A comparison of pilot-aided channel estimation methods for OFDMsystems
IEEE Transactions on Signal Processing
Optimal training design for MIMO OFDM systems in mobile wireless channels
IEEE Transactions on Signal Processing
Parametric Channel Estimation for Pseudo-Random Tile-Allocation in Uplink OFDMA
IEEE Transactions on Signal Processing
Multiuser OFDM with adaptive subcarrier, bit, and power allocation
IEEE Journal on Selected Areas in Communications
Channel-independent synchronization of orthogonal frequency division multiple access systems
IEEE Journal on Selected Areas in Communications
Low complexity iterative interference cancelation for OFDMA uplnik with carrier frequency offsets
APCC'09 Proceedings of the 15th Asia-Pacific conference on Communications
Carrier frequency offset tracking in the IEEE 802.16e OFDMA uplink
IEEE Transactions on Wireless Communications
Wireless Personal Communications: An International Journal
Hi-index | 0.03 |
For the uplink transmission of an OFDMA system, frequency synchronization is particularly challenging due to the presence of multiple Carrier Frequency Offsets (CFOs). This problem is investigated in this paper, and we propose a novel low complexity pilot aided frequency synchronization algorithm based on two consecutive OFDMA blocks, which are assigned with identical tile structure and pilot symbols. The pilot symbols can be used for both the CFO estimation and the channel estimation and hence effectively increases the spectral efficiency, since no additional pilot symbols or training sequence are needed exclusively for the CFO estimation. However, the solution to this multi-parameter estimation problem is prohibitively complex since it demands a multi-dimensional search. To solve this problem, we propose an iterative joint CFO estimation and compensation algorithm, which reduces the multi-dimensional search to only one simple one-dimensional search. In addition, the proposed scheme allows the CFO estimation and compensation to operate without the channel information and thereby further reduces the computational complexity. We analyze the identifiability in the CFO estimation and derive the analytical mean square error (MSE) of the CFO estimates to serve as the performance benchmark. The simulation results show that the synchronization algorithm achieves fast convergence in two iterations, and the accuracy of the CFO estimates matches the benchmark performance closely at moderate and high SNRs and outperforms an existing similar algorithm proposed in the literature.