Research On Multi-Resources Optimization Strategies In Heteregeneous Wireless Networks

In order to satisfy the increasing requirements of the quality of the information communication service and data rate, and to effectively reduce the blind area of the coverage, the wireless networks shows a heterogeneous trend. However, while meeting the needs of signal coverage, heteregeneous wireless networks may cause a series of problems such as new serious interferences, additional energy consumption, more network security risk. Therefore, how to allocate these scarce heterogeneous wireless resources、energy saving and the guarantee of network security are urgent problem in the wireless communication system.This thesis studies the multi-dimensional resources optimization strategy in heterogeneous wireless networks regarding the above mentioned problems. For the two-tier heterogeneous femtocell network and heterogeneous relay cooperation network, we propose an interference suppression multi-dimensional resources optimization strategy based on QoS guarantee, an energy saving communication multi-dimensional resources optimization strategy based on super-model game, a multi-dimensional resources optimization strategy based on reliability and fairness and a multi-dimensional resources optimization strategy based on security satisfaction ratio. The detailed descriptions are as follows:1. For the interference suppression problem of the two-tire heterogeneous femtocell network, an interference suppression multi-dimensional resources optimization strategy based on QoS guarantee is proposed. First, a multi-dimensional resources optimization model is built based on the pricing factor by using the interval collaboration technology and pricing mechanism. Secondly, according to the multi-users and multi-business differential QoS requirements and potential game theory, while considering multi-dimensional resources of sub-channels, power and signaling, etc, we analyzed the potential function with the pricing factor and proved the existence and uniqueness of the Nash Equilibrium. Meanwhile, the complexity of solving the target problem is reduced and the scalability of the model is enhanced. Finally, we adopt the threshold limit method, capacity maximization method, improved gradient projection method and the Jacobi iteration method to solve the optimization problem. Simulation resullts show that the strategy effectively restrains the interval interference of femtocells, reduces the network signaling overhead and promotes the overall throughput of the femtocell network with guarantee of the user heterogeneous QoS.2. For the energy consumption problem of the two-tire heterogeneous femtocell network, an energy saving communication strategy based on the super-model game is proposed. First, the strategy comprehensively considers the QoS of user requirements and actual feeling, and builds a utility model for end users which reflects the relationship between users’business satisfaction and energy consumption. The purpose of the strategy is to maximize the energy efficiency and to achieve an equilibrium among QoS requirements of users. Secondly, based on the non-cooperative game theory and convex pricing mechanism, we set up a resource optimization utility function model with the convex pricing factor. The overhead of network signaling is reduced by setting up a threshold boundary to promote the resource utility rate. Furthermore, a minimum interval interference sub-channel allocation strategy is proposed through analysis of the relationship between the channel allocation and interval interference. Finally, we prove that the non-cooperative game mentioned above is a parameter limited super-model game, which seeks the pareto optimal power control strategy through the analysis of the target problem.3. For the capacity maximization problem of heterogeneous one-way relay networks, a multi-dimensional resources optimization strategy based on reliability and fairness is proposed. First, considering multi-users and multi relays as our research scene, in order to satisfy the users’capacity needs and to improve the efficiency of the one-way relaying, we design a multi-resources optimization model based on the end-to-end network capacity. Secondly, considering both relay nodes selection and sub-channel allocation, a joint relay node selection and channel allocation scheme is proposed. To guarantee the reliability and fairness, the rule of maximizing minimizing balance and optimizing mechanism of user preference are designed respectively. Finally, a power allocation scheme is proposed, and solved by interior point methods. The simulation shows that this strategy not only effectively enhances the capacity of the relay network, but also well guarantees the reliability and fairness, and enhances users’business experiences4. For secutiry problems of the heterogeneous two-way relay networks, a multi-dimensional resources optimization strategy based on the security satisfaction ratio is proposed. First, this strategy fully considers the concerns of end users of their communication security and introduces a novel security satisfaction ratio (SSR) model, which is utilized as an objection function to analyze the information security problem through resource optimization. Secondly, for heterogeneous security requirement of users, diverse security tolerances are defined in order to protect the security requirement of higher security users. Meanwhile, the data transmission requirement of low security users are considered by building the CDF fairness curve and their fairness experience and business experience are guaranteed. Finally, we obtain near optimal resource optimization strategy by using the particle swarm optimization algorithm (CPSO), binary CPSO (B_CPSO) and classic Hungarian algorithm (CHA). Furthermore, a suboptimal subchannel pairing algorithm is proposed to reduce the computational complexity of subchannel pairing compared with CHA. The proposed two strategies not only improves the user’s security satisfaction and network security, but also specifically achieved the user’s heterogeneous security requirement.