为了进一步提高多级单元(multi-level-cell,MLC)闪存的耐久度和可靠性,提出了一种MLC闪存信道中基于互信息量(mutual information,MI)异构的polar码优化方法.该方法利用对数似然比(log-likelihood ratio,LLR)分布在MLC闪存信道和AWGN(additivewhite Gaussian noise)信道中的差异性,以MI重新拟合LLR分布,得到在闪存信道下等效的标准方差,从而进行高密度存储系统中的polar码优化设计.随后,分析了不同的polar码构造法对多级存储单元的纠错性能影响,并与所提的构造方法进行比较.仿真结果表明该文优化方法优于AWGN信道下传统的构造方法,当编程/擦除(program-and-erase,PE)循环为21 000次时,与蒙特卡罗法相比其误码率(bit error rate,BER)性能提升2个数量级,且在BER为2 × 10-5时可增加6 800次的编程/擦除循环.
In order to further improve the durability and reliability of multi-level-cell (MLC) flash memory, a polar code optimization method based on mutual information (MI) heterogeneity in the MLC flash channel is proposed. By exploiting the differences of log-likelihood ratio (LLR) distribution between MLC flash channels and AWGN (additive white Gaussian noise) channels, and employing MI re-fitting for obeying Gaussian distribution in AWGN channels, the method obtains its equivalent variance of AWGN channels. Thereafter, the polar code optimization design in the high-density storage system is performed according to the obtained new variance. This paper also analyzes the effects of other different polar code construction methods on the error correction of multi-level memory cells, and compares them with the proposed construction method. Simulation results show that the optimization method is better than the traditional construction methods in AWGN channels. It improves bit error rate (BER) by more than 2 orders of magnitudes compared with Monte-Carlo method when program-and-erase (P/E) cycles is 21 000, and it can increase the lifetime of MLC flash memory up to 6 800 P/E cycles at the BER of 2×10-5.
[1] Kim K. Future memory technology:challenges and opportunities[J]. International Symposium on VLSI technology, Systems and Applications, 2008:5-9.
[2] Chen P P, Cai K, Zheng S. ATE-adaptive protograph LDPC codes for multi-level-cell (MLC) NAND flash memory[J]. IEEE Communications Letters, 2018, 22(6):1112-1115.
[3] Aikan E. Channel polarization:a method for constructing capacity-achieving codes for symmetric binary-input memoryless channels[J]. IEEE Transaction on Information Theory, 2009, 55(7):3051-3073.
[4] Song H C, Zhang C, Zhang S Q, et al. Polar code-based error correction code scheme for NAND flash memory applications[J]. International Conference on Wireless Communications & Signal Processing, Yangzhou, China, 2016:1-5.
[5] Song H C, Chien J F, Jia S Z, et al. Polar-coded forward error correction for MLC NAND flash memory[J]. Science China (Information Sciences), 2018, 61(10):224-239.
[6] 卞建慧,赵生妹,孔令军. MLC型NAND闪存中Polar码的优化设计[J].南京邮电大学学报(自然科学版),2018, 38(3):40-46. Bian J H, Zhao S M, Kong L J. Optimal design of polar codes in MLC NAND flash memory[J]. Journal of Nanjing University of Posts and Telecommunications (Natural Science Edition), 2018, 38(3):40-46.(in Chinese)
[7] Li Y, Alhussien H, Haratsch E F, et al. A study of polar codes for MLC NAND flash memories[C]//International Conference on Computing, Networking and Communications, Garden Grove, CA, USA, 2015:608-612.
[8] Arikan E. A performance comparison of polar codes and Reed-Muller codes[J]. IEEE Communications Letters, 2008, 12(6):447-449.
[9] Li Q, Jiang A X, Haratsch E F. Noise modeling and capacity analysis for NAND flash memories[J]. IEEE International Symposium on Information Theory, Honolulu, HI, USA, 2014:2262-2266.
[10] 张璇,周乐,侯爱华.一种适用于MLC闪存的CCI噪声均衡化算法[J].计算机科学,2018, 45(S1):541-544. Zhang X, Zhou L, Hou A H. CCI noise equalization algorithm for MLC flash memory[J]. Computer Science, 2018, 45(S1):541-544.(in Chinese)
[11] Dong G Q, Li S, Zhang T. Using data post compensation and predistortion to tolerate cell-tocell interference in MLC NAND flash memory[J]. IEEE Transactions on Circuits and Systems I, 2010, 57(10):2718-2728.
[12] Compagnoni C M, Ghidotti M, Lacaita A L, et al. Random telegraph noise effect on the programmed threshold-voltage distribution of flash memories[J]. IEEE Electron Device Letters, 2009, 30(9):984-986.
[13] 李坤,吴绍华,高翔,等.基于凿孔的系统极化码编码协作[J].应用科学学报,2017, 35(2):139-148. Li K, Wu S H, Gao X, et al. Systematic polar coded cooperation based on puncturing[J]. Journal of Applied Sciences, 2017, 35(2):139-148.(in Chinese)
[14] Chen K, Li B, Shen H, et al. Reduce the complexity of list decoding of polar codes by treepruning[J]. IEEE Communications Letters, 2016, 20(2):204-207.
[15] Aslam C A, Guan Y L, Cai K. Read and write voltage signal optimization for multi-level-cell (MLC) NAND Flash memory[J]. IEEE Transaction on Communications, 2016, 64(4):1613-1623.