An improved Gaussian approximation for probability of bit-error analysis of asynchronous bandlimited DS-CDMA systems with BPSK spreading
Bibliographic record
Abstract
This paper analyzes probability of bit-error (P/sub e/) performance of asynchronous bandlimited direct-sequence code-division multiple-access systems with binary phase-shift keying spreading. The two present methods of P/sub e/ analysis under bandwidth-efficient pulse shaping: the often-cited standard Gaussian approximation and the characteristic function (CF) method suffer from either a low accuracy in regions of low P/sub e/ (< 10/sup -3/) or a prohibitively large computational complexity. The paper presents an alternate method of P/sub e/ analysis with moderate computational complexity and high accuracy based on a key observation. A sequence of chip decision statistics (whose sum yields a bit statistic) forms a stationary, m-dependent sequence when conditioned on the chip delay and phase offset of each interfering signal. This observation permits the generalization of the improved Gaussian approximation previously derived for the rectangular pulse and the derivation of a numerically efficient approximation based on the CF method. Numerical examples of systems using the square-root raised-cosine and IS-95 pulses illustrate THE P/sub e/ performance, user capacity and the accuracy of the proposed method.
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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 | 0.003 | 0.017 |
| 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 | 0.002 |
| Open science | 0.001 | 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".