Blind detection of polar codes

Giard, Pascal; Balatsoukas‐Stimming, Alexios; Burg, Andreas

doi:10.1109/sips.2017.8109977

Cited by 22 publications

(16 citation statements)

References 16 publications

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“…In the first three methods, each step involves a refinement of the channel and codeword log-likelihood ratios using the BP decoding algorithm followed by a simple metric calculation derived from early-termination criteria. For the fourth method, the metric itself is calculated and refined in steps based on intermediate results of the decoding algorithm presented in [13]. ACKNOWLEDGEMENT This work has been supported by the Swiss National Science Foundation under grant #175813.…”

Section: Discussionmentioning

confidence: 99%

“…To this end, we present new polar-code detection algorithms based on belief-propagation (BP) decoding of polar codes by adapting early-stopping criteria developed for BP decoding for the purpose of detection. Using the newly proposed algorithms as well as a detection algorithm from [13] (with a slight modification that enables complexity-performance tradeoffs), our simulation results show that good accuracy can be achieved with a significant reduction in complexity.…”

Section: Contributionsmentioning

confidence: 99%

“…As will be shown in Section IV, it may be beneficial not to update the detection metric after visiting an SPC node. For a detailed description of the detection-metric calculations, we refer the reader to [13].…”

Section: Fast-ssc-based Blind Detection Of Polar Codesmentioning

confidence: 99%

“…Existing blind detection methods for polar codes use variants of SC decoding for detection [11]- [13]. Due to the stringent latency requirements for blind detection imposed by the 5G standard, blind detection methods based on BP decoding are of interest for the first stage because BP decoding is highly parallelizable and its complexity can be scaled easily by changing the number of performed iterations.…”

Section: Bp-based Blind Detectionmentioning

confidence: 99%

“…The right-hand-side one, Fig. 4b, shows the accuracy of the same method when SPC nodes are excluded, i.e., when [13,Eq. (4)] is not applied.…”

Section: Fast-ssc-based Detectionmentioning

confidence: 99%

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On the Tradeoff Between Accuracy and Complexity in Blind Detection of Polar Codes

Giard

Balatsoukas‐Stimming

Burg

2018

2018 IEEE 10th International Symposium on Turbo Codes &Amp; Iterative Information Processing (ISTC)

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Polar codes are a recent family of error-correcting codes with a number of desirable characteristics. Their disruptive nature is illustrated by their rapid adoption in the 5 th -generation mobile-communication standard, where they are used to protect control messages. In this work, we describe a two-stage system tasked with identifying the location of control messages that consists of a detection and selection stage followed by a decoding one. The first stage spurs the need for polar-code detection algorithms with variable effort to balance complexity between the two stages. We illustrate this idea of variable effort for multiple detection algorithms aimed at the first stage. We propose three novel blind detection methods based on belief-propagation decoding inspired by early-stopping criteria. Then we show how their reliability improves with the number of decoding iterations to highlight the possible tradeoffs between accuracy and complexity. Additionally, we show similar tradeoffs for a detection method from previous work. In a setup where only one block encoded with the polar code of interest is present among many other blocks, our results notably show that, depending on the complexity budget, a variable number of undesirable blocks can be dismissed while achieving a missed-detection rate in line with the block-error rate of a complex decoding algorithm.

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Section: Discussionmentioning

confidence: 99%

Section: Contributionsmentioning

confidence: 99%

Section: Fast-ssc-based Blind Detection Of Polar Codesmentioning

confidence: 99%

Section: Bp-based Blind Detectionmentioning

confidence: 99%

“…The right-hand-side one, Fig. 4b, shows the accuracy of the same method when SPC nodes are excluded, i.e., when [13,Eq. (4)] is not applied.…”

Section: Fast-ssc-based Detectionmentioning

confidence: 99%

See 3 more Smart Citations

On the Tradeoff Between Accuracy and Complexity in Blind Detection of Polar Codes

Giard

Balatsoukas‐Stimming

Burg

2018

2018 IEEE 10th International Symposium on Turbo Codes &Amp; Iterative Information Processing (ISTC)

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Hash-Polar Codes With Application to 5G

et al. 2019

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This paper presents a kind of concatenated polar codes called hash-polar codes with flexible outer code lengths, in which a hash function-based encoder is used as an outer encoder. A partial hashpolar code is also proposed to enhance the error-correcting performance at high signal-to-noise ratios. Since polar codes have been recommended by 3GPP as the channel coding scheme for the 5G enhanced mobile broadband control channel, the design of hash-polar codes for 5G is considered, where both good errorcorrecting performance and low false alarm rate (FAR) are required. The simulation results show that, under the 5G FAR requirement, the proposed hash-polar codes have similar frame error rate performance to cyclic redundancy check (CRC)-polar codes and perform better than parity check polar codes. In order to support early termination (ET) for 5G coding, we then propose segmented hash-polar codes, which exhibit the advantages of the ET gain compared with both CRC-polar codes and distributed CRC-polar codes.INDEX TERMS Concatenated polar codes, hash-polar codes, false alarm rate, early-termination, 5G channel codes.

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Scenario-Simplified Successive Cancellation Decoding of Polar Codes for Channel With Deletions

Tian

Liu

2019

IEEE Access

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Successive cancellation-based decoding algorithm and corresponding polarization theorems for polar codes over channels with deletions have been proposed recently. In that decoding algorithm, each node in the conventional successive cancellation decoding trellis is divided into many different scenarios according to different deletion patterns. The number of scenarios increases with the square of the number of deletion errors d which results in high decoding complexity. In this paper, to reduce the decoding complexity, we propose the scenario-simplified successive cancellation decoding algorithm for the polar codes over the deletion channel. In the proposed decoding algorithm, we use exact upper and lower bounds to identify the feasible scenarios of each node in the decoding trellis and avoid calculating the impossible scenarios. And by rearranging the scenario index table, the operations of calculating indices of scenarios can be simplified. We also investigate the joint-weight for each scenario. By setting a threshold τ to prune the scenarios with low joint-weight probabilities, the complexity can be reduced further. For polar codes of length N = 512 and d = 10, we can reduce 42.5% stored scenarios and 46.8% computed scenarios when τ = 10 −5 with a negligible performance loss.

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Blind detection of polar codes

Cited by 22 publications

References 16 publications

On the Tradeoff Between Accuracy and Complexity in Blind Detection of Polar Codes

On the Tradeoff Between Accuracy and Complexity in Blind Detection of Polar Codes

Hash-Polar Codes With Application to 5G

Scenario-Simplified Successive Cancellation Decoding of Polar Codes for Channel With Deletions

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