Abstract
In this paper, we focus on maximizing weighted sum energy efficiency (EE) for a multi-cell multi-user channel. In order to solve this non-convex problem, we first decompose the original problem into a sequence of parallel subproblems which can optimized separately. For each subproblem, a base station employs dirty paper coding to maximize the EE for users within a cell while regulating interference induced to other cells. Since each subproblem can be transformed to a convex multiple-access channel problem, the proposed method provides a closed-form solution for power allocation. Then, based on the derived optimal covariance matrix for each subproblem, a local optimal solution is obtained to maximize the sum EE. Finally, simulation results show that our algorithm based on non-linear precoding achieves about 20 percent performance gains over the conventional linear precoding method.
| Original language | English |
|---|---|
| Article number | 000122 |
| Pages (from-to) | 873-883 |
| Number of pages | 11 |
| Journal | Journal of Communications and Networks |
| Volume | 18 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2016 Dec 1 |
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Keywords
- Dirty paper coding
- Energy efficiency
- Multicell broadcast channels
ASJC Scopus subject areas
- Information Systems
- Computer Networks and Communications
Cite this
Joint energy efficiency optimization with nonlinear precoding in multi-cell broadcast systems. / Gui, Xin; Lee, Kyoung Jae; Jung, Jaehoon; Lee, Inkyu.
In: Journal of Communications and Networks, Vol. 18, No. 6, 000122, 01.12.2016, p. 873-883.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Joint energy efficiency optimization with nonlinear precoding in multi-cell broadcast systems
AU - Gui, Xin
AU - Lee, Kyoung Jae
AU - Jung, Jaehoon
AU - Lee, Inkyu
PY - 2016/12/1
Y1 - 2016/12/1
N2 - In this paper, we focus on maximizing weighted sum energy efficiency (EE) for a multi-cell multi-user channel. In order to solve this non-convex problem, we first decompose the original problem into a sequence of parallel subproblems which can optimized separately. For each subproblem, a base station employs dirty paper coding to maximize the EE for users within a cell while regulating interference induced to other cells. Since each subproblem can be transformed to a convex multiple-access channel problem, the proposed method provides a closed-form solution for power allocation. Then, based on the derived optimal covariance matrix for each subproblem, a local optimal solution is obtained to maximize the sum EE. Finally, simulation results show that our algorithm based on non-linear precoding achieves about 20 percent performance gains over the conventional linear precoding method.
AB - In this paper, we focus on maximizing weighted sum energy efficiency (EE) for a multi-cell multi-user channel. In order to solve this non-convex problem, we first decompose the original problem into a sequence of parallel subproblems which can optimized separately. For each subproblem, a base station employs dirty paper coding to maximize the EE for users within a cell while regulating interference induced to other cells. Since each subproblem can be transformed to a convex multiple-access channel problem, the proposed method provides a closed-form solution for power allocation. Then, based on the derived optimal covariance matrix for each subproblem, a local optimal solution is obtained to maximize the sum EE. Finally, simulation results show that our algorithm based on non-linear precoding achieves about 20 percent performance gains over the conventional linear precoding method.
KW - Dirty paper coding
KW - Energy efficiency
KW - Multicell broadcast channels
UR - http://www.scopus.com/inward/record.url?scp=85010506529&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85010506529&partnerID=8YFLogxK
U2 - 10.1109/JCN.2016.000122
DO - 10.1109/JCN.2016.000122
M3 - Article
AN - SCOPUS:85010506529
VL - 18
SP - 873
EP - 883
JO - Journal of Communications and Networks
JF - Journal of Communications and Networks
SN - 1229-2370
IS - 6
M1 - 000122
ER -