Abstract
Fractional power control (FPC) is the simplified version of open loop power control (OLPC) in long term evolution (LTE) that relies on downlink path loss information from base station (BS). This allows user equipment (UE) to decide which power to use for uplink transmission. However, asymmetric behavior of uplink and downlink transmission in crowded network might cause unfair transmit power estimation. This motivates our investigation of implementing uplink path loss and q-learning algorithm to enable UE to decide appropriate transmit power on its own. In this study we apply the concept of FPC into q-learning, enabling UE to find suitable transmit power with respect to uplink path loss. 3GPP uplink path loss model is exploited in our study. We compare outputs between our proposed method and FPC.. From simulation, we find out that DQL performs better as compared to fractional power control in terms of signal-to-interference-noise-ratio (SINR) with average increase factor of 3.5.
| Original language | English |
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| Title of host publication | 2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks, CAMAD 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 54-58 |
| Number of pages | 5 |
| ISBN (Print) | 9781467381864 |
| DOIs | |
| Publication status | Published - 25 Jan 2016 |
| Event | 20th IEEE International Workshop on Computer Aided Modelling and Design of Communication Links and Networks, CAMAD 2015 - Guildford, United Kingdom Duration: 7 Sept 2015 → 9 Sept 2015 |
Conference
| Conference | 20th IEEE International Workshop on Computer Aided Modelling and Design of Communication Links and Networks, CAMAD 2015 |
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| Country/Territory | United Kingdom |
| City | Guildford |
| Period | 7/09/2015 → 9/09/2015 |
Keywords
- Decentralized q-learning
- Fractional power control
- Long term evolution
- Open loop power control