155 research outputs found
Capacity Bounds for Communication Systems with Quantization and Spectral Constraints
Low-resolution digital-to-analog and analog-to-digital converters (DACs and
ADCs) have attracted considerable attention in efforts to reduce power
consumption in millimeter wave (mmWave) and massive MIMO systems. This paper
presents an information-theoretic analysis with capacity bounds for classes of
linear transceivers with quantization. The transmitter modulates symbols via a
unitary transform followed by a DAC and the receiver employs an ADC followed by
the inverse unitary transform. If the unitary transform is set to an FFT
matrix, the model naturally captures filtering and spectral constraints which
are essential to model in any practical transceiver. In particular, this model
allows studying the impact of quantization on out-of-band emission constraints.
In the limit of a large random unitary transform, it is shown that the effect
of quantization can be precisely described via an additive Gaussian noise
model. This model in turn leads to simple and intuitive expressions for the
power spectrum of the transmitted signal and a lower bound to the capacity with
quantization. Comparison with non-quantized capacity and a capacity upper bound
that does not make linearity assumptions suggests that while low resolution
quantization has minimal impact on the achievable rate at typical parameters in
5G systems today, satisfying out-of-band emissions are potentially much more of
a challenge.Comment: Appears in the Proceedings of IEEE International Symposium on
Information Theory (ISIT) 202
On Optimal Multi-user Beam Alignment in Millimeter Wave Wireless Systems
Directional transmission patterns (a.k.a. narrow beams) are the key to
wireless communications in millimeter wave (mmWave) frequency bands which
suffer from high path loss and severe shadowing. In addition, the propagation
channel in mmWave frequencies incorporates only a few number of spatial
clusters requiring a procedure to align the corresponding narrow beams with the
angle of departure (AoD) of the channel clusters. The objective of this
procedure, called beam alignment (BA) is to increase the beamforming gain for
subsequent data communication. Several prior studies consider optimizing BA
procedure to achieve various objectives such as reducing the BA overhead,
increasing throughput, and reducing power consumption. While these studies
mostly provide optimized BA schemes for scenarios with a single active user,
there are often multiple active users in practical networks. Consequently, it
is more efficient in terms of BA overhead and delay to design multi-user BA
schemes which can perform beam management for multiple users collectively. This
paper considers a class of multi-user BA schemes where the base station
performs a one shot scan of the angular domain to simultaneously localize
multiple users. The objective is to minimize the average of expected width of
remaining uncertainty regions (UR) on the AoDs after receiving users'
feedbacks. Fundamental bounds on the optimal performance are analyzed using
information theoretic tools. Furthermore, a beam design optimization problem is
formulated and a practical BA scheme, which provides significant gains compared
to the beam sweeping used in 5G standard is proposed
Improvement of knowledge, attitude and perception of healthcare workers about ADR, a pre- and post-clinical pharmacists' interventional study
Purpose: Healthcare workers have a main role in detection, assessment and spontaneous reporting of adverse drug reactions (ADRs), and improvement of their related knowledge, attitude and perception is essential. The goal of this study was evaluation of clinical pharmacists' interventions in improvement of knowledge, attitude and perception of healthcare workers about ADRs in a teaching referral hospital, Tehran, Iran. Method: Changes in knowledge, attitude and perception of healthcare workers of Imam teaching hospital about ADRs were evaluated before and after clinical pharmacists' interventions including workshops, meetings and presentations. Results: From the 100 participated subjects, 82 of them completed the study. 51 of the health workers have been aware of the Iranian Pharmacovigilance Center at the ministry of health before intervention and after that all the participants knew this centre. About awareness and detection of ADRs in patients, 69 (84.1) healthcare workers recognised at least one, and following interventions, it was improved to 73 (89). Only seven (8.5) subjects have reported ADRs in before intervention phase that were increased significantly to 18 (22) after intervention. Conclusion: Clinical pharmacists' interventions were successful in improvement of healthcare workers' knowledge, attitude and perception about ADRs and spontaneous reporting in our hospital
Gamma-Normal-Gamma Mixture Model for Detecting Differentially Methylated Loci in Three Breast Cancer Cell Lines
With state-of-the-art microarray technologies now available for whole genome CpG island (CGI) methylation profiling, there is a need to develop statistical models that are specifically geared toward the analysis of such data. In this article, we propose a Gamma-Normal-Gamma (GNG) mixture model for describing three groups of CGI loci: hypomethylated, undifferentiated, and hypermethylated, from a single methylation microarray. This model was applied to study the methylation signatures of three breast cancer cell lines: MCF7, T47D, and MDAMB361. Biologically interesting and interpretable results are obtained, which highlights the heterogeneity nature of the three cell lines. This underlies the premise for the need of analyzing each of the microarray slides individually as opposed to pooling them together for a single analysis. Our comparisons with the fitted densities from the Normal-Uniform (NU) mixture model in the literature proposed for gene expression analysis show an improved goodness of fit of the GNG model over the NU model. Although the GNG model was proposed in the context of single-slide methylation analysis, it can be readily adapted to analyze multi-slide methylation data as well as other types of microarray data
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