Phase-swept and time-delay transmit diversity performance results for 1X RTT CDMA systems
Bibliographic record
Abstract
With the evolution of CDMA (code division multiple access), increased capacity gain in terms of "voice" users is the foremost expectation. Initial estimates were that the utilization of fast power control would double the forward link capacity. However, detailed simulations have shown that this is not true. Therefore, the additional concept of transmit diversity is investigated. Of the many methods under scrutiny, two offer relatively simple implementation with the advantage that they can be implemented on an IS-95 network, today, without any impact on mobile design or need for standardization. This paper reports on results obtained from simulations, as well as laboratory trials investigating the comparative performance of PSTD (phase-swept transmit diversity) and TDTD (time-delay transmit diversity) using an actual IS-95 base station at 1.9 GHz. The experimental results obtained substantiate the simulation results. The results show that PSTD and TDTD perform equally well. These forms of transmit diversity offer several dBs of gain under Rayleigh fading conditions for vehicle speeds less than 20 kph. A description of a planned field trial intended to confirm these results is also included. Such transmit diversity techniques coupled with fast power control can provide up to double the IS-95 capacity.
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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 | 0.005 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".