On the opportunistic multicasting in OFDM-based cellular networks

In this paper, we investigate the performance of opportunistic scheduling for delivering multicast information in an OFDM-based cellular network. The problem is formulated as a system throughput maximization problem subject to the fairness constraints derived from each user's specific minimum QoS requirement. As a solution we design an opportunistic scheduling algorithm based on a priority metric that follows an exponential rule. The metric takes into account the current channel state information to take advantage of the better channel states observed by different subsets of the multicast users at different time slots and sub-bands in order to increase the system throughput. The metric also explicitly includes a term to compensate the deviations observed by individual users from their QoS targets. Hence, our proposed algorithm jointly considers two issues in multicasting: throughput maximization and fairness in terms of the targeted QoS levels. In the paper, we further investigate the impact of feedback frequency on the system performance. For scenarios where feedback is not available for every time slot, a probabilistic scheduling algorithm is proposed based on a finite state Markov channel (FSMC) that models the underlying fading channel. Our simulation results show that our algorithm can achieve significantly better performance compared to other commonly used algorithms. Moreover, the solution can also achieve graceful performance degradation when CSI feedback is not available at every time slot.