Bibliographic record
Abstract
Relay-aided communication methods have gained strong interests in academic community and been applied in various wireless communication scenarios. Among different techniques in relay-aided communication system, two-way relaying communication (TWRC) achieves the highest spectral efficiency due to its bi-directional transmission capability. Nevertheless, different from the conventional point-to-point communication system, TWRC suffers from detection quality degradation caused by the multiple-access interference (MAI). In addition, because of the propagation characteristics of wireless channels, fading and multipath dispersion also contribute strongly to detection errors. Therefore, this thesis is mainly concerned with designing transmission and detection schemes to provide good detection quality of TWRC while taking into account the negative impacts of fading, multipath dispersion and multiple-access interference. First, a TWRC system operating over multipath fading channels is considered and orthogonal frequency-division multiplexing (OFDM) is adopted to handle the inter-symbol interference (ISI) caused by the multipath dispersion. In particular, adaptive physical-layer network coding (PNC) is employed to address the MAI issue. By analyzing the detection error probability, various adaptive PNC schemes are discussed for using with OFDM and the scheme achieving the best trade-off among performance, overhead and complexity is suggested. In the second part of the thesis, the design of distributed precoding in TWRC using OFDM under multipath fading channels is studied. The objective is to design a distributed precoding scheme which can alleviate MAI and achieve multipath diversity to combat fading. Specifically, three types of errors are introduced when analyzing the error probability in the multiple access (MA) phase. Through analysis and simulation, the scheme that performs precoding in both time and frequency domains is demonstrated to achieve the maximum diversity gains under all types of errors. Finally, the last part of the thesis examines a communication system incorporating forward error correction (FEC) codes. Specifically, bit-interleaved code modulation (BICM) without and with iterative decoding (BICM-ID) are investigated in a TWRC system. Distributed linear constellation precoding (DLCP) is applied to handle MAI and the design of DLCP in a TWRC system using BICM/BICM-ID is discussed. Taking into account the multiple access channel from the terminal nodes to the relay node, decoding based on the quaternary code representation is introduced. Several error probability bounds are derived to aid in the design of DLCP. Based on these bounds, optimal parameters of DLCP are obtained through analysis and computer search. It is also found that, by combining XORbased network coding with successful iterative decoding, the MAI is eliminated and thus DLCP is not required in a BICM-ID system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".