Low complexity channel estimation technique for 1- bit ADC MIMO-constant envelope modulation using compressive sensing

The power efficient multi-input multi-output constant envelope modulation (MIMO-CEM) overcomes the power in-efficiency in MIMO-OFDM. However, MIMO-CEM channel estimation is a highly-sophisticated problem. This is owing to the use of a low resolution 1-bit analog to digital converter (ADC) that eliminates the received signal amplitude. Moreover, MIMO-CEM receiver is based on a maximum likelihood MIMO decoder (MLD) that needs an accurate channel estimation. Hence, a robust compressive sensing based MIMO-CEM channel estimator is proposed in this paper. In the first stage, the sparsity property of the MIMO-CEM channel is used to efficiently estimate a primary version of the MIMO-CEM channel. In the second stage, a refinement adaptive filter utilizing the pre-estimated primary channel to estimate the accurate MIMO-CEM channel. The proposed technique not only reduces the channel estimation complexity over the recently proposed MIMO-CEM channel estimators, but also it introduces spectrum saving. Via numerical simulations, the proposed MIMO-CEM channel estimator can capture the exact performance of the conventional MIMO-CEM channel estimator with only 20% preamble length, and a 70% complexity reduction.