GLOBAL APPROACH OF CHANNEL MODELING IN MOBILE AD HOC NETWORKS INCLUDING SECOND ORDER STATISTICS AND SYSTEM PERFORMANCES ANALYSIS
Bibliographic record
Abstract
Mobile ad hoc networks (MANET) are very difficult to design in terms of scenarios specification and propagation modeling. All these aspects must be taken into account when designing MANET. For cost-effective designing, powerful and accurate simulation tools are needed. Our first contribution in this paper is to provide a global approach process (GAP) in channel modeling combining scenarios and propagation in order to have a better analysis of the physical layer, and finally to improve performances of the whole network. The GAP is implemented in an integrated simulation tool, Ad-SMPro. Moreover, channel statistics, throughput and delay are some key points to be considered when studying a mobile wireless networks. A carefully analysis of mobility effects over second order channel statistics and system performances is made based on our optimized simulation tool, Ad-SMProl. The channel is modeled by large scale fading and small scale fading including Doppler spectrum due to the double mobility of the nodes. Level Cross Rate and Average Duration of Fade are simulated as function of double mobility degree, a defined to be the ratio of the nodes' speeds. These results are compared to the theoretical predictions. We demonstrate that, in mobile ad hoc networks, flat fading channels and frequency-selective fading channels are differently affected. In addition, Bit Error rate is analysed as function of the ratio of the average bit energy to thermal noise density. Other performances (such as throughput, delay and routing traffic) are analysed and conclusions related to the proposed simulation model and the mobility effects are drawn.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.002 | 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".