Towards quantum belief propagation for LDPC decoding in wireless networks
Towards quantum belief propagation for LDPC decoding in wireless networks
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DOI：
10.1145/3372224.3419207
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发表时间：
2020-07
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通讯作者：
Srikar Kasi;K. Jamieson
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作者：
Srikar Kasi;K. Jamieson
我们提出了量子置信传播（QBP），基于量子退火（QA）的低密度奇偶校验（LDPC）错误控制码的解码器设计，它已经在Wi-Fi，卫星通信，移动的蜂窝系统和数据存储系统中找到了许多有用的应用。QBP将LDPC解码简化为离散优化问题，然后将简化的设计嵌入到量子退火硬件中。QBP的嵌入式设计可以在具有2，048个量子位的真实的最先进的QA硬件上支持块长度高达420位的LDPC码。我们评估性能的真实的量子退火硬件，进行各种参数设置的灵敏度分析。在高斯噪声无线信道中，信噪比为9dB时，20 μ s内误码率为10- 8，50 μs内误帧率为10- 6。进一步的实验测量了真实无线信道的性能，在SNR 15-20 dB时，需要30 μs才能实现1，500字节的99.99%帧传输速率。与基于FPGA的软置信传播LDPC译码器相比，QBP译码器在信噪比降低2.5- 3.5dB的情况下，误码率达到10- 8，误帧率达到10- 6，性能得到了改善。就局限性而言，QBP目前无法实现实际的协议大小（例如，Wi-Fi、WiMax）LDPC码。我们在这项工作中的进一步研究提出了未来的成本，吞吐量和QA硬件的趋势考虑。
We present Quantum Belief Propagation (QBP), a Quantum Annealing (QA) based decoder design for Low Density Parity Check (LDPC) error control codes, which have found many useful applications in Wi-Fi, satellite communications, mobile cellular systems, and data storage systems. QBP reduces the LDPC decoding to a discrete optimization problem, then embeds that reduced design onto quantum annealing hardware. QBP's embedding design can support LDPC codes of block length up to 420 bits on real state-of-the-art QA hardware with 2,048 qubits. We evaluate performance on real quantum annealer hardware, performing sensitivity analyses on a variety of parameter settings. Our design achieves a bit error rate of 10--8 in 20 μs and a 1,500 byte frame error rate of 10--6 in 50 μs at SNR 9 dB over a Gaussian noise wireless channel. Further experiments measure performance over real-world wireless channels, requiring 30 μs to achieve a 1,500 byte 99.99% frame delivery rate at SNR 15-20 dB. QBP achieves a performance improvement over an FPGA based soft belief propagation LDPC decoder, by reaching a bit error rate of 10--8 and a frame error rate of 10--6 at an SNR 2.5--3.5 dB lower. In terms of limitations, QBP currently cannot realize practical protocol-sized (e.g., Wi-Fi, WiMax) LDPC codes on current QA processors. Our further studies in this work present future cost, throughput, and QA hardware trend considerations.