Energy Consumption Effects of WiFi Off-Loading Access in 3G or LTE Public Wireless Networks

Energy Consumption Effects of WiFi Off-Loading Access in 3G or LTE Public Wireless Networks

L.F. Pau
DOI: 10.4018/jbdcn.2013040101
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Abstract

As 3G, HSPDA and already now LTE wireless networks become ever more pervasive, especially for wireless high data rate and Internet traffic (>100 Mbps), increasing focus is given on ways to offload access by re-utilizing WiFi access points available in-doors (offices, homes), or installing such access points outdoors in/alongside high demand density public areas (hot spots, public areas, road traffic lanes, etc..). In view of the relative much higher WiFi access node power consumption and much smaller coverage compatible with interference reduction, the WiFi off-loading access may have a significant negative impact on energy consumption and emissions per user. The paper builds on earlier extensive work on the modeling of 3G or LTE wireless infrastructure energy consumption on an incremental basis per new user. It addresses the questions of the best mix between LTE cellular base stations and WiFi off-load access nodes from the energy/emissions perspective. Detailed sub-system model and design improvements are carried out on a continuous basis in collaboration with industry.
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1. Introduction To Wifi Off-Loading

Over the years, many studies have reported the common features and differences between IEEE Wireless Ethernet 802.11B (WiFi) wireless communications networks, and UMTS/ 3G/4G cellular network evolution as standardized by ETSI/ITU. Both offer wireless access, broadband data service, but they are different in radio links, business models, spectrum policy and management, deployment, and they complement each other (Lehr, 2003).

Under the heterogeneous network concept surveyed for example in (Lampropoulos, 2010)(Taha, 2011), the co-existence and joint operations of 3G/WIMAX and WiFi access networks has been widely researched and engineered with many patents being generated. At network level, emphasis has been mostly on interference, on hand-over delays and mobility management (Zekri, 2012), on automatic radio activation (Thomson, 2011), on end-to-end security, and on subscriber management. Different spectral bands are assumed, one at least of which is licensed, as well as advanced interference rejection and adaptive signal control.

WiFi offloading is then defined, under a heterogeneous network concept, as the means and technologies whereby cellular subscriber traffic is at access level handled in part by WiFi access points, the bulk being accessed and carried by cellular networks. One key motivation for WiFi offloading is to add capacity to meet rapidly growing traffic levels, especially for data, with an annual doubling being the recent trend. Telefonica O2, for example, reports that their own London WiFi hotspots offload 5-10% of data traffic from their 3G network (Dyer, 2013b).

For user equipment (UE), many patents exist for dual stack WiFi/ LTE (3G) wireless modems, or separate modems with hand-over (UMA) and corresponding handover protocols. Many UE designs are also optimized for minimum power consumption, because the power consumption in mobile user equipment due to active WiFi connections is far greater than for 3G/EDGE/LTE user equipments/terminals (Gobriel, 2012). These solutions have been satisfactory, but not always optimal, as long as the data rates offered by 3G/EDGE were clearly below those offered by WiFi, a situation in which voice was normally carried by 3G/EDGE and data carried short range by WiFi.

With the advent of LTE access networks offering coverage data access at rates of about 100 MB/s comparable or better than WiFi access, the notion of wireless off-loading has led to designs driven by new fundamental reasons (Afridi, 2011; Raleigh, 2011) and servicing modes (Dyer,2013b). Amongst servicing modes, wireless offloading provides first tools to a service provider to encourage or direct a subscriber to offload from a default network, e.g., a cellular network, to a second network, e.g. a WiFi network. Secondly, the cellular service provider can use network data to determine wireless offloading priorities for cellular subscribers on an individual or group basis. Third, the cellular service provider may use for the same purpose profile data it has, combined with WiFi network data from beacon frames of WiFi networks or active scanning.

The new fundamental reasons are some, or all of the following:

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