  We propose a best arm identification multi-armed bandit algorithm in the
fixed-confidence setting for mmWave beam alignment initial access called
\ac{SSE}. The algorithm performance approaches that of state-of-the-art
Bayesian algorithms at a fraction of the complexity and without requiring
channel state information. The algorithm simultaneously exploits the benefits
of hierarchical codebooks and the approximate unimodality of rewards to achieve
fast beam steering, in a sense that we precisely define to provide fair
comparison with existing algorithms. We derive a closed-form sample complexity,
which enables tuning of design parameters. We also perform extensive
simulations over slow fading channels to demonstrate the appealing performance
versus complexity trade-off struck by the algorithm across a wide range of
channel conditions.

Signal Processing