Distributed primary user identification from imprecise location information

We study a cognitive radio scenario in which the network of sec- ondary users wishes to identify which primary user, if any, is trans- mitting. To achieve this, the nodes will rely on some form of location information. In our previous work we proposed two fully distributed algorithms for this task, with and without a pre-detection step, using propagation parameters as the only source of location information. In a real distributed deployment, each node must estimate its own po- sition and/or propagation parameters. Hence, in this work we study the effect of uncertainty, or error in these estimates on the proposed distributed identification algorithms. We show that the pre-detection step significantly increases robustness against uncertainty in nodes' locations

Location-aided Distributed Primary User Identification in a Cognitive Radio Scenario

We address a cognitive radio scenario, where a number of secondary users performs identification of which primary user, if any, is transmitting, in a distributed way and using limited location information. We propose two fully distributed algorithms: the first is a direct identification scheme, and in the other a distributed sub-optimal detection based on a simplified Neyman-Pearson energy detector precedes the identification scheme. Both algorithms are studied analytically in a realistic transmission scenario, and the advantage obtained by detection pre-processing is also verified via simulation. Finally, we give details of their fully distributed implementation via consensus averaging algorithms.Comment: Submitted to IEEE ICASSP201

Biochemical failure and toxicity in treatment with brachytherapy and external beam radiotherapy compared with radical prostatectomy in localized prostate cancer

Antecedentes: El cáncer de próstata localizado (T1-3N0M0) tiene opciones terapéuticas como la prostatectomía radical (PR), la radioterapia de haz externo (EBRT) y la braquiterapia (BT). Sin embargo, la evidencia de los resultados de estos tratamientos es limitada y no se han realizado estudios que comparen el Falla Bioquímica (FB) y la toxicidad asociada al tratamiento quirúrgico y a la EBRT + Braquiterapia de alta dosis (HDBT) en la región. Material y Métodos: Estudio de cohorte retrospectivo, se revisaron las historias clínicas de los pacientes diagnosticados con cáncer de próstata localizado entre 2014 y 2018 en uno de los principales centros privados de neoplasias de Lima, Perú; se utilizó la regresión de Cox tanto para el resultado de BF como para el resultado de toxicidad grado 2, calculando el HR con IC 95%. Resultados: De 549 pacientes, el 76,3% (419) recibió RP como tratamiento primario, y el 72% tenía entre 50 y 70 años en el momento del diagnóstico. Los pacientes tratados con EBRT + HDBT presentaron peores características. El grupo de EBRT + HDBT tuvo un 40% menos de riesgo de presentar FB (HR 0,6; IC 95% 0,4 - 0,9), y también un 50% más de riesgo de presentar toxicidad mayor o igual a grado 2 (HR 1,5; IC 95% 1,0 - 2,0) que el grupo tratado con RP. Conclusión: Nuestros resultados muestran que al comparar los pacientes tratados con EBRT + HDBT y RP, el BF fue mayor en RP, y la toxicidad post-tratamiento fue mayor en EBRT + HDBT. Sin embargo, ambos grupos de comparacion no son homogéneos por lo que la comparacion no puede ser objetiva.Background: Localized prostate cancer (T1-3N0M0) has therapeutic options such as Radical Prostatectomy (RP), external beam radiation therapy (EBRT) and Brachytherapy (BT). However, the evidence of the outcome of these treatments is limited and no studies have been conducted comparing Biochemical Failure (BF) and toxicity associated with surgical treatment and EBRT + High-Dose Brachytherapy (HDBT) in the region. Methods and Materials: Retrospective cohort study, clinical records of patients diagnosed with localized prostate cancer between 2014 and 2018 were reviewed at one of the main private neoplasm centers in Lima, Peru; Cox regression was used for both the BF outcome and the grade 2 toxicity outcome, calculating the HR with 95% CI. Results: Of 549 patients, 76.3% (419) received RP as primary treatment, and 72% were between 50 and 70 years old at the time of diagnosis. The patients treated with EBRT + HDBT presented worse characteristics. The EBRT + HDBT group had a 40% lower risk of presenting BF (HR 0.6; 95% CI 0.4 - 0.9), and also a 50% greater risk of presenting toxicity greater than or equal to grade 2 (HR 1.5; CI 95% 1.0 - 2.0) than the group treated with RP. Conclusion: Our results show that when comparing patients treated with EBRT + HDBT and RP, BF was greater in RP, and post-treatment toxicity was greater in EBRT + HDBT. However, both comparison groups are not homogeneous, so the comparison cannot be objective.Tesi

Improved Animal Tracking Algorithm using Distributed Kalman Filter-based Algortihms

Animal tracking has been addressed by different initiatives over the last two decades. Most of them rely on satellite connectivity on every single node and lack of energy-saving strategies. This paper presents several new contributions on the tracking of dynamic heterogeneous asynchronous networks (primary nodes with GPS and secondary nodes with a kinetic generator) motivated by the animal tracking paradigm with random transmissions. A simple approach based on connectivity and coverage intersection is compared with more sophisticated algorithms based on ad-hoc implementations of distributed Kalman-based filters that integrate measurement information using Consensus principles in order to provide enhanced accuracy. Several simulations varying the coverage range, the random behavior of the kinetic generator (modeled as a Poisson Process) and the periodic activation of GPS are included. In addition, this study is enhanced with HW developments and implementations on commercial off-the-shelf equipment which show the feasibility for performing these proposals on real hardware

A Multipurpose Testbed for Full-Duplex Wireless Communications

Unlike in the traditional half-duplex (HD) mode of transmission over a wireless link, in the full-duplex (FD) mode both terminals receive and transmit on the same frequency band, simultaneously. Hence, FD gives us up to twice the spectral efficiency of HD, has the potential to resolve the hidden terminal problem, and makes relaying much more efficient. As such, FD is one of the most promising new physical layer techniques being developed at the moment. However, a major difficulty in achieving FD operation is that it requires cancelation of self-interference. In this demonstration, we show various methods of operating in FD mode, offering live, interactive, and visual insight into the operation of the link. The parameters shown include the power budget, signal-to-interference-and-noise ratio, frequency spectrum, constellation graphs, and bit error rate. We compare the operation of the same link in HD and FD mode, highlight the effect of each type of cancelation, as well as show what happens when self-interference is not mitigated at all

Effects of the COVID-19 pandemic on the prevalence of obsessive-compulsive symptoms among young adults in Peru

The COVID-19 pandemic has exposed the general population to constant stressful and traumatic situations. This, added to the necessary and constant dissemination of preventive measures for COVID-19 infection, can generate an increase in the prevalence of Obsessive-Compulsive (OC) symptoms. Thus, this research aimed to evaluate the prevalence of OC symptoms and explore associated factors in young adults in Peru, the country with the highest COVID-19 death rate in the world. In this analytical cross-sectional study, an online survey distributed through social networks was used. OC symptomatology during the last week was measured by the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). Possible Generalized Anxiety Disorder (GAD) and Major Depressive Disorder (MDD) were evaluated with the General Anxiety Disorder 7-items (GAD-7) and Patient Health Questionnaire-9 (PHQ-9), respectively. 1243 young adults were evaluated. Of these, the mean age was 24.1 years, 54.3% were women, and the prevalence of OC symptoms was 50%. Participants who had experienced a traumatic event during COVID-19 pandemic had higher prevalence of OC symptoms (PR 1.54; CI 95% 1.27 – 1.85), when compared to those did not experience such events. In the same way, participants diagnosed with depression (PR 2.37; CI 95% 1.96 – 2.86) and anxiety (PR 1.11; CI 95% 1.02 – 1.21) also had a higher prevalence of OC symptoms, compared with those without depression and anxiety. In conclusion, obsessive-compulsive symptomatology has a high prevalence in young adults, and is associated with the death of a family member or close friend from the COVID-19 disease. The prevalence of possible depression and anxiety are high and are associated with higher prevalence of obsessive-compulsive symptoms. This highlights the importance of including mental health programs during the pandemic for the population who has suffered traumatic events, to be able to give them adequate follow-up and support.Revisión por pare

On Self-interference Suppression Methods for Low-complexity Full-duplex MIMO

Full-duplex wireless communication offers improved spectral efficiency, as well as more efficient relaying and medium access, but requires suppression of self-interference. In this paper we analyze the existing methods for active RF suppression and use the ”Rice architecture” for its low complexity and favorable scaling when applied to multi-antenna systems. We analyze the effects of the different sources of self-interference and quantify the potential for further suppression (genie-aided suppression). Our single-chain implementation using a circulator achieves −48 dB of active RF suppression, but only −66 dB of total suppression in the analog domain. On the other hand, our single-chain implementation using separate antennae reaches −85 dB of total analog suppression, thus reducing the self-interference to the noise floor. Extending these setups, we present a low complexity implementation of a 2 × 2 full-duplex MIMO node, which achieves even higher suppression than the single-chain counterparts

Distributed static linear Gaussian models using consensus

Algorithms for distributed agreement are a powerful means for formulating distributed versions of existing centralized algorithms. We present a toolkit for this task and show how it can be used systematically to design fully distributed algorithms for static linear Gaussian models, including principal component analysis, factor analysis, and probabilistic principal component analysis. These algorithms do not rely on a fusion center, require only low-volume local (1-hop neighborhood) communications, and are thus efficient, scalable, and robust. We show how they are also guaranteed to asymptotically converge to the same solution as the corresponding existing centralized algorithms. Finally, we illustrate the functioning of our algorithms on two examples, and examine the inherent cost-performance tradeoff