QoS-aware Selective Feedback and Optimal Channel Allocation in Multiple Shared Channel Environments

It is well known that opportunistic scheduling by using feedback information significantly improves wireless network performance. Most opportunistic scheduling works have focused on the case where a single channel is shared by multiple users. However, emerging wireless technologies (e.g., MIMO, OFDMA, etc.) are characterized by multiple shared channels, which complicates the problem. Moreover, it is necessary for the network to be able to provide various levels of quality of service (QoS). To address these issues, we develop a QoS-aware selective feedback model and a method to do optimal resource allocation. In our feedback model, each user chooses those channel sets that meet its QoS requirements by exploiting user diversity, thus resulting in a significant reduction in the amount of feedback information. Given the feedback channel sets for each user, the base station then distributes channels to each user with the objective of maximizing the number of accommodated users or the sum of users' utility values. We use a graph theoretic approach to solve these maximization problems by mapping them to clique searching problems. We develop some interesting theoretical results and properties but show that the complexity of this problem can be exponential in the number of channels. Thus, we also develop two suboptimal algorithms to handle the case when the number of shared channels is large. Finally, we demonstrate the efficacy of our results through an extensive numerical study