Scalar Ambiguity Estimation Based on Maximum Likelihood Criteria for Totally Blind Channel Estimation in Block Transmission Systems

This paper proposes a scalar ambiguity estimation method that sublimates the blind channel estimation method to totally blind estimation. Generally, the blind channel estimation method can identify the channel impulse response or channel frequency response up to scalar ambiguity. For coherent detection, the ambiguity should also be estimated. Exploiting the multiple modulation scheme, we estimate the scalar ambiguity for zero forcing equalization by maximum likelihood (ML). We also detect some equalized symbols fed into the ML estimation, which reduces the computational complexity of the proposed scalar ambiguity estimation. To efficiently reduce the complexity, we derive the Bayesian Cramér Rao lower bound (BCRB) of the ambiguity estimation. When evaluated in computational simulations, the performance of the proposed method achieved the BCRB performance at high signal-to-noise ratios. We also confirmed that when the proposed method is combined with the existing blind channel estimation, coherent detection is possible without any pilot symbols.