A Discrete-Time Mixing Receiver Architecture with Wideband Harmonic Rejection

A discrete-time mixing architecture for software-defined radio receivers exploits 8 RF voltage oversampling followed by charge-domain weighting to achieve 40dB 3rd and 5th harmonic rejection without channel bandwidth limitations. Noise folding is also reduced by 3dB. A zero-IF downconverter chip in 65nm CMOS can receive RF signals up to 900MHz, with NFmin=12dB, IIP3=11dBm at <20mW power consumption including multi-phase clock generation

A Software-Defined Radio Receiver Architecture Robust to Out-of-Band Interference

In a software-defined radio (SDR) receiver it is desirable to minimize RF band-filtering for flexibility, size and cost reasons, but this leads to increased out-of-band interference (OBI). Besides harmonic and intermodulation distortion (HD/IMD), OBI can also lead to blocking and harmonic mixing. A wideband LNA [1, 2] amplifies signal and interference with equal gain. Even a low gain of 6dB can clip 0dBm OBI to a 1.2V supply, blocking the receiver. Hard-switching mixers not only translate the wanted signal to baseband but also the interference around LO harmonics. Harmonic rejection (HR) mixers have been used [3, 1, 4], but are sensitive to phase and gain mismatch. Indeed the HR in [4] shows a large spread, whereas other work only shows results from one chip [3, 1]. This paper describes techniques to relax blocking and HD/IMD, and make HR robust to mismatch

Los actos de habla como teor?a de la acci?n en el lenguaje de las v?ctimas del conflicto armado en el sur oriente del departamento del Tolima

94 p. Recurso Electr?nicoEl presente trabajo es el resultado de una investigaci?n cualitativa, de las Ciencias Sociales, realizado en el suroriente del Departamento del Huila, en los municipios de Guadalupe, Suaza y Acevedo, donde se estableci? una poblaci?n de v?ctimas de los actores del conflicto armado, procedentes del Caquet? por desplazamiento inmediato y/o desmovilizaci?n luego de la antigua zona de distensi?n y que ahora conforman territorios de marginalidad y comparten su existencia en condiciones de pobreza, precariedad y ausencia del Estado. El estudio es de car?cter ling??stico, realiza un recorrido general por el lenguaje del conflicto colombiano desde la intervenci?n de los actores armados, instituciones y sociedad civil para cumplir con el prop?sito de conocer y analizar el impacto de los actos de habla en el lenguaje de las v?ctimas a trav?s de la aplicaci?n de la teor?a de Austin, quien afirma que los enunciados y las expresiones no solo describen la realidad sino que la transforman, la palabra es acci?n y decir es hacer.This work is the result of a qualitative research of Social Sciences, made in the southeast of the department of Huila, in the municipalities of Guadalupe, Suaza, and Acevedo, where a population of victims of the armed conflict was established from Caquet? department due to displacement or demobilization often the former demilitarized zone and now they form part of the marginal territories and share their existence in poverty, insecurity and absence of the State. This research is of Linguistic character, make a general route for the language of Colombian conflict from the intervention of armed actors, institutions and civil society in order to comply with a purpose, to understand and analyze the impact of speech acts in the language of victims through application of the Austin theory, who says that statements and expressions not only describe reality also it is transformed, the word is action and say is to do. Keywords: Language, speech acts, victims of armed conflict

A 0.2-to-2.0GHz 65nm CMOS Receiver without LNA achieving >11dBm IIP3 and <6.5 dB NF

Spurious-free dynamic range (SFDR) is a key specification of radio receivers and spectrum analyzers, characterizing the maximum distance between signal and noise+distortion. SFDR is limited by the linearity (intercept point IIP3 mostly, sometimes IIP2) and the noise floor. As receivers already have low noise figure (NF) there is more room for improving the SFDR by increasing the linearity. As there is a strong relation between distortion and voltage swing, it is challenging to maintain or even improve linearity intercept points in future CMOS processes with lower supply voltages. Circuits can be linearized with feedback but loop gain at RF is limited [1]. Moreover, after LNA gain, mixer linearity becomes even tougher. If the amplification is postponed to IF, much more loop gain is available to linearize the amplifier. This paper proposes such an LNA-less mixer-first receiver. By careful analysis and optimization of a passive mixer core [2,3] for low conversion loss and low noise folding it is shown that it is possible to realize IIP3≫11dBm and NF≪6.5dB, i.e. a remarkably high SFDR≫79dB in 1MHz bandwidth over a decade of RF frequencies

Discrete-Time receivers for software-defined radio: challenges and solutions

Abstract—CMOS radio receiver architectures, based on radio frequency (RF) sampling followed by discrete-time (DT) signal processing via switched-capacitor circuits, have recently been proposed for dedicated radio standards. This paper explores the suitability of such DT receivers for highly flexible softwaredefined radio (SDR) receivers. Via symbolic analysis and simulations we analyze the properties of DT receivers, and show that at least three challenges exist to make a DT receiver work for SDR: 1) the sampling clock frequency is related to the radio frequency, complicating baseband filter design; 2) a frequencydependent phase shift is introduced by pseudo-quadrature and pseudo-differential sampling; 3) the conversion gain of a charge sampling front-end is strongly frequency-dependent. Some potential solutions are also suggested for each challenge. Compared to a mixer based radio receiver, extra costs are needed to solve these problems

Fermi Surface reconstruction in the CDW state of CeTe3 observed by photoemission

CeTe3 is a layered compound where an incommensurate Charge Density Wave (CDW) opens a large gap (400 meV) in optimally nested regions of the Fermi Surface (FS), whereas other sections with poorer nesting remain ungapped. Through Angle-Resolved Photoemission, we identify bands backfolded according to the CDW periodicity. They define FS pockets formed by the intersection of the original FS and its CDW replica. Such pockets illustrate very directly the role of nesting in the CDW formation but they could not be detected so far in a CDW system. We address the reasons for the weak intensity of the folded bands, by comparing different foldings coexisting in CeTe3

ENHANCING ONLINE PUBLIC NOTICES USING GIS TO FACILITATE PUBLIC PARTICIPATION IN MUNICIPAL DEVELOPMENTS

By-laws of many municipalities and local governments require certain level of public participation in their decision-making processes for municipal planning and development activities. One of the common practices in Canada is to hold public meetings, during which the proposed developments are explained and discussed, and public opinions are collected. The problems associated with existing practices are twofold: insufficient access to information required for public input and lack of effective, innovative communication channels other than public meetings. Having municipal environmental assessment (EA) process as the application context, this paper presents our effort on developing methodology and software tools, using advanced information technology including GIS, that facilitate information access, understanding of EA study, and proactive participation in public meetings and, eventually, in overall municipal class EA process. 1

Multi-view Contrastive Learning for Entity Typing over Knowledge Graphs

Knowledge graph entity typing (KGET) aims at inferring plausible types of entities in knowledge graphs. Existing approaches to KGET focus on how to better encode the knowledge provided by the neighbors and types of an entity into its representation. However, they ignore the semantic knowledge provided by the way in which types can be clustered together. In this paper, we propose a novel method called Multi-view Contrastive Learning for knowledge graph Entity Typing (MCLET), which effectively encodes the coarse-grained knowledge provided by clusters into entity and type embeddings. MCLET is composed of three modules: i) Multi-view Generation and Encoder module, which encodes structured information from entity-type, entity-cluster and cluster-type views; ii) Cross-view Contrastive Learning module, which encourages different views to collaboratively improve view-specific representations of entities and types; iii) Entity Typing Prediction module, which integrates multi-head attention and a Mixture-of-Experts strategy to infer missing entity types. Extensive experiments show the strong performance of MCLET compared to the state-of-the-artComment: Accepted at EMNLP 2023 Mai

HyperFormer:Enhancing entity and relation interaction for hyper-relational knowledge graph completion

Hyper-relational knowledge graphs (HKGs) extend standard knowledge graphs by associating attribute-value qualifiers to triples, which effectively represent additional fine-grained information about its associated triple. Hyper-relational knowledge graph completion (HKGC) aims at inferring unknown triples while considering its qualifiers. Most existing approaches to HKGC exploit a global-level graph structure to encode hyper-relational knowledge into the graph convolution message passing process. However, the addition of multi-hop information might bring noise into the triple prediction process. To address this problem, we propose HyperFormer, a model that considers local-level sequential information, which encodes the content of the entities, relations and qualifiers of a triple. More precisely, HyperFormer is composed of three different modules: an entity neighbor aggregator module allowing to integrate the information of the neighbors of an entity to capture different perspectives of it; a relation qualifier aggregator module to integrate hyper-relational knowledge into the corresponding relation to refine the representation of relational content; a convolution-based bidirectional interaction module based on a convolutional operation, capturing pairwise bidirectional interactions of entity-relation, entity-qualifier, and relation-qualifier. Furthermore, we introduce a Mixture-of-Experts strategy into the feed-forward layers of HyperFormer to strengthen its representation capabilities while reducing the amount of model parameters and computation. Extensive experiments on three well-known datasets with four different conditions demonstrate HyperFormer's effectiveness