Energy-Efficient Resource Allocation in Single-RF Load-Modulated Massive MIMO HetNets
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Bibliographic record
Abstract
Due to the dramatic increase in wireless data traffic and the associated increase in energy consumption, designing energy-efficient wireless networks with improved spectral efficiency is a pressing concern. The focus of this article is the design of a green, highly energy-efficient cellular heterogeneous network (HetNet) by taking advantage of multiple-input-multiple-output (MIMO) structure and deployment of small cells. We consider the downlink of a two-tier HetNet, in which multiple-antenna small cells are coordinated to serve users. Even though the deployment of MIMO together with small cells improves the communication system's performance in terms of data rate and reliability, circuit energy consumption in such a network is a critical issue. To address this, an energy-efficient antenna selection and radio resource block assignment algorithm is proposed for the small cells, and a single radio-frequency (RF) chain structure is considered for the massive MIMO macro base station. Then, while coordinating transmissions between cells subject to user-centric clustering, an energy-efficient beamforming design and power allocation optimization problem with respect to the quality of service requirement of users, transmit power budget of base stations, and fronthaul capacity is formulated; the problem is solved using the Dinkelbach method. Simulation results demonstrate the performance potential of our proposed algorithm in terms of energy efficiency and spectral efficiency.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it