812 research outputs found
Joint Frequency and Timing Recovery for MSK-Type Modulation
No full textWe investigate a novel nondata-aided method for jointly estimating timing and carrier frequency offset in MSK-type modulation. The algorithm has a feedforward structure and lends itself to a simple digital implementation. Its estimation accuracy depends on a design parameter that may be varied to trade performance for computational complexity. Setting the parameter to unity yields a synchronization scheme already known in the literature. Computer simulations are used to assess the synchronizer performance on AWGN Rayleigh fading channels with MSK and Gaussian MSK modulation
A Comparison of Pilot-Aided Channel Estimation Methods for OFDM Systems
No full textThis paper deals with the estimation of the channel impulse response (CIR) in orthogonal frequency division multiplexed (OFDM) systems. In particular, we focus on two pilot-aided schemes: the maximum likelihood estimator (MLE) and the Bayesian minimum mean square error estimator (MMSEE). The advantage of the former is that it is simpler to implement as it needs no information on the channel statistics. On the other hand, the MMSEE is expected to have better performance as it exploits prior information about the channel. Theoretical analysis and computer simulations are used in the comparisons. At SNR values of practical interest, the two schemes are found to exhibit nearly equal performance, provided that the number of pilot tones is sufficiently greater than the CIRs length. Otherwise, the MMSEE is superior. In any case, the MMSEE is more complex to implement
Carrier-Frequency Estimation for Transmissions over Selective Channels
No full textThis paper deals with carrier-frequency estimation
for burst transmissions over frequency-selective channels. Three
estimation schemes are proposed, all based on the use of known
training sequences. The first scheme employs an arbitrary sequence
and provides joint maximum-likelihood (ML) estimates
of the carrier frequency and the channel response. Its implementation
complexity is relatively high but its accuracy achieves
the Cramer–Rao bound. The second scheme is still based on
the ML criterion, but the training sequence is periodic, which
helps to reduce the computational load. The third scheme also
employs periodic sequences, but its structure comes from heuristic
reasoning. Theoretical analysis and simulations are employed to
assess the performance of the three schemes
On large enterprises: new findings from a European comparison
No full textCorporate governance, Firm performance, G32, G34, L25,
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