A Real-Time DSP-based Iterative (Turbo) Multiuser Detection Employing Interference Cancellor-MMSE
Bibliographic record
Abstract
In this paper, we investigate the implementation of an efficient low complexity iterative detector (namely IC-MMSE), for coded direct sequence code division multiple access (DS-CDMA) system, under fixed-point data representation and computation constraint. TMS320C6416 TI's fixed point DSP, part of the C6416 DSK platrform, is utilized. Real time simulations are made possible by using real time data exchange (RTDX) technology. For performance evaluation extrinsic information transfer (EXIT) chart analysis is used. EXIT charts reveal that fixed point implementation is feasible at possibly no performance degradation. Based on the measured number of cycles of different constituent sub-functions of the IC-MMSE receiver, a data transmission rate of up to 186 Kb/s can be reached for a 5-users load and processing gain of 7 in an AWGN channel
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".