Simulation of potential adaptive array algorithms for 3G CDMA systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The goal of using adaptive arrays is to increase the Signal-to-Interference-Noise Ratio (SINR) of the communication in order to reduce error rates and to lead to better utilization of the capacity of the channel. This paper considers a number of algorithms that could be used for antenna array receivers in the mobile-to-base station link of a cellular code division multiple access (CDMA) system. Two classes of algorithms are considered: non-blind and blind adaptive beamforming algorithms. For non-blind beamforming, two solutions are presented: 1) LMS solution with training sequence, 2) Wiener solution with pilot channel on reverse link of 3G CDMA systems. For blind beamforming, we choose Least Squares De-spread Re-spread Multitarget Constant Modulus Algorithm (LS-DRMTCMA). The simulation results show the improvement of both system SINR and BER.
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.
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 | 0.000 | 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 it