### Abstract

In this paper, we investigate an energy efficiency (EE) maximization problem in multiple input single output broadcast channels. The optimization problem in this system model is difficult to solve in general, since it is in non-convex fractional form. Hence, conventional algorithms have addressed the problem in an iterative manner for each channel realization, which leads to high computational complexity. To tackle this complexity issue, we propose a new simple method by utilizing the fact that EE maximization becomes identical to spectral efficiency (SE) maximization for the region of the power below a certain transmit power termed as saturation power. In order to calculate the saturation power, we first introduce upper and lower bounds of the EE performance by adopting a maximal ratio transmission beamforming strategy. Then, we propose an efficient way to compute the saturation power for the EE maximization problem. Once we determine the saturation power in advance, we can transform the EE maximization problem into a simplified suboptimal EE problem which can be solved by the SE maximization schemes with low complexity. The derived saturation power is parameterized by employing random matrix theory, which relies only on the second order channel statistics. Hence, this approach needs much lower computational complexity compared to a conventional scheme which requires instantaneous channel state information. Numerical results validate that the proposed algorithm achieves near optimal EE performance with significantly reduced complexity.

Original language | English |
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Journal | IEEE Transactions on Wireless Communications |

DOIs | |

Publication status | Accepted/In press - 2017 Jun 27 |

### Fingerprint

### Keywords

- Array signal processing
- Complexity theory
- Energy efficiency (EE)
- MISO
- multiple-input single-output broadcast channels
- Optimization
- Power demand
- random matrix theory
- saturation power
- Upper bound
- Wireless communication

### ASJC Scopus subject areas

- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering

### Cite this

**Saturation Power based Simple Energy Efficiency Maximization Schemes for MISO Broadcast Channel Systems.** / Jung, Jaehoon; Lee, Sang Rim; Lee, Inkyu.

Research output: Contribution to journal › Article

}

TY - JOUR

T1 - Saturation Power based Simple Energy Efficiency Maximization Schemes for MISO Broadcast Channel Systems

AU - Jung, Jaehoon

AU - Lee, Sang Rim

AU - Lee, Inkyu

PY - 2017/6/27

Y1 - 2017/6/27

N2 - In this paper, we investigate an energy efficiency (EE) maximization problem in multiple input single output broadcast channels. The optimization problem in this system model is difficult to solve in general, since it is in non-convex fractional form. Hence, conventional algorithms have addressed the problem in an iterative manner for each channel realization, which leads to high computational complexity. To tackle this complexity issue, we propose a new simple method by utilizing the fact that EE maximization becomes identical to spectral efficiency (SE) maximization for the region of the power below a certain transmit power termed as saturation power. In order to calculate the saturation power, we first introduce upper and lower bounds of the EE performance by adopting a maximal ratio transmission beamforming strategy. Then, we propose an efficient way to compute the saturation power for the EE maximization problem. Once we determine the saturation power in advance, we can transform the EE maximization problem into a simplified suboptimal EE problem which can be solved by the SE maximization schemes with low complexity. The derived saturation power is parameterized by employing random matrix theory, which relies only on the second order channel statistics. Hence, this approach needs much lower computational complexity compared to a conventional scheme which requires instantaneous channel state information. Numerical results validate that the proposed algorithm achieves near optimal EE performance with significantly reduced complexity.

AB - In this paper, we investigate an energy efficiency (EE) maximization problem in multiple input single output broadcast channels. The optimization problem in this system model is difficult to solve in general, since it is in non-convex fractional form. Hence, conventional algorithms have addressed the problem in an iterative manner for each channel realization, which leads to high computational complexity. To tackle this complexity issue, we propose a new simple method by utilizing the fact that EE maximization becomes identical to spectral efficiency (SE) maximization for the region of the power below a certain transmit power termed as saturation power. In order to calculate the saturation power, we first introduce upper and lower bounds of the EE performance by adopting a maximal ratio transmission beamforming strategy. Then, we propose an efficient way to compute the saturation power for the EE maximization problem. Once we determine the saturation power in advance, we can transform the EE maximization problem into a simplified suboptimal EE problem which can be solved by the SE maximization schemes with low complexity. The derived saturation power is parameterized by employing random matrix theory, which relies only on the second order channel statistics. Hence, this approach needs much lower computational complexity compared to a conventional scheme which requires instantaneous channel state information. Numerical results validate that the proposed algorithm achieves near optimal EE performance with significantly reduced complexity.

KW - Array signal processing

KW - Complexity theory

KW - Energy efficiency (EE)

KW - MISO

KW - multiple-input single-output broadcast channels

KW - Optimization

KW - Power demand

KW - random matrix theory

KW - saturation power

KW - Upper bound

KW - Wireless communication

UR - http://www.scopus.com/inward/record.url?scp=85023761277&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85023761277&partnerID=8YFLogxK

U2 - 10.1109/TWC.2017.2718503

DO - 10.1109/TWC.2017.2718503

M3 - Article

AN - SCOPUS:85023761277

JO - IEEE Transactions on Wireless Communications

JF - IEEE Transactions on Wireless Communications

SN - 1536-1276

ER -