Indoor SDMA capacity using a smart antenna base station
Bibliographic record
Abstract
In this paper we consider the capacity of a set of portable stations sharing a single indoor radio channel. The stations communicate with a base station which is equipped with a smart antenna operating in multibeam SDMA/FDMA mode, Both theoretical models and measured data from an experimental testbed are presented. The experimental system operates at 1.86 GHz and uses an 8 element circular antenna array. This system was built at the Communications Research Laboratory at McMaster University. The paper focuses on the static TDMA network capacity of this system. In particular, we explore the value of performing dynamic slot assignment when constructing the SDMA/TDMA frames. Slot assignment algorithms are introduced which are capable of increasing static system capacity under non-ideal propagation situations. In all cases, optimal SINR beamforming is used to determine the performance of the system. The results presented give clear insights into the network capacity possible in such systems and indicate the value of dynamic slot assignment under time division duplex operation. The results can also be used to motivate the design of media access protocols for these types of networks.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".