Joint Spectrum Sharing and Power Allocation for OFDM-Based Two-Way Relaying
Bibliographic record
Abstract
Considering a bidirectional amplify-and-forward based multi-carrier multi-relay network, we formulate two different joint power allocation and network beamforming problems. In the first formulation, we aim to minimize the total transmit power of the network, subject to two constraints on the transceiver rates. In the second problem, our goal is to maximize the sum-rate of the two transceivers subject to a constraint on the total network transmit power. In both problems, the design parameters include the relay beamforming weights and the transceiver power allocations over all subcarriers. We propose a two-step iterative method to tackle each problem and show that each method leads to (at least) a locally optimum solution. Each iterative method alternates between solving the underlying problem for one set of variables while the other set is fixed and vice versa. Each subproblem is shown to be amenable to a computationally efficient solution. Our simulation results show the efficiency of the proposed techniques.
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 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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".