Energy Efficiency Optimization Algorithm In Heterogeneous Cloud Radio Access Networks

With the rapid development of Internet of Things and mobile internet,the wireless communication system is faced with the explosion of data traffic and the huge terminal access.It also brings the growing consumption of energy from base stations.Nowadays,energy efficiency performance metric has become an important indicator to assess network performance.This thesis turns to the study of energy-efficient optimization problem based on Heterogeneous cloud radio access networks(HCRANs).Firstly,this thesis proposes an optimizing energy efficiency algorithm based on the cell range expansion.When the user is distributed dispersedly,it is efficient for the cell with the low load to sleep and the user in sleeping cell will select new station according to the reference signal receiving power and cell range expansion.In hot spots,when the channel capacity threshold value of the fronthaul is reached,the edge users will be restricted to access the remote radio heads(RRHs).Simulation Results confirm that the optimal cell range expansion bias is related to cell load and compared with the existing algorithm,the proposed algorithm can significantly improve the energy efficiency.Next,according to the impact of interference on energy efficiency,this thesis proposes the energy efficiency optimized algorithm based on the fractional frequency reuse(FFR)mechanism and coordinated multipoint(CoMP)transmission method.Taking the geographic location and the user density into account,the frequency spectrum is divided into five segments which are orthogonal to each other.The joint transmission scheme of CoMP technology guarantees the quality of service for all users at speed.Simulation Results confirm that with the increase of the central frequency band,the energy efficiency of the system increases and the number of users who need to cooperate in the edge area be larger.At last,this thesis proposed a modified particle swarm optimization(MPSO)algorithm to adjust power allocation.The improved algorithm readjusts the location of particles whose location beyond the search space randomly and adjust the local and global search ability by changing the inertia gene dynamically.The result of simulation shows proposed algorithm speeds up convergence and avoid the particle stagnate in the local best value compared with the PSO algorithm.Besides,the proposed algorithm will achieve the higher energy efficiency compared with the maximum transmit power allocation algorithm.HCRANs takes full advantages of both heterogeneous networks(HetNets)and cloud radio access networks(C-RANs),which degrades the control and user planes.By moving remote radio heads closer to the users,lower power and higher system capacity can be achieved because the signal doesn’t need to propagate a long distance to reach the users.The HCRAN architecture is a promising architecture and the corresponding resource allocation scheme can significantly improve the energy efficiency.