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        5G抽頭延遲模型中極化譯碼后處理方案

        2023-12-31 00:00:00沈園園馬秀榮單云龍
        計算機應用研究 2023年8期

        摘 要:考慮5G協(xié)議中的抽頭延遲信道模型,針對分段循環(huán)冗余比特自適應(SCAD-SCL)極化譯碼算法未考慮信噪比對接收序列對數(shù)似然比影響的問題,提出SCAD-SCL的后處理(PSCAD-SCL)譯碼算法。通過仿真確定用于提高可靠性設定的常數(shù)和不可靠對數(shù)似然比的數(shù)目,翻轉(zhuǎn)并適當放大不可靠的對數(shù)似然比值,從而提高誤比特率性能。仿真結(jié)果表明,PSCAD-SCL的誤比特率在信噪比1~3 dB優(yōu)于原有SCAD-SCL譯碼算法。在誤比特率為10-4時PSCAD-SCL較SCAD-SCL算法性能提升了約0.3 dB,提出算法能夠提升5G傳輸性能。

        關鍵詞:5G; 抽頭延遲信道模型; 極化碼; 分段循環(huán)冗余; 后處理

        中圖分類號:TP911.22文獻標志碼:A

        文章編號:1001-3695(2023)08-034-2457-04

        doi:10.19734/j.issn.1001-3695.2022.10.0633

        Post-processing scheme for polar decoding in 5G tap delay model

        Shen Yuanyuan Ma Xiurong Shan Yunlong

        (1.School of Integrated Circuit Science amp; Engineering, Tianjin University of Technology, Tianjin 300384, China; 2.Engineering Research Center of Communication Devices amp; Technology, Ministry of Education, Tianjin 300384, China)

        Abstract:Considering the tap delay channel model in 5G protocol, and aiming the problem that the segmented cyclic redundancy bit adaptive (SCAD-SCL) polarization decoding algorithm does not consider the influence of SNR on the log-likelihood ratio of the received sequence, this paper proposed the post-processing(PSCAD-SCL) decoding algorithm for SCAD-SCL. The algorithm determined the number of constant and unreliable log-likelihood ratio used to improve the reliability setting through simulation, and fliped and appropriately enlarged the unreliable log-likelihood ratio to improve the bit error rate performance. The simulation results show that the bit error rate of PSCAD-SCL is better than the original SCAD-SCL decoding algorithm in the signal-to-noise ratio of 1~3 dB. When the bit error rate is 10-4, the performance of PSCAD-SCL algorithm is about 0.3 dB higher than that of the SCAD-SCL algorithm. The proposed algorithm can improve 5G transmission performance.

        Key words:5G; tapped delay channel model; polar code; segmented cyclic redundancy check; post-processing

        2016年11月,3GPP組織將極化碼定為第五代移動通信(5G)系統(tǒng)增強移動寬帶場景中控制信道的編碼方案[1]。極化碼[2]是一種在無限碼長的情況下經(jīng)理論證明可以達到信道容量的信道編碼。但在較短的碼長時,極化碼糾錯性能會下降。為提升譯碼性能,學者們提出了多種譯碼算法。

        極化碼的發(fā)明者Arikan教授[3]首先提出了連續(xù)抵消(successive cancellation,SC)極化譯碼算法,該算法以深度優(yōu)先為原則,輸出一條譯碼路徑,在碼長較長時譯碼性能良好,但在碼長較短時,信道極化不完整且譯碼時僅存儲1條譯碼路徑,正確譯碼路徑被保留的概率較低,譯碼性能較差。Tal等人[4]提出了列表大小為L的連續(xù)抵消列表(successive cancellation list,SCL)極化譯碼算法,該算法以廣度優(yōu)先為原則,輸出L條譯碼路徑,選擇最優(yōu)解完成譯碼,譯碼性能有很大提升,但保留的L條譯碼路徑可能不包含正確路徑。Niu等人[5]提出了循環(huán)冗余比特輔助的連續(xù)抵消列表(CRC-aided SCL,CA-SCL)譯碼算法,進一步提高了譯碼性能,但譯碼延遲較高。Li等人[6]提出了基于CA-SCL的自適應SCL譯碼算法(adaptive SCL,AD-SCL),自適應列表大小L,可在信噪比高時降低譯碼延遲,但在信噪比低時需要較多次重新譯碼,譯碼延遲較高。

        近年,王瓊等人[7]提出了分段循環(huán)冗余比特輔助自適應(segmented-CRC adaptive SCL,SCAD-SCL)譯碼算法,在信噪比低時譯碼延時較低,誤比特率與AD-SCL算法相近。為提高誤比特率性能,受基于CA-SCL后處理算法[8]啟發(fā),本文提出了分段循環(huán)冗余比特自適應極化譯碼的后處理(post-proces-sing segmented-CRC ADaptive SCL,PSCAD-SCL)算法,該算法對傳輸中某些不可靠的接收似然比值進行處理完成重新譯碼,得到了更好的譯碼性能。

        1 極化碼基本原理

        極化碼基于信道極化現(xiàn)象[9],將N個獨立信道遞歸計算成N個極化信道,劃分為信道容量趨于1的可靠信道和信道容量趨于0的不可靠信道。

        1.1 5G極化碼編碼

        1.2 PSCAD-SCL譯碼算法

        2 5G抽頭延遲模型及協(xié)議實現(xiàn)

        2.1 抽頭延遲模型

        2.2 5G協(xié)議中的抽頭延遲模型

        3 仿真分析

        3.1 仿真參數(shù)設置

        3.2 仿真性能分析

        3.3 結(jié)果分析

        4 結(jié)束語

        本文考慮5G協(xié)議中的抽頭延遲信道模型[15],改善SCAD-SCL譯碼算法性能,提出PSCAD-SCL算法。優(yōu)化接收對數(shù)似然比值進行重新譯碼,降低信道噪聲引起錯誤的概率。仿真結(jié)果表明,PSCAD-SCL與原始SCAD-SCL算法相比,誤比特率性能提升較大,復雜度增加較小。未來可繼續(xù)研究其他譯碼算法,使用后處理思想提升其性能。

        參考文獻:

        [1]吳湛擊, 吳熹. 5G控制信道極化碼的研究[J]. 北京郵電大學學報, 2018,41(4): 110-118. (Wu Zhanji, Wu Xi. Research on 5G control channel polarization code[J]. Journal of Beijing University of Posts and Telecommunications, 2018,41(4): 110-118.)

        [2]吳荻. 基于極化碼的5G-NR通信系統(tǒng)信道編碼技術研究[J]. 新一代信息技術, 2022,5(1): 31-34. (Wu Di. Research on channel coding technology of 5G-NR communication system based on polarization code[J]. New Generation Information Technology, 2022,5(1): 31-34.)

        [3]Arikan E. Channel polarization: a method for constructing capacity-achieving codes for symmetric binary-input memoryless channels[J]. IEEE Trans on Information Theory, 2009,55(7): 3051-3073.

        [4]Tal I, Vardy A. List decoding of polar codes[J]. IEEE Trans on Information Theory, 2012,61(5): 2213-2226.

        [5]Niu Kai, Chen Kai. CRC-aided decoding of polar codes[J]. IEEE Communications Letters, 2012, 16(10): 1668-1671.

        [6]Li Bin, Shen Hui, Tse D. An adaptive successive cancellation list decoder for polar codes with cyclic redundancy check[J]. IEEE Communications Letters, 2012,16(12): 2044-2047.

        [7]王瓊, 羅亞潔, 李思舫. 基于分段循環(huán)冗余校驗的極化碼自適應連續(xù)取消列表譯碼算法[J]. 電子與信息學報, 2019,41(7): 1572-1578. (Wang Qiong, Luo Yajie, Li Sifang. Adaptive conti-nuous de-listing decoding algorithm for polarization codes based on piecewise cyclic redundancy check[J]. Journal of Electronics and Information, 2019,41(7): 1572-1578.)

        [8]Wang C H, Pan Yihan, Lin Yuheng, et al. Post-processing for CRC-aided successive cancellation list decoding of polar codes[J]. IEEE Communications Letters, 2020,24(7): 1395-1399.

        [9]Tian Kuangda, Fazeli A, Vardy A. Polar coding for channels with deletions[J]. IEEE Trans on Information Theory, 2021,67(11): 7081-7095.

        [10]Technical Specification Group Radio Access Network. 3GPP TS38.212, Multiplexing and channel coding[S/OL]. (2023-03-30). https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=3214.

        [11]魏貴明, 張翔, 郭宇航, 等. 5G信道建模與性能測試方法[J]. 電信科學, 2021,37(2): 13-21. (Wei Guiming, Zhang Xiang, Guo Yuhang, et al. 5G channel modeling and performance test me-thod[J]. Telecommunication Science, 2021,37(2): 13-21.)

        [12]Technical Specification Group Radio Access Network.3GPP TS38.901, Study on channel model for frequencies from 0.5 to 100 GHz[S/OL]. (2022-03-31). https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=3173.

        [13]Patzold M, Wang Chengxiang, Hogstad B. Two new sum-of-sinusoids-based methods for the efficient generation of multiple uncorrela-ted Rayleigh fading waveforms[J]. IEEE Trans on Wireless Communications, 2009,8(6): 3122-3131.

        [14]陳發(fā)堂, 趙昊明, 石丹, 等. 低時間復雜度的極化碼譯碼算法[J]. 重慶郵電大學學報:自然科學版, 2021,33(4): 571-576. (Chen Fatang, Zhao Haoming, Shi Dan, et al. Decoding algorithm of polarization code with low time complexity[J]. Journal of Chongqing University of Posts and Telecommunications: Natural Science Edition, 2021, 33(4): 571-576.)

        [15]邢冰倩, 韋再雪. 基于3GPP TR38.901信道模型的時變信道建模與仿真[J]. 北京郵電大學學報, 2021,44(1): 45-51. (Xing Bingqian, Wei Zaixue. Time-varying channel modeling and simulation based on 3GPP TR38.901 channel model[J].Journal of Beijing University of Posts and Telecommunications, 2021,44(1):45-51.)

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