Name
Abstract | ||
|---|---|---|
In this paper, the energy efficiency in a cellular network with
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">device-to-device</italic>
communications is studied from user fairness perspective. A mixed-integer max-min optimization problem is formulated, in which both mode selection and resource allocation are considered. Since the optimal solution requires exhaustive search, which is NP-hard, two suboptimal methods are derived. First, a Lagrangian decomposition-based method is proposed to jointly solve subcarrier assignment and power allocation with integer constraint relaxation under different modes. To further reduce the computational complexity, a
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">low-complexity decomposition</italic>
(LCD) method is derived. A novel mode selection scheme, a subcarrier assignment scheme, a power allocation scheme, and a mode switching scheme are introduced and analyzed. The LCD method is scalable and suitable for a large number of devices and subcarriers. Simulation results demonstrate that our proposed suboptimal methods achieve satisfactory energy efficiency performance and promote the fairness among individual users. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/jsyst.2018.2838539 | IEEE Systems Journal |
Keywords | Field | DocType |
Device-to-device communication,Resource management,Liquid crystal displays,Cellular networks,Optimization,Communication networks,Switches | Resource management,Subcarrier,Mathematical optimization,Brute-force search,Efficient energy use,Computer science,Computer network,Resource allocation,Cellular network,Optimization problem,Computational complexity theory | Journal |
Volume | Issue | ISSN |
13 | 99 | 1932-8184 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shengjie Guo | 1 | 19 | 3.31 |
| Xiangwei Zhou | 2 | 451 | 35.87 |
| Sa Xiao | 3 | 21 | 9.05 |
| Mingxuan Sun | 4 | 180 | 20.16 |