On Coordinated Scheduling of Radio and Computing Resources in Cloud-RAN

Cloud Radio Access Network is a promising mobile network architecture based on centralizing the baseband processing of many cellular base stations in a BBU (BaseBand Unit) pool. Such architecture has many advantages. However, computing resources are shared among the base stations connected to the BB...

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Published in:	IEEE eTransactions on network and service management Vol. 20; no. 3; p. 1
Main Authors:	Sharara, Mahdi, Hoteit, Sahar, Brown, Patrick, Veque, Veronique
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.09.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Automatic repeat request Broadband Cloud computing Cloud-RAN Computer architecture Computer Science Computing Resources Allocation Coordination Decoding Encoding Indexes Integer Linear Programming (ILP) Integer programming Linear programming Mobile computing Modulation and Coding Scheme (MCS) Network latency Networking and Internet Architecture Performance evaluation Radio equipment Resource management Scheduling Throughput Ultra reliable low latency communication Computing Resources Allocation 5G Modulation and Coding Scheme (MCS) Integer Linear Programming (ILP) Cloud-RAN
ISSN:	1932-4537, 1932-4537
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Abstract	Cloud Radio Access Network is a promising mobile network architecture based on centralizing the baseband processing of many cellular base stations in a BBU (BaseBand Unit) pool. Such architecture has many advantages. However, computing resources are shared among the base stations connected to the BBU pool. It is challenging to schedule the processing of users' data, especially on overloaded BBU pools, while respecting the time constraints imposed by the Hybrid Automatic Repeat Request (HARQ) mechanism. Given that the processing time of users' data and the computing requirement depends on the radio parameters such as the Modulation and Coding Scheme (MCS), we propose to enable the coordination between radio and computing resources schedulers; such coordination makes the selection of MCS dependent on the availability of radio and computing resources and on the ability to process data while respecting the HARQ-deadline. In this context, we propose and evaluate three Integer Linear Programming (ILP)-based schemes and three low-complexity heuristics, demonstrating their ability to reduce the wasted transmission power. Moreover, we evaluate the performance of the coordination under a multi-services scenario consisting of two services having heterogeneous requirements, enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communication (URLLC).
AbstractList	Cloud Radio Access Network is a promising mobile network architecture based on centralizing the baseband processing of many cellular base stations in a BBU (BaseBand Unit) pool. Such architecture has many advantages. However, computing resources are shared among the base stations connected to the BBU pool. It is challenging to schedule the processing of users’ data, especially on overloaded BBU pools, while respecting the time constraints imposed by the Hybrid Automatic Repeat Request (HARQ) mechanism. Given that the processing time of users’ data and the computing requirement depends on the radio parameters such as the Modulation and Coding Scheme (MCS), we propose to enable the coordination between radio and computing resources schedulers; such coordination makes the selection of MCS dependent on the availability of radio and computing resources and on the ability to process data while respecting the HARQ-deadline. In this context, we propose and evaluate three Integer Linear Programming (ILP)-based schemes and three low-complexity heuristics, demonstrating their ability to reduce the wasted transmission power. Moreover, we evaluate the performance of the coordination under a multi-services scenario consisting of two services having heterogeneous requirements, enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communication (URLLC). Cloud Radio Access Network is a promising mobile network architecture based on centralizing the baseband processing of many cellular base stations in a BBU (BaseBand Unit) pool. Such architecture has many advantages. However, computing resources are shared among the base stations connected to the BBU pool. It is challenging to schedule the processing of users' data, especially on overloaded BBU pools, while respecting the time constraints imposed by the Hybrid Automatic Repeat Request (HARQ) mechanism. Given that the processing time of users' data and the computing requirement depends on the radio parameters such as the Modulation and Coding Scheme (MCS), we propose to enable the coordination between radio and computing resources schedulers; such coordination makes the selection of MCS dependent on the availability of radio and computing resources and on the ability to process data while respecting the HARQ-deadline. In this context, we propose and evaluate three Integer Linear Programming (ILP)-based schemes and three low-complexity heuristics, demonstrating their ability to reduce the wasted transmission power. Moreover, we evaluate the performance of the coordination under a multiservices scenario consisting of two services having heterogeneous requirements, enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communication (URLLC).
Author	Sharara, Mahdi Veque, Veronique Brown, Patrick Hoteit, Sahar
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SubjectTerms	Automatic repeat request Broadband Cloud computing Cloud-RAN Computer architecture Computer Science Computing Resources Allocation Coordination Decoding Encoding Indexes Integer Linear Programming (ILP) Integer programming Linear programming Mobile computing Modulation and Coding Scheme (MCS) Network latency Networking and Internet Architecture Performance evaluation Radio equipment Resource management Scheduling Throughput Ultra reliable low latency communication
Title	On Coordinated Scheduling of Radio and Computing Resources in Cloud-RAN
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