Research Of Resource Distribution And Access Selsction Based On Game Theory In Lte

In the current days, with the rapid progress of technology, telecommunication has taken a great step out of3G and the era of4G telecommunication technology has come already. And as the technical standard of4G, LTE has obtained a huge progress compared to the prior technology. LTE uses the OFDM(Orthogonal Frequency Division Multiple) and MIMO(Multiple Input Multiple Output) techniques in wireless portion which have show their great advantages and become mature; in the network portion LTE uses the flatter architecture which is able to reduce the delay time caused by the signal overhead. LTE can support a variety of business and bring the better user experience, meanwhile the operators can differentiate users who can be served by different qualities of services and gain larger benefits.First of all this thesis focuses on the problem of resource distribution in wireless portion of LTE system and come up with an algorithm of resource distribution in the situation where resource is lack. In this thesis a bargaining game theory is applied to solve this problem. The resource blocks provided within the unit time can be regarded as the resource that could be distributed. When the sum demand from uses is bigger than the network capacity, users come up with the distribution strategies in turn and finally reach to an agreement by bargaining. This algorithm is able to distribute the resource more properly according to the demand and class of users, improving the user experience in general. And this thesis also raises an algorithm of access network selection according to the network’s state and the business in use in the situation of TDD-LTE, FDD-LTE, WLAN all can provide data network access. This algorithm uses the evolutionary game theory and customers’access selection is modeling into a dynamic game progress. When a large amount of users get into the system, they are likely to get infected by each other and finally the system could get to a stable state. By this algorithm uses are able to get higher benefits and the network can achieve a more balanced load, reducing network load pressure.