System cost minimization in cloud RAN with limited fronthaul capacity
Cloud radio access network (C-RAN) is emerging as a potential alternative for the next generation RAN by merging RAN and cloud computing together. In this paper, we consider the baseband unit (BBU) pool of C-RAN as a collection of virtual machines (VMs). We allow each user equipment (UE) to associat...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
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2019
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| Online Access: | https://hdl.handle.net/10356/102695 http://hdl.handle.net/10220/47837 |
| _version_ | 1811689389647986688 |
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| author | Tang, Jianhua Tay, Wee Peng Quek, Tony Q. S. Liang, Ben |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Tang, Jianhua Tay, Wee Peng Quek, Tony Q. S. Liang, Ben |
| author_sort | Tang, Jianhua |
| collection | NTU |
| description | Cloud radio access network (C-RAN) is emerging as a potential alternative for the next generation RAN by merging RAN and cloud computing together. In this paper, we consider the baseband unit (BBU) pool of C-RAN as a collection of virtual machines (VMs). We allow each user equipment (UE) to associate with multiple VMs in the BBU pool, and each remote radio head (RRH) can only serve a limited number of UEs. Under this model, we jointly optimize the VM activation in the BBU pool and sparse beamforming in the coordinated RRH cluster, which is constrained by limited fronthaul capacity, to minimize the system cost of C-RAN. We formulate this problem as a mixed-integer nonlinear programming problem, and then propose efficient methods to optimize the number of active VMs, as well as the sparse beamforming vectors. Moreover, we derive a closed-form solution for the beamforming vectors. Simulation results suggest that our proposed algorithms have better performance than the benchmark algorithms in terms of both system cost and robustness. |
| first_indexed | 2024-10-01T05:47:20Z |
| format | Journal Article |
| id | ntu-10356/102695 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:47:20Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | ntu-10356/1026952020-03-07T14:00:34Z System cost minimization in cloud RAN with limited fronthaul capacity Tang, Jianhua Tay, Wee Peng Quek, Tony Q. S. Liang, Ben School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering VM activation C-RAN Cloud radio access network (C-RAN) is emerging as a potential alternative for the next generation RAN by merging RAN and cloud computing together. In this paper, we consider the baseband unit (BBU) pool of C-RAN as a collection of virtual machines (VMs). We allow each user equipment (UE) to associate with multiple VMs in the BBU pool, and each remote radio head (RRH) can only serve a limited number of UEs. Under this model, we jointly optimize the VM activation in the BBU pool and sparse beamforming in the coordinated RRH cluster, which is constrained by limited fronthaul capacity, to minimize the system cost of C-RAN. We formulate this problem as a mixed-integer nonlinear programming problem, and then propose efficient methods to optimize the number of active VMs, as well as the sparse beamforming vectors. Moreover, we derive a closed-form solution for the beamforming vectors. Simulation results suggest that our proposed algorithms have better performance than the benchmark algorithms in terms of both system cost and robustness. MOE (Min. of Education, S’pore) Accepted version 2019-03-18T07:27:06Z 2019-12-06T20:59:16Z 2019-03-18T07:27:06Z 2019-12-06T20:59:16Z 2017 Journal Article Tang, J., Tay, W. P., Quek, T. Q. S., & Liang, B. (2017). System cost minimization in cloud RAN with limited fronthaul capacity. IEEE Transactions on Wireless Communications, 16(5), 3371-3384. doi:10.1109/TWC.2017.2682079 1536-1276 https://hdl.handle.net/10356/102695 http://hdl.handle.net/10220/47837 10.1109/TWC.2017.2682079 en IEEE Transactions on Wireless Communications © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TWC.2017.2682079 15 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering VM activation C-RAN Tang, Jianhua Tay, Wee Peng Quek, Tony Q. S. Liang, Ben System cost minimization in cloud RAN with limited fronthaul capacity |
| title | System cost minimization in cloud RAN with limited fronthaul capacity |
| title_full | System cost minimization in cloud RAN with limited fronthaul capacity |
| title_fullStr | System cost minimization in cloud RAN with limited fronthaul capacity |
| title_full_unstemmed | System cost minimization in cloud RAN with limited fronthaul capacity |
| title_short | System cost minimization in cloud RAN with limited fronthaul capacity |
| title_sort | system cost minimization in cloud ran with limited fronthaul capacity |
| topic | DRNTU::Engineering::Electrical and electronic engineering VM activation C-RAN |
| url | https://hdl.handle.net/10356/102695 http://hdl.handle.net/10220/47837 |
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