  In this paper, we consider the problem of minimizing the uplink delays of
users in a 5G cellular network. Such cellular network is based on a Cloud Radio
Access Network (CRAN) architecture with limited fronthaul capacity, where our
goal is to minimize delays of all users through an optimal resource allocation.
Earlier works minimize average delay of each user assuming same transmit power
for all users. Combining Pareto optimization and Markov Decision Process (MDP),
we show that every desired balance in the trade-off among infinite-horizon
average-reward delays, is achievable by minimizing a properly weighted sum
delays. In addition, we solve the problem in two realistic scenarios;
considering both power control and different (random) service times for the
users. In the latter scenario, we are able to define and minimize the more
preferred criterion of total delay vs. average delay for each user. We will
show that the resulting problem is equivalent to a discounted-reward
infinite-horizon MDP. Simulations show significant improvement in terms of
wider stability region for arrival rates in power-controlled scenario and
considerably reduced sum of users total delays in the case of random service
times.
