Mitigation of Imperfect Successive Interference Cancellation and Wavelet‐Based Nonorthogonal Multiple Access in the 5G Multiuser Downlink Network
Why this work is in the frame
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Bibliographic record
Abstract
The fourth Industrial Revolution is expected to lead to an era of technological innovation and digitization that would require connectivity by the users, anywhere and anytime. The fifth generation of wireless communication systems and the technologies therein are being explored to cater to high connectivity needs that encompass high data rates, very low latencies, energy‐efficient systems, etc. A multiuser environment is anticipated that would require multiple access techniques, such as Nonorthogonal Multiple Access (NOMA). The user data in the power domain NOMA is superimposed, at the transmitter base station, which is in turn subjected to Successive Interference Cancellation at the user end. In the multiuser downlink, the desired user’s signal is subjected to imperfect SIC due to incomplete cancellation of the undesired user’s signal. Pulse‐shaping of NOMA symbols using wavelet transform is proposed to mitigate the multiuser interference due to imperfect SIC. Closed‐form symbol error rate (SER) expression is derived for the wavelet NOMA system for a three‐user scenario. Analytical results show that wavelet transform pulse‐shaped NOMA performs better compared to Fourier transform pulse‐shaped NOMA symbols in mitigating SIC and thereby minimize the residual error due to imperfect SIC.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it