Learning-Based Small Cell Traffic Balancing Over Licensed and Unlicensed Bands
| Autor: | Mehdi Bennis, M. G. S. Sriyananda |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science 020302 automobile design & engineering 020206 networking & telecommunications Throughput 02 engineering and technology Maximization Interference (wave propagation) Spectrum management Signal-to-noise ratio 0203 mechanical engineering Control and Systems Engineering Telecommunications link 0202 electrical engineering electronic engineering information engineering Macrocell Electrical and Electronic Engineering business Efficient energy use Computer network |
| Zdroj: | IEEE Wireless Communications Letters. 6:694-697 |
| ISSN: | 2162-2345 2162-2337 |
| DOI: | 10.1109/lwc.2017.2734082 |
| Popis: | Unlicensed spectrum can be utilized by long term evolution (LTE) cellular systems to satisfy high throughput requirements. In this letter, a regret-based learning aided downlink traffic balancing scheme for licensed and unlicensed bands is proposed while ensuring fair coexistence of LTE-unlicensed (LTE-U) and Wi-Fi devices in the same band. It is further improved with the optimization of energy efficiency (EE) for small cell (SC) and macrocell scenarios followed by an inter-SC interference management mechanism with better performance over the existing literature. Compared to the cases with fixed airtime, up to 8%–10% superior results are shown for the scenarios of EE and rate maximization, respectively. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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