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Record W2131289733 · doi:10.1109/tsp.2007.895992

Biwindowed Discrete Multitone Transceiver Design

2007· article· en· W2131289733 on OpenAlexaff
Bahram Borna, Timothy N. Davidson

Bibliographic record

VenueIEEE Transactions on Signal Processing · 2007
Typearticle
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCyclic prefixIntersymbol interferenceComputer scienceTransceiverTransmitterDigital subscriber lineElectronic engineeringSpectral efficiencyNarrowbandAdjacent-channel interferenceBit error rateOrthogonal frequency-division multiplexingChannel (broadcasting)Interference (communication)TelecommunicationsEngineeringWireless

Abstract

fetched live from OpenAlex

A family of biwindowed discrete multitone (DMT) transceivers that provide both subchannel spectral containment at the transmitter and spectral selectivity at the receiver is proposed. These systems have the attractive feature that they provide spectral shaping at both ends of the transceiver without requiring the cyclic prefix to be longer than the order of the channel impulse response. The windows are designed in a channel independent manner and are constrained to produce subchannel outputs that are free from (intrasubchannel) intersymbol interference (ISI). Furthermore, the design allows the intersubchannel interference (ICI) to be controlled in such a way that it can be mitigated using a relatively simple minimum mean-square error (MMSE) successive interference cancellation scheme. Under a realistic model for a digital subscriber line (DSL) environment, the achievable bit rate of the proposed system is significantly higher than that of the conventional DMT system and some established windowed DMT systems with receiver-only windowing. This performance gain is a result of the capability of the proposed system to combat the near-end crosstalk (NEXT) at the transmitter and receiver and to mitigate the narrowband noise at the receiver, without the requirement of excess cyclic prefix.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.978
Threshold uncertainty score0.827

Codex and Gemma teacher scores by category

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

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 head0.026
GPT teacher head0.263
Teacher spread0.236 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations3
Published2007
Admission routes1
Has abstractyes

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