Coding-Aided K-Means Clustering Blind Transceiver for Space Shift Keying MIMO Systems

In this paper, we propose coding-aided K-means clustering (CKMC) blind transceiver for space shift keying (SSK) multiple-input multiple-output (MIMO) systems, where the training of channel state information (CSI) is not required for detection. For the scenario where transmitter is with limited processing capability and limited power such as Internet Of Things (IOT) and wireless sensor network (WSN), SSK is preferable to typical MIMO due to its simplicity and improved energy efficiency. The proposed CKMC blind communication trades off receiver complexity for training overhead, which provides better spectral efficiency compared to training-based transceiver. In CKMC, the blind communication problem is converted to the problems of clustering and permutation; for the clustering problem, we propose K-means clustering (KMC) detector to reduce detection complexity; for the permutation problem, we propose to perform depermutation with the aid of channel decoding. The analysis of CKMC blind transceiver is conducted, and the verification of performance of CKMC is presented in the simulations section. The results show that the performance of CKMC blind communication can closely approach the performance of optimal receiver with perfect CSI under certain scenarios.