Abstract
Multiuser MIMO (multiple-input multiple-output) communication techniques (MU-MIMO) use spatial sharing by means of joint optimization of antenna by a user. Specifically, the resulting multiuser interference is handled by the multiple antennas which also give the degrees of freedom required for spatial separation of the users. MU-MIMO has advantages over their single counterparts due to several reasons. For one, they permit for a direct gain in multiple access capacity thanks to multiuser multiplexing schemes. Another is that they appear more tolerant to most of propagation limitations plaguing their single counterparts such as antenna correlation or channel rank. In addition, they permit the spatial multiplexing gain at the base station to be obtained without the need for multiple antenna terminals, which allow the development of small and cheap terminals. However, the catch is that MU-MIMO requires channel state information at transmitter to properly serve the spatially multiplexed user, which only places a burden on uplink capacity in most systems. Such limitations are mitigated by other MU-MIMO strategies, such as linear minimum mean square error techniques and non-linear approaches. Nevertheless, MU-MIMO networks bring robustness with respect to multipath richness, which allow for compact antenna spacing at the base station and yield the diversity and multiplexing gains without the need for multiple antenna user terminals. They can also cope with very coarse channel information.
Original language | English |
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Pages (from-to) | 36-46 |
Number of pages | 11 |
Journal | IEEE Signal Processing Magazine |
Volume | 24 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2007 Sept |
Bibliographical note
Funding Information:degree at ENST—Eurecom Institute, France, funded by France Telecom R&D. During the summer of 2004, he interned with Samsung Advanced Institute of Technology, Korea, developing MU-MIMO precoding and scheduling techniques for 3GPP, and IEEE 802.16e systems. His research interests include precoding and resource allocation for multiuser MIMO systems and cross-layer design for wireless networks. He is a Student Member of the IEEE.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Electrical and Electronic Engineering
- Applied Mathematics