  For decades, Simultaneous Ascending Auction (SAA) has been the most widely
used mechanism for spectrum auctions, and it has recently gained popularity for
allocating 5G licenses in many countries. Despite its relatively simple rules,
SAA introduces a complex strategic game with an unknown optimal bidding
strategy. Given the high stakes involved, with billions of euros sometimes on
the line, developing an efficient bidding strategy is of utmost importance. In
this work, we extend our previous method, a Simultaneous Move Monte-Carlo Tree
Search (SM-MCTS) based algorithm named $SMS^{\alpha}$ to incomplete information
framework. For this purpose, we compare three determinization approaches which
allow us to rely on complete information SM-MCTS. This algorithm addresses, in
incomplete framework, the four key strategic issues of SAA: the exposure
problem, the own price effect, budget constraints, and the eligibility
management problem. Through extensive numerical experiments on instances of
realistic size with an uncertain framework, we show that $SMS^{\alpha}$ largely
outperforms state-of-the-art algorithms by achieving higher expected utility
while taking less risks, no matter which determinization method is chosen.
