The Impact of Mobile Broadband Tariff and Usage Control Policy on Users’ Utility
Date Issued
2014
Date
2014
Author(s)
Han, Siang-Ying
Abstract
With the popularity of smart devices and Internet society, Internet, especially wireless Internet becomes more and more in need. However, radio resources are limited. Therefore, problems such as wireless Internet congestion and wireless Internet resource allocation appear. Users may be unable to access the wireless Internet or face the wireless Internet with slow speed due to the congestion, and small amount of heavy users occupy the wireless Internet resource more than other users. Both situations can lower the users’ utility and may lead to the loss of mobile broadband providers. With the introduction of LTE, different tariff policies are implemented in expect of solving the problems mentioned above. Meanwhile, fair usage policy is an important issue. Mobile broadband providers often propose tariff plan with quota limit. When the monthly usage of a user reaches his/her limitation, this user has to pay for the excess bandwidth or the mobile broadband provider would degrade the maximum speed of the user.
In this thesis, we include models such as users’ access behavior model, data consumption model, utility function model, and tariff plan model. While 3G and LTE network coexist, how mobile broadband providers’ policies influence the migration behavior of users and their utility with a medium-high loading are studied. In the first scenario, we compare cases with no quota limit, 4GB quota limit and 7GB quota limit as a basis. The other scenarios are then designed to examine how different operation strategies influence users’ utility. In the second scenario, the quota limit is increased at the beginning of year 5; in scenario three, the capacity of LTE is also increased at the beginning of year 5; in scenario four, different LTE capacity are provided from the beginning of year 1; in scenario five, we control the data usage of heavy users; and in scenario six, the ratio of heavy user stops increasing after year four.
The results of scenario one show that when 3G and LTE networks coexist in the environment, it is necessary for a certain ratio of users to stay in the 3G tariff plan, so that the utilization of both of the 3G and LTE channel would be balanced. With a reasonable quota limit of LTE plan, a higher ratio of heavy user would stay in the LTE tariff plan. However, if the quota limit is unreasonably low, for example, if the quota limit is set to be too small, the utilization of LTE network would be low and the whole 3G-LTE dual network operation would be inefficient. Scenario two show that with quota limit expansion, the utilization of LTE network would be effectively increased. However, since the ratio of heavy user staying in LTE plan increases, the utility of light user decreases, and the light users would tend to move back to the 3G tariff plan. And the results of scenario three show that with the expansion of LTE capacity, the data usage consumption of heavy users increases as well, which causes the increase of quota limit to become ineffective, and the heavy users would tend to move back to 3G tariff plan again. In scenario four we learn that when the capacity of LTE is set to be 150Mbps from year 1, since the allocated bandwidth for each user accessing LTE channel increased significantly, heavy users are more likely to be downgraded, and they would return to 3G plan. And in scenario five we could see that if we can control the increase of IPTV usage effectively, one can expect that the investment of mobile broadband providers’ on the expansion of LTE network capacity may bring better returns. In scenario six, the ratio of both heavy users and light users choosing LTE plan and 3G plan would become stable, since both the utility of heavy users and network utilization are improved and controlled.
Our study has successfully predict how mobile broadband providers’ policy influence users’ utility and their migration behavior in the long run. What’s more, in the model we adopted, its component model could be replaced by another component model to adapt to other kinds of market environment, including other kinds of tariff plans, or different types of users’ behavior.
Subjects
行動寬頻
資費
用量管制
使用者效益
使用者遷徙
SDGs
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-103-R01942036-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):145aa93f173c154b8ed0849ca9fe2101