Large Scale MIMO System Signal Detection Technology Based On Spatial Modulation

MIMO(Multiple Input Multiple Output,MIMO)technology has been extensively studied by many researchers due to its multiple antennas at transmitter and receiver,which can effectively expand the system capacity.Currently,the widely used 4G communication systems use MIMO technology.In the MIMO system,the signals received at the receiver are the superposition of the desired signals and the interference signals.In order to correctly recover the information sent by the transmitter,excepting accurately estimating the channel state information in the intermediate transmission,it is ultimately necessary to recover the signal at the receiver.That requires good reception detection at the receiver.The main research of this paper is the problem of signal detection in MIMO system.MIMO systems based on space-modulated signals have become hot topics due to the limited bandwidth resources.Spatial modulation technology improves the utilization of spectrum resources by introducing a third-dimensional spatial domain.The spatial modulation system model used in this paper adopts the idea of grouped transmission and interleaving technology to improve system performance.In this paper,the detection performance of the traditional MIMO detection methods in the spatial modulation MIMO system is simulated and analyzed.It is verified that some traditional methods are not suitable for spatial modulation MIMO systems because of poor detection performance or high complexity.A signal detection algorithm based on distributed compressed sensing is proposed,the core of this algorithm is to use the inherent sparseness of the spatially modulated signal and combine it with the theory of compressed sensing,which realizes the joint detection of signals under the premise of low complexity and achieves the near-optimal detection performance.