523 research outputs found

    A two phase successive cancellation decoder architecture for polar codes

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    We propose a two-phase successive cancellation (TPSC) decoder architecture for polar codes that exploits the array-code property of polar codes by breaking the decoding of a length-TV polar code into a series of length-√ L decoding cycles. Each decoding cycle consists of two phases: a first phase for decoding along the columns and a second phase for decoding along the rows of the code array. The reduced decoder size makes it more affordable to implement the core decoder logic using distributed memory elements consisting of flip-flops (FFs), as opposed to slower random access memory (RAM), leading to a speed up in clock frequency. To minimize the circuit complexity, a single decoder unit is used in both phases with minor modifications. The re-use of the same decoder module makes it necessary to recall certain internal decoder state variables between decoding cycles. Instead of storing the decoder state variables in RAM, the decoder discards them and calculates them again when needed. Overall, the decoder has O(√ L) circuit complexity excluding RAM, and a latency of approximately 2.57V. A RAM of size O(N) is needed for storing the channel log-likelihood variables and the decoder decision variables. As an example of the proposed method, a length N = 214 bit polar code is implemented in an FPGA and the synthesis results are compared with a previously reported FPGA implementation. The results show that the proposed architecture has lower complexity, lower memory utilization with higher throughput, and a clock frequency that is less sensitive to code length. © 2013 IEEE

    A Multi-Kernel Multi-Code Polar Decoder Architecture

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    Polar codes have received increasing attention in the past decade, and have been selected for the next generation of wireless communication standard. Most research on polar codes has focused on codes constructed from a 2×22\times2 polarization matrix, called binary kernel: codes constructed from binary kernels have code lengths that are bound to powers of 22. A few recent works have proposed construction methods based on multiple kernels of different dimensions, not only binary ones, allowing code lengths different from powers of 22. In this work, we design and implement the first multi-kernel successive cancellation polar code decoder in literature. It can decode any code constructed with binary and ternary kernels: the architecture, sized for a maximum code length NmaxN_{max}, is fully flexible in terms of code length, code rate and kernel sequence. The decoder can achieve frequency of more than 11 GHz in 6565 nm CMOS technology, and a throughput of 615615 Mb/s. The area occupation ranges between 0.110.11 mm2^2 for Nmax=256N_{max}=256 and 2.012.01 mm2^2 for Nmax=4096N_{max}=4096. Implementation results show an unprecedented degree of flexibility: with Nmax=4096N_{max}=4096, up to 5555 code lengths can be decoded with the same hardware, along with any kernel sequence and code rate

    Fast Software Polar Decoders

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    Among error-correcting codes, polar codes are the first to provably achieve channel capacity with an explicit construction. In this work, we present software implementations of a polar decoder that leverage the capabilities of modern general-purpose processors to achieve an information throughput in excess of 200 Mbps, a throughput well suited for software-defined-radio applications. We also show that, for a similar error-correction performance, the throughput of polar decoders both surpasses that of LDPC decoders targeting general-purpose processors and is competitive with that of state-of-the-art software LDPC decoders running on graphic processing units.Comment: 5 pages, 3 figures, submitted to ICASSP 201

    Comparison of Polar Decoders with Existing Low-Density Parity-Check and Turbo Decoders

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    Polar codes are a recently proposed family of provably capacity-achieving error-correction codes that received a lot of attention. While their theoretical properties render them interesting, their practicality compared to other types of codes has not been thoroughly studied. Towards this end, in this paper, we perform a comparison of polar decoders against LDPC and Turbo decoders that are used in existing communications standards. More specifically, we compare both the error-correction performance and the hardware efficiency of the corresponding hardware implementations. This comparison enables us to identify applications where polar codes are superior to existing error-correction coding solutions as well as to determine the most promising research direction in terms of the hardware implementation of polar decoders.Comment: Fixes small mistakes from the paper to appear in the proceedings of IEEE WCNC 2017. Results were presented in the "Polar Coding in Wireless Communications: Theory and Implementation" Worksho

    Rate-Flexible Fast Polar Decoders

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    Polar codes have gained extensive attention during the past few years and recently they have been selected for the next generation of wireless communications standards (5G). Successive-cancellation-based (SC-based) decoders, such as SC list (SCL) and SC flip (SCF), provide a reasonable error performance for polar codes at the cost of low decoding speed. Fast SC-based decoders, such as Fast-SSC, Fast-SSCL, and Fast-SSCF, identify the special constituent codes in a polar code graph off-line, produce a list of operations, store the list in memory, and feed the list to the decoder to decode the constituent codes in order efficiently, thus increasing the decoding speed. However, the list of operations is dependent on the code rate and as the rate changes, a new list is produced, making fast SC-based decoders not rate-flexible. In this paper, we propose a completely rate-flexible fast SC-based decoder by creating the list of operations directly in hardware, with low implementation complexity. We further propose a hardware architecture implementing the proposed method and show that the area occupation of the rate-flexible fast SC-based decoder in this paper is only 38%38\% of the total area of the memory-based base-line decoder when 5G code rates are supported
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