Multiple Description and Multi-Path Routing for Robust Voice Transmission over Ad Hoc Networks
Bibliographic record
Abstract
Achieving real-time voice communication over a mobile wireless ad hoc network poses many challenges both in speech coding and network protocols. In this paper, we investigate the real-time voice transmission capacity of ad hoc networks using a multiple description coding (MDC) scheme along with a new multi-path routing protocol called MSBR. The MDC generates two or more complementary bitstreams from the bitstream of the speech encoder, each sent along different routes. This allows the receiver to maintain acceptable speech quality even with missing packets. MSBR algorithm attempts to find multiple reliable stable routes to the destination node. Simulations using the GloMoSim network simulator and speech audio evaluation setups were used to study the performances of the approach in different network scenarios. Results show that the MDC scheme, together with MSBR, makes an effective use of the network and provides good performances for real time voice transmission
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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 | 0.000 |
| 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 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".