Power-Efficient Resource Allocation in C-RANs With SINR Constraints and Deadlines

In this paper, we address the problem of power-efficient resource management in Cloud Radio Access Networks (C-RANs). Specifically, we consider the case where Remote Radio Heads perform data transmission, and signal processing is executed in a virtually centralized Base-Band Units pool. Users reques...

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Vydáno v:	IEEE transactions on vehicular technology Ročník 68; číslo 6; s. 6099 - 6113
Hlavní autoři:	D'Oro, Salvatore, Marotta, Marcelo Antonio, Both, Cristiano Bonato, DaSilva, Luiz, Palazzo, Sergio
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.06.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Cloud Radio Access Networks Complexity Complexity theory Data transmission Downlink Dynamic programming energy efficiency Greedy algorithms Interference Mixed integer Optimization Polynomials Power consumption Power demand Power management Radio Resource allocation Resource management Signal processing Signal to noise ratio User satisfaction
ISSN:	0018-9545, 1939-9359
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Abstract	In this paper, we address the problem of power-efficient resource management in Cloud Radio Access Networks (C-RANs). Specifically, we consider the case where Remote Radio Heads perform data transmission, and signal processing is executed in a virtually centralized Base-Band Units pool. Users request to transmit at different time instants; they demand minimum signal-to-noise-plus-interference ratio (SINR) guarantees, and their requests must be accommodated within a given deadline. These constraints pose significant challenges to the management of C-RANs and, as we will show, considerably impact the allocation of processing and radio resources in the network. Accordingly, we analyze the power consumption of the C-RAN system, and we formulate the power consumption minimization problem as a weighted joint scheduling of processing and power allocation problem for C-RANs with minimum SINR and finite horizon constraints. The problem is a Mixed Integer Non-Linear Program, and we propose an optimal offline solution based on Dynamic Programming. We show that the optimal solution is of exponential complexity; thus, we propose a sub-optimal greedy online algorithm of polynomial complexity. We assess the performance of the two proposed solutions through extensive numerical results. Our solution aims to reach an appropriate tradeoff between minimizing the power consumption and maximizing the percentage of satisfied users. We show that it results in power consumption that is only marginally higher than the optimum, at significantly lower complexity.
AbstractList	In this paper, we address the problem of power-efficient resource management in Cloud Radio Access Networks (C-RANs). Specifically, we consider the case where Remote Radio Heads perform data transmission, and signal processing is executed in a virtually centralized Base-Band Units pool. Users request to transmit at different time instants; they demand minimum signal-to-noise-plus-interference ratio (SINR) guarantees, and their requests must be accommodated within a given deadline. These constraints pose significant challenges to the management of C-RANs and, as we will show, considerably impact the allocation of processing and radio resources in the network. Accordingly, we analyze the power consumption of the C-RAN system, and we formulate the power consumption minimization problem as a weighted joint scheduling of processing and power allocation problem for C-RANs with minimum SINR and finite horizon constraints. The problem is a Mixed Integer Non-Linear Program, and we propose an optimal offline solution based on Dynamic Programming. We show that the optimal solution is of exponential complexity; thus, we propose a sub-optimal greedy online algorithm of polynomial complexity. We assess the performance of the two proposed solutions through extensive numerical results. Our solution aims to reach an appropriate tradeoff between minimizing the power consumption and maximizing the percentage of satisfied users. We show that it results in power consumption that is only marginally higher than the optimum, at significantly lower complexity.
Author	Both, Cristiano Bonato Marotta, Marcelo Antonio Palazzo, Sergio DaSilva, Luiz D'Oro, Salvatore
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SubjectTerms	Cloud Radio Access Networks Complexity Complexity theory Data transmission Downlink Dynamic programming energy efficiency Greedy algorithms Interference Mixed integer Optimization Polynomials Power consumption Power demand Power management Radio Resource allocation Resource management Signal processing Signal to noise ratio User satisfaction
Title	Power-Efficient Resource Allocation in C-RANs With SINR Constraints and Deadlines
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