Resource Allocation For Multi-RAT Wireless Network

In Multi-RAT wireless network,a variety of different kinds technologies coexistence will bring multiple access selection gain.The multi-mode terminal can simultaneously access multiple wireless networks for using multiple wireless network resources,which will result in high transmission rate.On the one hand,the terminal can flexibly access a more suitable wireless network according to the traffic requirements and user preferences for satisfying its quality of service.On the other hand,the network operators can access a variety of wireless network access technology to improve the network resource utilization,achieve to greater performance.In order to improve the utilization efficiency of wireless resources,this paper studies the problem of resource allocation in Multi-RAT wireless networks.Then,these solutions are also applied in the visible light communications(VLC)and radio frequency(RF)Multi-RAT wireless networks.The main contributions of this dissertation are summarized as follows:In Multi-RAT wireless network,the terminal’s network selection will not only affect its own throughput,energy efficiency and transmission delay,but also affect the other terminal’s performance.In addition,the network selection of multiple terminals will lead to a combinatorial optimization problem,which is NP hard.This paper builds a Markov model to describe the network states transfer,and then develops a transition probability between different network topologies,which depends only on the local information.Based on this probability,the sub-optimal solution of this network topology optimization problem can be obtained.In addition to the network selection problem,a relaxation strategy is developed to solve the mixed integer nonlinear optimization(MINO)problem about the resource allocation.Finally,this paper designs a joint network selection and resource allocation algorithm for achieving the maximum energy efficiency of the network.The effects of network dynamic characteristics on the process of traffic flow splitting is studied in this paper.An equivalent transformation method is proposed to convert the longterm energy efficiency maximization into a convex optimization problem on each time slot,and then a dynamic flow splitting algorithm is proposed to adapt to the time-varying wireless channel states.Then,a mean continuous-time dynamic system(MCTS)is developed to describe the dynamic flow splitting iterations.The “moving inertia” is defined to describe the motion of the iterative algorithm.Then,the “moving inertia” is considered as a compensation term to offset the tracking error.Finally,the sufficient condition that the algorithm can track the equilibrium point without error is obtained.The joint flow splitting and resource allocation in dynamic Multi-RAT wireless networks is studied.In order to adapt to the network hierarchical protocol architecture,the resource allocation problem is decomposed into two subproblems.The corresponding distributed algorithms are developed to avoid the problem of signaling overhead,outdated dynamic information and expansibility.Then,by abstracting the distributed algorithm into a MCTS and analyzing the tracking error between the distributed algorithm and the equilibrium point of the MCTS,the adaptive compensation flow splitting and power allocation algorithms are developed.Finally,the tradeoff between network utility and media transmission delay is obtained.This dissertation designs an energy-aware design of network selection and resource allocation for a Multi-RAT wireless network combining with RF and VLC technologies.For adapting to different timescale network states and stochastic data arrival,an on-line twotimescale adaptive network resource optimization(ANRO)framework is proposed.At the large timescale,a closed-form solution for the subproblem of network selection of user terminals is developed.Second,this paper designs a cost-effective and easy-to-realize algorithm for VLC’s joint transmission scheduling and power control subproblem,which is a nonconvex optimization.While,at the small timescale,this paper obtains the optimal solution for RF’s joint resource block and power allocation subproblem,which is proven a MINO problem.Simulation results demonstrate that the ANRO can achieve a tradeoff between network power consumption and delay.