LDPC-Coded LDM Systems Employing Non-Uniform Injection Level for Combining Broadcast and Multicast/Unicast Services
Why this work is in the frame
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Bibliographic record
Abstract
Layered Division Multiplexing (LDM) is a Power-based Non-Orthogonal Multiplexing (P-NOM) technique that has been implemented in the Advanced Television System Committee (ATSC) 3.0 terrestrial TV physical layer to effectively multiplex services with different robustness and data rate requirements. As communication systems quickly evolve, the services to be delivered are becoming more diverse and versatile. Up to now, the LDM system adopted in the terrestrial TV system uses a uniform injection level for the lower-level (or Layer 2) signal injection. This paper investigates the non-uniform injection level LDM (NULDM). The proposed technique can explore the Unequal Error Protection (UEP) property of Low-Density Parity-Check (LDPC) codes and the flexible power allocation nature of the NULDM to improve the system performance and spectrum efficiency. NULDM enables the seamless integration of broadcast/multicast and unicast services in one RF channel, where the unicast signal can assign different resources (power, frequency, and time) based on the UE distance and service requirements. Meanwhile, more power could be allocated to improve the upper layer (or Layer 1) broadcast and datacast services. To make better use of the UEP property of LDPC codes in NULDM, the extended Gaussian mixture approximation (EGMA) method is used to design bit interleaving patterns. Additionally, inspired by the channel order of polar codes, this paper proposes an LDPC sub-block interleaving order (SBIO) scheme that performs similarly to the EGMA interleaving model, while better adapting to the diverse needs of proposed mixed service delivery scenarios for convergence of broadband wireless communications and broadcasting systems.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 it