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基于本地人工信道的新型OFDM信道估計方法

2014-09-17 17:32張家輝解永生李寶清
現(xiàn)代電子技術(shù) 2014年17期
關(guān)鍵詞:奇異值分解

張家輝 解永生 李寶清

摘 要: 介紹了一種新穎的基于本地人工信道的信道估計方法,并對該方法進行進一步的奇異值分解和簡化,使其具有較少的存儲量和計算量,具有很大的實際應(yīng)用價值。對相關(guān)方法進行了仿真和比較,在誤比特率性能上與傳統(tǒng)線性最小均方誤差估計相差小于1 dB。

關(guān)鍵詞: OFDM; 信道估計; 本地人工信道; 奇異值分解

中圖分類號: TN92?34 文獻標(biāo)識碼: A 文章編號: 1004?373X(2014)17?0013?03

Abstract: A novel channel estimation method based on local artificial channel is introduced in this paper. The singular value decomposition and simplification of the method were conducted to make it have small storage content, calculated amount and high application value. The relevant methods were simulated and compared with the novel one. The results shown that its bit error rate is only 1 dB less than that of the traditional linear minimum mean?squared error estimation method.

Keyword: OFDM; channel estimation; local artificial channel; singular value decomposition

0 引 言

正交頻分復(fù)用(OFDM)技術(shù)由于具有較高的頻譜利用率、對抗多徑干擾效果好、較高的數(shù)據(jù)速率等優(yōu)點,廣泛地應(yīng)用到無線通信系統(tǒng)中。因為無線信道具有多徑和時變特性,為了降低多徑和衰弱對系統(tǒng)性能的影響,需要在接收端利用信道估計來補償信道的變化。

OFDM信道估計是一個古老的話題,但是對于它的研究一直沒有停止,有對估計算法的研究,如文獻[1]提出的基于本地人工信道的估計方法;還有設(shè)計合適導(dǎo)頻序列來對抗頻率偏移的信道估計[2];有針對MIMO系統(tǒng)的遞歸更新的信道估計方法[3];有對導(dǎo)頻擺放方法的研究[4];有基于二維擴展的對時域快變信道的估計[5];當(dāng)然也有對現(xiàn)有算法的改進的文章[6?7]。本文主要針對基于導(dǎo)頻的信道估計算法的研究,這類算法是利用在數(shù)據(jù)流中插入一定數(shù)量的已知數(shù)據(jù)(導(dǎo)頻)進行信道估計,傳統(tǒng)估計方法包括最小二乘估計(LS)和線性最小均方誤差估計(LMMSE),兩種方法在性能和復(fù)雜度上各有利弊。本文介紹了這兩種基于導(dǎo)頻的OFDM信道估計基本方法,以降低LMMSE復(fù)雜度為目標(biāo),引入一種基于本地人工信道的估計方法來減少LMMSE方法中的自相關(guān)矩陣問題,并對此改進方法進行進一步的奇異值分解解決矩陣求逆的問題,使本文的方法不但具有很少的計算量而且在性能上與傳統(tǒng)LMMSE方法相差不到1 dB,是一種具有實際應(yīng)用價值的OFDM信道估計方法。

需要在接收端存儲人工信道[G(N×1)、]部分的奇異值([P]個)和奇異向量組成的矩陣[(N×P),]并在接收端增加一個估計SNR的模塊。這樣就把普通的LMMSE簡化成為只需要進行簡單的相乘相加的運算,而舍去了自相關(guān)矩陣的計算和復(fù)雜的矩陣求逆運算,而這僅僅需要增加一小部分的數(shù)據(jù)存儲。

3 仿 真

用Matlab進行仿真,接收端只考慮信道估計的性能,不計其他糾錯編碼的影響。子載波數(shù)[N=]1 024,CP長度為[N4]256,采樣率為10 MHz,采用塊狀導(dǎo)頻結(jié)構(gòu)。實際信道采用COST 207標(biāo)準(zhǔn)的典型城區(qū)Ⅰ多徑信道[10],多普勒頻移為25 Hz,本地人工信道多徑延時滿足均勻分布,功率延時譜滿足負(fù)指數(shù)分布,應(yīng)用與中低速的圖傳系統(tǒng)。

圖4顯示了幾種AC(Artificial Channel)方法的性能,其中Delay Sufficient表示的是按照文中的要求構(gòu)造本地人工信道,即本地人工信道的[τmax]設(shè)為CP的長度(遠(yuǎn)大于實際信道);而Delay Insufficient1和Delay Insufficient2都與文中的要求有一定的差距,情況1的本地人工信道的[τmax]略小于實際信道的[τmax,]而情況2的本地人工信道的[τmax]為實際信道的[τmax]的一半??梢钥闯觯?dāng)本地人工信道設(shè)置合理時,它的性能基本跟實際的LMMSE算法接近,相同BER信噪比差距小于1 dB;而當(dāng)本地人工信道設(shè)置不合理時,性能會有很大的差距,如情況1在10 dB之后開始逐漸地變差,16 dB之后甚至比LS算法還要差;而情況2由于人工信道設(shè)置得更不合理,導(dǎo)致從8 dB開始就比LS算法差了。

圖5顯示AC和SVD結(jié)合后的性能,其中AC SVD1表示的是按文中要求進行取舍奇異值,即取了最大的前CP個奇異值;而AC SVD2只取了最大的前CP/2奇異值。從圖中可以看出,SVD1與普通的AC基本重合,可以認(rèn)為基本沒有性能上的損失,而SVD2因為少取了一些奇異值,丟棄了一些有用信息而導(dǎo)致性能下降,尤其是在信噪比10 dB之后性能迅速下降,16 dB之后甚至比LS算法的性能還要差。

4 結(jié) 論

通過以上仿真可以看出,本文提出的AC+SVD的方法不但減少了求自相關(guān)矩陣、矩陣求逆在內(nèi)的大量計算,只需要進行簡單的乘法和加法,而且在性能上跟傳統(tǒng)的LMMSE算法差距在1 dB以內(nèi),所以該方法是一種具有實際應(yīng)用價值的、高性能的OFDM信道估計方法。

參考文獻

[1] SAVAUX Vincent, SKRZYPCZAK Alexandre, LOUET Yves, et al. Near LMMSE channel estimation preformance with artificial channel at receiver for OFDM systems [C]// 13th International Workshop on Signal Processing in Wireless Communications. [S.l.]: [s.n.], 2012: 545?549.

[2] OLIVER J, ARAVIND R, PRABHU K M M. Improved least squares channel estimation for orthogonal frequency division multiplexing [J]. IET Signal Processing, 2012, l.6: 45?53.

[3] HESKETH Thomas, DE LAMARE Rodrigo C, WALES Stephen. Adaptive MMSE channel estimation algorithms for MIMO system [EB/OL]. [2012?11?26]. www.ymcn.org/d?9bs1.html.

[4] Qun Yu and Ronglin Li.”Research on Pilot Pattern Design of Channel Estimation”Journal of Automation and Control Engineering,Vol.1,No.2,March 2013.

[5] PENA?CAMPOS F, CARRASCO?ALVAREZ R, LONGORIA?GANDARA O, et al. Estimation of fast time?varying channels in OFDM systems using two?dimensional prolate [J]. IEEE Transaction on wireless communications, 2013, 12(2): 898?907.

[6] ZHOU Wen, LAM Wong Hing. A fast LMMSE channel estimation method for OFDM systems [D]. Hong Kong, China: Department of Electrical and Electronics Engineering, The University of Hong Kong, 2009.

[7] MINN H, BHARGAVA V K. An investigation into time?domain approach for OFDM channel estimation [J]. IEEE Transactions on Broadcasting, 2009, 46(4): 240?248.

[8] EDFORDS O, SANDELL M, VAN DE BEEK J J, et al. OFDM channel estimation by singular value decomposition [J]. IEEE Transactions on Communications, 1998, 46(7): 923?927.

[9] VAN DE BEEK J J, EDFORS O, SANDELL M, et al. On Channel Estimation in OFDM Systems [C]// Proceedings of IEEE conference on Vehicular Technology. Chicago, USA: IEEE, 1995, 2: 815?819.

[10] 楊大成.移動傳播環(huán)境[M].北京:機械工業(yè)出版社,2003.

參考文獻

[1] SAVAUX Vincent, SKRZYPCZAK Alexandre, LOUET Yves, et al. Near LMMSE channel estimation preformance with artificial channel at receiver for OFDM systems [C]// 13th International Workshop on Signal Processing in Wireless Communications. [S.l.]: [s.n.], 2012: 545?549.

[2] OLIVER J, ARAVIND R, PRABHU K M M. Improved least squares channel estimation for orthogonal frequency division multiplexing [J]. IET Signal Processing, 2012, l.6: 45?53.

[3] HESKETH Thomas, DE LAMARE Rodrigo C, WALES Stephen. Adaptive MMSE channel estimation algorithms for MIMO system [EB/OL]. [2012?11?26]. www.ymcn.org/d?9bs1.html.

[4] Qun Yu and Ronglin Li.”Research on Pilot Pattern Design of Channel Estimation”Journal of Automation and Control Engineering,Vol.1,No.2,March 2013.

[5] PENA?CAMPOS F, CARRASCO?ALVAREZ R, LONGORIA?GANDARA O, et al. Estimation of fast time?varying channels in OFDM systems using two?dimensional prolate [J]. IEEE Transaction on wireless communications, 2013, 12(2): 898?907.

[6] ZHOU Wen, LAM Wong Hing. A fast LMMSE channel estimation method for OFDM systems [D]. Hong Kong, China: Department of Electrical and Electronics Engineering, The University of Hong Kong, 2009.

[7] MINN H, BHARGAVA V K. An investigation into time?domain approach for OFDM channel estimation [J]. IEEE Transactions on Broadcasting, 2009, 46(4): 240?248.

[8] EDFORDS O, SANDELL M, VAN DE BEEK J J, et al. OFDM channel estimation by singular value decomposition [J]. IEEE Transactions on Communications, 1998, 46(7): 923?927.

[9] VAN DE BEEK J J, EDFORS O, SANDELL M, et al. On Channel Estimation in OFDM Systems [C]// Proceedings of IEEE conference on Vehicular Technology. Chicago, USA: IEEE, 1995, 2: 815?819.

[10] 楊大成.移動傳播環(huán)境[M].北京:機械工業(yè)出版社,2003.

參考文獻

[1] SAVAUX Vincent, SKRZYPCZAK Alexandre, LOUET Yves, et al. Near LMMSE channel estimation preformance with artificial channel at receiver for OFDM systems [C]// 13th International Workshop on Signal Processing in Wireless Communications. [S.l.]: [s.n.], 2012: 545?549.

[2] OLIVER J, ARAVIND R, PRABHU K M M. Improved least squares channel estimation for orthogonal frequency division multiplexing [J]. IET Signal Processing, 2012, l.6: 45?53.

[3] HESKETH Thomas, DE LAMARE Rodrigo C, WALES Stephen. Adaptive MMSE channel estimation algorithms for MIMO system [EB/OL]. [2012?11?26]. www.ymcn.org/d?9bs1.html.

[4] Qun Yu and Ronglin Li.”Research on Pilot Pattern Design of Channel Estimation”Journal of Automation and Control Engineering,Vol.1,No.2,March 2013.

[5] PENA?CAMPOS F, CARRASCO?ALVAREZ R, LONGORIA?GANDARA O, et al. Estimation of fast time?varying channels in OFDM systems using two?dimensional prolate [J]. IEEE Transaction on wireless communications, 2013, 12(2): 898?907.

[6] ZHOU Wen, LAM Wong Hing. A fast LMMSE channel estimation method for OFDM systems [D]. Hong Kong, China: Department of Electrical and Electronics Engineering, The University of Hong Kong, 2009.

[7] MINN H, BHARGAVA V K. An investigation into time?domain approach for OFDM channel estimation [J]. IEEE Transactions on Broadcasting, 2009, 46(4): 240?248.

[8] EDFORDS O, SANDELL M, VAN DE BEEK J J, et al. OFDM channel estimation by singular value decomposition [J]. IEEE Transactions on Communications, 1998, 46(7): 923?927.

[9] VAN DE BEEK J J, EDFORS O, SANDELL M, et al. On Channel Estimation in OFDM Systems [C]// Proceedings of IEEE conference on Vehicular Technology. Chicago, USA: IEEE, 1995, 2: 815?819.

[10] 楊大成.移動傳播環(huán)境[M].北京:機械工業(yè)出版社,2003.

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