Browsing by Subject "Sequential decoding"

Now showing 1 - 14 of 14

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A Monte-Carlo based construction of polarization-adjusted convolutional (PAC) codes
(Elsevier BV, 2024-12-05) Moradi, Mohsen; Mozammel, Amir
This paper proposes a rate-profile construction method for polarization-adjusted convolutional (PAC) codes of any code length and rate, which is capable of preserving the trade-off between the error-correction performance and decoding complexity of PAC codes. The proposed method can improve the error-correction performance of PAC codes while guaranteeing a low mean sequential decoding complexity for signal-to-noise ratio (SNR) values beyond a target SNR value.
Open Access
A tree pruning technique for decoding complexity reduction of polar codes and PAC codes
(Institute of Electrical and Electronics Engineers , 2023-05-18) Moradi, Mohsen; Mozammel, Amir
Sorting operation is one of the main bottlenecks for the successive-cancellation list (SCL) decoding. This paper introduces an improvement to the SCL decoding for polar and pre-transformed polar codes that reduces the number of sorting operations without visible degradation in the code’s error correction performance. In an SCL decoding with an optimum metric function we show that, on average, the correct branch’s bit-metric value must be equal to the bit-channel capacity, and on the other hand, the average bit-metric value of a wrong branch can be at most zero. This implies that a wrong path’s partial path metric value deviates from the bit-channel capacity’s partial summation. For relatively reliable bit-channels, the bit metric for a wrong branch becomes very large negative number, which enables us to detect and prune such paths. We prove that, for a threshold lower than the bit-channel cutoff rate, the probability of pruning the correct path decreases exponentially by the given threshold. Based on these findings, we presented a pruning technique, and the experimental results demonstrate a substantial decrease in the amount of sorting procedures required for SCL decoding. In the stack algorithm, a similar technique is used to significantly reduce the average number of paths in the stack.
Open Access
Application of guessing to sequential decoding of polarization-adjusted convolutional (PAC) codes
(Institute of Electrical and Electronics Engineers Inc., 2023-08-16) Moradi, Mohsen
Despite the extreme error-correction performance, the amount of computation of sequential decoding of the polarization-adjusted convolutional (PAC) codes is random. In sequential decoding of convolutional codes, the cutoff rate denotes the region between rates whose average computational complexity of decoding is finite and those which is infinite. In this paper, by benefiting from the polarization and guessing techniques, we prove that the required computation in sequential decoding of pre-transformed polar codes polarizes, and this polarization determines which set of bit positions within the rate profile may result in high computational complexity. Based on this, we propose a technique for taming the Reed-Muller (RM) rate-profile construction, and the performance results demonstrate that the error-correction performance of the PAC codes can achieve the theoretical bounds using the tamed RM rate-profile construction and requires a significantly lower computational complexity than the RM rate-profile construction.
Open Access
Bit-flipping for stack decoding of polarization-adjusted convolutional (PAC) codes
(Institute of Electrical and Electronics Engineers, 2022-09-06) Moradi, Mohsen
While sequential decoding of polarization-adjusted convolutional (PAC) codes constructed using polar rate profile has low computational complexity, their error-correction per-formance falls far short of the theoretical bounds for finite blocklength codes. In this paper, we use the bit-flipping technique in the stack decoding algorithm of PAC codes in order to improve their error-correction performance. This technique maintains the low memory requirements of stack decoding and polar demapper. Additionally, at high SNR values, the number of visits at each level of the decoding tree is almost one. Numerical findings indicate that this approach is capable of outperforming the stack decoding algorithm.
Open Access
Guessing with lies
(IEEE, 2002-06-07) Arıkan, Erdal; Boztaş, S.
A practical algorithm was obtained for directly generating an optimal guessing sequence for guessing under lies. An optimal guessing strategy was defined as one which minimizes the number of average number of guesses in determining the correct value of a random variable. The information-theoretic bounds on the average number of guesses for optimal strategies were also derived.
Open Access
Hardware implementation of Fano Decoder for polarization-adjusted convolutional (PAC) codes
(2022-06) Hokmabadi, Amir Mozammel
Polarization-adjusted convolutional (PAC) codes are a new class of error-correcting codes that have been shown to achieve near-optimum performance. By combining ideas from channel polarization and convolutional coding, PAC codes create an overall encoding transform that achieves a performance near the information-theoretic limits at short block lengths. In this thesis we propose a hardware implementation architecture for Fano decoding of PAC codes. First, we introduce a new variant of Fano algorithm for decoding PAC codes which is suitable for hardware implementation. Then we provide the hardware diagrams of the sub-blocks of the proposed PAC Fano decoder and an estimate of their hardware complexity and propagation delay. We also introduce a novel branch metric unit for sequential decoding of PAC codes which is capable of calculating the current and previous branch metric values online, without requiring any storage element or comparator. We evaluate the error-correction performance of the proposed decoder on FPGA and its hardware characteristics on ASIC with TSMC 28 nm 0.72 V library. We show that, for a block length of 128 and a message length of 64, the proposed decoder can be clocked at 500 MHz and achieve approximately 38.1 Mb/s information throughput at 3.5 dB signal-to-noise ratio with a power consumption of 3.85 mW.
Open Access
Hardware implementation of fano decoder for polarization-adjusted convolutional (PAC) codes
(IEEE, 2021-10-26) Mozammel, Amir
This brief proposes a hardware implementation architecture for Fano decoding of polarization-adjusted convolutional (PAC) codes. This architecture uses a novel branch metric unit specific to PAC codes. The proposed decoder is tested on FPGA, and its performance is evaluated on ASIC using TSMC 28 nm 0.72 V library. The decoder can be clocked at 500 MHz and reach an average information throughput of 38 Mb/s at 3.5 dB signal-to-noise ratio for a block length of 128 and a code rate of 1/2.
Open Access
Joint source-channel coding and guessing with application to sequential decoding
(Institute of Electrical and Electronics Engineers, 1998-09) Arikan, E.; Merhav, N.
We extend our earlier work on guessing subject to distortion to the joint source-channel coding context. We consider a system in which there is a source connected to a destination via a channel and the goal is to reconstruct the source output at the destination within a prescribed distortion level with respect to (w.r.t.) some distortion measure. The decoder is a guessing decoder in the sense that it is allowed to generate successive estimates of the source output until the distortion criterion is met. The problem is to design the encoder and the decoder so as to minimize the average number of estimates until successful reconstruction. We derive estimates on nonnegative moments of the number of guesses, which are asymptotically tight as the length of the source block goes to infinity. Using the close relationship between guessing and sequential decoding, we give a tight lower bound to the complexity of sequential decoding in joint source-channel coding systems, complementing earlier works by Koshelev and Hellman. Another topic explored here is the probability of error for list decoders with exponential list sizes for joint source-channel coding systems, for which we obtain tight bounds as well. It is noteworthy that optimal performance w.r.t. the performance measures considered here can be achieved in a manner that separates source coding and channel coding.
Open Access
Lower bounds to moments of list size
(IEEE, 1990) Arıkan, Erdal
Summary form only given. The list-size random variable L for a block code is defined as the number of incorrect messages that appear to a maximum-likelihood decoder to be at least as likely as the true message. Lower bounds to the moments of L have been obtained. For sequential decoding, the results imply that the tth moment of computation is unbounded at rates above a certain value, for all t≥0, and settle a long-standing open problem.
Open Access
On sequential decoding metric function of polarization-adjusted convolutional (PAC) codes
(IEEE, 2021-09-07) Moradi, Mohsen
In this paper, we present a sequential decoding metric function, which leads to significantly improved computational complexity while maintaining the superiority of polarizationadjusted convolutional (PAC) codes’ error-correction performance. With the proposed metric function, the PAC codes’ decoding computational complexity is comparable to the computational complexity of sequential decoding of conventional convolutional codes (CCs). Moreover, simulation results show an improvement in the error-correction performance of low rate PAC codes when using the proposed metric function. Simulation results also show that using the proposed metric, the upper bound on the PAC codes’ computational complexity has a Pareto distribution. To reduce the worst-case latency of PAC sequential decoder, we limit the number of searches performed by sequential decoder. The results show that for PAC codes of length 128, search-limited sequential decoding can achieve an error-correction performance close to the error-correction performance of polar codes with successive cancellation list decoding with list size 64 and CRC length 11 with considerably less computational complexity.
Open Access
On the origin of polar coding
(Institute of Electrical and Electronics Engineers Inc., 2016) Arıkan, E.
Polar coding was conceived originally as a technique for boosting the cutoff rate of sequential decoding, along the lines of earlier schemes of Pinsker and Massey. The key idea in boosting the cutoff rate is to take a vector channel (either given or artificially built), split it into multiple correlated subchannels, and employ a separate sequential decoder on each subchannel. Polar coding was originally designed to be a low-complexity recursive channel combining and splitting operation of this type, to be used as the inner code in a concatenated scheme with outer convolutional coding and sequential decoding. However, the polar inner code turned out to be so effective that no outer code was actually needed to achieve the original aim of boosting the cutoff rate to channel capacity. This paper explains the cutoff rate considerations that motivated the development of polar coding.
Open Access
Performance and computational analysis of polarization-adjusted convolutional (PAC) codes
(2022-06) Moradi, Mohsen
We study the performance of sequential decoding of polarization-adjusted con- volutional (PAC) codes. We present a metric function that employs bit-channel mutual information and cutoff rate values as the bias values and significantly re- duces the computational complexity while retaining the excellent error-correction performance of PAC codes. With the proposed metric function, the computa- tional complexity of sequential decoding of PAC codes is equivalent to that of conventional convolutional codes. Our results indicate that the upper bound on the sequential decoding compu- tational complexity of PAC codes follows a Pareto distribution. We also employ guessing technique to derive a lower bound on the computational complexity of sequential decoding of PAC codes. To reduce the PAC sequential decoder’s worst-case latency, we restrict the number of searches executed by the sequential decoder. We introduce an improvement to the successive-cancellation list (SCL) decod- ing for polarized channels that reduces the number of sorting operations without degrading the code’s error-correction performance. In an SCL decoding with an optimum metric function, we show that, on average, the correct branch’s bit- metric value must be equal to the bit-channel capacity. On the other hand, the average bit-metric value of a wrong branch can be at most 0. This implies that a wrong path’s partial path metric value deviates from the bit-channel capacity’s partial summation. This enables the decoder to identify incorrect branches and exclude them from the list of metrics to be sorted. We employ a similar technique to the stack algorithm, resulting in a considerable reduction in the stack size. Additionally, we propose a technique for constructing a rate profile for PAC codes of arbitrary length and rate which is capable of balancing the error- correction performance and decoding complexity of PAC codes. For signal-to- noise ratio (SNR) values larger than a target SNR value, the proposed approach can significantly enhance the error-correction performance of PAC codes while retaining a low mean sequential decoding complexity. Finally, we examine the weight distribution of PAC codes with the goal of providing a new demonstration that PAC codes surpass polar codes in terms of weight distribution.
Open Access
Sequential decoding on intersymbol interference channels with application to magnetic recording
(1990) Alanyalı, Murat
In this work we treat sequential decoding in the problem of sequence estimation on intersymbol interference ( ISI ) channels. We consider the magnetic recording channel as the particular ISI channel and investigate the coding gains that can be achieved with sequential decoding for different information densities. Since the cutoff rate determines this quantity , we find lower bounds to the cutoff rate. The symmetric cutoff rate is computed as a theoretical lower bound and practical lower bounds are found through simulations. Since the optimum decoding metric is impractical, a sub-optimum metric has been used in the simulations. The results show that this metric can not achieve the cutoff rate in general, but still its performance is not far from that of the optimum metric. We compare the results to those of Immink[9] and see that one can achieve positive coding gains at information densities of practical interest where other practical codes used in magnetic recording show coding loss.
Open Access
Trellis coding for high signal-to-noise ratio Gaussian noise channels
(IEEE, 1989) Arıkan, Erdal
It is known that under energy constraints it is best to have each code word of a code satisfy the constraint with equality, rather than have the constraint satisfied only in an average sense over all code words. This suggests the use of fixed-composition codes on additive Gaussian noise channels, for which the coding gains achievable by this method are significant, especially in the high signal-to-noise-ratio case. The author examines the possibility of achieving these gains by using fixed-composition trellis codes. Shell-constrained trellis codes are promising in this regard, since they can be decoded by sequential decoding at least at rates below the computational cutoff rate.