Abstract
In the future, the channel requirement increase rapidly. How to improve the communication systems performance has become an important issue. The conventional method to transmit signals need pilot sequence. The pilot sequence also need frequency band to transmit. If we do the channel estimation, we can transmit signals with less pilot sequence or without the pilot sequence. The problem of the channel requirement will be improved. In the previous communication systems, the number of antennas in transmitter and receiver is not large. By the developing of the communication systems in the recent years, the concept of the massive MIMO will be applied in the future. When the number of the DOA is much smaller than the number of antennas in the receiver, the DOA estimation problem can be regard as the famous sparse signal reconstruction problem. Recently, the concept of cognitive radio and massive Multi-input Multi-output (MIMO) system model has been proposed and it is possible to improve the communication systems performance by combining the concept of the channel estimation that the channel estimation based on direction of arrival (DOA) can be regarded as a solution to this problem. Since the resolution of the channel estimation based on DOA with compressive sampling is higher than the resolution of the conventional DOA method Multiple Signal Classification (MUSIC), we focus on the channel estimation based on DOA with compressive sampling in this thesis.