Research On Key Technologies Of Radio Resource Management In Heterogeneous Networks

The rapid development of wireless communication technologies result in the heterogeneous wireless network environment.An essential trends of wireless communication systems in the future will be heterogeneous,convergence,and collaboration.The wireless system would integrate and manage multiple wireless access networks,providing a ubiquitous heterogeneous wireless access environment to multiple terminals for fully satisfying the growing service demands in different application scenarios.Wireless network resource management is a key technology for improving system performance,ensuring quality of service(QoS),and improving quality of experience(QoE).This thesis focuses on wireless resource management under heterogeneous wireless network environment.We do research on user access selection algorithms,power allocation algorithms,and joint resource optimization algorithms for multiple service types in heterogeneous converged networks.The energy efficiency in heterogeneous network is also analyzed and modeled to improve the communication performance of wireless heterogeneous systems and fully utilize system resources.An access selection algorithm based on attributes dependence is proposed to solve the problem of user access selection in heterogeneous wireless convergence environment.The algorithm constructs a decision matrix based on the remaining bandwidth,blocking probability,signal strength and sojourn time.The attribute measurement matrix for measuring the actual performance of the network is obtained through normalization and orthogonalization.Then construct a reasonable attribute weight optimization function,and use the chaotic glowworm swarm algorithm to solve the attribute weight optimization function to obtain a reasonable weight value allocation scheme,and finally select the optimal network for the user to access.The simulation results show that the access algorithm can effectively improve the network load balance and reduce the handoff dropping rate users.Aiming at working out the problem of improing user quality of experience and saving energy in heterogeneous networks,A joint access selection and power allocation algorithm is proposed.The algorithm builds a multi-objective optimization model with the lowest system energy consumption and the highest user average quality of experience.Through the differential evolution algorithm,the optimal solution set of the joint allocation problem is obtained.Further the compromised joint allocation scheme is gained according to the TOPSIS method.Secondly,considering the differences of the services,a joint resource allocation optimization algorithm based on service differentiation is studied.This algorithm establishes a user quality of experience model based on service characteristics,and combines system energy efficiency.An optimization model for maximizing the user QoE aware energy efficiency in the user dimension is proposed.Moreover a solution of the optimization problem is achieved through a chaotic genetic algorithm,which can achieve efficient access of wireless users and power allocation of heterogeneous networks.The simulation results show that the algorithms can effectively reduce the energy consumption,improve the energy efficiency of the system,and improve the user's quality of experience.In view of the fairness of user services in heterogeneous wireless networks,a user quality of experience of unit energy consumption(QEE)model is first constructed.Combining with the characteristics of the proposed QEE model,the maximum QEE value in theoretically is studied.By optimizing the sum of the proximity degree of the QEE and the ideal QEE in the actual transmission process,the power distribution of the heterogeneous network in a fairness manner can be realized.Secondly,considering the importance of the service carried by users,we propose a weighted proportional fair optimization algorithm that considering the importance of the service.This algoritm,investigates the impact of the service on the operation of the network and uses operational research theory to calculate the importance of each business.Then we combine the proportional fairness model and propose a weighted proportional fairness model.Finally the user's optimal access and optimal power allocation scheme are achieved through the optimization of the model.A power distribution algorithm based on game theory is proposed in order to solve the problem of power allocation under heterogeneous network environment with distributed architecture.Firstly,under the condition of analyzing macro-micro-cell frequency reuse,the interference characteristics between macro and micro cells and the users quality of service requirements is analyzed.Then the micro-cell user transmission power allocation process is established as a user's non-cooperative game process,and an iterative methods is proposed to obtain the optimal power allocation scheme.Secondly,we focuses on the network with hybrid energy source,and design the utility of each user in the hybrid energy source system from the perspective of stability,economy and environment pollution.A dual power allocation algorithm based on Stackelberg game to maximize the utilities of users and networks is proposed.The algorithm establishes the macro and micro-cellular users as leaders and followers,respectively.We design a distributed iterative algorithm to achieve the Stackelberg equilibrium point,which is the optimal power allocation in heteregeneous networks with hybrid energy source.