An Efficient Data-aided Synchronization in L-DACS1 for Aeronautical Communications

L-band Digital Aeronautical Communication System type-1 (L-DACS1) is an emerging standard that aims at enhancing air traffic management (ATM) by transitioning the traditional analog aeronautical communication systems to the superior and highly efficient digital domain. L-DACS1 employs modern and efficient orthogonal frequency division multiplexing (OFDM) modulation technique to achieve more efficient and higher data rate in comparison to the existing aeronautical communication systems. However, the performance of OFDM systems is very sensitive to synchronization errors. L-DACS1 transmission is in the L-band aeronautical channels that suffer from large interference and large Doppler shifts, which makes the synchronization for L-DACS more challenging. This paper proposes a novel computationally efficient synchronization method for L-DACS1 systems that offers robust performance. Through simulation, the proposed method is shown to provide accurate symbol timing offset (STO) estimation as well as fractional carrier frequency offset (CFO) estimation in a range of aeronautical channels. In particular, it can yield excellent synchronization performance in the face of a large carrier frequency offset.Comment: In the proceeding of International Conference on Data Mining, Communications and Information Technology (DMCIT

Fine Timing and Frequency Synchronization for MIMO-OFDM: An Extreme Learning Approach

Multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) is a key technology component in the evolution towards cognitive radio (CR) in next-generation communication in which the accuracy of timing and frequency synchronization significantly impacts the overall system performance. In this paper, we propose a novel scheme leveraging extreme learning machine (ELM) to achieve high-precision synchronization. Specifically, exploiting the preamble signals with synchronization offsets, two ELMs are incorporated into a traditional MIMO-OFDM system to estimate both the residual symbol timing offset (RSTO) and the residual carrier frequency offset (RCFO). The simulation results show that the performance of the proposed ELM-based synchronization scheme is superior to the traditional method under both additive white Gaussian noise (AWGN) and frequency selective fading channels. Furthermore, comparing with the existing machine learning based techniques, the proposed method shows outstanding performance without the requirement of perfect channel state information (CSI) and prohibitive computational complexity. Finally, the proposed method is robust in terms of the choice of channel parameters (e.g., number of paths) and also in terms of "generalization ability" from a machine learning standpoint.Comment: 13 pages, 12 figures, has been accepted for publication in IEEE Transactions on Cognitive Communications and Networkin

Low Complexity Time Synchronization Algorithm for OFDM Systems with Repetitive Preambles

In this paper, a new time synchronization algorithm for OFDM systems with repetitive preamble is proposed. This algorithm makes use of coarse and fine time estimation; the fine time estimation is performed using a cross-correlation similar to previous proposals in the literature, whereas the coarse time estimation is made using a new metric and an iterative search of the last sample of the repetitive preamble. A complete analysis of the new metric is included, as well as a wide performance comparison, for multipath channel and carrier frequency offset, with the main time synchronization algorithms found in the literature. Finally, the complexity of the VLSI implementation of this proposal is discussed. © 2011 Springer Science+Business Media, LLC.This work was supported by the Spanish Ministerio de Educacion y Ciencia under grants TEC2006-14204-C02-01 and TEC2008-06787.Canet Subiela, MJ.; Almenar Terre, V.; Flores Asenjo, SJ.; Valls Coquillat, J. (2012). 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