  We study the tradeoff between the sum rate and the error probability in
downlink of wireless networks. Using the recent results on the achievable rates
of finite-length codewords, the problem is cast as a joint optimization of the
network sum rate and the per-user error probability. Moreover, we develop an
efficient algorithm based on the divide-and-conquer technique to simultaneously
maximize the network sum rate and minimize the maximum users' error probability
and to evaluate the effect of the codewords length on the system performance.
The results show that, in delay-constrained scenarios, optimizing the per-user
error probability plays a key role in achieving high throughput.
