A New Construction of Signature Waveforms for Synchronous CDMA Systems
Bibliographic record
Abstract
We consider synchronous code-division multiple access (CDMA) systems over an additive white Gaussian noise (AWGN) channel, where all users are divided into groups of small size. The signature waveforms for users in each group are constructed from the same signature sequence but with different chip waveforms. To minimize the multiple access interference (MAI) at the output of the correlators, Welch-bound-equality (WBE) sequences and chip waveforms having optimal correlation property are employed. The main idea behind the proposed construction is to suppress the inter-group interference from users in different groups as much as possible (even to remove it completely) at the expense of introducing the intra-group interference among the users in the same group. The intra-group interference, however, can be easily handled by a low-complexity, optimal (or suboptimal) multiuser detector(s) if the group size is kept small enough. As special cases, the proposed constructions correspond to the optimal design of the signature waveforms and the conventional system that uses a single chip waveform, respectively. Thus the proposed construction offers a flexibility to trade performance for complexity. In particular, it is demonstrated that, while the conventional system's error performance is very sensitive to even a small amount of overload, the proposed system with two users per group can have up to 100% overload with an excellent error performance.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
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".