The combination of powerful error correcting codes such as (LDPC) codes and Quadrature Amplitude Modulation (QAM) has been widely deployed in wireless communication standards such as the IEEE 802.11n and DVB-T2. Recently, several Unequal Error Protection schemes which exploit non-uniform degree distribution of bit nodes in irregular LDPC codes have been proposed. In parallel, schemes that exploit the inherent UEP characteristics of the QAM constellation have also been developed. In this paper, a hybrid UEP scheme is proposed for LDPC codes with QAM. The scheme uses statistical distribution of source symbols to map the systematic bits of the LDPC encoded symbols to the QAM constellation. Essentially, systematic symbols having highest probabilities of occurrence are mapped onto the low power region of the QAM constellation and those with a low probability of occurrence are mapped onto the high power region. The decrease in overall transmission power allows for an increased spacing between the QAM constellation points. Additionally, the scheme uses the distribution of the bit node degree of the LDPC code-word to map the parity bits having the highest degree onto prioritised QAM constellation points. Simulations with the IEEE 802.11n LDPC codes revealed that the proposed scheme can provide gains of up to 0.91 dB in Eb/No compared with other UEP schemes for a range of Bit Error Rate (BER) values

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SUMMARYJPEG image transmission over noisy channels is highly problematic due to the sensitivity of the JPEG bit stream to error propagation. The use of resynchronization markers and channel coding do not alleviate the problem completely thus making retransmissions inevitable. In packetized image transmission, image packets are repeated n times, to ensure reliable transmission. This paper proposes a new unequal error protection (UEP) scheme which jointly optimizes the allocation of channel code rates and number of repeats to image packets, subject to a constraint on the maximum overall transmission rate. The coding scheme used is the rate compatible punctured convolutional code coupled with the code-combining technique. An unequal allocation of headers to the image packets is also performed in order to reduce the overall distortion due to error propagation. Simulation results show that the proposed UEP scheme provides a gain of more than 8 dB in peak-to-peak signal-to-noise ratio over a tandem scheme. The flexibility of the proposed scheme, and the major performance gains obtained, make the scheme appealing for applications like, web-based image browsing, multi-hop networks, and wireless image transmission.

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This paper investigates the performance of three different symbol level decoding algorithms for Duo-Binary Turbo codes. Explicit details of the computations involved in the three decoding techniques, and a computational complexity analysis are given. Simulation results with different couple lengths, code-rates, and QPSK modulation reveal that the symbol level decoding with bit-level information outperforms the symbol level decoding by 0.1 dB on average in the error floor region. Moreover, a complexity analysis reveals that symbol level decoding with bit-level information reduces the decoding complexity by 19.6 % in terms of the total number of computations required for each half-iteration as compared to symbol level decoding.

5G is the next generation of mobile communications networks which will use cutting-edge network technologies to deliver enhanced mobile connectivity. 5G has introduced new requirements for channel coding in its three different service classes which are enhanced mobile broadband (eMBB), ultrareliable low latency communications (URLLC) and massive machine-type communications (mMTC). eMBB is expected to keep up with consumer's insatiable demand for high mobile data rates to support data-extensive applications. mMTC will provide connectivity to a massive number of connected devices sending short data packets simultaneously to support applications such as Internet of Things (IoT). Finally, URLLC will ensure reliable low latency connectivity to support mission-critical latency-sensitive applications such as telesurgery. To address these new requirements, several new channel coding schemes are being developed. This review article provides a detailed analysis of the new channel coding challenges set out by 5G. A detailed review of existing and emerging solutions is provided. Moreover, simulation are performed to assess the performances of Low-Density Parity-Check (LDPC) codes and Polar codes used in 5G's eMBB. Directions for future works and new solutions for 5G channel coding are also discussed.

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