MIMO空间相关信道下格规约辅助的信号检测

doi:10.3969/j.issn.1001-2400.2012.01.003

J4 ›› 2012, Vol. 39 ›› Issue (1): 11-16+22.doi: 10.3969/j.issn.1001-2400.2012.01.003

MIMO空间相关信道下格规约辅助的信号检测

李建东;陈睿;李长乐;刘伟;陈丹

(西安电子科技大学综合业务网理论及关键技术国家重点实验室，陕西西安 710071)

收稿日期:2010-11-13 出版日期:2012-02-20 发布日期:2012-04-06
基金资助:
国家杰出青年科学基金资助项目(60725105)；国家重点基础研究发展计划(973计划)课题资助项目(2009CB320404)；“长江学者和创新团队发展计划”资助项目(IRT0852)；国家自然科学基金资助项目(60702057)；“高等学校创新引智计划”资助项目(B08038)；中央高校基本科研业务费专项资金资助项目(JY10000901030)；西安电子科技大学留学回国人员创新基金资助项目(64101879)；综合业务网理论及关键技术国家重点实验室资助项目(MIMO非再生中继传输系统联合收发机设计)

Lattice-reduction-aided detection in spatial correlated MIMO channels

LI Jiandong;CHEN Rui;LI Changle;LIU Wei;CHEN Dan

(State Key Lab. of Integrated Service Networks, Xidian Univ., Xi'an 710071， China)

Received:2010-11-13 Online:2012-02-20 Published:2012-04-06
Supported by:
李建东(1962-)，男，教授，E-mail: jdli@mail.xidian.edu.cn．

摘要/Abstract

摘要：

针对多输入多输出空间相关信道环境，提出了一种基于格规约理论的最小均方误差检测算法．该算法考虑了空间相关性的影响，利用复数Lenstra-Lenstra-Lovász格规约算法克服了传统的线性最小均方误差检测器分集阶数随相关系数增加而减小的缺点，使检测到的信号在高信噪比下可以达到比传统算法低几个数量级的误码率．理论分析与仿真结果表明，在信道为Kronecker相关平坦衰落模型下，接收端采用最小均方误差信道估计，发射端采用QPSK调制未使用信道编码，当比特信噪比大于18dB时，基于格规约理论的最小均方误差检测器的误码率低于传统最小均方误差检测器的误码率；发射端采用(2,1,3)卷积码、接收端采用硬判决Viterbi译码，当信噪比大于16dB时，基于格规约理论的最小均方误差检测器的误码率低于传统最小均方误差检测器的误码率，且基于格规约理论的最小均方误差检测器的分集阶数不受相关系数的影响，等于接收天线数N．

关键词: 多输入多输出, 空间相关信道, 格规约, 信号检测

Abstract:

To overcome the drawback that the diversity order of the traditional linear MMSE detection algorithm decreases with the increase of the correlation coefficient, a lattice-reduction-aided MMSE (LRA-MMSE) detection algorithm is proposed for spatial correlated MIMO channels. The LRA-MMSE detection algorithm considers the effect of spatial correlation in the algorithm design and takes advantage of the complex Lenstra-Lenstra-Lovász (LLL) algorithm so that its BER (bit error rate) is several orders of magnitude smaller than that of the traditional linear MMSE detection at a high SNR (signal to noise ratio). Theoretical analysis and simulation results show that with QPSK modulation and the MMSE channel estimator at the receiver, the uncoded BER of the LRA-MMSE detector is lower than that of the traditional linear MMSE detector if the bit SNR (E_b/N₀) is greater than 18dB, while the coded BER of the LRA-MMSE detector is lower than that of the traditional linear MMSE detector if E_b/N₀ is greater than 16dB when (2,1,3) convolutional channel coding and Viterbi decoding are adopted under the Kronecker correlated flat fading channel. Furthermore, the diversity order of the LRA-MMSE detector in the correlated MIMO channel is equal to the number of the receive antenna N.

Key words: multiple input multiple output, spatial correlated channel, lattice reduction, signal detection

李建东;陈睿;李长乐;刘伟;陈丹. MIMO空间相关信道下格规约辅助的信号检测[J]. J4, 2012, 39(1): 11-16+22.

LI Jiandong;CHEN Rui;LI Changle;LIU Wei;CHEN Dan. Lattice-reduction-aided detection in spatial correlated MIMO channels[J]. J4, 2012, 39(1): 11-16+22.

参考文献

［1］吕卓，李建东，李维英. MIMO-OFDM系统在选择性衰落信道下的容量分析［J］. 西安电子科技大学学报, 2005, 32(6): 935-939.
LüZhuo, Li Jiandong, Li Weiying. Capacity Analysis of the MIMO-OFDM System over Frequency-and Time-Selectivity fading channels ［J］. Journal of Xidian University, 2005, 32(6): 935-939.
［2］ Yao H, Wornell G. Lattice-Reduction-Aided Detectors for MIMO Communication Systems［C］// IEEE Globecom. Taipei: IEEE Press, 2002: 424-428.
［3］ Wübben D, Bohnke R. Near Maximum Likelihood Detection of MIMO Systems Using MMSE-based Lattice Reduction［C］// IEEE ICC. Paris: IEEE Press, 2004: 798-802.
［4］ Taherzadeh M, Mobasher A, Khandani A K. LLL Reduction Achieves the Receiver Diversity in MIMO Decoding［J］. IEEE Trans on Information Theory, 2007, 53(12): 4801-4805.
［5］ Ma X, Zhang W. Performance Analysis for MIMO Systems with Lattice-Reduction Aided Linear Equalization［J］. IEEE Trans on Communications, 2008, 56(2): 309-318.
［6］ Kernoal J P, Schumacher L. A Stochastic MIMO Radio Channel Model With Experimental Validation［J］. IEEE Journal on Selected Areas in Communications, 2002, 20(6): 1211-1266.
［7］ Ivrlac M, Utschick W, Nossek J. Fading Correlations in Wireless MIMO Communication Systems［J］. IEEE Selected Areas in Communications, 2003, 21(5): 819-828.
［8］ van Zelst A, Hammerschmidt J. A Single Coefficient Spatial Correlation Model for Multiple-Input Multiple-Output(MIMO) Radio Channel［C］// URSI General Assembly. Maastricht: IEEE Press, 2002: 1-4.
［9］ Yoo T, Goldsmith A J. Capacity and Power Allocation for Fading MIMO Channels with Channel Estimation Error ［J］. IEEE Trans on Information Theory, 2006, 52(5): 2203-2214.
［10］ Dabbagh A D, Love D J. Multiple Antenna MMSE Based Downlink Precoding with Quantized Feedback or Channel Mismatch［J］. IEEE Trans on Wireless Communications, 2008, 56(11): 1859-1868.
［11］ Biguesh M, Gershman A B. Training-based MIMO Channel Estimation: a Study of Estimator Tradeoffs and Optimal Training Signals［J］. IEEE Trans on Signal Processing, 2006, 54(3): 884-893.
［12］ Steven M Kay. Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory［M］. New Jersey: Prentice-Hall, 1993.
［13］ Agrell E, Eriksson T. Closest Point Search in Lattices［J］. IEEE Trans on Information Theory, 2002, 48 (8): 2201-2214.
［14］ Schnorr C P, M. Euchner. Lattice Basis Reduction: Improved Practical Algorithms and Solving Subset Sum Problems［J］. Math Programming, 1994(66): 181-191.
［15］ Lenstra A K, Lenstra H W, Lovász L. Factoring Polynomials with Rational Coefficients［J］. Math Ann, 1982(261): 515-534.
［16］ Ma X, Zhang W. Fundamental Limits of Linear Equalizers: Diversity, Capacity and Complexity ［J］. IEEE Trans on Information Theory, 2008, 53(12): 4801-4805.

[1]	刘敏提, 曾操, 胡树林, 陈建忠, 李军, 李世东, 廖桂生. 存在幅相误差时二维稳健超分辨测角算法[J]. 西安电子科技大学学报, 2024, 51(3): 55-62.
[2]	周硕,周一青,张冲,邢旺. ResNet使能的OTFS联合信道估计和信号检测[J]. 西安电子科技大学学报, 2023, 50(3): 19-30.
[3]	刘刚,娄增进,林勤华,郭漪. 大规模MIMO系统中的改进CG迭代算法[J]. 西安电子科技大学学报, 2022, 49(4): 8-15.
[4]	蒋芳,黄兴,胡梦钰,王翊,许耀华,胡艳军. 降噪自编码器辅助的下行MIMO-SCMA编解码方法[J]. 西安电子科技大学学报, 2022, 49(3): 74-82.
[5]	曹鹏程,刘伟伟,刘光杰,茅伟伟,戴跃伟. 一种基于预编码的MIMO无线隐信道[J]. 西安电子科技大学学报, 2022, 49(2): 42-49.
[6]	王勇,王喜媛,任泽洋. 毫米波MIMO的DNN混合预编码梯度优化方法[J]. 西安电子科技大学学报, 2022, 49(1): 202-207.
[7]	廖勇,孙宁,王帅,陈颖. 面向LTE-V2X系统的双迭代信号检测算法[J]. 西安电子科技大学学报, 2021, 48(3): 1-8.
[8]	李文刚;胡爱丽;孙珑心;王屹伟. LOS环境下零导频Massive MIMO通信方法[J]. 西安电子科技大学学报, 2018, 45(4): 1-5+85.
[9]	刘洁怡;张林让;于恒力;唐世阳; 赵珊珊. 分集MIMO雷达目标回波相关性分析[J]. 西安电子科技大学学报, 2018, 45(4): 69-74.
[10]	宫健;楼顺天;郭艺夺;张伟涛. 非平稳噪声下相干信源MIMO雷达角度估计[J]. 西安电子科技大学学报, 2018, 45(4): 174-180.
[11]	李升远;张馨恬;唐世阳. 采用OFDM-LFM的MIMO雷达高速目标波形设计[J]. 西安电子科技大学学报, 2018, 45(3): 7-12.
[12]	李川. MIMO异构网络下行链路干扰对齐[J]. 西安电子科技大学学报, 2018, 45(2): 176-180.
[13]	李晓洁;李颖;韩会梅. 大规模MIMO系统下的导频随机接入方案[J]. 西安电子科技大学学报, 2018, 45(1): 55-59.
[14]	王玉玺;黄国策;李伟;王叶群. 杂波和有色噪声条件下MIMO雷达波形设计[J]. 西安电子科技大学学报, 2017, 44(4): 125-131.
[15]	刘帅琦;王布宏;李龙军;李夏;曹帅. 二维混合MIMO相控阵雷达的DOA估计算法[J]. 西安电子科技大学学报, 2017, 44(3): 157-163.

MIMO空间相关信道下格规约辅助的信号检测

Lattice-reduction-aided detection in spatial correlated MIMO channels

PDF (PC)

赞

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 0