Throughput/Reliability Tradeoffs in Spread Spectrum Multi-Hop Ad-Hoc Wireless Networks with Multi-Packet Detection
Bibliographic record
Abstract
Wireless ad hoc networks with nodes capable of simultaneous multiple packet reception are considered. We focus on spread spectrum networks and address the relationship between the packet detection success, probability of the packet success over multiple hops, and asymptotic throughput capacity of the network in terms of power and bandwidth resources as well as the multi-packet detection capability of the nodes. In the second part of the paper we consider network with nodes employing partitioned code division multiple access (CDMA) transmission and joint iterative reception. We study local communication in the network and derive a relationship between the probability of detection success and a fraction of the multiple access channel capacity that can be achieved at any communicating node. We use this result to demonstrate that near optimum throughput and reliable end-to-end communication can be achieved in the network with use of a practical detection method. Finally, we present simulation results which demonstrate the advantage of partitioned CDMA with iterative receivers over CDMA with linear receivers in a network setting.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".