TY - JOUR
T1 - Delay-energy tradeoff in multicast scheduling for green cellular systems
AU - Huang, Chuan
AU - Zhang, Junshan
AU - Poor, H. Vincent
AU - Cui, Shuguang
N1 - Funding Information:
The work of C. Huang was supported in part by NSFC under Grant 61501093 and in part by the National Major Project 2014ZX03003001-002. The work of J. Zhang was supported in part by the U.S. National Science Foundation under Grant CNS-1218484, Grant CNS-1422277, and Grant ECCS-1408409 and in part by DoD under Grant HDTRA1-13-1-0029. The work of H. V. Poor was supported in part by the U.S. National Science Foundation under Grant CNS-1456793. The work of S. Cui was supported in part by DoD under Grant HDTRA1-13-1-0029, Grant NSFC-61328102 and in part by NSF under Grant AST-1547436, Grant ECCS-1508051, Grant CNS-1343155, Grant ECCS-1305979, and Grant CNS-1265227.
Publisher Copyright:
© 1983-2012 IEEE.
PY - 2016/5
Y1 - 2016/5
N2 - Multicast transmission based on real-time network state information is a resource-friendly technique to improve the energy efficiency and reduce the traffic burden for cellular systems. This paper evaluates the effectiveness of this technique for downlink transmissions. In particular, a scenario is considered in which multiple mobile users (MUs) asynchronously request to download one common message locally cached at a base station (BS). Due to the randomness of both the channel conditions and the request arrivals from the MUs, the BS may choose to intelligently hold the arrived requests, especially when the channel conditions are bad or the number of requests is small, and then serve them in one shot later via multicasting. Clearly it is of great interest to balance the delay (incurred by holding the requests) and the energy efficiency (EE, defined as the energy cost per request), and this motivates us to quantify the fundamental tradeoff for the proposed 'hold-then-serve' scheme. For the scenario with single channel and unit message sizes, it is shown that for a fixed channel bandwidth, the delay-EE tradeoff reduces to judiciously choosing the optimal stopping rule for when to serve all the arrived requests, where the effect of the bandwidth on the achievable delay-EE region is discussed further. By using optimal stopping theory, it is shown that the optimal stopping rule exists for general Markov channel models and request arrival processes. Particularly, for the hard deadline and proportional delay penalty cases, it is shown that the optimal stopping rule exhibits a threshold structure, and the corresponding threshold in the former case is time varying while in the latter case it is a constant. Finally, for the more general scenario with multiple channels and arbitrary message sizes, the optimal scheduling is formulated as a Markov decision process problem, where some efficient suboptimal scheduling algorithms are proposed.
AB - Multicast transmission based on real-time network state information is a resource-friendly technique to improve the energy efficiency and reduce the traffic burden for cellular systems. This paper evaluates the effectiveness of this technique for downlink transmissions. In particular, a scenario is considered in which multiple mobile users (MUs) asynchronously request to download one common message locally cached at a base station (BS). Due to the randomness of both the channel conditions and the request arrivals from the MUs, the BS may choose to intelligently hold the arrived requests, especially when the channel conditions are bad or the number of requests is small, and then serve them in one shot later via multicasting. Clearly it is of great interest to balance the delay (incurred by holding the requests) and the energy efficiency (EE, defined as the energy cost per request), and this motivates us to quantify the fundamental tradeoff for the proposed 'hold-then-serve' scheme. For the scenario with single channel and unit message sizes, it is shown that for a fixed channel bandwidth, the delay-EE tradeoff reduces to judiciously choosing the optimal stopping rule for when to serve all the arrived requests, where the effect of the bandwidth on the achievable delay-EE region is discussed further. By using optimal stopping theory, it is shown that the optimal stopping rule exists for general Markov channel models and request arrival processes. Particularly, for the hard deadline and proportional delay penalty cases, it is shown that the optimal stopping rule exhibits a threshold structure, and the corresponding threshold in the former case is time varying while in the latter case it is a constant. Finally, for the more general scenario with multiple channels and arbitrary message sizes, the optimal scheduling is formulated as a Markov decision process problem, where some efficient suboptimal scheduling algorithms are proposed.
KW - Multicast
KW - caching
KW - delay
KW - energy efficiency
KW - optimal stopping
UR - http://www.scopus.com/inward/record.url?scp=84976426621&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84976426621&partnerID=8YFLogxK
U2 - 10.1109/JSAC.2016.2551559
DO - 10.1109/JSAC.2016.2551559
M3 - Article
AN - SCOPUS:84976426621
SN - 0733-8716
VL - 34
SP - 1235
EP - 1249
JO - IEEE Journal on Selected Areas in Communications
JF - IEEE Journal on Selected Areas in Communications
IS - 5
M1 - 7448817
ER -