Research Themes
- Subcarrier index modulation based flexible OFDM system
- Radio over Fiber Technology
- Throughput Measurement of 2-by-2 LCX-MIMO System in Real Indoor Liner-cell Environment
- Diversity Gain Analysis of SFN-STBC Digital Terrestrial TV System using Dual Polarized MIMO Antenna
- Linear cell system of LCX-MIMO and its beam-forming
- Compressed Sensing based Channel Estimation Algorithm for MIMO-OFDM System
- Sensing
- High-resolution localization using leaky coaxial cable antenna
- RFID tag localization using hybrid inductive-capacitive coupling
- Wireless Power Transmission
Research Topic: Compressed Sensing based Channel Estimation Algorithm for MIMO-OFDM System
Research Brief
A multiple-input multiple-output (MIMO) communication system combined with the orthogonal frequency division multiplexing (OFDM) modulation technique can help in mitigating the effects of multipath fading and achieve reliable high data rate transmission over broadband wireless channels. The channel estimation has an important role in determining the quality of the data transmission from transmitter to receiver. Channel estimation using Compressed Sensing (CS) algorithms can achieve higher correctness of channel status but using small number of pilots than conventional interpolation based methods. This research proposed to reduce the complexity in sensing matrix algorithm for MIMO-OFDM. By using STBC MIMO, the pilot matrixes of 2 antennas are same. So we can share the measurement matrix (A) for CS algorithm process to reduce the computational complexity. To improve the bit error rate (BER) performance, we can use average process by summarize the known received vector (y) to find the correct position of CIR.
