Channel Estimation Based On Zadoff-Chu Sequence For OFDM System

With the channel estimation, the receiver in OFDM systems can conduct channel equalization and finally decode the signals efficiently. Since the conventional methods for channel estimation mainly focus on dense cases, they usually fail to take advantages of the features in sparse cases. Compressed sensing based estimation is a novel solution to the sparse channel estimation, which can achieve high precisions. However, the computing complexity is tough and sparse degree is also required. For conventional channel estimations in MIMO-OFDM systems, which is regarded as an efficient way to achieve higher spectral efficiency, the subcarrier as pilot in one certain antenna is left unused in the other antennas.Thus, the pilot overhead and the number of antennas increase by times in conventional ways,and finally depress the spectral efficiency sharply in MIMO systems. This article mainly focus on the sparse channel estimation in OFDM systems. The main works are as follows:1. Based on analyzing and summarizing the channel estimations existed, we adopt circular shift from Zadoff-Chu sequences, and propose a novel channel estimation algorithm based on Zadoff-Chu sequences for the OFDM system. Simulation results show that our proposal outperforms over the LSE, and is less complex than Matching Pursuit Algorithm based on Compressed Sensing.2. We consider the adaption design for the algorithm above, and then propose a self-adapted channel estimation algorithm without knowing the sparse degree.Simulation results show that the proposal achieves a good balance between system performance and computing complexity.3. By adopting different Zadoff-Chu sequences as pilots to conduct channel estimation in time domain, we can separate the antennas with low-relevant Zadoff-Chu sequences, and finally cut down the pilot overhead for the channel estimation.Simulation results reveal that the algorithm proposed can achieve efficient estimation with relatively lower computing complexity, which remarkably improves the performance of MIMO-OFDM.