We consider the estimation of an integer vectorx ∈ Z n from the linear observation y = Ax + v, where A ∈ R m×n is a random matrix with independent and identically distributed (i.i.d.) standard Gaussian N (0, 1) entries, and v ∈ R m is a noise vector with i.i.d. N (0, σ 2 ) entries with given σ. In digital communications,x is typically uniformly distributed over an n-dimensional box B. For this estimation problem, successive interference cancellation (SIC) decoders are popular due to their low complexity, and a detailed analysis of their word error rates (WERs) is highly useful. In this paper, we derive closed-form WER expressions for two cases: (1)x ∈ Z n is fixed and (2) x is uniformly distributed over B. We also investigate some of their properties in detail and show that they agree closely with simulated word error probabilities.Index Terms-Word error rate, successive interference cancellation, Babai's nearest plane algorithm, integer least-squares problems.