Research On Resource Allocation Algorithms For Energy Harvesting Wireless Relay Networks

In wireless communication systems,energy harvesting technology can continuously harvest energy from the surrounding environment,which greatly extends the life cycle of equipment and improves the performance of wireless networks.In addition,relay technology extends the coverage of wireless networks and ensures the communication quality of cell-edge users.Therefore,the study on the resource allocation problem in energy harvesting wireless relay networks is very significant.In this thesis,the resource allocation algorithms based on energy harvesting for wireless relay networks is studied,and the resource allocation problems considering the combination of energy harvesting,relay,cognitive radio,energy cooperation and OFDM are considered separately.The main research contents and contributions are as follows:(1)An algorithm to optimize the power allocation by minimizing the transmission completion time in energy harvesting wireless relay networks is proposed.The algorithm considers the energy harvesting relay which uses decode-and-forward(DF)mode and assumes that the data packets sizes and the harvested energy amounts have been got before the data transmission begins.According to the queue lengths of data and harvested energy,the algorithm optimizes the power policy of the source and relay by minimizing the time that all data is transmitted limited by the causality constraints of data and harvested energy.Simulation results verify that the proposed algorithm can minimize the transmission completion time of the data transmission.(2)An algorithm to optimize the power allocation by maximizing the system throughput in cognitive radio energy harvesting networks is proposed.The algorithm formulates the throughput optimization model subject to the causality constraints of the harvested energy within the two secondary users(SUs)and the interference constraint of the primary user(PU).In addition,by applying the variable-substitution method and problem equivalence transformation,the joint optimization problem of power and cooperative energy is decoupled into two problems: a power allocation problem and a cooperative energy one.The original problem can be solved by iterating the two decoupled problems.As shown in the simulation results,the energy cooperation can significantly improve the system throughput when the harvested energy difference between two nodes is rather large.(3)We consider a two-way cognitive radio relay network where two SUs can simultaneously transfer energy and information to a relay.Then,a joint optimization algorithm for power allocation and energy cooperation is proposed.The algorithm proves that the formulated throughput maximization problem is a convex optimization problem under the energy causality constraints of the two SUs and relay,and the interference constraint of the PU.Next,we decompose the formulated problem into a power allocation problem and an energy transmission problem by the equivalence transformation of the problem.Finally,the power allocation problem is solved by an iteration water-filling algorithm,and the energy transmission problem of each timeslot is solved by the derivative method.For the energy backflow phenomenon in some timeslots,this thesis gives the water-filling interpretation.(4)A resource allocation algorithm based on simultaneous wireless information and power transfer(SWIPT)to maximize the system throughput is proposed in OFDM relay networks.The algorithm formulates the problem under the peak power constraints of the source and each subcarrier(SC),and the energy causality constraint of the relay.With the given SC allocation of the source,we give and prove the optimal propositions of the formulated problem.Then,the formulated problem could be decomposed into two separate throughput maximization sub-problems by setting the total power to transfer energy.Finally,several SC allocation schemes are proposed,which are energy priority scheme,information priority scheme,balanced allocation scheme and exhaustive scheme.The simulation results reveal that the energy priority scheme can significantly reduce computational complexity and achieve approximate performance with the exhaustive scheme.