Transmission Control And Topology Identification Of Wireless Network Based On State Feedback Control

With the development of wireless networks, the communication quality requirements from users are increasing. The link transmission control such as frequency hopping (FH) and power control technology can increase the network capacity and improve the performance in jamming environment. Network topology identification is significant to improve multimedia streaming transmission quality in Ad hoc network. Some new ideas and methods for FH transmission, power control and network topology identification are provided from the perspective of control theory based on state feedback control.Firstly, the frequency hopping technology based on chaos and state feedback control is studied. A kind of chaotic sequence non-periodic self-perturbation method is proposed on DSP in order to overcome the finite precision effect.In the chaotic FH synchronization scheme, a new nonlinear feedback function and genetic algorithm based nonlinear feedback control method are proposed. The Logistic map chaotic sequences synchronization under different parameter space are achieved. Experiments and performance analysis show the effectiveness of the proposed methodsSecondly,The time delay and inteference based state space(TDISS) model is proposed for the closed loop power control in the DS-CDMA system. The impact of actual interference, noise and time delay are considered in the model. Additionally, The optimal power control with time delay and interference compensation(OPC_TDIC) method is proposed for the power control system. The quadratic performance is defined to meet the practical requirements of power control.Then, the optimal state feedback controller design is obtained. The strong robustness and good convergence of the proposed algorithm is demonstrated by the simulation, in comparison with some other improved power control algorithms.Finally, the topology of wireless network is investigated based on complex network theory. Small world model and scale-free model can reflect the actual characteristics of the wireless network better than the stochastic model. A new method based on the reduced-order observer or the output is proposed to identify complex dynamical networks, in which only some state viariables or the output as feedback can be measured. The network topology can be identified through the node output and the observed state variables. Furthermore, the network with time delay and different nodes is taken into account in this proposed simple technique.A large number of simulation results in the small wireless Ad hoc network based on complex network topology confirm the effectiveness of the methods.