348 research outputs found
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
Performance Analysis of Heterogeneous Feedback Design in an OFDMA Downlink with Partial and Imperfect Feedback
Current OFDMA systems group resource blocks into subband to form the basic
feedback unit. Homogeneous feedback design with a common subband size is not
aware of the heterogeneous channel statistics among users. Under a general
correlated channel model, we demonstrate the gain of matching the subband size
to the underlying channel statistics motivating heterogeneous feedback design
with different subband sizes and feedback resources across clusters of users.
Employing the best-M partial feedback strategy, users with smaller subband size
would convey more partial feedback to match the frequency selectivity. In order
to develop an analytical framework to investigate the impact of partial
feedback and potential imperfections, we leverage the multi-cluster subband
fading model. The perfect feedback scenario is thoroughly analyzed, and the
closed form expression for the average sum rate is derived for the
heterogeneous partial feedback system. We proceed to examine the effect of
imperfections due to channel estimation error and feedback delay, which leads
to additional consideration of system outage. Two transmission strategies: the
fix rate and the variable rate, are considered for the outage analysis. We also
investigate how to adapt to the imperfections in order to maximize the average
goodput under heterogeneous partial feedback.Comment: To appear in IEEE Trans. on Signal Processin
Wireless Cellular Networks
When aiming for achieving high spectral efficiency in wireless cellular networks, cochannel interference (CCI) becomes the dominant performancelimiting factor. This article provides a survey of CCI mitigation techniques, where both active and passive approaches are discussed in the context of both open- and closed-loop designs.More explicitly, we considered both the family of flexible frequency-reuse (FFR)-aided and dynamic channel allocation (DCA)-aided interference avoidance techniques as well as smart antenna-aided interference mitigation techniques, which may be classified as active approach
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
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