Integrated Sensing and Communication in mmWave Wireless Backhaul Networks
Bibliographic record
Abstract
Integrated sensing and communication (ISAC) becomes prevailing in wireless communications since it fully exploits the spectrum resources by incorporating data transmission and potential sensing functionalities of radio networks. With large bandwidth and directional communication, millimeter wave has the potentials for high data-rate communications and favorable time and spatial domain resolution, which can provide extensive sensing functionalities if properly utilized. Since self-backhauling at mm Wave bands is considered a promising technology to enable high-throughput networks, we investigate how to embed ISAC functions into mm Wave network by jointly considering high-speed data transmissions and high accuracy localization. To maximize the utilization of mm Wave BSs for sensing and communication, we study the problem of optimal sensing task allocation taking into account target location, the requirements of different sensing tasks, user distribution, link scheduling, and data routing. With ISAC operations in mind, we analyze the time needed to complete each sensing task to facilitate problem formulation. To overcome the computational complexity in solution finding, we propose a sensing-oriented column generation (SOCG) scheme, which is shown to achieve near optimal performance via extensive performance evaluation. Furthermore, evaluation results demonstrate that the obtained sensing task allocation provides good throughput performance while ensuring the requirements of sensing tasks are satisfied.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".