Research On Uplink Multi-user Detection Technology For Satellite Communication Systems

As an important part of the construction of national mobile communication facilities,the satellite mobile communication system has many advantages,such as good mobility,wide coverage area,excellent transmission reliability and higher efficiency.However,there are many factors in transit,these make the satellite communication unstable.For example,the multipath fading,the time-varying characteristics,and the shadowing effects.These factors caused the signal distortion.In addition,with the increasing demand for users,the demands for the frequency resource are booming.And then the resource will become more and more scarce.Therefore,in order to solve these problems in satellite transmission,the research on key technologies of communication transmission has never stopped.In order to increase the capacity of the communication system and reduce the interferences,the research on multi-user detection technology has become a hot spot.This thesis studies the multi-user detection technology for the uplink of satellite communication systems.The content of this research is as follows:Firstly,according to the key technologies of satellite communication,this thesis introduced the classification and characteristics of satellite communications systems and analyzed their transmission characteristics.And then several common satellite transmission models are introduced in detail.Based on this,the multi-user detection technology is introduced,the importance of it in satellite communication systems are explained,and the performance evaluation criteria are analyzed,and some common algorithms in multi-user detection are analyzed after that.Secondly,an improved Expanded Deep Neural Network(EDNN)algorithm is proposed.This algorithm is derived from the Deep Belief Network(DBN),which is used for the multi-user uplink signal detection architecture.Finally,the uplink multi-user access model of the satellite communication system is established,and then we compared the detection results of the traditional multi-user detectors with the algorithm we proposed in this thesis.The results showed that the EDNN algorithm we proposed here has better bit error rate under the same Signal to Noise Ratio.