Synchronization and Channel Estimation at Millimeter Wave
MIMO channels at Millimeter Wave (mmWave) are approximately sparse in the angle and delay domain. Exploiting this property, several compressed sensing (CS) based algorithms have been proposed in the literature for mmWave channel estimation with fewer measurements. Most of them, however, assume perfect timing and carrier synchronization and fail to perform well due to synchronization errors. Our group is currently working towards developing synchronization and channel estimation algorithms that exploit sparsity and meet the constraints of potential mmWave hardware architectures.
In our recent work, we proposed a phase error robust compressive algorithm for narrowband mmWave systems. We assumed perfect timing synchronization, and considered phase errors arising due to carrier frequency offset (CFO) and phase noise. Exploiting the sparsity of mmWave channels, we formulated a tensor based algorithm to jointly estimate the CFO and channel compressively. Our approach is shown to be analogous to lifting techniques that exist in the literature and is shown to perform better than the existing ones that address the same problem.
N. J. Myers and R. W. Heath, Jr. , A compressive channel estimation algorithm robust to synchronization impairments, to appear in Proc. of the IEEE International Workshop on Signal Processing Advances in Wireless Commn. (SPAWC), July 2017