Linear processing and sum throughput in the multiuser MIMO downlink?
IEEE Transactions on Wireless Communications
Low complexity general antenna selection algorithm for MU-MIMO-BC systems
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
A joint TX-RX user scheduling scheme for multiuser MIMO systems
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Eigenmode transmission for the MIMO broadcast channel with semi-orthogonal user selection
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Probabilistic voting-theoretic strategies for resource allocation in heterogenous wireless networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Channel norm-based user scheduler in coordinated multi-point systems
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Fair user selection for zero-forcing precoding in multi-user MISO systems
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Weighted sum rate maximization in the MIMO MAC with linear transceivers: algorithmic solutions
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Eigen-based transceivers for the MIMO broadcast channel with semi-orthogonal user selection
IEEE Transactions on Signal Processing
Efficient weighted sum rate maximization with linear precoding
IEEE Transactions on Signal Processing
Power Control and Allocation for MIMO Broadcast Channels in Cognitive Radio Networks
Wireless Personal Communications: An International Journal
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In this paper, we propose a generalized greedy (G-greedy) algorithm based on zero-forcing beamforming (ZFBF) for the multiple-input multiple-output (MIMO) broadcast channel. This algorithm serves as a general mathematical framework that includes a number of existing greedy user selection methods as its realizations. As previous results only give the scaling law of the sum rate of dirty paper coding (DPC), with the help of the G-greedy structure, we are able to obtain the exact limit of the DPC sum rate for a large number of users. We also prove that the difference between the sum rates obtained by G-greedy user selection and by DPC goes to zero as the number of users increases. In addition to this, we investigate one particular greedy user selection scheme called sequential water-filling (SWF). For this algorithm, a complexity reduction is achieved by an iterative procedure based on an LQ decomposition, which converts the calculation of the Moore-Penrose matrix inverse to one vector-matrix multiplication. A sufficient condition is given to prune the search space of this algorithm that results in further complexity reduction. With the help of the G-greedy algorithm, we prove that SWF achieves the full DPC sum rate for a large number of users. For a moderate number of users, simulation demonstrates that, compared with other user selection algorithms, SWF achieves a higher sum rate that is close to the maximal sum rate achievable by ZFBF with the same order of complexity.