Bibliographic record
Abstract
Orthogonal frequency-division multiplexing (OFDM) with multiple transmit and multiple receive antennas (MIMO-OFDM) is considered a candidate for high-data rate communication in various existing and forthcoming system standards. To achieve the usually desired low frame and bit error rates, MIMO-OFDM should be combined with adaptive bit loading (ABL) and forward error correction (FEC) coding, where the former is particularly apt for moderate mobility as considered in, for example, IEEE 802.16e OFDM systems. In this paper, we investigate "simple" coding schemes and their combination with ABL for MIMO-OFDM. In particular, we consider wrapped space-frequency coding (WSFC) and coded V-BLAST with ABL and optimize both schemes to mitigate error propagation inherent in the detection process. Simulation results show that bit-loaded WSFC and V-BLAST optimized for coded MIMO-OFDM achieve excellent error rate performances, close to that of quasioptimal MIMO-OFDM based on singular value decomposition of the channel, while their feedback requirements for loading are low.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".