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The demand for mobile video is increasing every year. To address the strain on long term evolution (LTE) networks 3GPP introduced multimedia broadcast multicast operation (MBMS). As of LTE release 12, support for MBMS operation on-demand (MooD) was also added (MooD enables dynamic resource configuration of multicast flows). While multicast algorithms assuage the demands on the network, quality-of-service performance metrics no longer are considered an accurate measure of a user's satisfaction with the network; recent multimedia studies show that quality-of-experience (QoE) is more accurate. In order to maximize the QoE of all users in a LTE MooD system, we propose two resource allocation algorithms, both of which efficiently allocate resource blocks (RBs) based on both the demand for each live video stream and the channel conditions of the users within each group. We also compare our resource allocation algorithms against four other commonly used resource allocation algorithms. Both of our algorithms achieve a higher QoE and video quality, when compared to other commonly used resource allocation algorithms. Furthermore, our algorithms demonstrate efficient resource allocation regardless of whether or not the RBs are sufficient.