed to be detectable. If it is the other way, the error correction capability of Polar codes would be drastically decreases. These results are expected to be a reference for developments of Polar codes for 5G technologies and beyond.

The general idea to achieve error detection and correction is to add some extra bit to an original message, in which the receiver can use to check the flexibility of the message which has been delivered, and to recover the noisy data. Turbo code is one of the forward error correction method, which is able to achieve the channel capacity, with nearer Shannon limit, encoding and decoding of text and images are performed. Methods and the working have been explained in this paper. The error has also introduced and detection and correction of errors have been achieved. Transmission will be secure it can secure the information by the theft.

For secure and high-quality wireless transmission, we propose a chaos multiple-input multiple-output (C-MIMO) transmission scheme, in which physical layer security and a channel coding effect with a coding rate of 1 are obtained by chaotic MIMO block modulation. In previous studies, we introduced a log-likelihood ratio (LLR) to C-MIMO to exploit LLR-based outer channel coding and turbo decoding, and obtained further coding gain. However, we only studied the concatenation of turbo code, low-density parity check (LDPC) code, and convolutional code which were relatively high-complexity or weak codes; thus, outer code having further low-complexity and strong error correction ability were expected. In particular, a transmission system with short and good code is required for control signaling, such as in 5G networks. Therefore, in this paper, we propose a polar code concatenation to C-MIMO, and introduce soft successive decoding (SCAD) and soft successive cancellation list decoding (SSCLD) as LLR-based turbo decoding for polar code. We numerically evaluate the bit error rate performance of the proposed scheme, and compare it to the conventional LDPC-concatenated transmission.

In this work, we investigate the MARC (Multiple Access Relay Channel) setup, in which two Markov sources communicate to a single destination, aided by one relay, based on Joint Source Channel Network (JSCN) LDPC codes. In addition, the two source nodes compress the information sequences with an LDPC source code. The compressed symbols are directly transmitted to both a relay and a destination nodes in two transportation phases. Indeed, the relay performs the concatenation of the received compressed sequences to obtain a recovered sequence, which is encoded with an LDPC channel code, before being forwarded to the destination. At the receiver, we propose an iterative joint decoding algorithm that exploits the correlation between the two sources-relay data and takes into account the errors occurring in the sources-relay links to estimate the source data. We show based on simulation results that the JSCN coding and decoding scheme into a MARC setup achieves a good performance with a gain of about 5 dB compared to a conventional LDPC code.

This paper is concerned with three ensembles of systematic low density generator matrix (LDGM) codes, all of which were provably capacity-achieving in terms of bit error rate (BER). This, however, does not necessarily imply that they achieve the capacity in terms of frame error rate (FER), as seen from a counterexample constructed in this paper. We then show that the first and second ensembles are capacity-achieving under list decoding over binary-input output symmetric (BIOS) memoryless channels. We point out that, in principle, the equivocation due to list decoding can be removed with negligible rate loss by the use of the concatenated codes. Simulation results show that the considered convolutional (spatially-coupled) LDGM code is capacity-approaching with an iterative belief propagation decoding algorithm.