A Heterogeneous Network Transmission Architecture Based on NOMA for Next-Generation Converged Communications and Broadcasting Systems
Bibliographic record
Abstract
Inter-Tower Communication Network (ITCN), which supports communication between different base stations via wireless links, has excellent potential for simultaneous transmission of broadcast data and personalized data using Layered Division Multiplexing (LDM). In this paper, a heterogeneous ITCN architecture using LDM and wireless backhauling is proposed. In uplink transmission, the power-limited user devices transmit data to the secondary transmitters (STs), and the STs relay the data to the master transmitter (MT). In downlink transmission, the MT and multiple STs cooperatively transmit broadcast data using single frequency network (SFN) mode, and the STs relay the personalized data from the MT to users simultaneously. Considering the co-channel interference, this paper proposes a joint subchannel assignment and power allocation scheme for both uplink and downlink transmission. A mixed integer optimization problem is formulated, and an alternating optimization algorithm (AO) based on game theory and convex optimization is proposed. Simulation results are conducted with different system configurations to demonstrate the convergence and effectiveness of the proposed algorithms.
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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 | 0.001 | 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".