This letter focuses on the metric sorter, which is a module that affects the overall latency in the LLR-based successive cancellation list (SCL) decoder of polar codes. We propose two improved two-step sorters, which are achieved by revising the sorters used in the pruned bitonic extractor (PBE), and selecting one of two candidate architectures based on a threshold on $L$ . Moreover, we remove the first stage of the PBE in the second step sorting, which can reduce the latency in the second step and further increase the throughput of the sorting units. We first describe the architectures of the proposed sorters, and then derive the required number of the compare-and-swap units (CASUs) and the stages. The evaluation results indicate that the two proposed improved sorters outperform the state-of-the-art sorters in terms of the CASUs and the stages, which significantly lowers the overall latency and resource consumption. Compared with the PBE, the proposed sorters can reduce 57.8% of stages and 46.3% of CASUs for $L=128$ , and 33.3% of stages and 21.1% of CASUs for $L=8$ .

Although the traditional successive cancellation list (SCL) decoding algorithm can greatly improve the performance of successive cancellation (SC) decoding algorithm, multiple path splitting and sorting operations increase the complexity. In order to reduce the complexity of the SCL algorithm, a new path splitting decision strategy is proposed to reduce the number of path splitting (PSN). This strategy is based on a new auxiliary path metric (APM) proposed in this letter, which is used to identify whether the decoding path is wrong. Wrong paths can be avoided by comparing the predicted APM with the threshold. The simulation results show that the proposed path splitting decision-aided SCL (PSD-SCL) algorithm reduces the complexity compared with other list decoding algorithms with small performance loss at high signal-noise ratio (SNR).

To solve the problem of load imbalance and system interference in heterogeneous networks (HetNets), an energy efficiency (EE) optimized strategy based on enhanced Inter-Cell Interference Coordination (eICIC) technology is proposed. The optimization of the EE of the system is established by taking into account four components which are the connection between the users and base stations (BSs), almost blank sub-frame (ABS) ratio, resource allocation in the frequency domain, and the power transmission of the macro base stations (MBSs). In our optimized strategy, the user’s optimal BS connection status are determined according to the overall EE change of the system, and the allocation of sub-frames and resource blocks of the MBSs both in the time domain and frequency domain are optimized respectively. We use the Gauss-Seidel method to iteratively solve the optimization problem. Simulation results show that the optimized strategy outperforms other solutions in terms of EE and user fairness in average. The proposed optimization strategy increases the system EE by 24.2% and 19.1% respectively when compared with the maximal reference signal received power (MAX-RSRP) and the low power-ABS (LP-ABS) strategies. The Jain fairness index of our proposed optimization strategy is averagely increased by 33.8% and 23.4% respectively. In addition, the proposed strategy can further improve the user satisfaction and the performance in the system.

Although the performance of belief propagation (BP) decoder is slightly better than that of successive cancellation (SC) decoder, it has remarkable performance gap compared with improved SC decoders. In this paper, we propose BP bit-strengthening (BPBS) decoder and concept of relative code rate for polar codes. When conventional BP decoding fails, the stable information bits are found by submatrix check and relative code rate, then a priori message of stable information bits is strengthened by hard decision. The simulation results show that BPBS decoder can achieve significant performance gains compared with conventional BP decoder. Furthermore, as signal-to-noise ratio (SNR) increases, the performance of BPBS is close to that of successive cancellation list (SCL) decoder in the medium and high SNR regions.

In this letter, a new soft cancellation bit-flip (SCAN-BF) decoding algorithm is proposed, reducing errors caused by error propagation. In order to find the bit index with high error probability, a flipping set for soft cancellation (SCAN) decoding algorithm is constructed based on special error distribution regularity. Segmented submatrix check is adopted in the proposed SCAN-BF algorithm to find the subblock where decoding error occurred. Since the search range of finding candidate flipping bits is reduced, the decoding complexity of SCAN-BF algorithm is also reduced. Experimental simulation shows that SCAN-BF decoding obtains a large performance gain in short and medium code lengths.

Polar codes have received significant attention as part of the 5G standard. The successive cancellation list (SCL) decoding can provide superior decoding performance compared with successive cancellation (SC) decoding. To improve the performance of SCL decoding, the key is to obtain the indices of the bit-channels which contribute the most to the elimination of the correct path. In this letter, we analyze the distribution of bit positions where the correct path is eliminated and propose an offline improved critical set (ICS) that obtains the index of the erroneous bit for SCL decoding. Numerical results show that ICS is an effective alternative to the conventional critical set (CS) for SCL decoding and the average computational complexity is reduced significantly without performance loss compared with CS.