An overview of load balancing in hetnets: old myths and open problems

• Published in: IEEE wireless communications Vol. 21; no. 2; pp. 18 - 25
• Main Authors: Andrews, Jeffrey, Singh, Sarabjot, Qiaoyang Ye, Xingqin Lin, Dhillon, Harpreet
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.04.2014; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Access methods and protocols, osi model; Applied sciences; Cellular; Cellular communication; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Decision theory; Demand (economics); Economics; Equipments and installations; Exact sciences and technology; Game theory; IEEE 802.11 Standards; Interference; Load balancing (computing); Load management; Load modeling; Macrocell networks; Matching; Mobile radiocommunication systems; Optimization; Radiocommunications; Signal to noise ratio; Software; Telecommunications; Telecommunications and information theory; Teleprocessing networks. Isdn; Wireless communication; Wireless networks; Markov process; Markov decision; Myth; Cellular radio; Frequency division multiple access; Cell network; Context aware; Communication network; Game theory; Optimization; Heterogeneity; Orthogonal frequency division multiplexing; Wireless network; Internet; Cell system; Load balancing; Logistics
• ISSN: 1536-1284; 1558-0687
• DOI: 10.1109/MWC.2014.6812287

Matching the demand for resources ("load") with the supply of resources ("capacity") is a basic problem occurring across many fields of engineering, logistics, and economics, and has been considered extensively in both the Internet and wireless networks. The ongoing evolution of cellular communication networks into dense, organic, and irregular heterogeneous networks (HetNets) has elevated load awareness to a central problem, and introduces many new subtleties. This article explains how several long-standing assumptions about cellular networks need to be rethought in the context of a load-balanced HetNet: we highlight these as three deeply entrenched myths that we then dispel. We survey and compare the primary technical approaches to HetNet load balancing: (centralized) optimization, game theory, Markov decision processes, and the newly popular cell range expansion (a.k.a. biasing), and draw design lessons for OFDMA-based cellular systems. We also identify several open areas for future exploration.