強(qiáng)干擾環(huán)境下無速率隨機(jī)碼編譯碼方案及其性能分析
doi: 10.11999/JEIT230879
-
1.
中山大學(xué)計(jì)算機(jī)學(xué)院 廣州 510006
-
2.
中山大學(xué)廣東省信息安全重點(diǎn)實(shí)驗(yàn)室 廣州 510006
Rateless Random Coding Scheme and Performance Analysis in Strong Interference Environments
-
1.
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China
-
2.
Guangdong Key Laboratory of Information Security Technology, Sun Yat-sen University, Guangzhou 510006, China
-
摘要: 面向強(qiáng)干擾通信環(huán)境,區(qū)別于傳統(tǒng)的無速率Luby變換(LT)碼,該文提出一種基于伯努利隨機(jī)構(gòu)造的無速率編碼方案,并在接收端采用高效的局部約束順序統(tǒng)計(jì)量譯碼(LC-OSD)算法進(jìn)行譯碼,從而有效對抗強(qiáng)干擾噪聲,實(shí)現(xiàn)自適應(yīng)超高可靠傳輸。為降低收發(fā)端通信資源消耗,提出了3個(gè)有效譯碼準(zhǔn)則:(1) 基于隨機(jī)碼并集(RCU)界提出的啟動(dòng)準(zhǔn)則,當(dāng)接收符號數(shù)大于由RCU得到的閾值時(shí)才啟動(dòng)譯碼;(2) 基于軟重量提出的早停準(zhǔn)則,在譯碼過程中軟重量超過一個(gè)預(yù)設(shè)的閾值則提前終止譯碼;(3) 基于碼字與硬判決序列比較提出的跳過準(zhǔn)則,當(dāng)新接收序列的硬判決滿足重編碼校驗(yàn)時(shí)跳過當(dāng)前譯碼。仿真結(jié)果顯示,在塊刪除與加性噪聲混合信道下,無速率隨機(jī)碼的性能顯著優(yōu)于LT碼,且因無速率碼具備自適應(yīng)信道質(zhì)量的能力,其性能同樣顯著優(yōu)于固定速率碼。仿真結(jié)果還顯示了提出的啟動(dòng)、早停和跳過準(zhǔn)則能夠有效降低收發(fā)端的傳輸資源消耗和計(jì)算復(fù)雜度。
-
關(guān)鍵詞:
- 順序統(tǒng)計(jì)量譯碼 /
- 隨機(jī)碼 /
- 無速率碼 /
- 強(qiáng)干擾信道
Abstract: A rateless coding scheme based on Bernoulli random construction is proposed for strong interference communication environments, which differs from the traditional Luby Transform (LT) rateless codes. The scheme utilizes the Locally Constrained Ordered Statistic Decoding (LC-OSD) algorithm at the receiver to effectively combat strong interference noise and achieve adaptive and ultra-reliable transmission. To reduce the communication resource consumption at both the transmitter and receiver, three effective decoding criteria are proposed: (1) a startup criterion based on the Random Code Union (RCU) bound, which initiates decoding only when the number of received symbols exceeds a threshold derived from RCU; (2) an early stopping criterion based on soft weights, which stops decoding early when the soft weights exceed a preset threshold; and (3) a skipping criterion based on the comparison between the codeword and the hard decision sequence, which skips the current decoding process when the hard decision of the newly received sequence satisfies the recoding check. Simulation results show that the performance of the rateless random codes is significantly better than that of LT codes in a channel with block erasures and additive noise. Moreover, due to the adaptive to channel quality capability of rateless codes, their performance is also significantly better than fixed-rate codes. The simulation results also show that the proposed startup, early stopping, and skipping criteria effectively reduce transmission resources and computational complexity for both the sender and receiver.-
Key words:
- Ordered statistic decoding /
- Random code /
- Rateless code /
- Strong interference channel
-
表 1 隨機(jī)碼并集限與實(shí)際仿真所需接收符號數(shù)對比
信噪比(dB) ${L_{{\text{RCU}}}}$ 實(shí)際仿真 1.0 150 151 1.5 135 137 2.0 128 126 2.5 120 118 3.0 110 110 下載: 導(dǎo)出CSV
-
[1] IMT-2030(6G)推進(jìn)組. 《6G典型場景和關(guān)鍵能力》白皮書[R]. 2022.IMT-2030 (6G) Propulsion Group. Typical scenarios and key capabilities of 6G white paper[R]. 2022. [2] 于全. 戰(zhàn)術(shù)通信理論與技術(shù)[M]. 北京: 人民郵電出版社, 2020.YU Quan. Communications in Tactical Environments: Theories and Technologies[M]. Beijing: Posts & Telecom Press, 2020. [3] BYERS J W, LUBY M, MITZENMACHER M, et al. A digital fountain approach to reliable distribution of bulk data[J]. ACM SIGCOMM Computer Communication Review, 1998, 28(4): 56–67. doi: 10.1145/285243.285258. [4] LUBY M. LT codes[C]. Proceedings of the 43rd Annual IEEE Symposium on Foundations of Computer Science, Vancouver, Canada, 2002: 271–271. doi: 10.1109/SFCS.2002.1181950. [5] SHOKROLLAHI A. Raptor codes[J]. IEEE Transactions on Information Theory, 2006, 52(6): 2551–2567. doi: 10.1109/TIT.2006.874390. [6] YANG Shenghao and YEUNG R W. Batched sparse codes[J]. IEEE Transactions on Information Theory, 2014, 60(9): 5322–5346. doi: 10.1109/TIT.2014.2334315. [7] CASSUTO Y and SHOKROLLAHI A. Online fountain codes with low overhead[J]. IEEE Transactions on Information Theory, 2015, 61(6): 3137–3149. doi: 10.1109/TIT.2015.2422697. [8] 姚渭箐, 易本順. 新型LT碼編譯碼方法及其在認(rèn)知無線電中的應(yīng)用[J]. 電子與信息學(xué)報(bào), 2019, 41(3): 571–579. doi: 10.11999/JEIT180427.YAO Weiqing and YI Benshun. A novel encoding and decoding method of LT codes and application to cognitive radio[J]. Journal of Electronics & Information Technology, 2019, 41(3): 571–579. doi: 10.11999/JEIT180427. [9] 宋鑫, 程乃平, 倪淑燕, 等. 采用定長節(jié)點(diǎn)分類窗口的低誤碼平臺(tái)LT編碼算法[J]. 通信學(xué)報(bào), 2021, 42(9): 31–42. doi: 10.11959/j.issn.1000-436x.2021155.SONG Xin, CHENG Naiping, NI Shuyan, et al. Low error floor LT coding algorithm by using fixed-length node classification window[J]. Journal on Communications, 2021, 42(9): 31–42. doi: 10.11959/j.issn.1000-436x.2021155. [10] 龔茂康. 中短長度LT碼的展開圖構(gòu)造方法[J]. 電子與信息學(xué)報(bào), 2009, 31(4): 885–888. doi: 10.3724/SP.J.1146.2008.00218.GONG Maokang. Unfolding graphs for constructing of short and moderate-length LT codes[J]. Journal of Electronics & Information Technology, 2009, 31(4): 885–888. doi: 10.3724/SP.J.1146.2008.00218. [11] FOSSORIER M P C and LIN Shu. Soft-decision decoding of linear block codes based on ordered statistics[J]. IEEE Transactions on Information Theory, 1995, 41(5): 1379–1396. doi: 10.1109/18.412683. [12] YUE Chentao, SHIRVANIMOGHADDAM M, LI Yonghui, et al. Segmentation-discarding ordered-statistic decoding for linear block codes[C]. Proceedings of 2019 IEEE Global Communications Conference, Waikoloa, America, 2019: 1–6. doi: 10.1109/GLOBECOM38437.2019.9014173. [13] YUE Chentao, SHIRVANIMOGHADDAM M, PARK G, et al. Linear-equation ordered-statistics decoding[J]. IEEE Transactions on Communications, 2022, 70(11): 7105–7123. doi: 10.1109/TCOMM.2022.3207206. [14] YUE Chentao, SHIRVANIMOGHADDAM M, PARK G, et al. Probability-based ordered-statistics decoding for short block codes[J]. IEEE Communications Letters, 2021, 25(6): 1791–1795. doi: 10.1109/LCOMM.2021.3058978. [15] WANG Yiwen, LIANG Jifan, and MA Xiao. Local constraint-based ordered statistics decoding for short block codes[C]. Proceedings of 2022 IEEE Information Theory Workshop, Mumbai, India, 2022: 107–112. doi: 10.1109/ITW54588.2022.9965916. [16] POLYANSKIY Y, POOR H V, and VERDú S. Channel coding rate in the finite blocklength regime[J]. IEEE Transactions on Information Theory, 2010, 56(5): 2307–2359. doi: 10.1109/TIT.2010.2043769. [17] FABREGAS A G I and TANG Qi. Coding in the block-erasure channel[C]. Proceedings of 2006 Australian Communications Theory Workshop, Perth, Australia, 2006: 19–24. doi: 10.1109/AUSCTW.2006.1625249. [18] LIANG Jifan, WANG Yiwen, CAI Suihua, et al. A low-complexity ordered statistic decoding of short block codes[J]. IEEE Communications Letters, 2023, 27(2): 400–403. doi: 10.1109/LCOMM.2022.3222819. [19] SESHADRI N and SUNDBERG C E W. List Viterbi decoding algorithms with applications[J]. IEEE Transactions on Communications, 1994, 42(234): 313–323. doi: 10.1109/TCOMM.1994.577040. -