Feedforward data-aided phase noise estimation from a DCT basis expansion

This contribution deals with phase noise estimation from pilot symbols. The phase noise process is approximated by an expansion of discrete cosine transform (DCT) basis functions containing only a few terms. We propose a feedforward algorithm that estimates the DCT coefficients without requiring detailed knowledge about the phase noise statistics. We demonstrate that the resulting (linearized) mean-square phase estimation error consists of two contributions: a contribution from the additive noise, that equals the Cramer-Rao lower bound, and a noise independent contribution, that results front the phase noise modeling error. We investigate the effect of the symbol sequence length, the pilot symbol positions, the number of pilot symbols, and the number of estimated DCT coefficients it the estimation accuracy and on the corresponding bit error rate (PER). We propose a pilot symbol configuration allowing to estimate any number of DCT coefficients not exceeding the number of pilot Symbols, providing a considerable Performance improvement as compared to other pilot symbol configurations. For large block sizes, the DCT-based estimation algorithm substantially outperforms algorithms that estimate only the time-average or the linear trend of the carrier phase. Copyright (C) 2009 J. Bhatti and M. Moeneclaey

Feedforward pilot-aided carrier synchronization using a DCT basis expansion

This contribution deals with phase noise estimation from pilot symbols. The phase noise process is approximated by an expansion of Discrete Cosine-Transform (DCT) basis functions containing only a few terms. We propose a feedforward algorithm that estimates the DCT coefficients without requiring detailed knowledge about the phase noise statistics. We demonstrate that the resulting (linearized) mean-square phase estimation error consists of two contributions: a contribution from the additive noise, that equals the Cramer-Rao lower bound, and a noise-independent contribution that results from the phase noise modeling error. We investigate the effect of the symbol sequence length and the number of estimated DCT coefficients on the estimation accuracy and on the corresponding bit error rate (BER). We propose a pilot symbol configuration allowing to estimate any number of DCT coefficients not exceeding the number of pilot symbols. For large block sizes, the DCT-based estimation algorithm substantially outperforms algorithms that estimate only the time-average or the linear trend of the carrier phase

Pilot-aided carrier synchronization using an approximate DCT-based phase noise model

This contribution deals with phase noise estimation from pilot symbols. The phase noise process is approximated by an expansion of DCT basis functions containing only a few terms. We propose an algorithm that estimates the DCT coefficients without requiring detailed knowledge about the phase noise statistics. We demonstrate that the resulting (linearized) mean-square estimation error consists of two contributions: a contribution from the additive noise, that equals the Cramer-Rao lower bound, and a noise-independent contribution that results from the phase noise modeling error. Performance can be optimized by a proper selection of the symbol block length and of the number of DCT coefficients to be estimated. For large block sizes, considerable performance improvement is found as compared to the case where only the time-average of the carrier phase is estimated

Ages of Type Ia Supernovae Over Cosmic Time

We derive empirical models for galaxy mass assembly histories, and convolve these with theoretical delay time distribution (DTD) models for Type Ia supernovae (SNe Ia) to derive the distribution of progenitor ages for all SNe Ia occurring at a given epoch of cosmic time. In actively star-forming galaxies, the progression of the star formation rate is shallower than a $t^{-1}$ SN Ia DTD, so mean SN Ia ages peak at the DTD peak in all star-forming galaxies at all epochs of cosmic history. In passive galaxies which have ceased star formation through some quenching process, the SN Ia age distribution peaks at the quenching epoch, which in passive galaxies evolves in redshift to track the past epoch of major star formation. Our models reproduce the SN Ia rate evolution in redshift, the relationship between SN Ia stretch and host mass, and the distribution of SN Ia host masses in a manner qualitatively consistent with observations. Our model naturally predicts that low-mass galaxies tend to be actively star-forming while massive galaxies are generally passive, consistent with observations of galaxy "downsizing". Consequently, the mean ages of SNe Ia undergo a sharp transition from young ages at low host mass to old ages at high host mass, qualitatively similar to the transition of mean SN Ia Hubble residuals with host mass. The age discrepancy evolves with redshift in a manner currently not accounted for in SN Ia cosmology analyses. We thus suggest that SNe Ia selected only from actively star-forming galaxies will yield the most cosmologically uniform sample, due to the homogeneity of young SN Ia progenitor ages at all cosmological epochs.Comment: 15 pages, 15 figures, accepted for publication in MNRA

Weed flora, yield losses and weed control in cotton crop

Cotton (Gossypium spp.) is the most important fiber crop of world and provides fiber, oil, and animals meals. Weeds interfere with the growth activities of cotton plants and compete with it for resources. All kinds of weeds (grasses, sedges, and broadleaves) have been noted to infest cotton crop. Weeds can cause more than 30% decrease in cotton productivity. Several methods are available for weed control in cotton. Cultural control carries significance for weed control up to a certain extent. However, mechanical control and chemical control are the backbone of weed management plans in cotton crop. Use of allelopathy has also been found effective for suppressing weeds in cotton. Allelopathy used in several forms (such as intercropping, mulches, and crop rotation) contributes to weed control in cotton crop. All of these weed management practices may be integrated to achieve economical and sustainable weed control in cotton with an ultimate result of improved weed control, productivity, quality of produce in cotton crop.Unkrautflora, Ertragsverluste und Unkrautkontrolle in BaumwolleBaumwolle (Gossypium spp.) ist die bedeutsamste Faserpflanze der Welt und dient als Faser-, Öl- und Tiernahrungsquelle. Unkräuter beeinträchtigen das Wachstum der Baumwollpflanzen indem sie mit den Pflanzen um essentielle Ressourcen konkurrieren. Verschiedene Unkrautarten (Gräser, Seggen und dikotyle Arten) sind in Baumwolle bekannt und können zu Ertragsverlusten von mehr als 30 % führen. Für die Unkrautkontrolle in Baumwolle stehen verschiedene Verfahren zur Verfügung. Die Anwendung von ackerbaulichen Maßnahmen kann zu einem gewissen Teil zur Unkrautbekämpfung beitragen. Mechanische und chemische Verfahren werden aber als die wichtigsten Maßnahmen zur Unkrautkontrolle in Baumwolle angesehen. Auch der Einsatz von allelopathischen Einflüssen kann als wirkungsvolle Maßnahme eingestuft werden. Allelopathie kann in verschiedenen Formen (Zwischenfrüchte, Mulch and Fruchtfolge) genutzt werden und so zur Unkrautkontrolle in Baumwolle beitragen. Um eine ökonomische und nachhaltige Unkrautbekämpfung in Baumwolle sicherzustellen, sollten alle genannten Verfahren gemeinsam eingesetzt werden. Nur so kann das Ziel einer verbesserten Unkrautkontrolle, einer erhöhten Produktivität und einer verbesserter Qualität der Baumwolle erreicht werden

Optimization of pilot-aided DCT-based phase noise estimation

The presented work addresses the issue of phase noise estimation for pilot-aided burst-mode transmission in digital communication systems. We propose to estimate the phase noise from a truncated discrete-cosine transform (DCT) expansion model. The key idea is to reconstruct the low-pass phase noise process via only a small number N of DCT coefficients of the phase expansion. An evident question that arises is how to choose N. Based on a few valid approximations, we derive an analytical expression of the bit-error rate (BER) degradation in the presence of residual phase noise, which allows us to determine the value of N that yields the minimum BER degradation