东南大学学报(自然科学版)
東南大學學報(自然科學版)
동남대학학보(자연과학판)
JOURNAL OF SOUTHEAST UNIVERSITY
2009年
5期
884-888
,共5页
高星%张萌%戴志生%汤佳健%徐勐
高星%張萌%戴誌生%湯佳健%徐勐
고성%장맹%대지생%탕가건%서맹
置信传播译码算法%归一化译码算法%偏移译码算法%最小均方误差准则
置信傳播譯碼算法%歸一化譯碼算法%偏移譯碼算法%最小均方誤差準則
치신전파역마산법%귀일화역마산법%편이역마산법%최소균방오차준칙
belief propagation decoding algorithm%normalized decoding algorithm%offset decoding algorithm%minimum mean square error rule
为了降低LDPC码译码算法的复杂性并提高译码性能,针对传统的最小和译码算法的性能缺陷,提出一种改进型最小和译码算法.在最小均方误差准则下,该改进型译码算法充分利用了归一化译码算法和偏移译码算法的优点,以逼近置信传播译码算法.最后将LDPC码的改进型最小和译码算法应用于MIMO-OFDM系统中以降低载波干扰.仿真结果表明,若MIMO-OFDM系统要求的误码率为10~(-5),改进型最小和译码算法的编码增益比传统的最小和译码算法高出0.5 dB,比归一化译码算法和偏移译码算法分别高出0.3和0.2 dB,与置信传播译码算法仅差0.15dB.另外,改进型最小和译码算法也具有低的硬件复杂度.
為瞭降低LDPC碼譯碼算法的複雜性併提高譯碼性能,針對傳統的最小和譯碼算法的性能缺陷,提齣一種改進型最小和譯碼算法.在最小均方誤差準則下,該改進型譯碼算法充分利用瞭歸一化譯碼算法和偏移譯碼算法的優點,以逼近置信傳播譯碼算法.最後將LDPC碼的改進型最小和譯碼算法應用于MIMO-OFDM繫統中以降低載波榦擾.倣真結果錶明,若MIMO-OFDM繫統要求的誤碼率為10~(-5),改進型最小和譯碼算法的編碼增益比傳統的最小和譯碼算法高齣0.5 dB,比歸一化譯碼算法和偏移譯碼算法分彆高齣0.3和0.2 dB,與置信傳播譯碼算法僅差0.15dB.另外,改進型最小和譯碼算法也具有低的硬件複雜度.
위료강저LDPC마역마산법적복잡성병제고역마성능,침대전통적최소화역마산법적성능결함,제출일충개진형최소화역마산법.재최소균방오차준칙하,해개진형역마산법충분이용료귀일화역마산법화편이역마산법적우점,이핍근치신전파역마산법.최후장LDPC마적개진형최소화역마산법응용우MIMO-OFDM계통중이강저재파간우.방진결과표명,약MIMO-OFDM계통요구적오마솔위10~(-5),개진형최소화역마산법적편마증익비전통적최소화역마산법고출0.5 dB,비귀일화역마산법화편이역마산법분별고출0.3화0.2 dB,여치신전파역마산법부차0.15dB.령외,개진형최소화역마산법야구유저적경건복잡도.
To reduce the complexity and improve performance of decoding algorithm for LDPC(low density parity check) codes, a modified min-sum algorithm is proposed to make up the performance drawback of traditional min-sum algorithm. Based on minimum mean square error rule, the modified min-sum algorithm makes full use of advantages of normalized decoding algorithm and offset decoding algorithm to approach to belief propagation decoding algorithm. The modified min-sum algorithm is applied in MIMO-OFDM (multiple input multiple output-orthogonal frequency division multiplexing) system to reduce intercarrier interference. Simulation results show that when MIMO-OFDM system asks BER(bit error ratio) to be 10 ~(-5), the encoding gain of modified min-sum decoding algorithm can be 0. 5 dB better than traditional min-sum decoding algorithm, 0. 3 and 0. 2 dB better than normalized decoding algorithm and offset decoding algorithm respectively, and only 0. 15 dB worse than belief propagation decoding algorithm. In addition, the modified min-sum algorithm has low hardware complexity.