MIMO Decorrelating Discrete-Time RAKE Receiver
Bibliographic record
Abstract
In this paper, we introduce a decorrelating discrete-time RAKE receiver for MIMO systems. Conventional RAKE receivers require acquisition and tracking systems to detect new paths and to follow them. To avoid this requirement a discrete-time RAKE receiver (DTR) has been proposed, which is obtained by sampling the received signal at twice the chip rate. The DTR works well in both specular and diffuse multipath channels. A drawback of the DTR is its sensitivity to channel estimation errors. To eliminate this weakness an optimum combining technique has been introduced, called the decorrelating discrete-time RAKE receiver (D-DTR). The D-DTR exploits the covariance matrix of the discrete-time channel for a better robustness against channel estimation errors. In this paper, we extend this system to the MIMO case. Our simulations show that gains up to 2 dB are available in 2 transmit 2 receive antenna and 3 transmit 3 receive antenna systems at a bit error rate of 10.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".