Diversity Analysis of MIMO Network Coded Cooperation Systems with Relay Selection
Bibliographic record
Abstract
Network coded cooperation (NCC) has recently gained interest due to its ability to increase the network throughput in multisource cooperative systems. NCC with single relay selection (SRS) or multiple relay selection (MRS) has been studied for single-antenna terminals only. Employing multiple-input multiple-output (MIMO) can significantly improve the performance of NCC systems. In this paper, we consider a NCC system with decode-and-forward (DF) relaying where relays use maximum distance separable (MDS) codes as their encoding vectors. More specifically, we consider N sources, M relays and a single destination. Relays and the destination are equipped with multiple antennas whereas sources have single antenna. The performance of the system under consideration is investigated by deriving exact outage probability expressions for both SRS and MRS protocols. The asymptotical diversity orders are further provided to obtain valuable insights into practical system design. Furthermore, numerical results are provided to validate the accuracy of our derivations and quantify the effect of system parameters on the outage probability and diversity order.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".