The Gaussian assumption in second-order estimation problems in digital communications

This paper deals with the goodness of the Gaussian assumption when designing second-order blind estimationmethods in the context of digital communications. The low- andhigh-signal-to-noise ratio (SNR) asymptotic performance of the maximum likelihood estimator—derived assuming Gaussiantransmitted symbols—is compared with the performance of the optimal second-order estimator, which exploits the actualdistribution of the discrete constellation. The asymptotic study concludes that the Gaussian assumption leads to the optimalsecond-order solution if the SNR is very low or if the symbols belong to a multilevel constellation such as quadrature-amplitudemodulation (QAM) or amplitude-phase-shift keying (APSK). On the other hand, the Gaussian assumption can yield importantlosses at high SNR if the transmitted symbols are drawn from a constant modulus constellation such as phase-shift keying (PSK)or continuous-phase modulations (CPM). These conclusions are illustrated for the problem of direction-of-arrival (DOA) estimation of multiple digitally-modulated signals.

The IST METRA Project

This article summarizes the main achievementsof the Multi-Element Transmit andReceive Antennas (METRA) Project, an ISTresearch and technological development project carried out between January 2000 and June 2001 by Universitat Politècnica de Catalunya, the Center for Personkommunikation of Aalborg University, Nokia Networks, Nokia Mobile Phones, and Vodafone Group Research and Development.The main objective of METRA was the performanceevaluation of multi-antenna terminals incombination with adaptive antennas at the basestation in UMTS communication systems. 1 AMIMO channel sounder was developed that providedrealistic multi-antenna channel measurements.Using these measured data, stochasticchannel models were developed and properly validated.These models were also evaluated inorder to estimate their corresponding channelcapacity. Different MIMO configurations andprocessing schemes were developed for both theFDD and TDD modes of UTRA, and their linkperformance was assessed. Performance evaluationwas completed by system simulations thatillustrated the benefits of MIMO configurationsto the network operator. Implementation cost vs.performance improvement was also covered bythe project, including the base station and terminalmanufacturer and network operator viewpoints.Finally, significant standards contributionswere generated by the project and presented to the pertinent 3GPP working groups.

ML approaches to channel estimation for pilot-aided multi-rate DS/CDMA systems

This paper analyzes the asymptotic performance of maximum likelihood (ML) channel estimation algorithms in wideband code division multiple access (WCDMA) scenarios. We concentrate on systems with periodic spreading sequences (period larger than or equal to the symbol span) where the transmitted signal contains a code division multiplexed pilot for channel estimation purposes. First, the asymptotic covariances of the training-only, semi-blind conditional maximum likelihood (CML) and semi-blind Gaussian maximum likelihood (GML) channelestimators are derived. Then, these formulas are further simplified assuming randomized spreading and training sequences under the approximation of high spreading factors and high number of codes. The results provide a useful tool to describe the performance of the channel estimators as a function of basicsystem parameters such as number of codes, spreading factors, or traffic to training power ratio.

On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation

In this paper, the theory of hidden Markov models (HMM) isapplied to the problem of blind (without training sequences) channel estimationand data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedureassumes the model (i.e., the channel response) to be static throughoutthe observation sequence. By means of introducing a parametric model fortime-varying channel responses, a version of the algorithm, which is moreappropriate for mobile channels [time-dependent Baum-Welch (TDBW)] isderived. Aiming to compare algorithm behavior, a set of computer simulationsfor a GSM scenario is provided. Results indicate that, in comparisonto other Baum–Welch (BW) versions of the algorithm, the TDBW approachattains a remarkable enhancement in performance. For that purpose, onlya moderate increase in computational complexity is needed.

Blind channel estimation and data detection using hidden Markov models theory

In this correspondence, we propose applying the hiddenMarkov models (HMM) theory to the problem of blind channel estimationand data detection. The Baum–Welch (BW) algorithm, which is able toestimate all the parameters of the model, is enriched by introducingsome linear constraints emerging from a linear FIR hypothesis on thechannel. Additionally, a version of the algorithm that is suitable for timevaryingchannels is also presented. Performance is analyzed in a GSMenvironment using standard test channels and is found to be close to thatobtained with a nonblind receiver.

Asymptotic equivalence between the unconditional maximum likelihood and the square-law nonlinearity symbol timing estimation

This paper provides a systematic approach to theproblem of nondata aided symbol-timing estimation for linearmodulations. The study is performed under the unconditionalmaximum likelihood framework where the carrier-frequencyerror is included as a nuisance parameter in the mathematicalderivation. The second-order moments of the received signal arefound to be the sufficient statistics for the problem at hand and theyallow the provision of a robust performance in the presence of acarrier-frequency error uncertainty. We particularly focus on theexploitation of the cyclostationary property of linear modulations.This enables us to derive simple and closed-form symbol-timingestimators which are found to be based on the well-known squaretiming recovery method by Oerder and Meyr. Finally, we generalizethe OM method to the case of linear modulations withoffset formats. In this case, the square-law nonlinearity is foundto provide not only the symbol-timing but also the carrier-phaseerror.

Motion estimation using higher-order statistics

The objective of this paper is to introduce a fourth-order cost function of the displaced frame difference (DFD) capable of estimatingmotion even for small regions or blocks. Using higher than second-orderstatistics is appropriate in case the image sequence is severely corruptedby additive Gaussian noise. Some results are presented and compared to those obtained from the mean kurtosis and the mean square error of the DFD.

Biotechnology in Lausanne: the Rh D project.

Hemolytic disease of the newborn is an often fatal condition of some newborn babies due to the immunogenicity of their Rh D positive erythrocytes in the Rh D negative mother. This condition can be prevented by injecting anti-Rh D antibodies. The current source of these antibodies is blood from immunized human donors. In order to avoid problems with limited supply and donor safety, the Rh D project was set up to develop recombinant monoclonal anti-Rh D antibodies as a possible replacement. In a multidisciplinary collaboration between the Zentrallaboratorium Blutspendedienst (ZlB) of the Swiss Red Cross, the Center of Biotechnology of the University and the EPFL (CBUE), and the Institute of Chemical and Biochemical Engineering (EPFl), co-funded by the Swiss National Science Foundation and ZLB, a candidate monoclonal anti-Rh D antibody has been selected, expressed in CHO cells, and a manufacturing process for large-scale production has been developed.

Second-order parameter estimation

This work provides a general framework for the design of second-order blind estimators without adopting anyapproximation about the observation statistics or the a prioridistribution of the parameters. The proposed solution is obtainedminimizing the estimator variance subject to some constraints onthe estimator bias. The resulting optimal estimator is found todepend on the observation fourth-order moments that can be calculatedanalytically from the known signal model. Unfortunately,in most cases, the performance of this estimator is severely limitedby the residual bias inherent to nonlinear estimation problems.To overcome this limitation, the second-order minimum varianceunbiased estimator is deduced from the general solution by assumingaccurate prior information on the vector of parameters.This small-error approximation is adopted to design iterativeestimators or trackers. It is shown that the associated varianceconstitutes the lower bound for the variance of any unbiasedestimator based on the sample covariance matrix.The paper formulation is then applied to track the angle-of-arrival(AoA) of multiple digitally-modulated sources by means ofa uniform linear array. The optimal second-order tracker is comparedwith the classical maximum likelihood (ML) blind methodsthat are shown to be quadratic in the observed data as well. Simulationshave confirmed that the discrete nature of the transmittedsymbols can be exploited to improve considerably the discriminationof near sources in medium-to-high SNR scenarios.

NDA waveform estimation in the low-SNR regime

This correspondence addresses the problem of nondata-aidedwaveform estimation for digital communications. Based on the unconditionalmaximum likelihood criterion, the main contribution of this correspondenceis the derivation of a closed-form solution to the waveform estimationproblem in the low signal-to-noise ratio regime. The proposed estimationmethod is based on the second-order statistics of the received signaland a clear link is established between maximum likelihood estimation andcorrelation matching techniques. Compression with the signal-subspace isalso proposed to improve the robustness against the noise and to mitigatethe impact of abnormals or outliers.

Maximum likelihood estimation of position in GNSS

In this letter, we obtain the Maximum LikelihoodEstimator of position in the framework of Global NavigationSatellite Systems. This theoretical result is the basis of a completelydifferent approach to the positioning problem, in contrastto the conventional two-steps position estimation, consistingof estimating the synchronization parameters of the in-viewsatellites and then performing a position estimation with thatinformation. To the authors’ knowledge, this is a novel approachwhich copes with signal fading and it mitigates multipath andjamming interferences. Besides, the concept of Position–basedSynchronization is introduced, which states that synchronizationparameters can be recovered from a user position estimation. Weprovide computer simulation results showing the robustness ofthe proposed approach in fading multipath channels. The RootMean Square Error performance of the proposed algorithm iscompared to those achieved with state-of-the-art synchronizationtechniques. A Sequential Monte–Carlo based method is used todeal with the multivariate optimization problem resulting fromthe ML solution in an iterative way.

Offering planning with support of roadmapping in project business

Tämän tutkielman tavoitteena on tutkia kuinka roadmapping-tekniikkaa voidaan käyttää tarjonnan suunnittelun tukena uusien tuotteiden valmistamisen yhteydessä. Työ koostuu teoreettisesta ja käytännönläheisestä osasta. Teoreettinen runko on luotu selventämään kuinka tämän hetkisen tutkimus- ja kehitys projektit lopulta muodostavat tulevaisuuden tarjoaman. Menestyksekkään tuotetarjoaman luominen vaatii, sekä uusien teknologioiden kehittämistä, että markkinoilla olevien asiakkaiden tarpeiden ymmärtämistä. Asiakassuuntaisten tuotteiden kehittäminen vaatii toimintaympäristöstä ja asiakasrajapinnasta tulevien signaalien tunnistamista ja niiden ohjaamista tuote- ja teknologia platformeille. Strategia luodaan tukemaan päätöksentekoa prosessin eri vaiheissa. Yrityskohtainen osio koostuu analyysistä, joka on tehty teetetyn kyselyn ja haas-tattelujen pohjalta. Osana analyysia ovat Major project-yksikön tämänhetkinen tarjonnansuunnitteluprosessi, strategian soveltaminen, informaation kerääminen ja priorisointi, portfolionhallinta ja roadmap-tekniikan käyttö. Ratkaisussa on esitet-ty tarjonnan suunnitteluprosessi ja siihen liittyvät kriittiset komponentit. Roadmapping-tekniikkaaon luotu yhdistämään toimintaympäristö, tuotteet ja teknologia toisiinsa. Toimintaympäristö ja tuotteet on yhdistetty myös linked-grids-tekniikan avulla.

Project SKY-EYE: applying UAVs to forest fire fighter support and monitoring

Peer reviewed

Using tools to help cost estimating and pricing: examination of costing model's and cost breakdown's workability and their capability to cooperative work

Tämä diplomityö käsittelee työkaluja, jotka on suunniteltu kustannusten ennakointiin ja hinnan asetantaan. Aluksi on käyty läpi perinteisen ja toimintoperusteisen kustannuslaskennan perusteita. Näiden menetelmien välisiä eroja on tarkasteltu ja toimintoperusteisen kustannuslaskennan paremmin sopivuus nykypäivän yrityksille on perusteltu. Toisena käsitellään hinnoittelu. Hinnan merkitys, hinnoittelumenetelmät ja päätös lopullisesta hinnasta on käyty läpi. Hinnoittelun jälkeen esitellään kustannusjärjestelmät ja kustannusten arviointi. Nämä asiat todistavat, että tarkat kustannusarviot ovat elintärkeitä yritykselle. Tuotteen kustannusarviointi, hinnan asetanta ja tarjoaminen ovat erittäin merkityksellisiä asioita ottaen huomioon koko projektin elinkaaren ja tulevat tuotot. Nykyään on yleistä käyttää työkaluja kustannusarvioinnissa ja joskus myös hinnoittelussa. Työkalujen luotettavuus on tiedettävä, ennenkuin työkalut otetaan käyttöön. Myös työkalujen käyttäjät täytyy perehdyttää hyvin. Muuten yritys todennäköisesti kohtaa odottamattomia ja epämiellyttäviä yllätyksiä.