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Next generation wireless networks will exploit the large amount of spectrumavailable at millimeter wave (mmWave) frequencies. Design of mmWave systems,however, is challenging due to strict power, cost and hardware constraints athigher bandwidths. To achieve a good SNR for communication, mmWave systems uselarge antenna arrays. Beamforming with highly directional beams is one way touse the antennas. As the channel changes over time, the beams that maximize theSNR have to be estimated quickly to reduce the training overhead. Prior workhas exploited the observation that mmWave channels are sparse to performcompressed sensing (CS) based beam alignment with few channel measurements.Most of the existing CS-based algorithms, however, assume perfectsynchronization and fail in the presence of carrier frequency offset (CFO).This paper presents Swift-Link, a fast beam alignment algorithm that is robustagainst the offset. Swift-Link includes a novel randomized beam trainingsequence that minimizes the beam alignment errors due to CFO and alow-complexity algorithm that corrects these errors. Even with strict hardwareconstraints, our algorithm uses fewer channel measurements than comparable CSalgorithms and has analytical guarantees. Swift-Link requires a small outputdynamic range at the analog-to-digital converter compared to beam-scanningtechniques.

Swift-Link: A compressive beam alignment algorithm for practical mmWave radios