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.

ML estimator and hybrid beamformer for multipath and interference mitigation in GNSS receivers

This paper addresses the estimation of the code-phase(pseudorange) and the carrier-phase of the direct signal received from a direct-sequence spread-spectrum satellite transmitter. Thesignal is received by an antenna array in a scenario with interferenceand multipath propagation. These two effects are generallythe limiting error sources in most high-precision positioning applications.A new estimator of the code- and carrier-phases is derivedby using a simplified signal model and the maximum likelihood(ML) principle. The simplified model consists essentially ofgathering all signals, except for the direct one, in a component withunknown spatial correlation. The estimator exploits the knowledgeof the direction-of-arrival of the direct signal and is much simplerthan other estimators derived under more detailed signal models.Moreover, we present an iterative algorithm, that is adequate for apractical implementation and explores an interesting link betweenthe ML estimator and a hybrid beamformer. The mean squarederror and bias of the new estimator are computed for a numberof scenarios and compared with those of other methods. The presentedestimator and the hybrid beamforming outperform the existingtechniques of comparable complexity and attains, in manysituations, the Cramér–Rao lower bound of the problem at hand.

Contribuição da densidade do PSA para predizer o câncer da próstata em pacientes com valores de PSA entre 2,6 e 10,0 ng/ml

OBJETIVO: Estudar o perfil dos pacientes submetidos a biópsia prostática, determinando possíveis padrões que, associados aos níveis de PSA entre 2,6 e 10,0 ng/ml, possam levar a uma diminuição de biópsias desnecessárias. MATERIAIS E MÉTODOS: De 2007 a 2009, foi realizado um estudo transversal com 1.282 indivíduos submetidos a biópsia prostática e que apresentavam níveis de PSA entre 2,6 e 10,0 ng/ml. RESULTADOS: A prevalência de câncer foi de 28,6%. Pacientes com câncer eram, em média, mais idosos, com valores de PSA e densidade de PSA mais altos e menor volume da próstata. Na análise da densidade de PSA, os pacientes com câncer tiveram média de 0,31 ng/ml/cc, enquanto nos pacientes com resultado negativo a média foi de 0,10 ng/ml/cc. Utilizando como critério de positividade para câncer o ponto de corte de densidade de PSA de 0,15 ng/ml/cc, obtivemos especificidade de 74% e sensibilidade de 70%. Para aumentar a sensibilidade é preciso reduzir o ponto de corte. Com o valor 0,09 ng/ml/cc, obtivemos sensibilidade de 84% (IC 95%: 80-87%) e especificidade de 75% (IC 95%: 72-78%). CONCLUSÃO: O uso sistemático da densidade de PSA na indicação de prosseguimento da investigação do paciente com biópsia poderia reduzir a quantidade de procedimentos desnecessários.

Pulmonary 64-MDCT angiography with 50 mL of iodinated contrast material in an unselected patient population: a feasible protocol

Abstract Objective: To propose a protocol for pulmonary angiography using 64-slice multidetector computed tomography (64-MDCT) with 50 mL of iodinated contrast material, in an unselected patient population, as well as to evaluate vascular enhancement and image quality. Materials and Methods: We evaluated 29 patients (22-86 years of age). The body mass index ranged from 19.0 kg/m2 to 41.8 kg/m2. Patients underwent pulmonary CT angiography in a 64-MDCT scanner, receiving 50 mL of iodinated contrast material via venous access at a rate of 4.5 mL/s. Bolus tracking was applied in the superior vena cava. Two experienced radiologists assessed image quality and vascular enhancement. Results: The mean density was 382 Hounsfield units (HU) for the pulmonary trunk; 379 and 377 HU for the right and left main pulmonary arteries, respectively; and 346 and 364 HU for the right and left inferior pulmonary arteries, respectively. In all patients, subsegmental arteries were analyzed. There were streak artifacts from contrast material in the superior vena cava in all patients. However, those artifacts did not impair the image analysis. Conclusion: Our findings suggest that pulmonary angiography using 64-MDCT with 50 mL of iodinated contrast can produce high quality images in unselected patient populations.

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