Ambient IoT: Transmit Power Minimization for NOMA-Enabled BackCom
Bibliographic record
Abstract
Ambient internet-of-things networks are just emerging to support sixth-generation wireless goals. We thus investigate a symbiotic radio (SR) system for a single-user primary network and a backscatter communication network that supports non-orthogonal multiple access. The primary base station (BS) concurrently supports the primary user and multiple tags, which modulate and reflect their data using the primary BS signal. The user decodes its data and the tags’ data using the successive interference cancellation technique. We propose a novel optimization framework to accommodate the requirements of both the primary user and the tags while also improving SR network performance. By constructing the beamforming vectors to support both primary and backscatter networks, we develop a BS transmit power minimization problem. The problem formulation ensures the various quality-of-service demands of the user and the tags and the tag energy harvesting requirements. Because of the non-convexity of the problem, we employ semi-definite relaxation techniques to obtain a sub-optimal solution. We evaluate the computational complexity of the proposed algorithm. Finally, we present extensive numerical results and simulations that establish the validity and performance gains of the proposed optimization scheme without modifying the fundamental passive tag architecture.
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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 | 0.000 |
| 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".