Robust estimator for lens-based hybrid MIMO with low-resolution sampling

It is well known that large antenna arrays with beamforming capabilities are required to compensate for the high path-loss at millimeter-wave (mmWave) frequencies. Recently, a practical two-stage Rotman lens beamformer has demonstrated increased antenna gain with reduced implementation complexity, since the conventional beam selection network was omitted. In this work, we adopt this system and we investigate its performance in terms of symbol estimation when analog-to-digital converters (ADCs) with low-resolution sampling being employed. Although this design is characterized by low-complexity and low-cost, the analog beamformer and the ADCs introduce several impairments to the received signal. To mitigate these effects, we have developed a robust maximum a posteriori (MAP) estimator based on the Expectation-Maximization (EM) iterative algorithm. The proposed algorithm outperforms the conventional EM approach, exhibiting small mean-square-error in the medium to high signal-to-noise ratio regimes.