Research On The Energy Efficiency Of Wireless Resource Management In The M2M Communication

Machine to Machine(M2M)is a promising technique connecting smart wireless devices.In the near future,a 5G system should comprise not only conventional Human to Human(H2H)devices,but also considerable delay tolerant M2M devices.The most obvious feature of M2M is that it can work without human intervention.Thus,to ensure low energy consumption of M2M devices is a necessary condition to increase their lifetime,which also means to increase the energy efficiency(EE)of each device.In general,there are two scenarios where M2M coexist with H2H.In one case,frequency spectrum resources are used orthogonally by M2M devices and H2H devices.In another case,M2M devices reuses the frequency resource of the H2H devices to satisfy their own performance.Therefore,in both scenarios reasonable resource management programs deserve further exploration.In this thesis,the coexistence of M2M and H2H in orthogonal scenarios and interference scenarios are considered respectively.Then we investigate a tradeoff between the EE of the M2M devices and channel capacity(CC)of the H2H devices,and a multi-objective optimization problem(MOOP)is formulated to allocate the bandwidth and power resources.Finally,a Weighted Tchebyshev(WT)algorithm is proposed to solve the MOOP.The innovations of this thesis are as follows:(1)When frequency resources are used orthogonally,taking into account the delay constraints of M2M devices and three types of MTCDs' Quality of Service(QoS),a MOOP is proposed based on the EE of M2M devices and the CC of H2H devices.In order to reduce the impact of M2M equipment on H2H equipment during resource competition,a weighting function based on M2M demand factor is also proposed in this thesis.Simulation results show that HTCDs' performances are guarranted by the proposed weighted function.(2)In addition,in order to solve the pareto optimal solution set of the MOOP,this thesis adopts a Weighted Tchebyshev method to convert the MOOP into a single objective optimization problem.The simulation results show that the proposed algorithm not only has good performance,but also yields a flexible tradeoff between the M2M EE and the H2HCC.(3)When frequency resources are reused,the thesis combines M2M with Device to Device(D2D),and it allows M2M to reuse the spectrum resource of H2H.The EE of M2M devices,the CC of H2H devices and the interference of M2M devices to the eNB are three objectives for multi-objective problem modeling.Due to the fact that the indicators of spectrum resource allocation are binary variables,the thesis first uses the penalty function to convert binary variables into relaxation constraints.Then,the Weighted Tchebyshev method is adopted to convert the MOOP to a single-objective problem,and the non-convex single-objective problem can be solved by Concave Convex Procedure(CCCP)method.Finally,the approximate optimal solutions to the original problem are obtained,which show the effectiveness of the proposed algorithm.