电子与信息学报
電子與信息學報
전자여신식학보
JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY
2014年
11期
2640-2645
,共6页
段琳琳%王忠勇%王玮%高向川%肖岩
段琳琳%王忠勇%王瑋%高嚮川%肖巖
단림림%왕충용%왕위%고향천%초암
低密度奇偶校验迭代译码算法%差分映射机制%因子图变换%自适应归一化系数
低密度奇偶校驗迭代譯碼算法%差分映射機製%因子圖變換%自適應歸一化繫數
저밀도기우교험질대역마산법%차분영사궤제%인자도변환%자괄응귀일화계수
LDPC iterative decoding algorithm%Difference-Map (DM) strategy%Transforming factor graph%Adaptive normalized factor
针对中短码长的低密度奇偶校验规则码(Low Density Parity Check, LDPC)规则码,该文采用消息更新规则改进和因子图变换方法,提出一种低复杂度差分迭代译码算法。在置信传播算法的基础上,仅当变量节点的消息值振荡时引入差分映射策略,得出一种选择性的置信差分规则,自适应地调整校验节点消息的归一化系数,提高译码性能。同时,采用展开校验节点的图变换方法,将计算复杂度从随节点度分布指数性增长降至线性增长。分别在高斯白噪声信道和瑞利衰落信道下进行仿真实验,结果表明该算法和基于图变换的其他低复杂度译码算法相比,性能优越且复杂度低,和对数似然比的置信传播算法(LLR-BP)相比,高信噪比区域内的性能优异,低信噪比区域内的计算复杂度明显降低。
針對中短碼長的低密度奇偶校驗規則碼(Low Density Parity Check, LDPC)規則碼,該文採用消息更新規則改進和因子圖變換方法,提齣一種低複雜度差分迭代譯碼算法。在置信傳播算法的基礎上,僅噹變量節點的消息值振盪時引入差分映射策略,得齣一種選擇性的置信差分規則,自適應地調整校驗節點消息的歸一化繫數,提高譯碼性能。同時,採用展開校驗節點的圖變換方法,將計算複雜度從隨節點度分佈指數性增長降至線性增長。分彆在高斯白譟聲信道和瑞利衰落信道下進行倣真實驗,結果錶明該算法和基于圖變換的其他低複雜度譯碼算法相比,性能優越且複雜度低,和對數似然比的置信傳播算法(LLR-BP)相比,高信譟比區域內的性能優異,低信譟比區域內的計算複雜度明顯降低。
침대중단마장적저밀도기우교험규칙마(Low Density Parity Check, LDPC)규칙마,해문채용소식경신규칙개진화인자도변환방법,제출일충저복잡도차분질대역마산법。재치신전파산법적기출상,부당변량절점적소식치진탕시인입차분영사책략,득출일충선택성적치신차분규칙,자괄응지조정교험절점소식적귀일화계수,제고역마성능。동시,채용전개교험절점적도변환방법,장계산복잡도종수절점도분포지수성증장강지선성증장。분별재고사백조성신도화서리쇠락신도하진행방진실험,결과표명해산법화기우도변환적기타저복잡도역마산법상비,성능우월차복잡도저,화대수사연비적치신전파산법(LLR-BP)상비,고신조비구역내적성능우이,저신조비구역내적계산복잡도명현강저。
In this paper, an adaptive belief difference-map propagation algorithm with low complexity is proposed for short and middle length LDPC regular codes by modifying message update rules and transforming factor graph. To improve decoding performance, a new selective belief propagation difference-map message update rule is introduced by borrowing the difference-map strategy for variable node messages oscillation, and the normalized factor is adjusted adaptively. Meanwhile, the computational complexity exponential in the degree of check node is decreased into linear in degree by opening the check node. The simulation results illustrate that the proposed algorithm has better performance and lower complexity than other iterative decoding algorithms based on the modified factor graphs. Compared to the LLR-BP, it better performance at high Eb/N0 and the computational complexity is apparently downgraded at low Eb/N0.