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Record W4408441438 · doi:10.1109/lwc.2025.3551510

Waveform Design for Integrated Sensing and Communications With PAPR Constraint

2025· article· en· W4408441438 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Wireless Communications Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsUniversity of Alberta
FundersNatural Science Basic Research Program of Shaanxi ProvinceAeronautical Science Foundation of ChinaNational Natural Science Foundation of China
KeywordsWaveformComputer scienceConstraint (computer-aided design)Electronic engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

This letter investigates the peak-to-average-power ratio (PAPR)-controllable waveform design problem in an integrated sensing and communication (ISAC) system, aiming to minimize downlink multi-user interference energy and maximize the detection probability of multiple-input multiple-output (MIMO) radar. The waveform design is formulated as a weighted optimization problem based on signal similarity to achieve a flexible trade-off between sensing and communication performance. The problem is non-convex, and we thus propose an iterative waveform design algorithm. We validate the effectiveness of our proposed scheme by comparing it with benchmark strategies for communication and sensing performance, demonstrating that our approach provides significant advantages in both communication and radar performance, as well as a flexible trade-off between the two functions.

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.

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 score0.897
Threshold uncertainty score0.782

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.031
GPT teacher head0.261
Teacher spread0.230 · 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