Pilot optimization method for large-scale MIMO channel estimation based on structural compressed sensing
By using the pilot optimization method of structured compressed sensing in large-scale MIMO-OFDM systems to optimize pilot positions and symbol sequences, the problem of insufficient channel estimation performance is solved and the channel estimation performance is significantly improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANJING UNIV OF POSTS & TELECOMM
- Filing Date
- 2016-11-23
- Publication Date
- 2017-02-22
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
In massive MIMO-OFDM systems, the performance of channel estimation is affected by the selection and placement of pilot symbols, and traditional methods fail to effectively optimize pilots, resulting in high mean square errors of channel estimation.
The pilot optimization method based on structured compressed sensing is used to reduce the complete inter-block correlation value by establishing a channel estimation model and optimizing the pilot position and symbol sequence to improve the performance of channel estimation. Specific steps include establishing a channel estimation model with overlapping pilot placement, simplifying it into a structured compressed sensing model, and solving the optimal pilot position and symbol sequence through a random search algorithm.
The mean square error (MSE) of channel estimation is significantly reduced and the performance of channel estimation is improved. The simulation results show that using the optimized pilot matrix can reduce MSE by about 3dB.