  In this paper, the performance limits and the computational complexity of the
lattice sequential decoder are analyzed for the unconstrained additive white
Gaussian noise channel. The performance analysis available in the literature
for such a channel has been studied only under the use of the minimum Euclidean
distance decoder that is commonly referred to as the lattice decoder. Lattice
decoders based on solutions to the NP-hard closest vector problem are very
complex to implement, and the search for low complexity receivers for the
detection of lattice codes is considered a challenging problem. However, the
low computational complexity advantage that sequential decoding promises, makes
it an alternative solution to the lattice decoder. In this work, we will
characterize the performance and complexity tradeoff via the error exponent and
the decoding complexity, respectively, of such a decoder as a function of the
decoding parameter --- the bias term. For the above channel, we derive the
cut-off volume-to-noise ratio that is required to achieve a good error
performance with low decoding complexity.
