Bibliographic record
Abstract
For a wireless network, the transmit power is one of the main radio resources. Two major objectives of power control in a wireless network are to extend UEs’ battery life and to maintain an acceptable QoS (e.g., in terms of the SINR or throughput) for all UEs by minimizing interferences to UEs. Data services require a higher SINR (as a measure of QoS) as compared to the voice service, because the latter is more tolerant to bit errors. In contrast to the voice service for which the QoS is measured by a step function of the SINR [1], the commonly used QoS measure for the data service is, in general, an increasing function of the SINR. A distributed scheme for power control is preferred to a centralized one, because in the former, the transmit power level of a user is decided by that user by utilizing the locally available information and uses minimal feedback from the BS. In this way, the need for frequent power setting commands by the BS are avoided, and the processing capabilities at the BS needed to obtain the instantaneous uplink power levels of all UEs are substantially reduced. In contrast, a centralized approach needs to have information about path-gains and throughput requirements for all UEs at the BS. In this chapter, we first discuss why power control is needed and state the objectives of power control, followed by a discussion on conventional open/closed loop and centralized power control algorithms. Then various existing distributed power control algorithms are presented and evaluated according to different criteria. Objectives of Power Control In Chapter 5, we studied the relation between transmit power and SINR vectors. We know that the achieved SINRs by UEs at uplink or downlink determine their experienced QoS. Now the question is how the predetermined target QoS for users can be achieved. The transmit power cannot be set at random or at a fixed level by the UEs. For example, if the UEs served by the same cell transmit at the same fixed power level, the SINR for the UEs with good path-gains (e.g., those near the BS) are high, whereas for the far UEs it will be low. This is called the near-far problem , which can be addressed if the transmit power is dynamically controlled.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.008 | 0.003 |
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".