12 research outputs found
Cdma blind channel equalization: a weighted subsface a proach
This paper considers the problem of blind demodulation of multiuser information symbols in a direct-sequence code-division multiple access (DS-CDMA) environment. Channel estimation and symbol detection in the presence of both multiple access interference (MAI) and intersymbol interference (ISI) is carried out with second order statistics methods from the received data. This problem is similar to direction of arrival (DOA) estimation, where many solutions like the MUSIC algorithm orPeer ReviewedPostprint (published version
Blind channel equalization using weighted subspace methods
This paper addresses the problems of blind channel estimation and symbol detection with second order statistics methods from the received data. It can be shown that this problem is similar to direction of arrival (DOA) estimation, where many solutions like the MUSIC algorithm orPeer ReviewedPostprint (published version
Symbol decoding based on signal subspace decomposition in msk
The availability of fast processors with architectures tailored to meet the computational demand of digital signal processing algorithms is widely applied to demodulation and decodification of CPM signals in some scenes: Mobiles, AWGN channels,… In this application the number of floating point operations executed by each processed symbol is a critical parameter to be designed, this is to be minimized. In this paper a method that reduces significantly the number of operations (until 80%) by symbol for CPM signals is presented. The decodification stage is performed from the rank reduced signal subspace obtained by means of an orthogonal decomposition of the signal [1].Peer ReviewedPostprint (published version
Effectiveness of an intervention for improving drug prescription in primary care patients with multimorbidity and polypharmacy:Study protocol of a cluster randomized clinical trial (Multi-PAP project)
This study was funded by the Fondo de Investigaciones Sanitarias ISCIII (Grant Numbers PI15/00276, PI15/00572, PI15/00996), REDISSEC (Project Numbers RD12/0001/0012, RD16/0001/0005), and the European Regional Development Fund ("A way to build Europe").Background: Multimorbidity is associated with negative effects both on people's health and on healthcare systems. A key problem linked to multimorbidity is polypharmacy, which in turn is associated with increased risk of partly preventable adverse effects, including mortality. The Ariadne principles describe a model of care based on a thorough assessment of diseases, treatments (and potential interactions), clinical status, context and preferences of patients with multimorbidity, with the aim of prioritizing and sharing realistic treatment goals that guide an individualized management. The aim of this study is to evaluate the effectiveness of a complex intervention that implements the Ariadne principles in a population of young-old patients with multimorbidity and polypharmacy. The intervention seeks to improve the appropriateness of prescribing in primary care (PC), as measured by the medication appropriateness index (MAI) score at 6 and 12months, as compared with usual care. Methods/Design: Design:pragmatic cluster randomized clinical trial. Unit of randomization: family physician (FP). Unit of analysis: patient. Scope: PC health centres in three autonomous communities: Aragon, Madrid, and Andalusia (Spain). Population: patients aged 65-74years with multimorbidity (≥3 chronic diseases) and polypharmacy (≥5 drugs prescribed in ≥3months). Sample size: n=400 (200 per study arm). Intervention: complex intervention based on the implementation of the Ariadne principles with two components: (1) FP training and (2) FP-patient interview. Outcomes: MAI score, health services use, quality of life (Euroqol 5D-5L), pharmacotherapy and adherence to treatment (Morisky-Green, Haynes-Sackett), and clinical and socio-demographic variables. Statistical analysis: primary outcome is the difference in MAI score between T0 and T1 and corresponding 95% confidence interval. Adjustment for confounding factors will be performed by multilevel analysis. All analyses will be carried out in accordance with the intention-to-treat principle. Discussion: It is essential to provide evidence concerning interventions on PC patients with polypharmacy and multimorbidity, conducted in the context of routine clinical practice, and involving young-old patients with significant potential for preventing negative health outcomes. Trial registration: Clinicaltrials.gov, NCT02866799Publisher PDFPeer reviewe
Decodificación de simbolo basada en sva para identificacion ciega de canal como reformacion lateral en el algoritmo de viterb
Peer ReviewedPostprint (published version
Cdma blind channel equalization: a weighted subsface a proach
This paper considers the problem of blind demodulation of multiuser information symbols in a direct-sequence code-division multiple access (DS-CDMA) environment. Channel estimation and symbol detection in the presence of both multiple access interference (MAI) and intersymbol interference (ISI) is carried out with second order statistics methods from the received data. This problem is similar to direction of arrival (DOA) estimation, where many solutions like the MUSIC algorithm orPeer Reviewe
Symbol decoding based on signal subspace decomposition in MSK
The availability of fast processors with architectures tailored
to meet the computational demand of digital signal
processing algorithms is widely applied to demodulation
and decodification of CPM signals in some scenes: Mobiles,
AWGN channels,... In this application the number of
floating point operations executed by each processed
symbol is a critical parameter to be designed, this is to be
minimized. In this paper a method that reduces significantly
the number of operations (until 80%) by symbol for CPM
signals is presented. The decodification stage is performed
from the rank reduced signal subspace obtained by means of
an orthogonal decomposition of the signal [1].Peer Reviewe
Symbol decoding based on signal subspace decomposition in msk
The availability of fast processors with architectures tailored to meet the computational demand of digital signal processing algorithms is widely applied to demodulation and decodification of CPM signals in some scenes: Mobiles, AWGN channels,… In this application the number of floating point operations executed by each processed symbol is a critical parameter to be designed, this is to be minimized. In this paper a method that reduces significantly the number of operations (until 80%) by symbol for CPM signals is presented. The decodification stage is performed from the rank reduced signal subspace obtained by means of an orthogonal decomposition of the signal [1].Peer Reviewe
Blind channel equalization using weighted subspace methods
This paper addresses the problems of blind channel estimation and symbol detection with second order statistics methods from the received data. It can be shown that this problem is similar to direction of arrival (DOA) estimation, where many solutions like the MUSIC algorithm orPeer Reviewe