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空军工程大学 信息与导航学院, 陕西 西安 710077
[ "孟庆微(1980-), 男, 黑龙江安达人, 博士, 讲师, 2007年于空军工程大学获得硕士学位, 2013年于西北工业大学获得博士学位, 主要从事高速无线通信、水声通信技术的研究。E-mail:qingw_meng@163.com" ]
孟相如(1963-), 男, 陕西西安人, 教授, 博士生导师, 1988年、1994年于西安交通大学分别获得硕士、博士学位, 1997年在电子科技大学博士后出站, 主要从事宽带通信与网络技术研究. E-mail:xrmeng@126.com MENG Xiang-ru, E-mail:xrmeng@126.com
收稿日期:2016-06-27,
录用日期:2016-8-1,
纸质出版日期:2016-09
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孟庆微, 苏令华, 苏玉泽, 等. 阈值判决引导的单载波分块传输稀疏信道估计[J]. 光学精密工程, 2016,24(9):2332-2338.
Qing-wei MENG, Ling-hua SU, Yu-ze SU, et al. Threshold decision directed sparse channel estimation for single carrier block transmission[J]. Optics and precision engineering, 2016, 24(9): 2332-2338.
孟庆微, 苏令华, 苏玉泽, 等. 阈值判决引导的单载波分块传输稀疏信道估计[J]. 光学精密工程, 2016,24(9):2332-2338. DOI: 10.3788/OPE.20162409.2332.
Qing-wei MENG, Ling-hua SU, Yu-ze SU, et al. Threshold decision directed sparse channel estimation for single carrier block transmission[J]. Optics and precision engineering, 2016, 24(9): 2332-2338. DOI: 10.3788/OPE.20162409.2332.
为利用高速无线通信时信道的稀疏多径传播特性,改善传统单载波分块传输(SCBT)信道估计方法的性能,提出了一种阈值判决引导的稀疏信道估计方法。该方法通过导频进行初始最小二乘信道估计,利用获取的信道估计值设置判决阈值。然后,将幅值低于判决阈值的信道抽头强制置零,仅保留幅度值大于判决阈值的信道抽头估计值,从而有效地改善单载波分块传输系统的稀疏信道估计性能。基于COST 207典型乡村信道模型进行了仿真实验,结果表明:阈值判决引导的稀疏信道估计方法的实验结果最接近于信道参数已知时的误比特率性能;在信噪比为20 dB条件下,新方法的误比特率可达到5×10
-4
,而最小二乘算法只能达到3×10
-2
。该方法改善了SCBT系统的稀疏信道估计精度与复杂度,得到的结果验证了提出方法的有效性。
A threshold decision directed sparse channel estimation (TDDSCE) method was proposed for a Single Carrier Block Transmission(SCBT) system
which can take advantage of the sparsity inherent in high rate wireless communication channels
and improve the channel estimation accuracy. Firstly
a pilot sequence was used to perform a least square (LS) channel estimation
then a decision threshold was derived by obtained channel estimated values. The channel taps whose values were smaller than the decision threshold were forced to be zeros
only the channel taps whose values were above the decision threshold were reserved
so that the sparse channel estimation accuracy was greatly improved. A simulation experiment was carried out based on a COST 207 rural area channel profile
and the results show that the performance of proposed method is most close to that of the known channel case
and its bit error rate (BER) reaches 5×10
-4
when the signal to noise ratio is 20 dB. However
the traditional LS channel estimation method only achieves the BER of 3×10
-2
. The method improves the sparse channel estimation accuracy and reduces the complexity of the SCBT system
and its feasibility is verified by obtained results.
DAOUD S, GHRAYEB A. Using resampling to combat doppler scaling in UWA channels with single-carrier modulation and frequency-domain equalization[J]. IEEE Transactions on Vehicular Technology, 2016, 65(3):1261-1270.
ZHANG J T, YANG L L, HANZO L, et al.. Advances in cooperative single-carrier FDMA communications:beyond LTE-advanced[J]. IEEE Communications Surveys & Tutorials, 2015, 17(2):730-756.
WANG D, ZHAO Q, YANG L. Robust signal-to-noise ratio and noise variance estimation for single carrier frequency domain equalisation ultra-wideband wireless systems[J]. IET Communications, 2015, 9(3):1598-1605.
COON J, SANDELL M, BEACH M, et al.. Channel and noise variance estimation and tracking algorithms for unique-word based single-carrier systems[J]. IEEE Transactions on Wireless Communications, 2006, 5(6):1488-1496.
ZHENG Y H, XIAO C S. Channel estimation for frequency-domain equalization of single-carrier broadband wireless communications[J]. IEEE Transactions on Vehicular Technology, 2009, 58(2):815-823.
焦现军, 张磊, 项海格.单载波频域均衡系统中的PN信道估计算法[J].北京大学学报, 2007, 37(1):103-108.
JIAO X J, ZHANG L, XIANG H G. PN based channel estimation in SC-FDE system[J]. Journal of Beijing University, 2007, 37(1):103-108. (in Chinese)
李丹萍, 刘毅, 张海林. MIMO SC-FDE系统的时域信道估计新算法[J].通信学报, 2011, 32(2):144-149.
LI D P, LIU Y, ZHANG H L.Channel estimation for MIMO SC-FDE systems via time-domain based approaches[J]. Journal of Communications, 2011, 32(2):144-149. (in Chinese)
SCHNITER P. A message-passing receiver for BICM-OFDM over unknown clustered-sparse channels[J]. IEEE Journal of Selected Topics in Signal Processing, 2011, 5(8):1462-1474.
WANG H, GUO Q, ZHANG G, et al.. Pilot pattern optimization for sparse channel estimation in OFDM systems[J]. IEEE Communications Letters, 2015, 19(7):1233-1236.
QI C, YUE G, WU L, et al.. Pilot design schemes for sparse channel estimation in OFDM systems[J]. IEEE Transactions on Vehicular Technology, 2015, 64(4):1493-1505.
HE X, SONG R, ZHU W P. Pilot allocation for distributed-compressed-sensing-based sparse channel estimation in MIMO-OFDM systems[J]. IEEE Transactions on Vehicular Technology, 2016, 65(5):2990-3004.
GAO Z, ZHANG C, WANG Z, et al.. Prior information aided iterative hard threshould:a low-complexity high-accuracy compressive sensing based channel estimation for TDS-OFDM[J]. IEEE Transactions on Wireless Communications, 2015, 14(1):242-250.
孟庆微, 黄建国, 韩晶, 等.水声单载波分块传输中基于压缩感知的稀疏信道估计方法[J].北京邮电大学学报, 2012, 35(5):14-17.
MENG Q W, HUANG J G, HAN J, et al.. Compressed sensing based sparse channel estimation scheme for underwater single carrier block transmission[J]. Journal of Beijing University of Posts and Telecommunications, 2012, 35(5):14-17. (in Chinese)
孟庆微, 黄建国, 何成兵, 等.采用时域测量矩阵的压缩感知稀疏信道估计方法[J].西安交通大学学报, 2012, 46(8):94-99.
MENG Q W, HUANG J G, HE CH B, et al.. An compressed sensing estimation method for sparse channels using time domain measurement matrix[J]. Journal of Xi'an Jiaotong University, 2012, 46(8):94-99. (in Chinese)
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