Kien-Giang Nguyen, ; Quang-Doanh Vu, ; Le-Nam Tran, ; Juntti, Markku: 'Energy-efficient methods for cloud radio access networks' (Telecommunications, 2020), 'Green Communications for Energy-Efficient Wireless Systems and Networks', Chap. 11, pp. 295-330, DOI: 10.1049/PBTE091E_ch11 IET Digital Library, https://digital-library.theiet.org/content/books/10.1049/pbte091e_ch11
Energy-efficient methods for cloud radio access networks
|Author:||Nguyen, Kien-Giang1,2; Vu, Quang-Doanh2; Tran, Le-Nam3;|
1Nokia, Oulu, Finland
2Centre for Wireless Communications, University of Oulu, Oulu, Finland
3School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland
|Online Access:||PDF Full Text (PDF, 0.4 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021101851329
The Institution of Engineering and Technology,
|Publish Date:|| 2021-10-18
Cloud radio access network (C-RAN) is an evolutionary radio network architecture in which a cloud-computing-based baseband (BB) signal-processing unit is shared among distributed low-cost wireless access points. This architecture offers a number of significant improvements over the traditional RANs, including better network scalability, spectral, and energy efficiency. As such C -RAN has been identified as one of the enabling technologies for the next-generation mobile networks. This chapter focuses on examining the energy-efficient transmission strategies of the C-RAN for cellular systems. In particular, we present optimization algorithms for the problem of transmit beamforming designs maximizing the network energy efficiency. In general, the energy efficiency maximization in C-RANs inherits the difficulty of resource allocation optimizations in interference-limited networks, i.e., it is an intractable non convex optimization problem. We first introduce a globally optimal method based on monotonic optimization (MO) to illustrate the optimal energy efficiency performance of the considered system. While the global optimization method requires extremely high computational effort and, thus, is not suitable for practical implementation, efficient optimization techniques achieving near -optimal performance are desirable in practice. To fulfill this gap, we present three low -complexity approaches based on the state-of-the-art local optimization framework, namely, successive convex approximation (SCA).
|Pages:||295 - 330|
Green Communications for Energy-Efficient Wireless Systems and Networks
|Host publication editor:||
Suraweera, Himal A.
Thompson, John S.
|Type of Publication:||
A3 Book chapter
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
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