6,392 research outputs found
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
Efficient space-frequency block coded pilot-aided channel estimation method for multiple-input-multiple-output orthogonal frequency division multiplexing systems over mobile frequency-selective fading channels
© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.An iterative pilot-aided channel estimation technique for space-frequency block coded (SFBC) multiple-input multiple-output orthogonal frequency division multiplexing systems is proposed. Traditionally, when channel estimation techniques are utilised, the SFBC information signals are decoded one block at a time. In the proposed algorithm, multiple blocks of SFBC information signals are decoded simultaneously. The proposed channel estimation method can thus significantly reduce the amount of time required to decode information signals compared to similar channel estimation methods proposed in the literature. The proposed method is based on the maximum likelihood approach that offers linearity and simplicity of implementation. An expression for the pairwise error probability (PEP) is derived based on the estimated channel. The derived PEP is then used to determine the optimal power allocation for the pilot sequence. The performance of the proposed algorithm is demonstrated in high frequency selective channels, for different number of pilot symbols, using different modulation schemes. The algorithm is also tested under different levels of Doppler shift and for different number of transmit and receive antennas. The results show that the proposed scheme minimises the error margin between slow and high speed receivers compared to similar channel estimation methods in the literature.Peer reviewe
Robust massive MIMO Equilization for mmWave systems with low resolution ADCs
Leveraging the available millimeter wave spectrum will be important for 5G.
In this work, we investigate the performance of digital beamforming with low
resolution ADCs based on link level simulations including channel estimation,
MIMO equalization and channel decoding. We consider the recently agreed 3GPP NR
type 1 OFDM reference signals. The comparison shows sequential DCD outperforms
MMSE-based MIMO equalization both in terms of detection performance and
complexity. We also show that the DCD based algorithm is more robust to channel
estimation errors. In contrast to the common believe we also show that the
complexity of MMSE equalization for a massive MIMO system is not dominated by
the matrix inversion but by the computation of the Gram matrix.Comment: submitted to WCNC 2018 Workshop
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