Can Unlicensed Bands Be Used by Unlicensed Usage?

Abstract

Since their introduction, unlicensed ISM bands have resulted in a wide range of new wireless devices and services. The success of ISM resulted in the opening of the TV white space for unlicensed access. Further bands (e.g., 3550-3650 MHz) are being studied to support unlicensed access. Expansion of the unlicensed bands may well address one of the principle disadvantages of unlicensed frequency (variable quality of service) which could result in a vibrant new group companies providing innovative services and better prices. However, given that many commercial mobile telephone operators are relying heavily on the unlicensed bands to manage growth in data traffic through the “offloading” strategy, the promise of these bands may be more limited than might otherwise be expected. Wireless data traffic has exploded in the past several years due to more capable devices and faster network technologies. While there is some debate the trajectory of data growth, some notable reports include ATT further, the “flat-rate” pricing strategy has led to declining Average Revenue Per User (ARPU). The challenge for mobile operators is how to satisfy the service demand with acceptable additional expenditures on infrastructure and spectrum utilization. A common response to this challenge has been to offload data traffic onto unlicensed (usually WiFi) networks. This can be accomplished either by establishing infrastructure (WiFi hotspots) or to use existing private networks. This phenomenon leads to two potential risks for spectrum entrants: (1) the use of offloading may overwhelm unlicensed spectrum and leave little access opportunities for newcomers; (2) the intensity of the traffic may increase interference and degrade innovative services. Consequently, open more unlicensed frequency bands alone may not necessarily lead to more unlicensed usage. The particular goals of this paper are: Quantifying unlicensed spectrum capacity under traffic offloading from primary mobile providers; Assessing the impact of additional bands on overall unlicensed capacity; Identify potential risks for unlicensed users in ISM and TV white space. We will accomplish these goals by (1) adopting a Markov based model to calculate spectrum capacity for unlicensed users considering the potential traffic offloading from mobile providers and quantifying the extra capacity that will be given by additional spectrum; (2) building a real option based engineering economic model to illustrate the monetary risks in unlicensed frequency and also capturing the value of risk mitigation strategies. Since there are two unlicensed bands that are suitable for data communications, the capacity and economic model will be evaluated in two different cases. In case 1, mobile operators use WLAN in ISM bands, and in case 2 TV white space is chosen to provide wireless services.