Performance Bounds for MIMO-OFDM Channel Estimation

被引:51
|
作者
Larsen, Michael D. [1 ]
Swindlehurst, A. Lee [2 ]
Svantesson, Thomas [3 ]
机构
[1] Brigham Young Univ, Dept Elect & Comp Engn, Provo, UT 84602 USA
[2] Univ Calif Irvine, Dept Elect Engn & Comp Sci, Irvine, CA 92697 USA
[3] ArrayComm Inc, San Jose, CA 95131 USA
基金
美国国家科学基金会;
关键词
Cramer-Rao Bound (CRB); direction-of-arrival (DOA) estimation; multiple-input multiple-output (MIMO) channels; orthogonal frequency division multiplexing (OFDM); parameter estimation; wireless communications; PREDICTION; SYSTEMS;
D O I
10.1109/TSP.2009.2014269
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
The performance of a mobile multiple-input multiple-output orthogonal-frequency-division multiplexing (MIMO-OFDM) system depends on the ability of the system to accurately account for the effects of the frequency-selective time-varying channel at every symbol time and at every frequency subcarrier. Typically, pilot symbols are strategically placed at various times over various subcarriers in order to calculate sample channel estimates, and then these estimates are interpolated or extrapolated forward to provide channel estimates where no pilot data was transmitted. Performance is highly dependent on the distribution of the pilots with respect to the coherence time and coherence bandwidth of the channel, and on the chosen channel parameterization. In this paper, a vector formulation of the Cramer-Rao bound (CRB) for biased estimators and for functions of parameters is used to derive a lower bound on the channel estimation and prediction error of such a system. Numerical calculations using the bound demonstrate the benefits of multiple antennas for channel estimation and prediction and illustrate the impact of modeling errors on estimation performance when using channel models based on calibrated arrays.
引用
收藏
页码:1901 / 1916
页数:16
相关论文
共 50 条
  • [1] FURTHER INVESTIGATIONS ON THE PERFORMANCE BOUNDS OF MIMO-OFDM CHANNEL ESTIMATION
    Ladaycia, Abdelhamid
    Mokraoui, Anissa
    Abed-Meraim, Karim
    Belouchrani, Adel
    2017 13TH INTERNATIONAL WIRELESS COMMUNICATIONS AND MOBILE COMPUTING CONFERENCE (IWCMC), 2017, : 223 - 228
  • [2] Performance of channel estimation in MIMO-OFDM systems
    Pramono, S. (subuhpramono@polines.ac.id), 2013, Universitas Ahmad Dahlan (11):
  • [3] A PERFORMANCE BOUND FOR MIMO-OFDM CHANNEL ESTIMATION AND PREDICTION
    Larsen, Michael D.
    Swindlehurst, A. Lee
    Svantesson, Thomas
    2008 IEEE SENSOR ARRAY AND MULTICHANNEL SIGNAL PROCESSING WORKSHOP, 2008, : 141 - +
  • [4] Performance Bounds Analysis for Semi-Blind Channel Estimation in MIMO-OFDM Communications Systems
    Ladaycia, Abdelhamid
    Mokraoui, Anissa
    Abed-Meraim, Karim
    Belouchrani, Adel
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2017, 16 (09) : 5925 - 5938
  • [5] Channel Estimation for MIMO-OFDM Systems
    Manzoor, Shahid
    Bamuhaisoon, Adnan Salem
    Alifa, Ahmed Nor
    2015 5TH NATIONAL SYMPOSIUM ON INFORMATION TECHNOLOGY: TOWARDS NEW SMART WORLD (NSITNSW), 2015,
  • [6] Channel estimation for MIMO-OFDM systems
    Liu, Gang
    Guo, Yi
    Ge, Jianhua
    Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition), 2005, 33 (09): : 26 - 29
  • [7] MIMO-OFDM channel modeling and performance
    Daoud, Omar
    Al-Akaidi, Marwan
    Ivins, Jonathan
    MESM '2006: 8TH MIDDLE EAST SIMULATION MULTICONFERENCE, 2006, : 92 - +
  • [8] Robust channel estimation in MIMO-OFDM systems
    Bai, W
    He, C
    Jiang, LG
    Li, XX
    ELECTRONICS LETTERS, 2003, 39 (02) : 242 - 244
  • [9] Channel estimation method for MIMO-OFDM system
    School of Electronics and Information Technology, Harbin Institute of Technology, Harbin 150001, China
    Dalian Haishi Daxue Xuebao, 2008, 2 (49-52):
  • [10] A channel estimation scheme for MIMO-OFDM systems
    He, Chunlong
    Tian, Chu
    Li, Xingquan
    Zhang, Ce
    Zhang, Shiqi
    Liu, Chaowen
    2ND ANNUAL INTERNATIONAL CONFERENCE ON INFORMATION SYSTEM AND ARTIFICIAL INTELLIGENCE (ISAI2017), 2017, 887