Abstract
In this paper, we propose a novel cell splitting approach
for massive multiple-input multiple-output (MIMO) base
stations to improve energy efficiency. The user
equipments (UEs) in the cell are divided into two groups
based on their distances to the base station. These two
UE groups are scheduled at different time slots, which
effectively splits a cell into inner and outer cells. The
number of transmitting and receiving antennas together
with the downlink and uplink transmission powers are
adapted according to the number of cell edge and center
UEs to maximize energy efficiency. We propose two
algorithms to optimize the number of antennas and
transmission powers. Cell splitting is able to reach
energy efficiency (EE) gain of 11-41 % depending on the
UE density when compared to a conventional
load-adaptive massive MIMO system. The inevitable loss of
cell edge UE rates can be controlled by setting a target
UE rate, which also reduces the search space of the
optimization algorithm.
| Original language | English |
|---|---|
| Title of host publication | 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall) |
| Publisher | IEEE Institute of Electrical and Electronic Engineers |
| Number of pages | 6 |
| ISBN (Electronic) | 978-1-5090-5935-5, 978-1-5090-5934-8 |
| ISBN (Print) | 978-1-5090-5936-2 |
| DOIs | |
| Publication status | Published - 2 Jul 2017 |
| MoE publication type | A4 Article in a conference publication |
| Event | IEEE 86th Vehicular Technology Conference, VTC-Fall 2017 - Toronto, Canada Duration: 24 Sept 2017 → 27 Sept 2017 |
Conference
| Conference | IEEE 86th Vehicular Technology Conference, VTC-Fall 2017 |
|---|---|
| Abbreviated title | VTC-Fall 2017 |
| Country/Territory | Canada |
| City | Toronto |
| Period | 24/09/17 → 27/09/17 |
Keywords
- 5G
- Energy Efficiency
- Load Adaptive Base Station
- Massive Mimo
- User Scheduling
