On bandwidth-efficient multiuser-space-time signal design and detection
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.
Bibliographic record
Abstract
Signals designed for transmission over multiple transmit antennas are capable for achieving significant capacity gain. Traditional approaches aim at improving the single-user link with a centralized control over the set of transmit antennas. In this paper, by considering a set of independent and synchronized users communicating with the base station on the up-link, the joint signal can be viewed as space-time coded signal without a centralized control. Co-channel/inter-antenna interference presents a major impairment that limits the capacity. We propose a novel multiuser signal structure called interference-resistant modulation (IRM) to improve performance without coding nor bandwidth expansion. IRM can also be combined with fading-resistant modulation or space-time coding to yield additional gain when each user employs multiple transmit antennas. We prove that, both analytically and by simulations, the IRM with maximum-likelihood (ML) detection achieves the single-user performance asymptotically. Furthermore, to reduce the prohibitive complexity posed by ML detection, we propose a simple minimum-mean-square-error based precombining group detector and an interference cancellation scheme. It is shown that the proposed detector combined with IRM provides significant improvement over previous approaches.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it