Power minimization and optimum ONU placements in integrated wireless optical access networks
Bibliographic record
Abstract
The deployment of optical fibre in place of copper cable in access networks has experienced remarkable growth over the past several years due to a wide range of benefits. A major benefit of optical fibre over copper cable is that it is more secure and immune to electromagnetic interferences. Optical fibre has also provided the capability of handling higher throughputs for longer distances, and experiences no crosstalk between other fibre optic cables. However, the last mile reach to end-users with optical fibre is very costly. This alternative replacement results in increased costs for manual labour and energy consumption in the access network. The current demand in all areas of telecommunications, and especially access networks, is greener networking. In order to offset the high costs of optical access implementations and to satisfy this demand, an investigation into integrated wireless optical access networks (IWOAN) is warranted. \nThe proliferation of wireless devices has also motivated the interest in IWOAN as it combines the flexibility and efficiency of wireless with the security and stability provided by optical. With the emergence of smart phones and tablets, wireless access networks are now supporting an increasing amount of traffic volume with improved throughput and accessibility. We employ a Passive Optical Network (PON) infrastructure from the central office to the customer, traced from the Optical Line Terminal (OLT) to the customer premises devices known as Optical Network Units (ONUs) for IWOAN. At the ONU, the optical fibre is terminated and wireless communication is implemented. The ONU acts as a wireless access point/gateway for wireless Base Stations (BS) serving different coverage areas in point-to-point topology. With recent trends of advanced wireless technologies, premium rich applications such as multimedia streaming, interactive gaming and cloud computing are delivered in a satisfactory and economic way. This wireless-optical integration aims to reduce and solve the cost of replacing copper cables. However, another issue is raised with increased costs in energy consumption due to the integration of wireless and optical communication. Typically a large number of ONUs need to be deployed in order to serve many wireless BSs located in different coverage areas. As a result, any cost savings gained by the integration process is exhausted with the increased cost of power consumption.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.004 | 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".