Research On Sleep Strategy In Dense Cellular Networks

With the maturity of the fifth-generation mobile communication technology,the explosive growth of wireless network user traffic.5G uses high frequency bands with abundant frequency band resources,resulting in higher energy consumption than other standard networks.In order to cope with the serious energy consumption problems of 5G,the dormancy strategy of base stations has become a hot topic in the field of communication energy saving.Based on the two-layer macro-micro cellular network,this paper proposes the following two base station dormancy strategies for the interference and energy consumption of dense wireless networks:Strategy 1: Micro-site regional hierarchical dormancy algorithm.In order to take advantage of the high energy-saving rate of the iterative algorithm and reduce its blindness,regional classification is carried out according to the different sleep probabilities of different locations where the micro-station is deployed.Micro-stations deployed in overlapping coverage areas between macro-stations have a high sleep probability,a low restart probability,and a good energy-saving effect by prioritizing sleep.After the micro-station classification is carried out,the influence of the micro-station load ratio and the distance between macro and micro-stations on the sleep priority is considered between the micro-stations at the same level.According to the classification of micro-stations and the priority of the same level,the micro-stations deployed in different areas are sorted and iterated,which avoids the blindness of the iterative algorithm and reduces the complexity of the algorithm to a certain extent.Control the switching state of each micro station,transfer the traffic load to the macro station or balance the load of the macro station,so that the load of the macro station is kept in a state of neither idle nor overly busy,making full use of the time-frequency resources of the macro station,and improving the system efficiency.The simulation shows that under the tidal user traffic demand,compared with the iterative algorithm,the energy saving rate is not more than 1.7% to save more than 50% of the running time,the sleep algorithm has better energy saving effect in large-scale networks.Strategy 2: Dynamic clustering sleep algorithm based on user interference value.The ratio C of the number of micro-station users to the minimum distance between micro-stations is used as the input reference value of the total interference value of micro-station users,and the C value is related to the interference level of the users carried by the micro-station.The micro-station with the largest C value in the system becomes the first cluster head.Considering the load similarity of the adjacent interval of the cluster head,the adjacent micro-stations with low load similarity are allocated to the cluster head to form a cluster.The microsite with higher C value becomes the new cluster head.The cluster head micro-station becomes a micro-station with a large number of users and a high level of interference.The cluster-head micro-station is kept normally open,and the in-cluster micro-stations with the greatest interference from the cluster-head micro-station are judged to sleep in turn,reducing the number of in-cluster micro-stations.The interference of the cluster head micro-station,and finally shut down the unloaded macro-station.Find and sleep the interfering base station to the high-load base station,and the energy-saving effect is superior when the system is under high load.Simulations show that the algorithm can save energy from6.6% to 27.9% under different network loads,reduce inter-station interference and improve energy-saving efficiency.