Performance of multidimensional multicode DS-CDMA using code diversity and error detection
Bibliographic record
Abstract
High rate transmission can be realized using multiple orthogonal codes (MOC), as proposed in the third-generation wide-band code-division multiple-access (W-CDMA) standard. However, the linear sum of MOC channels is no longer constant amplitude, and a highly linear, power-inefficient amplifier may be required for transmission. Recently, a nonlinear block coding technique called precoding is introduced to maintain a constant amplitude signal after superposition of MOC channels. This is achieved by adding redundancy. In this paper, we first describe a multidimensional signaling scheme that recovers some information rate loss by precoding. Second, we propose a self-interference (SI) cancellation scheme resulting from a code diversity between the in-phase and quadrature subchannels among MOC channels. In a typical wireless channel with multipath fading, this type of SI can be detrimental especially when the number of parallel MOC channels is large. Third, we show that the error detection capability of precoding can be combined with code diversity, resulting in a diversity gain. In addition, we show that the diversity gain can be achieved using antenna diversity to assure the degree of freedom in code diversity, and even with the large number of MOC channels, the error performance can be maintained reliably while outperforming the variable spreading factor scheme in W-CDMA.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".