Linear least squares computations
Linear least squares computations
Dynamic slot allocation (DSA) in indoor SDMA/TDMA using smart antenna basestation
IEEE/ACM Transactions on Networking (TON)
Smart Antennas for Wireless Communications
Smart Antennas for Wireless Communications
Fundamentals of WiMAX: Understanding Broadband Wireless Networking (Prentice Hall Communications Engineering and Emerging Technologies Series)
MIMO Wireless Communications: From Real-World Propagation to Space-Time Code Design
MIMO Wireless Communications: From Real-World Propagation to Space-Time Code Design
Computer Networks: The International Journal of Computer and Telecommunications Networking
Advances in Mobile and Wireless Communications: Views of the 16th IST Mobile and Wireless Communication Summit
A joint utility scheduler and SDMA resource allocation for mobile WiMAX networks
ISWPC'10 Proceedings of the 5th IEEE international conference on Wireless pervasive computing
Achievable rates for Tomlinson-Harashima precoding
IEEE Transactions on Information Theory
Writing on dirty paper (Corresp.)
IEEE Transactions on Information Theory
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming
IEEE Journal on Selected Areas in Communications
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Future wireless networks need to address the predicted growth in mobile traffic volume, expected to have an explosive growth in the next 5years mainly driven by video and web applications. Transmission schemes based on Orthogonal Frequency Division Multiple Access (OFDMA) combined with Space Division Multiple Access (SDMA) techniques are key promising technologies to increase current spectral efficiencies. A Joint SDMA-OFDMA system has to allocate resources in time, frequency and space dimensions to different mobile stations, resulting in a highly complex resource allocation problem. In contrast to related work approaches, in this paper we take a comprehensive view at the complete SDMA-OFDMA scheduling challenge and propose a SDMA-OFDMA Greedy Scheduling Algorithm (sGSA) for WiMAX systems. The proposed solution considers feasibility constraints in order to allocate resources for multiple mobile stations on a per packet basis by using (i) a low complexity SINR prediction algorithm, (ii) a cluster-based SDMA grouping algorithm and (iii) a computationally efficient frame layout scheme which allocates multiple SDMA groups per frame according to their packet QoS utility. A performance evaluation of the proposed sGSA solution as compared to state of the art solutions is provided, based on a comprehensive WiMAX simulation tool.