Channel Estimation for Hybrid MIMO Systems in Millimeter Wave Communications

Abstract

Channel estimation is of critical importance in a millimeter-wave (mm-wave) hybrid multiple-input multiple-output (MIMO) system consisting of radio-frequency (RF) beamformers with large antenna arrays followed by a baseband MIMO processor. Due to the use of large antenna arrays and rotating pilot beams to compensate for higher path loss, conventional channel estimation techniques developed for a lower-frequency MIMO system are not applicable and thus an efficient mm-wave specific channel estimation techniques are required. This dissertation proposes mm-wave specific pilot signal reception and channel estimation techniques for mm-wave hybrid MIMO systems with rotating pilot beams.

In the first half of this dissertation, a sparse signal recovery problem exploiting the sparse nature of mm-wave channels is formulated for channel estimation based on the parametric channel model with quantized angles of departures/arrivals (AoDs/AoAs), called the angle grids. The problem is solved by the orthogonal matching pursuit (OMP) algorithm employing a redundant dictionary consisting of array response vectors with finely quantized angle grids. We suggest the use of non-uniformly quantized angle grids and show that such grids reduce the coherence of the redundant dictionary. The lower- and upper-bounds of the sum-of-squared errors (SSE) of the proposed OMP-based estimator are derived analytically: the lower-bound is derived by considering the oracle estimator that assumes the knowledge of AoDs/AoAs, and the upper-bound is derived based on the results of the OMP performance guarantees. Analytical results indicate that the SSE increases with the number of channel paths (or the sparsity level). The design of pilot beam vectors (or sensing matrix) is particularly important in hybrid MIMO systems because the RF beamformer prevents the use of independent and identically distributed (i.i.d.) random training vectors which are popular in compressed sensing (CS). We design training vectors so that the total coherence of the equivalent sensing matrix is minimized for a given RF beamforming matrix which is assumed to be unitary. It is observed that the estimation accuracy can be improved significantly by randomly permuting the columns of the RF beamforming matrix. Simulation results demonstrate the advantage of the proposed OMP with a redundant dictionary over the existing methods such as the least squares (LS) method and the OMP based on the virtual channel model.

In the second half of this dissertation, a mm-wave specific process for pilot signal reception is developed while focusing on a pilot arrival time (PAT) discovery and a space-time alignment of the pilot signals received by rotating pilot beams. The PAT finder identifies the timing instants when the time domain (TD) orthogonal frequency division multiplexing (OFDM) pilot symbols are received, while compensating for the carrier frequency offset (CFO). The estimated PATs arise from different channel paths corresponding to different delay taps, which results in the phase offset and inter-symbol interference (ISI) on reference signals (RSs) after OFDM demodulation. To compensate for these effects of rotating pilot beams, the estimated PATs are adjusted by the space-time aligner. After reception process, the channel estimation is performed where the spatially common support in sparse channel vectors is exploited. The simulation results demonstrate that the proposed mm-wave specific process for pilot signal reception is essential in estimating mm-wave channels with rotating pilot beams.