Book contents
- Frontmatter
- Contents
- List of contributors
- Preface
- 1 Mobility performance optimization for 3GPP LTE HetNets
- 2 Design and performance analysis of multi-radio small cell networks
- 3 Dynamic TDD small cell management
- 4 3GPP RAN standards for small cells
- 5 Dense networks of small cells
- 6 Traffic offloading scenarios for heterogeneous networks
- 7 Required number of small cell access points in heterogeneous wireless networks
- 8 Small cell deployments: system scenarios, performance, and analysis
- 9 Temporary cognitive small cell networks for rapid and emergency deployments
- 10 Long-term evolution (LTE) and LTE-Advanced activities in small cell networks
- 11 Game theory and learning techniques for self-organization in small cell networks
- 12 Energy efficient strategies with BS sleep mode in green small cell networks
- 13 Mobility management in small cell heterogeneous networks
- 14 The art of deploying small cells: field trial experiments, system design, performance prediction, and deployment feasibility
- 15 Centralized self-optimization of interference management in LTE-A HetNets
- 16 Self-organized ICIC for SCN
- 17 Large-scale deployment and scalability
- 18 Energy efficient heterogeneous networks
- 19 Time- and frequency-domain e-ICIC with single- and multi-flow carrier aggregation in HetNets
- Index
- References
6 - Traffic offloading scenarios for heterogeneous networks
Published online by Cambridge University Press: 05 December 2015
Book contents
- Frontmatter
- Contents
- List of contributors
- Preface
- 1 Mobility performance optimization for 3GPP LTE HetNets
- 2 Design and performance analysis of multi-radio small cell networks
- 3 Dynamic TDD small cell management
- 4 3GPP RAN standards for small cells
- 5 Dense networks of small cells
- 6 Traffic offloading scenarios for heterogeneous networks
- 7 Required number of small cell access points in heterogeneous wireless networks
- 8 Small cell deployments: system scenarios, performance, and analysis
- 9 Temporary cognitive small cell networks for rapid and emergency deployments
- 10 Long-term evolution (LTE) and LTE-Advanced activities in small cell networks
- 11 Game theory and learning techniques for self-organization in small cell networks
- 12 Energy efficient strategies with BS sleep mode in green small cell networks
- 13 Mobility management in small cell heterogeneous networks
- 14 The art of deploying small cells: field trial experiments, system design, performance prediction, and deployment feasibility
- 15 Centralized self-optimization of interference management in LTE-A HetNets
- 16 Self-organized ICIC for SCN
- 17 Large-scale deployment and scalability
- 18 Energy efficient heterogeneous networks
- 19 Time- and frequency-domain e-ICIC with single- and multi-flow carrier aggregation in HetNets
- Index
- References
Summary
This chapter considers the challenges faced by network operators and service providers accommodating the increasing traffic demands in cellular networks in the most efficient yet inexpensive way. It proposes that these challenges are addressed by offloading part of the traffic to femto cell access points (FAPs) and WiFi access points (WiFiAPs). Whereas 4G micro and pico cell base stations are assumed to be managed by the network operator in terms of setup and maintenance, FAPs and WiFiAPs are normally bought and operated by the end-user. The main difference between these two solutions is that the FAPs operate on the frequency bands assigned to the network operator by national regulators, while WiFiAPs work on unlicensed spectrum. This chapter analyzes the pros and cons of such approaches, and the tradeoffs related to the different mechanisms employed in cellular and WiFi networks for interference management. Moreover, various methods for traffic offloading by the mobile network operator are discussed in detail, including local IP access (LIPA), selective IP traffic offloading (SIPTO), IP flow mobility (IFOM), access network discovery and selection function (ANDSF), and Hotspot 2.0, etc. In the experimental part of this chapter, means for traffic management from the network operator's perspective are discussed, taking into account costs and energy savings. Furthermore, a novel resource usage coordination concept in conjunction with the WiFi offloading concept is presented.
Introduction
The traffic served by cellular networks grows significantly on a yearly basis, making the efficient, fair, and inexpensive management of users’ traffic demands a real challenge. Various forecasts provided both by legal bodies and commercial companies show that this trend will not change in the future. One can, for example, consider the expectations provided in Table 6.1, created based on the data delivered in the Cisco Visual Networking Index [1, 2] in 2012 and 2013. It is shown that the monthly average traffic generated by mobile devices is foreseen to grow exponentially. Based on [3], it can be stated that in 2017 IP traffic originating from mobile devices will comprise more than 13% of fixed IP traffic, while in 2013 this comprised only around 4% of fixed IP traffic.
- Type
- Chapter
- Information
- Design and Deployment of Small Cell Networks , pp. 122 - 147Publisher: Cambridge University PressPrint publication year: 2015
References
[1] Cisco (2011), “Cisco visual networking index: global mobile data traffic forecast update 2012–2017,” www.slideshare.net/zahidtg/cisco-vni-2012.
[2] Cisco (2012), “Cisco visual networking index: global mobile data traffic forecast update 2012–2017,” www.slideshare.net/zahidtg/cisco-vni-2012.
[3] Cisco (2013), “Cisco visual networking index: forecast and methodology, 20122017,” www.cisco.com/en/US/solutions/collateral/ns341/ns525/ns537/ns705/ns827/white_paper_c11–481360.pdf.
[4] , , and (2010), “Radio resource allocation in urban femto-WiFi convergence scenarios,” In 6th EURO-NF Conference on Next Generation Internet (NGI), pp. 1–8.CrossRef
[5] Small Cell Forum (March 2013b), “Interference management in OFDMA femtocells,” www.smallcellforum.org.
[6] , , , et al. (2011), “A survey on 3GPP heterogeneous networks,” Wireless Communications, IEEE 18(3), 10–21.CrossRefGoogle Scholar
[7] , , , et al. (2012), “Heterogeneous cellular networks: from theory to practice,” Communications Magazine, IEEE 50(6), 54–64.CrossRefGoogle Scholar
[8] (2013), “Seven ways that HetNets are a cellular paradigm shift,” Communications Magazine, IEEE 51(3), 136–144.CrossRefGoogle Scholar
[9] SmallCellForum (2014a), www.smallcellforum.org.
[10] 3GPP (2013), “3GPP TS 23.402 V12.3.0 (2013–12); Technical Specification 3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Architecture enhancements for non-3GPP accesses (Release 12).”
[11] SmallCellForum (December 2013a), “Integrated femto–WiFi networks, version: 033.04.01,” www.smallcellforum.org.
[12] , , and (2009), “OFDMA femtocells: a roadmap on interference avoidance,” Communications Magazine, IEEE 47(9), 41–48.CrossRefGoogle Scholar
[13] and (2009), “Spectrum allocation in tiered cellular networks,” Communications, IEEE Transactions 57(10), 3059–3068.CrossRefGoogle Scholar
[14] , and (2010), “Distributed power allocation for interference limited networks,” In Personal Indoor and Mobile Radio Communications (PIMRC), 2010 IEEE 21st International Symposium, pp. 1342–1347.CrossRef
[15] , and (2009), “Autonomous component carrier selection: interference management in local area environments for LTE-Advanced,” Communications Magazine, IEEE 47(9), 110–116.CrossRefGoogle Scholar
[16] , , , and (2010), “Self-organizing coalitions for conflict evaluation and resolution in femtocells,” In Global Telecommunications Conference (GLOBECOM 2010), 2010 IEEE, pp. 1–6.CrossRef
[17] , , , and (2011), “Data fusion-based interference matrix generation for cellular system frequency planning,” International Journal of Communication Systems 24, 1506–1519.CrossRefGoogle Scholar
[18] , , , , and (2012), “Interference management in heterogeneous wireless networks based on context information,” In Wireless Communication Systems (ISWCS), 2012 International Symposium, pp. 251–255.CrossRef
[19] , , , and (2012), “Femtocell downlink power control based on radio environment maps,” In Wireless Communications and Networking Conference (WCNC), 2012 IEEE, pp. 1224–1228.CrossRef
[20] , and (2009), “Network support: the radio environment map”, In, ed., Cognitive Radio Technology, Butterworth-Heinemann.Google Scholar
[21] , and (2007), “Fairness and load balancing in wireless LANs using association control,” Networking, IEEE/ACM Transactions 15(3), 560–573.CrossRefGoogle Scholar
[22] , , and (2012), “Distributed alpha-optimal user association and cell load balancing in wireless networks,” Networking, IEEE/ACM Transactions 20(1), 177–190.CrossRefGoogle Scholar
[23] and (2012), “Load balancing in heterogeneous LTE: range optimization via cell offset and load-coupling characterization,” In Communications (ICC), 2012 IEEE International Conference, pp. 1357–1361.CrossRef
[24] , and (2003), “Dynamic load balancing through coordinated scheduling in packet data systems,” In INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies, Vol. 1, 786–796.
[25] , , and (2008), “Coordinated load balancing, handoff/cell-site selection, and scheduling in multi-cell packet data systems,” Wireless Networks 14(1), 103–120.CrossRefGoogle Scholar
[26] and (2009), “Cell breathing techniques for load balancing in wireless LANs,” Mobile Computing, IEEE Transactions 8(6), 735–749.CrossRefGoogle Scholar
[27] , and (2007), “Dynamic association for load balancing and interference avoidance in multi-cell networks,” In Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks and Workshops, 2007. WiOpt 2007. 5th International Symposium, pp. 1–10.CrossRef
[28] , , , , and (2013), “User association for load balancing in heterogeneous cellular networks,” Wireless Communications, IEEE Transactions 12(6), 2706–2716.CrossRefGoogle Scholar
[29] and (2014), “Joint resource partitioning and offloading in heterogeneous cellular networks,” Wireless Communications, IEEE Transactions 13(2), 888–901.CrossRefGoogle Scholar
[30] 3GPP (n.d.a), “3GPP TR 23.829 v10.0.0, Local IP access and selected IP traffic offload (LIPA-SIPTO) (Release 10).”
[31] 3GPP (n.d.b), “3GPP TS 23.261 v10.1.0, IP flow mobility and seamless wireless local area network (WLAN) offload (Release 10).”
[32] (2012), “Data offloading techniques in 3GPP Rel-10 networks: a tutorial,” Communications Magazine, IEEE 50(6), 46–53.CrossRefGoogle Scholar
[33] , and (2012), “Traffic offload enhancements for eU-TRAN,” Communications Surveys Tutorials, IEEE 14(3), 884–896.Google Scholar
[34] QUALCOMM (March 2013), “3G/WiFi seamless offload.”
[36] , , , and (2008), “Mobility management for all-IP mobile networks: mobile IPv6 vs. proxy mobile IPv6,” Wireless Communications, IEEE 15(2), 36–45.Google Scholar
[37] and (2012), “DSMIP and PMIP for mobility management of heterogeneous access networks: evaluation of authentication delay,” In Globecom Workshops (GC Wkshps), 2012 IEEE, pp. 308–313.CrossRef
[38] IETF (2011), “RFC 6182, architectural guidelines for multipath TCP development.”
[39] SmallCellForum (February 2014b), “Next generation hotspots (NGH)-based integrated small cell WiFi (ISW) networks, version: 089.03.01,” www.smallcellforum.org.
[40] 3GPP (2011), “3GPP TS 24.312, access network discovery and selection function (ANDSF) management object (MO).”
[41] and (2012), “WiFi roaming – building on ANDSF and Hotspot 2.0,” White Paper Alcatel-Lucent and BT, pp. 1–44.
[42] IEEE (2011a), “IEEE standard for information technology telecommunications and information exchange between systems. Local and metropolitan area networks. Specific requirements. Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications, Amendment 6: medium access control (MAC) security enhancements.”
[43] IEEE (2011b), “IEEE standard for information technology telecommunications and information exchange between systems. Local and metropolitan area networks. Specific requirements. Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications, Amendment 9: interworking with external networks.”
[44] RFC (2006a), “4186, Extensible authentication protocol method for global system for mobile communications (GSM) subscriber identity modules (EAP-SIM).”
[45] RFC (2006b), “4187, Extensible authentication protocol method for 3rd Generation authentication and key agreement (EAP-AKA).”
[46] RFC (2009), “5448, Improved extensible authentication protocol method for 3rd Generation authentication and key agreement (EAP-AKA).”
[47] RFC (2008a), “5216, The EAP-TLS authentication protocol.”
[48] RFC (2008b), “5281, Extensible authentication protocol tunneled transport layer security authenticated protocol version 0 (EAP-TTLSv0).”
[49] , and (2011), “Local IP access (LIPA) enabled 3G and 4G femtocell architectures,” In Electrical and Computer Engineering (CCECE), 24th Canadian Conference, pp. 1049–1053.CrossRef
[50] , , , and (2002), “Performance of reliable transport protocol over IEEE 802. 11 Wireless LAN: analysis and enhancement,” pp. 599–607.
[51] , and (2013), “A network-assisted user-centric WiFi-offloading model for maximizing per-user throughput in a heterogeneous network,” Vehicular Technology, IEEE Transactions (99), 1–1.Google Scholar