EM-Based Maximum-Likelihood Sequence Detection for MIMO Optical Wireless Systems

被引:0
|
作者
Chatzidiamantis, Nestor D. [1 ]
Uysal, Murat [2 ]
Tsiftsis, Theodoros A. [1 ]
Karagiannidis, George K. [1 ]
机构
[1] Aristotle Univ Thessaloniki, Dept Elect & Comp Engn, GR-54006 Thessaloniki, Greece
[2] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON, Canada
关键词
ATMOSPHERIC-TURBULENCE CHANNELS; MULTIPLE-SYMBOL DETECTION; COMMUNICATION; TRANSMISSION; PERFORMANCE; DIVERSITY; ALGORITHM; NOISE; LINKS; PPM;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A major performance-limiting factor in terrestrial optical wireless (OW) systems is turbulence-induced fading. Exploiting the additional degrees of freedom in the spatial dimension, multiple laser transmitters combined with multiple receiver apertures provide an effective solution for fading mitigation. Although MIMO (Multiple-Input Multiple-Output) OW systems have been extensively studied in recent years, most of these works are mainly limited to symbol-by-symbol decoding. Maximum Likelihood Sequence Detection (MLSD) exploits the temporal correlation of turbulence-induced fading and promises further performance gains. In this paper, we investigate MLSD for IM/DD (intensity-modulation/direct-detection) MIMO OW systems over log-normal atmospheric turbulence channels. Even with a low-order modulation scheme such as On-Off keying which is typically used in OW systems, the complexity of MLSD might be prohibitive. We therefore present an iterative sequence detector based on the expectation-maximization (EM) algorithm. The complexity of the proposed algorithm is much smaller than a direct evaluation of the log-likelihood function. The Monte-Carlo simulation results demonstrate that the EM-based algorithm outperforms the symbol-by-symbol decoder and achieves a performance which lies within 0.5 dB of that of the optimal MLSD.
引用
收藏
页码:2583 / +
页数:2
相关论文
共 50 条
  • [1] Iterative Near Maximum-Likelihood Sequence Detection for MIMO Optical Wireless Systems
    Chatzidiamantis, Nestor D.
    Uysal, Murat
    Tsiftsis, Theodoros A.
    Karagiannidis, George K.
    [J]. JOURNAL OF LIGHTWAVE TECHNOLOGY, 2010, 28 (07) : 1064 - 1070
  • [2] EM-Based Maximum-Likelihood Channel Estimation in Multicarrier Systems With Phase Distortion
    Carvajal, Rodrigo
    Aguero, Juan C.
    Godoy, Boris I.
    Goodwin, Graham C.
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2013, 62 (01) : 152 - 160
  • [3] Maximum-Likelihood Detection for MIMO Systems Based on Differential Metrics
    Chang, Ming-Xian
    Chang, Wang-Yueh
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2017, 65 (14) : 3718 - 3732
  • [4] The BEAST for Maximum-Likelihood Detection in Non-Coherent MIMO Wireless Systems
    Hug, Florian
    Rusek, Fredrik
    [J]. 2010 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2010,
  • [5] Maximum-likelihood detection based on branch and bound algorithm for MIMO systems
    LI Zi1 & CAI YueMing1
    2 National Mobile Communications Research Laboratory
    [J]. Science China(Information Sciences), 2008, (03) : 306 - 319
  • [6] Maximum-likelihood detection based on branch and bound algorithm for MIMO systems
    Li Zi
    Cai YueMing
    [J]. SCIENCE IN CHINA SERIES F-INFORMATION SCIENCES, 2008, 51 (03): : 306 - 319
  • [7] Maximum-likelihood detection based on branch and bound algorithm for MIMO systems
    Zi Li
    YueMing Cai
    [J]. Science in China Series F: Information Sciences, 2008, 51 : 306 - 319
  • [8] The Improved Maximum-Likelihood Detection Algorithm for MIMO Systems Based on Differential Metrics
    Deng Honggui
    Liu Xiaoxiong
    Liu Gang
    [J]. 2019 IEEE 11TH INTERNATIONAL CONFERENCE ON COMMUNICATION SOFTWARE AND NETWORKS (ICCSN 2019), 2019, : 353 - 357
  • [9] A Serial Maximum-likelihood Detection Algorithm for Massive MIMO Systems
    Zeng, Jing
    Lin, Jun
    Wang, Zhongfeng
    [J]. 2020 18TH IEEE INTERNATIONAL NEW CIRCUITS AND SYSTEMS CONFERENCE (NEWCAS'20), 2020, : 78 - 81
  • [10] Maximum-likelihood sequence estimation in nonlinear optical transmission systems
    Sauer-Greff, W
    Dittrich, A
    Urbansky, R
    Haunstein, H
    [J]. 2003 IEEE LEOS ANNUAL MEETING CONFERENCE PROCEEDINGS, VOLS 1 AND 2, 2003, : 167 - 168