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Record W4322731090 · doi:10.1109/tbc.2023.3243789

In-Band Full-Duplex Communications in ATSC 3.0 Single Frequency Network

2023· article· en· W4322731090 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Broadcasting · 2023
Typearticle
Languageen
FieldEngineering
TopicFull-Duplex Wireless Communications
Canadian institutionsCommunications Research Centre Canada
FundersEusko Jaurlaritza
KeywordsSingle-frequency networkTransmitterComputer scienceBackhaul (telecommunications)Electronic engineeringSIGNAL (programming language)MultiplexingInterference (communication)Pilot signalBroadcasting (networking)WirelessChannel (broadcasting)TelecommunicationsComputer networkEngineeringTransmission (telecommunications)

Abstract

fetched live from OpenAlex

Wireless in-band backhaul, a.k.a. in-band distribution links (IDL), is a spectrum-efficient and cost-effective enabling technology to the realization of Advanced Television Systems Committee (ATSC) 3.0 in the single frequency network (SFN) mode, where all the transmitter towers are synchronized to transmit the same broadcast signal in the same frequency band. Inter-tower communications network (ITCN) transforms the broadcast towers into a mesh network, thereby introducing datacasting capability to the traditional broadcast network. Both the ITCN and IDL can be operated in the most spectrum-efficient in-band full-duplex (IBFD) mode. In these situations, the ITCN/IDL receivers at the SFN towers receive the signal of interest (SOI) not only severely corrupted by the self-interference signal from its co-located transmitter, but also the co-channel interference signals from neighbouring transmitters. Moreover, the ITCN/IDL signals may be combined with the broadcast signal in the Layer Division Multiplexing (LDM) format to achieve better overall spectral efficiency. Therefore, the LDM inter-layer interference must also be mitigated. In this paper, the interferences for the ITCN/IDL signal in the SFN environment are analyzed, and a novel iterative successive signal cancellation scheme is proposed to effectively mitigate the interferences in the ITCN/IDL signal detection process in ATSC 3.0 SFNs.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.267
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it