Signal Recovery in Multiuser MIMO-OFDM Systems with Known Partial Channel State Information
スポンサーリンク
概要
- 論文の詳細を見る
A novel method for signal recovery in multiuser multi-input multi-output(MIMO) orthogonal frequency division multiplex(OFDM) systems with known partial channel state information(CSI) is proposed. Upon the arrival of a new user, the new interferences are introduced which results an expanding mixture. Usually, with the help of pilot symbols, the CSI is estimated. In this letter, from the second order statistics of the received signals, the parameters of the mixture caused by the new user are extracted. Then the signals from different users are separated at each frequency bin (FB).
- 2006-08-01
著者
-
GUO Bin
Graduate School of Engineering, Osaka Prefecture University
-
LIN Hai
Graduate School of Engineering, Osaka Prefecture University
-
YAMASHITA Katsumi
Graduate School of Engineering, Osaka Prefecture University
-
Yamashita Katsumi
Graduate School Of Engineering Osaka Prefecture University
-
Guo Bin
Graduate School Of Engineering Osaka Prefecture University
-
Lin Hai
Graduate School Of Engineering Osaka Prefecture University
-
Yamashita Katsumi
Graduate School of Engineenng, Osaka Prefecture University
関連論文
- lCA Based Blind MIMO OFDM Receiver
- Signal Recovery in Multiuser MIMO-OFDM Systems with Known Partial Channel State Information
- Multiuser data separation for short message service using ICA (通信方式)
- Multiuser data separation for short message service using ICA (回路とシステム)
- Multiuser data separation for short message service using ICA (信号処理)
- Channel Estimation for Mobile OFDM Systems Using CR Splines
- Fractionally Spaced Bayesian Decision Feedback Equalizer(Regular Section)
- PAPR Reduction for PCC-OFDM Systems Using Neural Phase Rotator
- Cluster Map Based Blind RBF Equalizer(Digital Signal Processing)
- An Equalization Technique for High-Speed-Mobile OFDM Systems in Rayleigh Multipath Channels(Fundamental Theories)
- Bayesian Decision Feedback Equalizer with Receiver Diversity Combining(Digital Signal Processing)
- A Cluster Map Based Blind RBF Decision Feedback Equalizer with Reduced Computational Complexity(Digital Signal Processing)
- Complexity Suppression of Neural Networks for PAPR Reduction of OFDM Signal
- A New Robust Watermarking Algorithm for Digital Image Based on DCT-SVD and Arnold Scrambling
- Semantic Self-Organizing Map for Natural Disasters News