1,904 research outputs found
Multi-User Diversity vs. Accurate Channel State Information in MIMO Downlink Channels
In a multiple transmit antenna, single antenna per receiver downlink channel
with limited channel state feedback, we consider the following question: given
a constraint on the total system-wide feedback load, is it preferable to get
low-rate/coarse channel feedback from a large number of receivers or
high-rate/high-quality feedback from a smaller number of receivers? Acquiring
feedback from many receivers allows multi-user diversity to be exploited, while
high-rate feedback allows for very precise selection of beamforming directions.
We show that there is a strong preference for obtaining high-quality feedback,
and that obtaining near-perfect channel information from as many receivers as
possible provides a significantly larger sum rate than collecting a few
feedback bits from a large number of users.Comment: Submitted to IEEE Transactions on Communications, July 200
Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems with Multi-Antenna Users
In downlink multi-antenna systems with many users, the multiplexing gain is
strictly limited by the number of transmit antennas and the use of these
antennas. Assuming that the total number of receive antennas at the
multi-antenna users is much larger than , the maximal multiplexing gain can
be achieved with many different transmission/reception strategies. For example,
the excess number of receive antennas can be utilized to schedule users with
effective channels that are near-orthogonal, for multi-stream multiplexing to
users with well-conditioned channels, and/or to enable interference-aware
receive combining. In this paper, we try to answer the question if the data
streams should be divided among few users (many streams per user) or many users
(few streams per user, enabling receive combining). Analytic results are
derived to show how user selection, spatial correlation, heterogeneous user
conditions, and imperfect channel acquisition (quantization or estimation
errors) affect the performance when sending the maximal number of streams or
one stream per scheduled user---the two extremes in data stream allocation.
While contradicting observations on this topic have been reported in prior
works, we show that selecting many users and allocating one stream per user
(i.e., exploiting receive combining) is the best candidate under realistic
conditions. This is explained by the provably stronger resilience towards
spatial correlation and the larger benefit from multi-user diversity. This
fundamental result has positive implications for the design of downlink systems
as it reduces the hardware requirements at the user devices and simplifies the
throughput optimization.Comment: Published in IEEE Transactions on Signal Processing, 16 pages, 11
figures. The results can be reproduced using the following Matlab code:
https://github.com/emilbjornson/one-or-multiple-stream
Outage Efficient Strategies for Network MIMO with Partial CSIT
We consider a multi-cell MIMO downlink (network MIMO) where base-stations
(BS) with antennas connected to a central station (CS) serve
single-antenna user terminals (UT). Although many works have shown the
potential benefits of network MIMO, the conclusion critically depends on the
underlying assumptions such as channel state information at transmitters (CSIT)
and backhaul links. In this paper, by focusing on the impact of partial CSIT,
we propose an outage-efficient strategy. Namely, with side information of all
UT's messages and local CSIT, each BS applies zero-forcing (ZF) beamforming in
a distributed manner. For a small number of UTs (), the ZF beamforming
creates parallel MISO channels. Based on the statistical knowledge of these
parallel channels, the CS performs a robust power allocation that
simultaneously minimizes the outage probability of all UTs and achieves a
diversity gain of per UT. With a large number of UTs (),
we propose a so-called distributed diversity scheduling (DDS) scheme to select
a subset of \Ks UTs with limited backhaul communication. It is proved that
DDS achieves a diversity gain of B\frac{K}{\Ks}(M-\Ks+1), which scales
optimally with the number of cooperative BSs as well as UTs. Numerical
results confirm that even under realistic assumptions such as partial CSIT and
limited backhaul communications, network MIMO can offer high data rates with a
sufficient reliability to individual UTs.Comment: 26 pages, 8 figures, submitted to IEEE Trans. on Signal Processin
Compressive Sensing for Feedback Reduction in MIMO Broadcast Channels
We propose a generalized feedback model and compressive sensing based
opportunistic feedback schemes for feedback resource reduction in MIMO
Broadcast Channels under the assumption that both uplink and downlink channels
undergo block Rayleigh fading. Feedback resources are shared and are
opportunistically accessed by users who are strong, i.e. users whose channel
quality information is above a certain fixed threshold. Strong users send same
feedback information on all shared channels. They are identified by the base
station via compressive sensing. Both analog and digital feedbacks are
considered. The proposed analog & digital opportunistic feedback schemes are
shown to achieve the same sum-rate throughput as that achieved by dedicated
feedback schemes, but with feedback channels growing only logarithmically with
number of users. Moreover, there is also a reduction in the feedback load. In
the analog feedback case, we show that the propose scheme reduces the feedback
noise which eventually results in better throughput, whereas in the digital
feedback case the proposed scheme in a noisy scenario achieves almost the
throughput obtained in a noiseless dedicated feedback scenario. We also show
that for a fixed given budget of feedback bits, there exist a trade-off between
the number of shared channels and thresholds accuracy of the feedback SINR.Comment: Submitted to IEEE Transactions on Wireless Communications, April 200
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