Performance Analysis of the V-BLAST Algorithm: An Analytical Approach
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Bibliographic record
Abstract
A geometrically based analytical approach to the performance analysis of the V-BLAST algorithm is presented in this paper, which is based on the analytical model of the Gramm-Schmidt process. This approach presents a new geometrical view of the V-BLAST and explains some of its properties in a complete and rigorous form, including a statistical analysis of postprocessing signal-to-noise ratios for a 2/spl times/n system (where n is the number of receive antennas). Closed-form analytical expressions of the vector signal at ith processing step and its power are presented. A rigorous proof that the diversity order at ith step (without optimal ordering) is (n-m+i) is given (where m is the number of transmit antennas). It is shown that the optimal ordering is based on the least correlation criterion and that the after-processing signal power is determined by the channel correlation matrices in a fashion similar to the channel capacity. Closed-form analytical expressions are derived for outage probabilities and average BER of a 2/spl times/n system. The effect of the optimal ordering is shown to be to increase the first step SNR by 3 dB (rather than to increase the diversity order as one might intuitively expect based on the selection combining argument) and to increase the second step outage probability twice.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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