IEEE 802.11 FHSS receiver design for cluster‐based multihop video communications
Bibliographic record
Abstract
Abstract Recently, we proposed an ad hoc, cluster‐based, multihop network architecture for video communications using IEEE 802.11 FHSS (Frequency Hopping Spread Spectrum) wireless LAN (WLAN) technology with 2GFSK (2‐level Gaussian Frequency Shift Keying) modulation capable of 1 Mb s−1 transmission. To increase the transmission rate to 2 Mb s−1 for higher‐quality video communications, we evaluated the performance of the IEEE 802.11 FHSS system when a 4GFSK modulation option is selected. Since the 2 Mb s−1 system utilizing 4GFSK modulation is not very efficient in terms of Radio Frequency (RF) range, to improve its performance for multihop applications a combination of diversity and noncoherent Viterbi equalizer are considered. For video transmission, we employed a bitstream‐splitting technique together with a packet‐based error‐protection strategy to combat packet drops under multipath fading conditions. The real‐time transport protocol (RTP), user datagram protocol (UDP), and Internet protocol (IP) are used for video streaming. This includes an RTP packetization scheme to control the packet size and to improve the error‐resilient decoding of the partitioned video signal. The paper includes the simulation results showing the effects of the receiver design and diversity on the quality of the received video signals. Copyright © 2002 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".