How to solve conditional expectation time series process

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The following is a time series process:

$y_t = _0 + _1e_t + _2e_{t-1} + _3e_{t-2}$, where all the are parameters, e is white noise, and t is the time index.

What is the result of taking the expectation of $y_t$ conditional on the information set available up and through period t-1?

So set up the equation but I'm not sure how to solve it after this. I used $Ω_{t-1}$ to represent the information set through period t-1.

$(y_t|Ω_{t-1}) = (_0 + _1_ + _2_{−1} + _3_{-2}|Ω)$