Bibliographic record
Abstract
In this paper; a new multiple access scheme suitable for the forward link transmission in a multiuser MIMO system is investigated. Unlike traditional MIMO multiple access schemes, which rely on orthogonal-temporal channels (e.g. TDMA), the proposed scheme, namely the spread space-spectrum multiple access (SSSMA), exploits the space-domain for multiuser multiplexing. As its name suggests, SSSMA utilizes the available degrees of freedom offered by the spread-spectrum and those by the multiple transmit antennas to perform multiple access. At the base-station transmitter, each coded data stream corresponding to a unique user-channel is modulated with a user-specific two-dimensional spreading sequence and added together with other channels' modulated signals. At each user's receiver, the multiple-access-interference (MAI) generated from the same base station is mitigated through iterative multiuser detection and decoding. We focus on the performance of SSSMA in two different environments: (1) local point-to-multipoint network such as central access LAN; and (2) a power-controlled cellular system. It is shown that not only does the SSSMA offer near-theoretic-capacity performance in both environments, it is able to exploit a new form of diversity, namely the space-interferers diversity, in an ideal power-controlled network while other MIMO multiple access schemes fail to do so.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".