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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Bibliographic Details
Published in:IEEE transactions on vehicular technology Vol. 68; no. 6; pp. 6099 - 6113
Main Authors: D'Oro, Salvatore, Marotta, Marcelo Antonio, Both, Cristiano Bonato, DaSilva, Luiz, Palazzo, Sergio
Format: Journal Article
Language:English
Published: New York IEEE 01.06.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
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
Online Access:Get full text
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Summary: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.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2019.2913310