Research On Topology Contorl For Multi-hops Cellular Networks

In order to meet the users'demand of higher transmission rate and larger bandwidth, the communication network has developed into an integrated communication system composed of multiple access networks. The wireless multi-hop relay network is an important part of the cellular communication system because of its flexibility and extensibility. According to the relay type,the network can be divided into two categories: multi-relay the cellular network based on mobile relay and the multi-relay cellular network based on fixed relay. The cellular network based on mobile relay is similar to the cognitive ad hoc network. In the network, network stability and transmission efficiency are two important issues. In the multi-relay cellular network based on fixed relay, improving the energy efficient of multi-relay networks is crucial for the whole communication networks.In this paper, we design two network optimization strategys solving the problem of the both scenarios.(1) For the multi-relay the cellular network based on mobile relay, in this paper, we proposed a robust and efficient ad hoc network topology evolution model, which is based on BBV model and the small-world model. In this model, the mobile users' residual energy, available channel quality, and the importance are taken into account. The model is analyzed and simulated numerically, and can significantly improve the stability of the network and data transmission efficiency.(2) In order to improve the energy efficient of multi-relay the cellular network based on fixed relay. In this paper, we design an energy flow management framework, which contains routing planning, traffic adjustment and power allocation. In order to reduce the energy consumption and gurantee the system capcity, a heuristic algorithm is designed in this paper which mixes the ant colony algorithm with convex optimization theory. Under the premise of guaranteeing the service quality of the users, the algorithm realizes the optimization of the power consumption and capacity of the whole network.