Distributed Space-Time Continuous Phase Modulation Code Design
Bibliographic record
Abstract
In this paper, distributed space-time (ST) codes for continuous-phase modulation (CPM) are introduced. The distributed ST codes are designed to operate in wireless networks containing a large set of nodes N, of which only a small a priori unknown subset S sub N will be active at any time. Under the proposed scheme, a relay node transmits a signal which is the product of a diagonal block-based ST code (optimized specifically for ST-CPM transmission) and a signature vector of length N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> uniquely assigned to each node in the network. An efficient method is presented for the design and optimization of appropriate signature vector sets, assuming a quasi-static, frequency nonselective fading channel model. If a properly designed signature vector set is employed it is shown that a diversity order of d = min{N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> ,N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> } can be achieved, where N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> is the number of active relay nodes. The decoding complexity of the proposed scheme is shown to be independent of the number of active relay nodes, and non-coherent receiver implementations, which do not require channel estimation, are applicable. Compared to distributed ST transmission with linear modulation, distributed ST-CPM can considerably reduce the energy consumption at the transmitter due to the constant envelope of the transmit signal. At the same time, the additional energy consumption due to more complex receiver processing can be kept low. Therefore, the proposed distributed ST-CPM scheme is particularly apt for energy-efficient cooperative transmission in wireless networks.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 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".