A novel delay dictionary design for compressive sensing-based time varying channel estimation in OFDM systems

Compressive sensing (CS) is a new attractive technique adopted for Linear Time Varying channel estimation. orthogonal frequency division multiplexing (OFDM) was proposed to be used in 4G and 5G which supports high data rate requirements. Different pilot aided channel estimation techniques were proposed to better track the channel conditions, which consumes bandwidth, thus, considerable data rate reduced. In order to estimate the channel with minimum number of pilots, compressive sensing CS was proposed to efficiently estimate the channel variations. In this paper, a novel delay dictionary-based CS was designed and simulated to estimate the linear time varying (LTV) channel. The proposed dictionary shows the suitability of estimating the channel impulse response (CIR) with low to moderate Doppler frequency shifts with acceptable bit error rate (BER) performance

Performance evaluation of high mobility OFDM channel estimation techniques

In wireless communication, Orthogonal Frequency Division Multiplexing (OFDM) has been adopted due to its robustness to multipath fading and high data rate transmissions. At the other hand, the performance of OFDM systems severely degraded due to multi-path fading and Doppler frequency shifts in mobile systems, which causes inter-carrier-interference (ICI). Thus, Estimation of channel parameters is required at the receiver using a pre designed estimator where pilot tones are inserted in each OFDM symbol. In this paper, a random pilot data are generated and inserted in each OFDM symbol at equally spaced locations. The performance test of Least Square (LS) and Linear Minimum Mean Square (LMMSE) estimation methods are proposed with Discrete Fourier Transform (DFT) based on both LS and LMMSE, where different ITU channel models are considered in order to compare their performance for data transmission in high mobile systems with different Doppler frequencies exceeds 200 Hz and minimal number of pilots

Fine-Grained Complexity of Analyzing Compressed Data: Quantifying Improvements over Decompress-And-Solve

Can we analyze data without decompressing it? As our data keeps growing, understanding the time complexity of problems on compressed inputs, rather than in convenient uncompressed forms, becomes more and more relevant. Suppose we are given a compression of size $n$ of data that originally has size $N$, and we want to solve a problem with time complexity $T(\cdot)$. The naive strategy of "decompress-and-solve" gives time $T(N)$, whereas "the gold standard" is time $T(n)$: to analyze the compression as efficiently as if the original data was small. We restrict our attention to data in the form of a string (text, files, genomes, etc.) and study the most ubiquitous tasks. While the challenge might seem to depend heavily on the specific compression scheme, most methods of practical relevance (Lempel-Ziv-family, dictionary methods, and others) can be unified under the elegant notion of Grammar Compressions. A vast literature, across many disciplines, established this as an influential notion for Algorithm design. We introduce a framework for proving (conditional) lower bounds in this field, allowing us to assess whether decompress-and-solve can be improved, and by how much. Our main results are: - The $O(nN\sqrt{\log{N/n}})$ bound for LCS and the $O(\min\{N \log N, nM\})$ bound for Pattern Matching with Wildcards are optimal up to $N^{o(1)}$ factors, under the Strong Exponential Time Hypothesis. (Here, $M$ denotes the uncompressed length of the compressed pattern.) - Decompress-and-solve is essentially optimal for Context-Free Grammar Parsing and RNA Folding, under the $k$-Clique conjecture. - We give an algorithm showing that decompress-and-solve is not optimal for Disjointness

{SETH}-Based Lower Bounds for Subset Sum and Bicriteria Path

Subset-Sum and k-SAT are two of the most extensively studied problems in computer science, and conjectures about their hardness are among the cornerstones of fine-grained complexity. One of the most intriguing open problems in this area is to base the hardness of one of these problems on the other. Our main result is a tight reduction from k-SAT to Subset-Sum on dense instances, proving that Bellman's 1962 pseudo-polynomial $O^{*}(T)$-time algorithm for Subset-Sum on $n$ numbers and target $T$ cannot be improved to time $T^{1-\varepsilon}\cdot 2^{o(n)}$ for any $\varepsilon>0$, unless the Strong Exponential Time Hypothesis (SETH) fails. This is one of the strongest known connections between any two of the core problems of fine-grained complexity. As a corollary, we prove a "Direct-OR" theorem for Subset-Sum under SETH, offering a new tool for proving conditional lower bounds: It is now possible to assume that deciding whether one out of $N$ given instances of Subset-Sum is a YES instance requires time $(N T)^{1-o(1)}$. As an application of this corollary, we prove a tight SETH-based lower bound for the classical Bicriteria s,t-Path problem, which is extensively studied in Operations Research. We separate its complexity from that of Subset-Sum: On graphs with $m$ edges and edge lengths bounded by $L$, we show that the $O(Lm)$ pseudo-polynomial time algorithm by Joksch from 1966 cannot be improved to $\tilde{O}(L+m)$, in contrast to a recent improvement for Subset Sum (Bringmann, SODA 2017)

Design of encrypted transceiver Non-coherent OFDM with ability to correct coding bits of information

A differential encrypted transceiver was designed in the signal-to-noise ratio systems. A time"-"spread" frequency-"encoded (TSFE) algorithm was proposed using the orthogonal frequency multiplexing multiplier OFDM. The proposed design was verified under the Doppler frequency effect and there was an improvement in the performance of the signal-to-noise ratio system. As a result, the reliability of decoded data was increased and achieves the ability to correct coding bits of information

A retrospective study of antibiotic resistance patterns of bacterial pathogens isolated from patients in two Lebanese hospitals for two consecutive years (2018 and 2019)

Background: Misuse of antibiotics is the leading factor promoting emergence of bacterial resistance, a situation that has become a serious public health challenge. Among the leading bacteria that have developed resistance to antibiotics are Staphylococcus aureus, Enterococcus faecalis, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa, which have caused infections in patients, resulting in considerable mortality. The objective of this retrospective study was to assess antibiotic resistance rates of bacterial pathogens isolated from clinical specimens in two Lebanese hospitals between the years 2018 and 2019. Methodology: Bacteria isolated from routine clinical specimens collected from hospitalized patients in two hospitals, Haroun and Bekaa, in Lebanon for 2018 and 2019, were analyzed. Bacteria isolation and identification were carried out at the laboratory of each hospital using conventional microbiological methods. Antimicrobial susceptibility testings (AST) of each bacterial isolate to antibiotics were performed by the disc diffusion test and interpreted using EUCAST, CLSI or WHO/AST guidelines. Comparisons of the mean resistance rates of each isolate to individual antibiotics by year of isolation were done using the Z-test and p< 0.05 was considered statistically significant. Results: There were a total of 1698 bacteria isolates recovered from hospitalized patients in the two hospitals for 2018 and 2019, of which 87.5% were Gram-negative and 12.5% were Gram-positive bacteria. The most frequent among the Gram-negative isolates was E. coli (66.1%) followed by P. aeruginosa (13.3%), K. pneumoniae (7.7%), Proteus mirabilis (6.7%) and Enterobacter spp (6.3%), while coagulase positive staphylococci CoPS (68.4%) and E. faecalis (31.6%) were the two Gram positive isolates. Of the Gram-negative isolates over the two-year period, 72.2% of E. coli and 76.3% of K. pneumoniae were resistant to ceftazidime, 93% of P. mirabilis to colistin, and 98% of Enterobacter to cefoxitin, but low resistance rates were demonstrated by E. coli to imipenem (1%), K. pneumoniae to tigecycline and amikacin (0.9%), P. mirabilis to imipinem (2%), and Enterobacter to amikacin, ertapenem and tigecycline (3%). Resistance of P. aeruginosa varied between 2% to colistin and 24% to levofloxacin. For the Gram-positive bacteria, 79.1% of E. faecalis were resistant to erythromycin while 70% of CoPS were resistant to cefoxitin, but no isolate was resistant (0%) to linezolid, and only 1% to teicoplanin. Except for Enterobacter spp that showed significant increase in resistance rates (by 250%) to piperacillin/tazobactam in 2019 over 2018, resistance rates of other Gram-negative isolates significantly decreased in 2019 compared to 2018 (p<0.05). For the Gram-positive isolates, resistance rates to many antibiotics tested significantly increased (by a factor of 36.5 - 2569%) in 2019 compared to 2018 among E. faecalis isolates in contrast to the rates for CoPS which significantly decreased by 16.7 - 65.7%, except for penicillin G which increased by a factor of 123%. Conclusion: Overuse and misuse of antibiotics, which is possible because of the easy access of the populace to these drugs, is a leading factor contributing to the high antibiotic resistance rates in this study. There is need to promote awareness of antimicrobial resistance in Lebanon among students especially in non-health related majors and enactment of govermental policy that will limit access to antibiotics. Keywords: antibiotic resistance; changing pattern; hospitalized patients; retrospective   French title: Une étude rétrospective des profils de résistance aux antibiotiques de pathogènes bactériens isolés de patients dans deux hôpitaux libanais pendant deux années consécutives (2018 et 2019) Contexte: La mauvaise utilisation des antibiotiques est le principal facteur favorisant l'émergence de la résistance bactérienne, une situation qui est devenue un sérieux défi de santé publique. Parmi les principales bactéries qui ont développé une résistance aux antibiotiques figurent Staphylococcus aureus, Enterococcus faecalis, Escherichia coli, Klebsiella pneumoniae et Pseudomonas aeruginosa, qui ont provoqué des infections chez les patients, entraînant une mortalité considérable. L'objectif de cette étude rétrospective est d'évaluer les taux de résistance aux antibiotiques des pathogènes bactériens isolés à partir d'échantillons cliniques dans deux hôpitaux Libanais entre les années 2018 et 2019. Méthodologie: Les isolats bactériens prélevés sur des patients hospitalisés dans deux hôpitaux, Haroun et Bekaa, au Liban pour 2018 et 2019, ont été analysés. L'isolement et l'identification des bactéries ont été réalisés au laboratoire de chaque hôpital en utilisant des méthodes microbiologiques conventionnelles. Les tests de sensibilité aux antimicrobiens (AST) de chaque isolat bactérien aux antibiotiques ont été réalisés par le test de diffusion sur disque et interprétés selon les directives EUCAST, CLSI ou WHO/AST. Des comparaisons des taux moyens de résistance de chaque isolat à des antibiotiques individuels par année d'isolement ont été effectuées à l'aide du test Z et p<0,05 a été considéré comme statistiquement significatif. Résultats: Il y a eu un total de 1698 isolats de bactéries récupérés de patients hospitalisés dans les deux hôpitaux durant 2018 et 2019, dont 87,5% étaient à Gram négatif et 12,5% étaient des bactéries à Gram positif. Les isolats à Gram négatif les plus fréquents étaient E. coli (66,1%), suivis de P. aeruginosa (13,3%), K. pneumoniae (7,7%), Proteus mirabilis (6,7%) et Enterobacter spp (6,3%), tandis que les staphylocoques à coagulase positive CoPS (68,4%) et E. faecalis (31,6%) étaient les deux isolats Gram positifs. Parmi les isolats à Gram négatif sur la période de deux ans, 72,2% d'E. coli et 76,3% de K. pneumoniae étaient résistants à la ceftazidime, 93% de P. mirabilis à la colistine et 98% d'Enterobacter à la céfoxitine, mais faible les taux de résistance ont été démontrés par E. coli à l'imipénem (1%), K. pneumoniae à la tigécycline et à l'amikacine (0,9%), P. mirabilis à l'imipinem (2%) et Enterobacter à l'amikacine, à l'ertapénem et à la tigécycline (3%). La résistance de P. aeruginosa variait entre 2% à la colistine et 24% à la lévofloxacine. Pour les bactéries Gram positif, 79,1% des E. faecalis étaient résistantes à l'érythromycine tandis que 70% des CoPS étaient résistantes au céfoxitin, mais aucun isolat n'était résistant (0%) au linézolide et seulement 1% à la teicoplanine. À l'exception d'Enterobacter spp qui ont montré une augmentation significative des taux de résistance (de 250%) à la  pipéracilline/tazobactam en 2019 par rapport à 2018, les taux de résistance des autres isolats à Gram négatif ont considérablement  diminué en 2019 par rapport à 2018 (p<0,05). Pour les isolats Gram-positifs, les taux de résistance à de nombreux antibiotiques testés ont augmenté de manière significative (d'un facteur de 36,5 à 2569%) en 2019 par rapport à 2018 parmi les isolats d'E. faecalis contrairement aux taux de CoPS qui ont significativement diminué de 16,7 à 65,7%, à l'exception de la pénicilline G qui a augmenté d'un facteur de 123%. Conclusion: la surutilisation et la mauvaise utilisation des antibiotiques, ce qui est possible en raison de l'accès facile de la population à ces médicaments, est l'un des principaux facteurs contribuant aux taux élevés de résistance aux antibiotiques dans cette étude. Il est nécessaire de promouvoir la sensibilisation à la résistance aux antimicrobiens au Liban parmi les étudiants, en particulier dans les spécialisations non liées à la santé, et la promulgation d'une politique gouvernementale qui limitera l'accès non contrôlé aux antibiotiques. Mots clés: résistance aux antibiotiques; changement de modèle; patients hospitalisés; rétrospectiv

PERFORMANCE ANALYSIS AND EVALUATION OF MASSIVE MIMO SYSTEM

This article examines the performance of massive MIMO uplink system over Rician fading channel. The performance is estimated regarding spectral efficiency versus number of base station antennas utilizing three plans of linear detection, maximum-ratio-combining (MRC), zero forcing receiver (ZF), and minimum mean-square error receiver (MMSE). The simulation results reveal that the spectral efficiency increments altogether with expanding the quantity of base station antennas. Additionally, the spectral efficiency with MMSE is superior to that with ZF, and the last is superior to that with MRC. Furthermore, the spectral efficiency diminishes with expanding the fading parameter