Energy Efficient Joint Power Allocation and Beamforming for Cloud Radio Access Network

Jiakuo ZUO; Longxiang YANG; Nan BAO; Guanming LU

doi:10.11999/JEIT180218

Volume 40 Issue 12

Nov. 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(12): 2979-2985

Jiakuo ZUO, Longxiang YANG, Nan BAO, Guanming LU. Energy Efficient Joint Power Allocation and Beamforming for Cloud Radio Access Network[J]. Journal of Electronics & Information Technology, 2018, 40(12): 2979-2985. doi: 10.11999/JEIT180218

Citation:

Jiakuo ZUO, Longxiang YANG, Nan BAO, Guanming LU. Energy Efficient Joint Power Allocation and Beamforming for Cloud Radio Access Network[J]. Journal of Electronics & Information Technology, 2018, 40(12): 2979-2985. doi: 10.11999/JEIT180218

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Energy Efficient Joint Power Allocation and Beamforming for Cloud Radio Access Network

doi: 10.11999/JEIT180218

1.
College of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
2.
College of Telecommunications & Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210023, China

Funds: The Postdoctoral Fund of Jiangsu Province (SBH17024), The Jiangsu University of Natural Science Foundation (15KJB510026), The Natural Science Foundation of Jiangsu Province (BK20150866), The Introduction of Talent Fund of Nanjing University of Posts and Telecommunications (NY215046, NY217056), The National Natural Science Fundation of China (61801237, 61701255)

Received Date: 2018-03-07
Rev Recd Date: 2018-08-16

Available Online: 2018-08-29

Publish Date: 2018-12-01

Abstract

Abstract

The resource allocation for Cloud Radio Access Network (C-RAN) is investigated. The max-min fairness criterion is used as the optimization criterion and the Energy Efficiency (EE) of C-RAN users is taken as the optimization objective function, by maximizing the EE of the worst link under the constraints of maximum transmit power and minimum transmit rate, the user transmit power and Remote Radio Heads (RRHs) beamforming vectors are jointly optimized. The above optimization problem belongs to the nonlinear and fractional programming problem. First, the original nonconvex optimization problem is transformed into an equivalent optimization problem in subtractive form. Then, by introducing a new variable, non-smooth equivalent optimization problem is transformed into a smooth optimization problem. Finally, a two-layer iterative power allocation and beamforming algorithm is proposed. The proposed algorithm is compared with traditional non-EE resource allocation algorithm and EE maximization algorithm. The experimental results show that the proposed algorithm is effective in improving the EE and the fairness of resource allocation.
- Cloud Radio Access Network (C-RAN),
- Energy efficiency,
- Power allocation,
- Beamforming

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References(18)

References

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