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Record W2765737508

Two–Way Relaying Communications with OFDM and BICM/BICM-ID

2016· article· en· W2765737508 on OpenAlexfundno aff
Hongzhong Yan

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2016
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Saskatchewan
KeywordsOrthogonal frequency-division multiplexingComputer scienceTelecommunicationsChannel (broadcasting)
DOInot available

Abstract

fetched live from OpenAlex

Relay-aided communication methods have gained strong interests in academic community\nand been applied in various wireless communication scenarios. Among different techniques\nin relay-aided communication system, two-way relaying communication (TWRC) achieves\nthe highest spectral efficiency due to its bi-directional transmission capability. Nevertheless,\ndifferent from the conventional point-to-point communication system, TWRC suffers from\ndetection quality degradation caused by the multiple-access interference (MAI). In addition,\nbecause of the propagation characteristics of wireless channels, fading and multipath\ndispersion also contribute strongly to detection errors. Therefore, this thesis is mainly concerned\nwith designing transmission and detection schemes to provide good detection quality\nof TWRC while taking into account the negative impacts of fading, multipath dispersion\nand multiple-access interference.\nFirst, a TWRC system operating over multipath fading channels is considered and orthogonal\nfrequency-division multiplexing (OFDM) is adopted to handle the inter-symbol\ninterference (ISI) caused by the multipath dispersion. In particular, adaptive physical-layer\nnetwork coding (PNC) is employed to address the MAI issue. By analyzing the detection\nerror probability, various adaptive PNC schemes are discussed for using with OFDM and\nthe scheme achieving the best trade-off among performance, overhead and complexity is\nsuggested.\nIn the second part of the thesis, the design of distributed precoding in TWRC using\nOFDM under multipath fading channels is studied. The objective is to design a distributed\nprecoding scheme which can alleviate MAI and achieve multipath diversity to combat fading.\nSpecifically, three types of errors are introduced when analyzing the error probability in the\nmultiple access (MA) phase. Through analysis and simulation, the scheme that performs\nprecoding in both time and frequency domains is demonstrated to achieve the maximum\ndiversity gains under all types of errors.\nFinally, the last part of the thesis examines a communication system incorporating forward\nerror correction (FEC) codes. Specifically, bit-interleaved code modulation (BICM)\nwithout and with iterative decoding (BICM-ID) are investigated in a TWRC system. Distributed\nlinear constellation precoding (DLCP) is applied to handle MAI and the design\nof DLCP in a TWRC system using BICM/BICM-ID is discussed. Taking into account the\nmultiple access channel from the terminal nodes to the relay node, decoding based on the\nquaternary code representation is introduced. Several error probability bounds are derived\nto aid in the design of DLCP. Based on these bounds, optimal parameters of DLCP are\nobtained through analysis and computer search. It is also found that, by combining XORbased\nnetwork coding with successful iterative decoding, the MAI is eliminated and thus\nDLCP is not required in a BICM-ID system.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.003
Open science0.0020.002
Research integrity0.0000.000
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 head0.016
GPT teacher head0.186
Teacher spread0.170 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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