Research On Compressive Sensing Detector For Generalized Space Shift Keying Signal

Generalized space shift keying(GSSK)system transmits signals through the indices of the antennas,it can better solve the issue of Inter Channel Interference(ICI),Inter Antenna Synchronization(IAS)and large number RF chains in traditional Massive Multiple Input Multiple Output(MIMO)systems.Therefore,it provides new ideas for the application of nextgeneration massive MIMO technology.However,the maximum likelihood(ML)detector has very high complexity which makes it computationally intractable for GSSK systems.By exploiting the sparse characters inherent of the signal,a Compressive Sensing(CS)scheme can be utilized to achieve the trade-off between the detection performance and the computational complexity.This study aims to research the compressive sensing algorithms and the GSSK signal detection in the massive MIMO systems,and obtains the following research results:Firstly,we studied the signal reconstruction algorithms based on compressed sensing theory,and emphatically studied the iterative-based greedy algorithms.Based on the generalized orthogonal matching pursuit(gOMP)algorithm,two orthogonal matching pursuit algorithms based on double selection strategy are proposed.By introducing backtracking and restrictive weak selection strategies,the reconstruction performance and the flexibility of atomic selection are improved.Secondly,we studied the existing signal detection algorithms for the GSSK systems,and a Euclidean distance-based backtracking matching pursuit(EBMP)detector was proposed using the inherent sparse characteristics of the GSSK signal.Meanwhile,the detection performance and the computational complexity comparison of the proposed algorithm with the existing sparse detection algorithms are given.Experimental results demonstrate that the proposed detector with low complexity outperforms the existing detectors.Finally,in view of the limited performance of the existing single-stage sparse detection scheme,we proposed a novel two-stage detection scheme which includes two stages of rough and precise selection.The Euclidean distance criterion is employed in the first stage to determine an optimized superset of active antenna indices,and then performs a further traversal search over the superset acquired by the first stage to obtain the final indices.The computer simulation results show that the proposed detector is able to achieve the trade-off between BER performance and computational complexity.In summary,the orthogonal matching pursuit algorithms based on the double selection strategy have a good theoretical significance,and the generalized space shift keying signal detection algorithms have a good practical application.