Design Considerations of OFDM Waveform for Millimeter-Wave Integrated Communication and Long-Range Sensing in High Mobility Channels
Bibliographic record
Abstract
Cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) is a promising waveform for integrated sensing and communication (ISAC). However, to avoid inter-symbol interference (ISI), the cyclic prefix (CP) duration must exceed the channel delay spread, which is determined by the channel length. Although beamforming in millimeter-wave (mmWave) systems can significantly reduce the delay spread for communication, radar sensing imposes distinct constraints. In particular, the maximum target detection range dictates the required CP duration, potentially requiring up to 50% of the symbol duration in long-range scenarios. This extended CP increases energy consumption and reduces spectral efficiency, as a substantial portion of transmission is allocated to CP rather than data symbols. Furthermore, Doppler shifts in high-mobility channels induce inter-carrier interference (ICI), further degrading radar performance. To address these challenges, which commonly arise in long-range and high-mobility applications such as UAVs and vehicular scenarios, we propose a novel resource element allocation scheme that employs a block-type pilot structure within the OFDM time-frequency grid. A dedicated low-PAPR pilot symbol, featuring nulls on the odd-indexed subcarriers and repeated periodically across the time-frequency grid, is utilized to support both communication and radar sensing functions. The proposed design facilitates effective long-range sensing and ICI mitigation without extending the CP length. Corresponding signal processing techniques are developed and analyzed to support the proposed approach.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".