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Record W7002353777

A Novel Retro-directive Phased Array Antenna Architecture

2018· dissertation· en· W7002353777 on OpenAlexfundno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2018
Typedissertation
Languageen
FieldPsychology
TopicPsychological Treatments and Disorders
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsBeamformingTransmitterAntenna (radio)Phased arrayChannel (broadcasting)Transmission (telecommunications)WirelessAntenna arraySmart antenna
DOInot available

Abstract

fetched live from OpenAlex

Mobile wireless communication scenarios can range from a simple indoor WiFi link to a satellite internet connection to an airplane. Virtually in all scenarios, dynamic changes in the propagation environment or the movement of transmitter and receiver are inevitable. Therefore, the wireless link often experiences quality degradation or even interruption.
\nAdaptive antenna arrays offer a promising solution to combat wireless channel impairments as they adaptively reshape their radiation pattern. For two-way communication, an antenna should be retro-directive meaning its transmit and receive beams are aligned. To achieve retro-directivity, techniques based on direction-of-arrival and self-phasing can be
\nused. The former usually calls for a complex calibration routine to estimate the direction of arrival and beamsteering; the latter relies on the received signal to generate the transmit beam, imposing several limitations on its adaptability.
\nIn this thesis, a novel retro-directive phased array architecture is proposed that does not require calibration and which generates its transmit wave independently of its receive wave. Moreover, its radiation pattern can be adaptively shaped by a simple beamforming algorithm, while its transmitted and received beams remain aligned. Structurally, it is
\ncomprised of independent modules that can be placed in virtually any arrangement without any hardware modification.
\nThe architecture uses the LO phase-shifting technique to steer its beams. The LO signals are generated with a novel frequency synthesizer; it creates a pair of LO signals for the transmission and reception paths to achieve retro-directivity. The proposed antenna architecture is demonstrated practically using a 10-element prototype, verifying its ability
\nto steer the transmit and receive beams while keeping them aligned. In addition, two of the key circuit components of the LO synthesizer, a fractional frequency divider and a novel phase-conjugating phase shifter, are designed and successfully implemented on 65nm CMOS technology, paving the path for use in future applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.733
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.266
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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