Minimizing Uplink Delay in Delay-Sensitive 5G CRAN platforms

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.