CORDIC-based LMMSE equalizer for Software Defined Radio
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Bibliographic record
Abstract
In Code Division Multiple Access (CDMA) systems, the orthogonality of the spreading codes used to achieve multiple access over a channel is severely degraded due to multi-path interference. Expensive equalization techniques are needed to recover the transmitted signal. The Linear Minimum Mean Square Error (LMMSE) equalizer is a sub-optimal equalizer that is a good compromise between computational complexity and communication system performance. It uses computationally-intensive matrix inversion operations to perform equalization. In this paper, we address the computational challenges of implementing the LMMSE equalizer on Software Defined Radio (SDR) platforms. SDR platforms are favored by the wireless industry due to their significant benefits of reduced development costs and accelerated time-to-market. We present COordinate Rotation DIgital Computer (CORDIC) Instruction Set Architecture (ISA) extensions that speed up the LMMSE equalization algorithm. The costs and benefits of the ISA extensions are evaluated on the Sandbridge Sandblaster 3000 (SB3000) low-power, multithreaded SDR processor. The proposed ISA extensions provide significant performance improvements with little hardware overhead, while improving the accuracy of the LMMSE Equalizer.
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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 | 0.000 |
| 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)
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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