A Power-Saving Scheme using Recursive Sleeping-Cycles and Active Wake-up in LTE-MTC networks
| Autor: | Cheng-Chun Liu, 劉貞君 |
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| Rok vydání: | 2018 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 106 In a Machine-Type Communication (MTC) network, since a machine has no way to know whether or not the base station has buffered data to deliver, it must continuously power on its receiving antenna. Thus, too much unnecessary energy may be consumed, if a machine in fact doesn’t have buffered data to receive. Therefore, in LTE standard, the Discontinuous Reception (DRX) mechanism for power saving is proposed to remedy the above-mentioned problem. However, DRX does not take into account the characteristics that different types of machine have different frequencies in receiving data. This thesis therefore modifies the DRX and proposes an innovative power-saving mechanism, referred to as Recursive Sleeping-cycles and active Wake-up (RSW). RSW differentiates machine types by its data-receiving frequencies and then attempts to enlarge the sleeping cycles, which can effectively reduce both power consumption and packet loss ratio. In the recursive sleeping-cycles scheme, we design a threshold for a machine to stay in the long-sleep state. When the threshold is reached, the long-sleep cycle will be increased exponentially. In the active wake-up scheme, we design a buffer threshold in the base station for each machine. When data packets accumulated in the buffer reaches the threshold, the base station will actively wake up the machine to receive the buffered data. Finally, we modified the NS-3 (Network Simulator-3) LTE modules to simulate the RSW and the DRX. Two traffic generators are designed respectively for two types of machine with high and low frequencies in receiving data. In the simulation, we vary three thresholds, respectively for short-sleep state, long-sleep state, and the buffer in base station to analyze and compare energy consumption and packet loss ratio between RSW and DRX. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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