Research On Communication Resource Management Strategies In Wireless CSMA Networks

To meet the growing demand for access for the large number of terminal devices,IEEE 802.11 ah standard has been proposed by the 802.11 task group to support access to large-scale devices.However,the large-scale access will intensify channel conflicts.Therefore,802.11 ah introduced restricted access window(RAW)mechanism in the media access control(MAC)layer.So as to reduce the collision probability between nodes by limiting the number of nodes competing channels at the same time.In order to address the problem of unbalanced level of contention between groups caused by the grouping efficiency in 802.11 ah heterogeneous network,we construct sensor grouping optimization model,and propose a heuristic sensor grouping algorithm to find sub-optimal sensor grouping scheme,which reduce the collision probability of nodes.Furthermore,the rapid use of wireless spectrum makes people seek for the use of unauthorized spectrum.TV frequency band has good propagation and building penetration,so it becomes an ideal choice to alleviate the problem of spectrum scarcity.However,when wireless network shares TV spectrum,it is necessary for wireless devices to effectively manage the interference received by authorized users of the primary network.To this end,for cognitive radio networks,a scheduling problem of secondary users with the aim of maximizing the sum utility of secondary networks is constructed,and the power and access-intensity of secondary users are jointly optimized to achieve the optimal scheduling algorithm.The main contribution of this thesis are as follows:For the 802.11 ah heterogeneous network,a sensor grouping optimization model based on the traffic distribution is established with the target of max-min energy efficiency,and a sensor-traffic mapping algorithm is designed.Specifically,we first take use of the energy efficiency distribution characteristics between wireless sensor groups,based on which an integer non-linear programming(INLP)sensor grouping model with the goal of max-min energy efficiency is established,we then propose a traffic grouping algorithm based on BBM to get the optimal traffic grouping scheme.Because different combination of heterogeneous sensors can generate the same traffic demands,an optimal sensor grouping scheme cannot be found.Then a heuristic sensor-traffic mapping algorithm is designed to find a sub-optimal sensor grouping scheme.Simulation results show that the proposed algorithm can achieve a better performance than other algorithms.For the cognitive radio network,a user scheduling optimization model is established with the target of maximizing sum utility and a user scheduling algorithm is designed.Specifically,we first calculate the network throughput based on ideal CSMA network model and establish a user scheduling model to maximize sum utility.Using the separation of access-intensity and power variables,decouple the optimization problem into two sub-problems and solve them separately,and the optimal joint optimization of power control and access-intensity adjustment algorithm is designed.Simulation results show that the proposed algorithm can achieve maximum sum utility and performs better than other user scheduling algorithms.