Integer QP relaxation-based algorithms for intercarrier-interference reduction in OFDM systems
Bibliographic record
Abstract
Orthogonal frequency-division multiplexing (OFDM) modulation can be utilized to deal with severe channel conditions without complex equalization. However, in a fast-fading channel, Doppler spread caused by user mobility destroys the orthogonality among subcarriers, prompting intercarrier interference (ICI). In this paper, the OFDM ICI reduction problem is formulated as a combinatorial optimization problem. Two relaxation methods are proposed to relax the maximum-likelihood detection problem into convex quadratic programming (QP) problems. To further reduce computational complexity, the QP problems are solved by limiting the search to the two-dimensional subspace. A low-bit descent search can also be employed to improve the system performance. The extension to higher-order quadrature amplitude modulation (QAM) OFDM systems is also addressed. Performance results are given which demonstrate that the integer QP relaxation-based algorithms provide excellent performance with reasonable computational complexity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".