| Spatial modulation(SM)technology is emerging as a modulation technique following multiple-input multiple-output(MIMO)technology.This scheme configures multiple antennas at both transmitter and receiver in communication system,thus,the problems of sub-channel interference and precise synchronization between transmitting antennas in traditional MIMO system is effectively improved by means of activating only one transmit antenna in each transmission time slot and using the index position of the antenna to carry some information,which has become a hot topic for many scholars in recent years.Multicarrier spatial modulation technology divides the transmitted bits into several parallel subbit streams and then modulates them into different sub-carriers for transmission.Generalized Frequency Division Multiplexing(GFDM)is a non-orthogonal multi-carrier transmission mode.GFDM is recognized as one of the most competitive 5G candidate waveforms with its unique frame structure.This thesis is based on the research of SM-GFDM system.The main work content and innovative ideas are as follows:1.Firstly,the background knowledge of SM system and GFDM system is introduced.Secondly,the signal model and basic principle of SM system and GFDM system are introduced respectively.Then several 5G candidate waveforms are introduced and the advantages of SM system combined with GFDM technology are analyzed.Finally,considering the disadvantages of the existing SM-GFMD system model and not considering the respective characteristics of SM and GFDM,and this thesis uses SM to replace the QAM modulation step in GFDM and proposes a simplified SM-GFDM system model.Then the transmission processes and modulation principle of the transmitted signal in the SM-GFDM system are introduced in detail.2.Aiming at the problem that the combined SM-GFDM system has a high complexity,the receiver detection algorithms are studied in this thesis.In SM-GFDM system,the transmission signal is first sent to the GFDM receiver by the wireless channel.Traditional GFDM detection algorithms have a high detection complexity.It is a fact that using matrix sparsity can reduce the computational complexity of the computing process without affecting the system performance.Secondly,several traditional signal detection algorithms including Matching Filter(MF)detection algorithm,Zero Forcing(ZF)detection algorithm and Minimum Mean Square Error(MMSE)detection algorithm are introduced and its performance simulations are performed.Simulation results show that the performance of the MMSE detection algorithm is optimal.Secondly,traditional detection algorithms are combined with the sparseness of the matrix.The signal is decomposed using a normalized discrete Fourier transform block matrix,and the process of implementing matrix sparsity is described in detail.Finally,the complexity of the proposed algorithms and traditional detection algorithms are analyzed.Several performance simulations of receiver detection schemes based on matrix sparsity are performed.The results show that in the SM-GFDM system,the proposed algorithms are significantly improved on complexity.3.Aiming at the problem that SM demodulation still has a high complexity in SMGFDM system,this thesis proposes an improved M-ML detection scheme with a dynamic M based on tree search structure.Some channel components remain in the complex signal demodulated by the GFDM demodulator.The GFDM demodulated signal is sent to the SM demodulator and an appropriate detection algorithm is selected to recover the original bit sequence.This thesis first introduces several traditional SM signal detection algorithms,of which the best performance is maximum likelihood(ML)detection.Based on this,a tree search-based M-ML detection scheme is introduced.The computational complexity is reduced by reducing the search space.However,the number of nodes retained in each layer in the traditional M-ML detection is an empirical value,so there is still a redundant search for different channel environments.In this thesis,the average accumulated branch metrics are calculated base on the fact that the accumulated branch metrics is different for different channel conditions.The branches which ABM are smaller than the average are reserved and the number of search branches M at each layer is dynamically reserved.Simulation results show that compared with the traditional M-ML detection,the performance of the proposed algorithm is slightly decreased.However,due to its ability to dynamically adjust the number of search nodes,its complexity has been improved.Compared with the traditional M-ML detection,it is more suitable for the SM-GFDM system. |
