A subspace channel estimation method for IDMA in 5G systems

A novel hybrid subspace training method is presented for channel estimation in slow fading multipath Interleave Division Multiple Access (IDMA) channels for the future 5th Generation (5G) wireless systems. By using a small number of training symbols, the proposed estimator outperforms the conventional single-user channel estimator and does not require any additional knowledge than does the conventional estimator.