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Record W2154844199 · doi:10.1109/ccece.2008.4564646

A pipelined implementation of OFDM transmission on reconfigurable platforms

2008· article· en· W2154844199 on OpenAlexaffvenue
Ahmad Sghaier, Shawki Areibi, Bob Dony

Bibliographic record

VenueConference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingField-programmable gate arrayComputer scienceDigital audio broadcastingDigital subscriber lineWirelessVirtexVHDLEmbedded systemTransmitterWireless broadbandApplication-specific integrated circuitMultiplexingComputer hardwareComputer architectureComputer networkTelecommunicationsChannel (broadcasting)Wireless network

Abstract

fetched live from OpenAlex

The principles of orthogonal frequency division multiplexing (OFDM) modulation have been around since 1960s. However, recently, the attention toward OFDM has grown dramatically in the field of wireless and wired communication systems. This is reflected by the adoption of this technique in applications such as digital audio/video broadcast (DAB/DVB), wireless LAN (802.11a and HiperLAN2), broadband wireless (802.16) and xDSL. In parallel, Field Programmable Gate Arrays (FPGAs) are also emerging as a fundamental paradigm in the implementation of these standards. This is due to their increased capabilities (speed and resources). Moreover, the FPGApsilas programmability make them a preferable choice for evolving standards in comparison with ASIC fixed designs. In this work, a pure VHDL design, integrated with some intellectual property (IP) blocks, is employed to implement an OFDM transmitter according to the IEEE 802.11a WLAN standard. The proposed design has been mapped and tested on Xilinx Virtex-II Pro (XC2VP30-7ff896) FPGA, and approximately 25% of the total available fabric was occupied.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.019
GPT teacher head0.209
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations28
Published2008
Admission routes2
Has abstractyes

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