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Research On Improving The Performance Of Link Simulation And System Simulation Interface For LTE Mobile Communication System

Posted on:2018-08-20Degree:MasterType:Thesis
Country:ChinaCandidate:G N HanFull Text:PDF
GTID:2348330542952070Subject:Electronic and communication engineering
Abstract/Summary:PDF Full Text Request
The mobile communication system in actual use,before base station location,network planning and other work,has to get the performance of the whole communication system through certain estimation and understanding,which is accomplished through system level simulation.System level simulation is focus on communication quality that composed of multi point to multipoint systems,but it is conceivable that the multipoint simulation will produce a huge amount of computation,which makes a sharp increase in the complexity of the system simulation.Compared with the system level simulation,link level simulation is concerned with the simulation of the link point to point,and the complexity of the simulation link is acceptable.Therefore,it is possible to obtain the performance of the communication system by the link simulation results through the link simulation and system simulation(L2S)interface algorithm.In this paper,we mainly study the L2S algorithm in order to improve the accuracy of the algorithm.For link level simulation,we have built the hardware link simulation platform in this paper.The conventional software simulation link has the advantages of simple and efficient,but compared with the actual communication system scene,it has simpler and abstract,and also have some deviations in the simulation accuracy.In this paper,the hardware platform is used to realize the data digital to analog conversion,through the hardware simulation channel and sampling process,what's more,the synchronization and channel estimation problem is considered,which will make the simulation results closer to the real communication scenario,and then makes the L2S algorithm more practical.Synchronization and channel estimation are two indispensable simulation modules in the hardware link simulation platform.Therefore,this paper studies the common methods of synchronization and channel estimation in downlink LTE,and different synchronization and channel estimation algorithm methods were compared with the simulation performance,in order to select the highest performance in the hardware link simulation platform.Exponential effective SNR mapping algorithm(EESM)is a widely used L2S interface algorithm.This paper studies the algorithm,an improved algorithm is proposed by using the symbol error formula instead of the original boundary approximation directly,the improved algorithm brings the improvement of accuracy at the cost of computational complexity.Then the simulation results of the hardware link simulation platform are used to validate the conventional EESM algorithm and the improved EESM algorithm,the simulation results show that the improved EESM algorithm has better accuracy in the high order MCS,but the performance of the low order MCS is slightly worse than the conventional EESM algorithm.Therefore,the improved EESM algorithm can be effectively applied to high order modulation communication scenarios.In this paper,we also study the received bit mutual information rate(RBIR)algorithm,which is more accurate than the EESM algorithm,and also adapted to adaptive coded modulation system.Conventional RBIR algorithm compression function using a simple direct average method,which will increase the error of the higher order modulation algorithm.In this paper,the RBIR algorithm is improved by changing the compression function is changed into exponential effective compression.The simulation results from hardware link simulation platform shows that,compared with the conventional RBIR algorithm the improved RBIR algorithm is basically the same in the low order MCS,but in the high order it has obvious performance improvement.It is proved that the algorithm is effective.
Keywords/Search Tags:L2S interface, Hardware link simulation platform, Synchronization and channel estimation, EESM algorithm, RBIR algorithm
PDF Full Text Request
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