Research on Interference Cancellation for Switched-on Small Cells in Ultra Dense Network

In ultra-dense heterogeneous networks, the co-channel inter- ference between small cells turns to be the major challenge to cell throughput improvement, especially for cell edge users. In this paper, we propose a distributed frequency resource al- location approach for interference cancellation, which allo- cates appropriate frequency resources when a small cell is switched on to reduce the co-channel interference to its neigh- boring small cells. This frequency resource pre-allocation aims at avoiding co-channel interference between small ceils and improving users ＇ throughput. The simulation results show that our proposed scheme can effectively reduce the co-chan- nel interference and achieve considerable gains in users＇ through put.

Enabling Energy Efficiency in 5G Network

The mobile Internet and Internet of Things are considered the main driving forc⁃es of 5G,as they require an ultra-dense deployment of small base stations to meet the in⁃creasing traffic demands.5G new radio(NR)access is designed to enable denser network deployments,while leading to a significant concern about the network energy consump⁃tion.Energy consumption is a main part of network operational expense(OPEX),and base stations work as the main energy consumption equipment in the radio access network(RAN).In order to achieve RAN energy efficiency(EE),switching off cells is a strategy to reduce the energy consumption of networks during off-peak conditions.This paper intro⁃duces NR cell switching on/off schemes in 3GPP to achieve energy efficiency in 5G RAN,including intra-system energy saving(ES)scheme and inter-system ES scheme.Addition⁃ally,NR architectural features including central unit/distributed unit(CU/DU)split and dual connectivity(DC)are also considered in NR energy saving.How to apply artificial in⁃telligence(AI)into 5G networks is a new topic in 3GPP,and we also propose a machine learning(ML)based scheme to save energy by switching off the cell selected relying on the load prediction.According to the experiment results in the real wireless environment,the ML based ES scheme can reduce more power consumption than the conventional ES scheme without load prediction.

Non-isolated Step-up DC-DC Converter Based on Switched Capacitor Cells

A non-isolated high gain step-up DC-DC converter for low power applications is suggested in this study.In the designed transformerless converter,the main switch current and voltage stress is reduced while maintaining high voltage gain.For instance,with a duty cycle of 0.5 a voltage gain equal to 5 is achieved while the normalized switch voltage stress is 0.4.Also,it decreases power losses of active and passive elements.In the proposed converter design,the switched-capacitor(SC)technique is used to obtain maximum voltage transfer gain using only one switch.The three modes of operation,i.e.,continuous conduction mode(CCM),boundary conduction mode(BCM),and discontinuous conduction mode(DCM),are studied in detail.The small signal analysis(SSA)of the designed converter is investigated,and its steady-state model is examined under CCM.Performance of the proposed converter proposed in this study is assessed and tested using a prototype.Efficiency of the converter is recorded above 94%in a wide range of output powers.Overall,compared to the other converters,the results suggest satisfactory performance of the designed converter.An issue of the proposed converter is that its input current is not smooth due to using the switched-capacitor cell in its structure.This issue is alleviated by using input filters.