A graph-based resource allocation algorithm for downlink MIMO-OFDMA networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Adaptive resource allocation in multiuser OFDM systems with proportional rate constraints
IEEE Transactions on Wireless Communications
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IEEE Transactions on Wireless Communications
Capacity Maximization for Zero-Forcing MIMO-OFDMA Downlink Systems with Multiuser Diversity
IEEE Transactions on Wireless Communications
Channel Allocation for UMTS Multimedia Broadcasting and Multicasting
IEEE Transactions on Wireless Communications - Part 1
Transmit power adaptation for multiuser OFDM systems
IEEE Journal on Selected Areas in Communications
Ergodic Sum Rate Maximization for Underlay Spectrum Sharing with Heterogeneous Traffic
Wireless Personal Communications: An International Journal
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This paper investigates the problem of resource allocation in a multiple-input multiple-output (MIMO) OFDM-based system, wherein multiple multicast groups exist. Multicasting is a transmission technique which enables a transmitter to communicate via a single wireless link with multiple receivers simultaneously. Moreover, the presence of multiple antennas in both transmitter and receiver enhances significantly the system spectral efficiency. MIMO technology along with multicasting offers major advantages to wireless systems. However, optimum exploitation of these technologies adds significant complexity to the system which makes very difficult any possible practical implementation. Another important issue of such systems is their capacity to ensure to all users a certain level of QoS. To that end, we propose a low complexity fair resource allocation algorithm aiming at ensuring a certain amount of resources to all users when multicasting is applied. Validation of the proposed solution is achieved through extensive simulation and it is compared to other multicast schemes for MIMO systems which exist in literature. Numerical results and complexity analysis show the feasibility of the proposed algorithm.