Training-based MIMO channel Rice factor estimation algorithms
Recently, to estimate the Rician flat fading Multiple-Input Multiple-Output (MIMO) channels, we have proposed the Shifted Scaled Least Squares (SSLS) channel estimator. In this paper, it is analytically shown that the performance of this estimator is less sensitive to the erroneous estimation of the Rice factor. Moreover, to estimate the channel Rice factor in the above mentioned channel model, two algorithms are proposed. These algorithms work based on the optimal training signal and Least Squares (LS) technique. The estimated Rice factor is used in the SSLS estimator. The performance of these algorithms is numerically compared in the Rician fading channel estimation. Simulation results confirm the efficiency of these algorithms.
Rice factor estimation MIMO SSLS Rician flat fading LS Optimal training signal
Hamid Nooralizadeh Shahriar Shirvani Moghaddam
Faculty of Electrical Engineering Department Islamshahr Branch, Islamic Azad University Islamshahr, DCSP Research Lab., Department of Electrical and Computer Engineering, Shahid Rajaee Teacher Trainin
国际会议
2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)
北京
英文
1441-1444
2010-08-24（万方平台首次上网日期，不代表论文的发表时间）