On Channel Reuse for Cloud Network Users

This paper deals with channel assignment for cloud network users based on the information from application layer. We assume a multiple user network where the services requested by the users are categorized into real-time (RT) and delay- tolerant (DT) services. We assign each wireless channel to a user who needs RT service. Inspired by the cognitive networks, we aim to assign the same channel to a second user who needs DT service, while minimizing the interference. Our objective is to simultaneously perform these assignments such that the SNR value of the worst user is maximized. This assignment significantly outperforms the separate assignment of the channels to RT users and then, to DT users. The resulting assignment problem turns out to be NP- hard. We propose a very simple, yet effective algorithm to solve this problem. In the second part of the paper, we will prove that the results of our suggested solution stay in a specific neighborhood of the optimal answer. In order to prove this fact, we statistically analyze the optimal solution, where we derive a general framework to express the statistical behavior of the optimal solution. Then we prove that both optimal solution and our solution achieve the same physical channel diversity.