Research On Signal Detection Algorithms In Space Modulation Systems

The wireless communication technique changes quickly,which not only brings infinite possibilities to technology and development but also adds color to people’s production and life.As one of the key techniques in the new generation wireless communication system,MultipleInput Multiple-Output（MIMO）makes full use of the spatial dimension to achieve higher reliability and spectrum utilization;however,MIMO system has problems such as system complexity and practical difficulty.Spatial Modulation（SM）technique addresses the shortcomings of MIMO,which has become a hot research topic in the field of wireless communication.SM activates only one transmitting antenna at each moment to transmit information by using not only the modulation but also the spatial domain.This paper focuses on the signal detection algorithms for SM,especially how to balance the detection performance and computational complexity of the algorithm.In this paper,the modulation principle of SM is firstly introduced in details and further explained in the context of its system model.Then,the principle of signal detection algorithms commonly used in SM systems is researched.Moreover,these algorithms are simulated and analyzed in terms of detection performance and computational complexity.Finally,the traditional Maximum Likelihood（ML）algorithm,Signal Vector based Detection（SVD）algorithm and M-algorithm to ML（MML）algorithm are discussed in depth,and three improved algorithms are given.In order to balance the detection performance and computational complexity,three improved algorithms are given on the basis of mathematical simplification and reduce of the number of search nodes,which are called the yhs-ML algorithm,the yhsSVD algorithm and the i-MML algorithm.From the simulation results,it is clear that the yhsML algorithm and the yhs-SVD algorithm lose a small part of the detection performance,and the i-MML algorithm does not lose the detection performance;furthermore,the computational complexity of all three improved algorithms is significantly reduced.Therefore,we achieve the expected results.