Blind Signal Separation in MIMO OFDM Systems Using ICA and Fractional Sampling
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Bibliographic record
Abstract
This paper addresses the problem of Blind Signal Separation (BSS) as it pertains to Multiple Input Multiple Output (MIMO) systems utilizing Orthogonal Frequency Division Multiplexing (OFDM). In systems with N subcarriers affected by frequency selective channels, when sampling the received signals at the Nyquist rate, the original BSS is transformed into a set of N standard Independent Component Analysis (ICA) problems. In this paper, fractional sampling is employed to increase the number of received signals and improve diversity at the receiver. The up-sampling of the OFDM frames is analyzed in the frequency domain with an up-sampling factor of 2. This doubles the number of ICA problems which provide N new solutions to aid in the recovery of the original data symbols. The additional solutions using equal gain combining improve signal-to-noise ratio (SNR) and therefore the data recovery. To achieve convergence of the ICA algorithm for the over-sampled data symbols, a specialized rotation of constellations on adjacent subcarriers is introduced. The simulation results demonstrate effectiveness of the overall system in its resiliency to inter-carrier interference and the AWGN channel.
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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 | 0.001 | 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 | 0.001 |
| 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