Opportunistic feedback for multiuser MIMO systems with linear receivers
- Authors
- Tang, Taiwen; Heath, Robert W., Jr.; Cho, Sunghyun; Yun, Sangboh
- Issue Date
- May-2007
- Publisher
- IEEE
- Keywords
- Diversity methods; Feedback; Multiple-input multiple-output (MIMO) systems; Multiuser channels; Scheduling
- Citation
- IEEE TRANSACTIONS ON COMMUNICATIONS, v.55, no.5, pp.1020 - 1032
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON COMMUNICATIONS
- Volume
- 55
- Number
- 5
- Start Page
- 1020
- End Page
- 1032
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/43751
- DOI
- 10.1109/TCOMM.2007.896013
- ISSN
- 0090-6778
- Abstract
- A novel multiuser scheduling and feedback strategy for the multiple-input multiple-output (MIMO) downlink is proposed in this paper. It achieves multiuser diversity gain without substantial feedback requirements. The proposed strategy uses per-antenna scheduling at the base station, which maps each transmit antenna at the base station (equivalently, a spatial channel) to a user. Each user has a number of receive antennas that is greater than or equal to the number of transmit antennas at the base station. Zero-forcing receivers are deployed by each user to decode the transmitted data streams. In this system, the base station requires users' channel quality on each spatial channel for scheduling. An opportunistic feedback protocol is proposed to reduce the feedback requirements. The proposed protocol uses a contention channel that consists of a fixed number of feedback minislots to convey channel state information. Feedback control parameters including the channel quality threshold and the random access feedback probability are jointly adjusted to maximize the average throughput performance. of this system. Multiple receive antennas at the base station are used on the feedback channel to allow decoding multiple feedback messages sent simultaneously by different users. This further reduces the bandwidth of the feedback channel. Iterative search algorithms are proposed to solve the optimization for selection of these parameters under both scenarios that the cumulative distribution functions of users are known or unknown to the base station.
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