Research On Heterogeneous Network Radio Resource Management Based On Pricing

Nowadays the requirement of communication quality increasingly raises and mobile user-s' demands for radio resource also increase accordingly.Due to the scarcity of radio resource and the cap of network capacity,the explosion of mobile traffic data brings severe challenges to the traditional cellular network architecture.The emergence of heterogeneous network solves the problem of resource scarcity to a certain extent.Through deploying different types of com-munication modes on the basis of the traditional macrocell,the system capacity and the indoor coverage can be improved obviously.However the coexistence of various communication modes makes the network environment become more complicated,resulting in the co-channel interfer-ence,the load imbalance and the unguaranteed users' service quality.How to reasonably and effectively manage the radio resource in the heterogeneous network is still an urgent issue to be addressed.This dissertation studies the radio resource allocation problem in four different heterogeneous network scenarios from the perspective of pricing,including the congestion pric-ing based cell association and bandwidth allocation,the incentive compensation strategy based traffic offloading scheme,pricing based resource management in heterogeneous cloud cellular network and mode selection and resource allocation in cellular-VANET(Vehicular Ad-hoc Net-work)heterogeneous network.By the way of resource pricing,the network congestion can be released and the users' satisfaction can be improved.On the other hand,the utility of each net-work entity can be guaranteed as well.The research methods of this dissertation incorporate convex optimization,microeconomics,game theory and system simulation.Firstly a utility maximization based cell association and bandwidth allocation scheme in the heterogeneous network is proposed.Strategic cell selection schemes always lead to load imbalance and low resource utilization.The utility maximization based cell selection schemes can not only maximize total satisfaction of all users,but also achieve the enhanced capacity and load balance.For the scenario where femtocells work in open access mode,a logarithmic utility maximization based cell selection mechanism is proposed and a shadow pricing regulation based distributed iterative algorithm is designed.Simulation results show that the proposed algorithm achieves the considerable throughput promotion.For the scenario where femtocells work in hybrid access mode,a network utility maximization based opportunistic cell selection scheme is proposed,meanwhile the congestion pricing strategy is used to control the load balance.A shadow pricing and load pricing regulation based distributed iterative algorithm is also designed.Simulation results show that the proposed scheme can produce a throughput gain in the case of congestion.The load balancing can be substantially improved as well.Next an incentive compensation strategy based traffic offloading scheme in heterogeneous networks is investigated.For the scenario where the wireless service provider and femtocell third parties coexist,an incentive pricing strategy is designed where wireless service provider offers a certain refund to third parties in order to achieve the spectrum resource sharing.An incentive pricing function in designed,within which the refund is a function of the pricing factor and the shared bandwidth proportion,and increases nonlinearly with the increase of the shared band-width proportion.The incentive factor can control the strength of compensation.Stackelberg game analysis obtains the optimal pricing factor and the optimal proportion of shared femtocell bandwidth resource.Results indicate that the utilities of both wireless service provider and femto holders are significantly improved due to the exploitation of incentive pricing strategy.Besides,for the heterogeneous network including cellular network and D2D communication links,a us-er compensation strategy based traffic offloading scheme is designed,where wireless service provider offers refund to stimulate some users to act as D2D cluster header for providing D2D service to adjacent users and the compensated users decide the reused spectrum proportion after they share the refund.Stackelberg game analysis obtains the optimal amount of refund and the optimal reused spectrum proportion of D2D cluster header.Results show that this proposal can achieve a win-win situation for both wireless service provider and D2D cluster header.Then a pricing based radio resource management scheme in the heterogeneous cloud cellular network is studied.An interference pricing based cell sleeping and user association scheme in the heterogeneous cloud cellular network is proposed.In such a scheme,the operation state of each base station is controlled by cloud computing center.A distributed heuristic algorithm is designed to maximize the users,aggregate utility.In this algorithm,the cloud computing center imposes a price on each base station,which is proportional to the interference each base station provides.Users select their own serving base station from the base stations which provide the least interference.Then the cloud computing center turns the idle base stations without any associated user into sleeping state.Simulation results show that the proposed scheme can achieve throughput gains under the same power consumption,which is more remarkable in large scale networks.Furthermore,a traffic prediction based cell selection algorithm is designed.This scheme utilizes data analysis module in the cloud platform which can predict the users' traffic demands and obtain the user's rules for traffic demands in advance.A throughput maximization based cell selection algorithm is designed,in which the traffic load of each cell is priced.In each iteration,users avoid to select the base station with heavy traffic to associate with.Simulation results show that the proposed algorithm produces considerable throughput gains and makes the number of satisfied users increase substantially.Finally,an optimal access mode selection and resource allocation scheme in cellular-VANET heterogeneous networks is designed.In this scheme,vehicular users choose the their optimal ac-cess modes between the D2D-based VANET and traditional network network,meanwhile cellu-lar users select the optimal base stations to associate with,in order to achieve the user aggregate utility maximization.Due to the high mobility of vehicles,the distance between vehicles for delay guarantee is derived.A shadow pricing regulation based distributed iterative algorithm is designed.Simulation results show that remarkable throughput gains are achieved.The through-put gains can be considerably improved with the adoption of power control.