Cancellation Decoding Of Polar Codes Research Articles

Low complexity list successive cancellation decoding of polar codes

The authors propose a low complexity list successive cancellation (LCLSC) decoding algorithm, where the advantages of the successive cancellation (SC) decoding and the list successive cancellation (LSC) decoding are both considered. In the proposed decoding, SC decoding instead of LSC decoding is implemented when all information bits from bad subchannels are received reliably. While the reliability of each information bit is estimated by its likelihood ratio (LR), the bit channel quality is measured via its Bhattacharyya parameter. To achieve this goal, the authors introduce two thresholds: LR threshold and Bhattacharyya parameter threshold. Also, the methods to determine them are both elaborated. The numerical results suggest that the complexity of LCLSC decoding is much lower than LSC decoding and can be close to that of SC decoding, while the error performance is almost equal to that of LSC decoding. Especially, when the code rate is in low region, the advantage of our decoding is more obvious.

Hardware Architecture for List Successive Cancellation Decoding of Polar Codes

This brief presents a hardware architecture and algorithmic improvements for list successive cancellation (SC) decoding of polar codes. More specifically, we show how to completely avoid copying of the likelihoods, which is algorithmically the most cumbersome part of list SC decoding. The hardware architecture was synthesized for a blocklength of N = 1024 bits and list sizes L = 2, 4 using a UMC 90 nm VLSI technology. The resulting decoder can achieve a coded throughput of 181 Mb/s at a frequency of 459 MHz.

Smart Decode-and-Forward Relaying with Polar Codes

Polar codes have recently been proven to be capacity achieving for the physically degraded relay channel and relevant coding schemes have been proposed in the literature. In this paper, we deal with the design of polar codes in decode-and-forward relaying and prove that the selective transmission of the relay to the destination, based on the decision of a detector of erroneous decoding - a method which we call smart relaying - can significantly improve the error probability performance. Furthermore, we propose a design for the aforementioned detector, that can be applied on the successive cancellation decoding of polar codes. Simulation results are presented to illustrate the efficiency of the proposed method.

Improved Successive Cancellation Decoding of Polar Codes

As improved versions of the successive cancellation (SC) decoding algorithm, the successive cancellation list (SCL) decoding and the successive cancellation stack (SCS) decoding are used to improve the finite-length performance of polar codes. In this paper, unified descriptions of the SC, SCL, and SCS decoding algorithms are given as path search procedures on the code tree of polar codes. Combining the principles of SCL and SCS, a new decoding algorithm called the successive cancellation hybrid (SCH) is proposed. This proposed algorithm can provide a flexible configuration when the time and space complexities are limited. Furthermore, a pruning technique is also proposed to lower the complexity by reducing unnecessary path searching operations. Performance and complexity analysis based on simulations shows that under proper configurations, all the three improved successive cancellation (ISC) decoding algorithms can approach the performance of the maximum likelihood (ML) decoding but with acceptable complexity. With the help of the proposed pruning technique, the time and space complexities of ISC decoders can be significantly reduced and be made very close to those of the SC decoder in the high signal-to-noise ratio regime.

List successive cancellation decoding of polar codes

A list successive cancellation (LSC) decoding algorithm to boost the performance of polar codes is proposed. Compared with traditional successive cancellation decoding algorithms, LSC simultaneously produces at most L locally best candidates during the decoding process to reduce the chance of missing the correct codeword. The complexity of the proposed algorithm is O(LNlog N), where N and L are the code length and the list size, respectively. Simulation results of LSC decoding in the binary erasure channel and binary-input additive white Gaussian noise channel show a significant performance improvement.

Latency reduced method for modified successive cancellation decoding of polar codes

A latency reduced method is proposed based on the modified successive cancellation (MSC) decoder for decoding polar codes. In the MSC decoder, it was shown that latencies for both the rate-zero and the rate-one nodes can be reduced. By redistributing the information bits, the proposed method can obtain a good rate-zero and rate-one nodes distribution, in which decoding latency can be further reduced under the MSC decoder. Simulation results show that the new polar code (obtained by the proposed method) achieves 8.5% latency reduction with neglected error performance loss compared with the original polar code. Furthermore, it is easy to adjust the trade-off between the error performance and decoding latency by the proposed method.