The rapid revolution of mobile communication technology provides a great avenue for efficient information transmission to facilitate digital multimedia services. In current 5G systems, broadcasting technology is used to improve the efficiency of information transmission, and polar codes are adopted to improve data transmission reliability. Reducing the decoding latency of polar codes is of great importance for ultra-low-latency and reliable data transmission for 5G broadcasting, which still remains a challenge in digital broadcasting services. In this paper, we propose an aggregation method to construct constituent codes for reducing the decoding latency of polar codes. The aggregation method jointly exploits the structure and reliability of constituent codes to increase the lengths of constituent codes that can be decoded in parallel, thus significantly reducing the decoding latency. Furthermore, an efficient parallel decoding algorithm is integrated with the proposed aggregation method to efficiently decode the reliable constituent codes without sacrificing error-correction performance. Simulation results show that the proposed method significantly reduces the decoding latency as compared to the existing state-of-the-art schemes.

When polar codes are decoded by the successive cancellation (SC) decoding algorithm, erroneously decoded non-frozen bits are caused by either channel noise or error propagation. SC-Flip algorithms aim to improve error performance by first identifying erroneous hard decisions due to channel noise and then flipping them during the decoding process to reduce error propagation. In existing SC-Flip algorithms, cyclic redundancy check (CRC) is used to check the decoded codeword to detect incorrect hard decisions. Differing from this detection approach based on CRC, we propose new SC-Flip decoders that take advantage of both the CRC and distributed parity checks (PCs) to detect, identify and flip erroneously decoded non-frozen bits. The proposed decoders terminate SC decoding early when a distributed PC is not satisfied. In addition, we propose a new metric to help locate the incorrect hard decisions. Finally, simulation results demonstrate that our SC-Flip decoders achieve better performance complexity tradeoffs than prior flipping algorithms, and approach the performance and complexity of the SC-Oracle algorithms.

Combined with the path splitting selecting (PSS) strategy, the successive cancellation list (SCL) decoder achieves a lower decoding complexity without any performance loss. The main purpose of the PSS strategy is to select fewer non-frozen bits to perform the path splitting and pruning operations. To make the selection more efficient, a neural network aided path splitting selecting strategy is proposed in this paper. In the proposed method, the path splitting is seen as a classification problem. With the help of the neural network, the proposed method can precisely locate the non-frozen bits which are needed to be split. Simulation results verify that the proposed method can reduce the sorting complexity (which is equal to the number of path splitting) without any performance loss.

As a class of bit-flipping (BF) decoder, the noisy gradient descent bit flipping (NGDBF) algorithm outperforms the original GDBF and other BF algorithms. To increase the reliability of the inversion function, we propose a modified NGDBF algorithm by introducing an adjustment factor on the syndrome. Moreover, for the multi-bit flipping, we present an adaptive inversion threshold which depends on the numbers of negative bipolar syndromes. The simulation results show that our proposed algorithm outperforms the NGDBF algorithm for both single-bit and multi-bit flipping schemes.

This paper investigates the application of reconfigurable intelligent surface (RIS) to assist a unified non-orthogonal multiple access (RIS-U-NOMA) framework. More specifically, the proposed RIS-U-NOMA can be applied to RIS assisted code-domain NOMA (RIS-CD-NOMA) and power-domain NOMA (RIS-PD-NOMA). To characterize the performance of RIS-U-NOMA framework, we derive new approximated expressions of outage probability and ergodic rate for a pair of users. Based on the asymptotic expressions, the diversity orders and high signal-to-noise ratio (SNR) slopes for the nearby and distant users are obtained in details. In addition, the system throughput of RIS-U-NOMA is discussed in the delay-limited and delay-tolerant transmission modes. Monte Carlo simulations are provided to verify the analytical results and indicate that: 1) The outage behaviors of RIS-U-NOMA are better than that of RIS assisted orthogonal multiple access (RIS-OMA) and conventional full/half-duplex decode-and-forward relays; 2) The RIS-U-NOMA networks are competent to obtain superior performance in ergodic rate and achieve steeper slope than RIS-OMA; and 3) The delay-limited and delay-tolerant throughput of RIS-CD-NOMA outperform that of RIS-PD-NOMA.

In this paper, a simplified successive cancellation (SC) decoding algorithm for polar codes on insertion/deletion error channels is proposed. First, the SC decoding is designed to decode polar codes on insertion/deletion channels and the joint weight distribution is derived to measure the occurrence probability of different scenarios. Some scenarios with small occurrence probability can be pruned to obtain lower decoding complexity with negligible performance loss. Inspired by this, a fixed pruning strategy (FPS) is proposed to reduce the decoding complexity, which can prune as many scenarios as possible with the given performance requirement. By exploiting the periodicity of the joint weight distribution, the upper bound of the block error rate of the pruned SC decoding is derived. Furthermore, according to the convergence of the upper bound, a dynamic self-adjusting pruning strategy is designed to further reduce the decoding complexity and improve the flexibility of the pruning algorithm. Simulation results show that the decoding complexity of the proposed pruning-based decoding algorithms is significantly reduced compared to the state-of-the-art scenario simplified SC decoding algorithm.