251 research outputs found
Cooperative Precoding with Limited Feedback for MIMO Interference Channels
Multi-antenna precoding effectively mitigates the interference in wireless
networks. However, the resultant performance gains can be significantly
compromised in practice if the precoder design fails to account for the
inaccuracy in the channel state information (CSI) feedback. This paper
addresses this issue by considering finite-rate CSI feedback from receivers to
their interfering transmitters in the two-user multiple-input-multiple-output
(MIMO) interference channel, called cooperative feedback, and proposing a
systematic method for designing transceivers comprising linear precoders and
equalizers. Specifically, each precoder/equalizer is decomposed into inner and
outer components for nulling the cross-link interference and achieving array
gain, respectively. The inner precoders/equalizers are further optimized to
suppress the residual interference resulting from finite-rate cooperative
feedback. Further- more, the residual interference is regulated by additional
scalar cooperative feedback signals that are designed to control transmission
power using different criteria including fixed interference margin and maximum
sum throughput. Finally, the required number of cooperative precoder feedback
bits is derived for limiting the throughput loss due to precoder quantization.Comment: 23 pages; 5 figures; this work was presented in part at Asilomar 2011
and will appear in IEEE Trans. on Wireless Com
Limited Feedback-based Block Diagonalization for the MIMO Broadcast Channel
Block diagonalization is a linear precoding technique for the multiple
antenna broadcast (downlink) channel that involves transmission of multiple
data streams to each receiver such that no multi-user interference is
experienced at any of the receivers. This low-complexity scheme operates only a
few dB away from capacity but requires very accurate channel knowledge at the
transmitter. We consider a limited feedback system where each receiver knows
its channel perfectly, but the transmitter is only provided with a finite
number of channel feedback bits from each receiver. Using a random quantization
argument, we quantify the throughput loss due to imperfect channel knowledge as
a function of the feedback level. The quality of channel knowledge must improve
proportional to the SNR in order to prevent interference-limitations, and we
show that scaling the number of feedback bits linearly with the system SNR is
sufficient to maintain a bounded rate loss. Finally, we compare our
quantization strategy to an analog feedback scheme and show the superiority of
quantized feedback.Comment: 20 pages, 4 figures, submitted to IEEE JSAC November 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
Multi-Cell Random Beamforming: Achievable Rate and Degrees of Freedom Region
Random beamforming (RBF) is a practically favourable transmission scheme for
multiuser multi-antenna downlink systems since it requires only partial channel
state information (CSI) at the transmitter. Under the conventional single-cell
setup, RBF is known to achieve the optimal sum-capacity scaling law as the
number of users goes to infinity, thanks to the multiuser diversity enabled
transmission scheduling that virtually eliminates the intra-cell interference.
In this paper, we extend the study of RBF to a more practical multi-cell
downlink system with single-antenna receivers subject to the additional
inter-cell interference (ICI). First, we consider the case of finite
signal-to-noise ratio (SNR) at each receiver. We derive a closed-form
expression of the achievable sum-rate with the multi-cell RBF, based upon which
we show an asymptotic sum-rate scaling law as the number of users goes to
infinity. Next, we consider the high-SNR regime and for tractable analysis
assume that the number of users in each cell scales in a certain order with the
per-cell SNR. Under this setup, we characterize the achievable degrees of
freedom (DoF) for the single-cell case with RBF. Then we extend the analysis to
the multi-cell RBF case by characterizing the DoF region. It is shown that the
DoF region characterization provides useful guideline on how to design a
cooperative multi-cell RBF system to achieve optimal throughput tradeoffs among
different cells. Furthermore, our results reveal that the multi-cell RBF scheme
achieves the "interference-free DoF" region upper bound for the multi-cell
system, provided that the per-cell number of users has a sufficiently large
scaling order with the SNR. Our result thus confirms the optimality of
multi-cell RBF in this regime even without the complete CSI at the transmitter,
as compared to other full-CSI requiring transmission schemes such as
interference alignment.Comment: 28 pages, 6 figures, to appear in IEEE Transactions of Signal
Processing. This work was presented in part at IEEE International Conference
on Acoustics, Speech, and Signal Processing (ICASSP), Kyoto, Japan, March
25-30, 2012. The authors are with the Department of Electrical and Computer
Engineering, National University of Singapore (emails: {hieudn, elezhang,
elehht}@nus.edu.sg
Performance of Orthogonal Beamforming for SDMA with Limited Feedback
On the multi-antenna broadcast channel, the spatial degrees of freedom
support simultaneous transmission to multiple users. The optimal multiuser
transmission, known as dirty paper coding, is not directly realizable.
Moreover, close-to-optimal solutions such as Tomlinson-Harashima precoding are
sensitive to CSI inaccuracy. This paper considers a more practical design
called per user unitary and rate control (PU2RC), which has been proposed for
emerging cellular standards. PU2RC supports multiuser simultaneous
transmission, enables limited feedback, and is capable of exploiting multiuser
diversity. Its key feature is an orthogonal beamforming (or precoding)
constraint, where each user selects a beamformer (or precoder) from a codebook
of multiple orthonormal bases. In this paper, the asymptotic throughput scaling
laws for PU2RC with a large user pool are derived for different regimes of the
signal-to-noise ratio (SNR). In the multiuser-interference-limited regime, the
throughput of PU2RC is shown to scale logarithmically with the number of users.
In the normal SNR and noise-limited regimes, the throughput is found to scale
double logarithmically with the number of users and also linearly with the
number of antennas at the base station. In addition, numerical results show
that PU2RC achieves higher throughput and is more robust against CSI
quantization errors than the popular alternative of zero-forcing beamforming if
the number of users is sufficiently large.Comment: 27 pages; to appear in IEEE Transactions on Vehicular Technolog
Antenna Combining for the MIMO Downlink Channel
A multiple antenna downlink channel where limited channel feedback is
available to the transmitter is considered. In a vector downlink channel
(single antenna at each receiver), the transmit antenna array can be used to
transmit separate data streams to multiple receivers only if the transmitter
has very accurate channel knowledge, i.e., if there is high-rate channel
feedback from each receiver. In this work it is shown that channel feedback
requirements can be significantly reduced if each receiver has a small number
of antennas and appropriately combines its antenna outputs. A combining method
that minimizes channel quantization error at each receiver, and thereby
minimizes multi-user interference, is proposed and analyzed. This technique is
shown to outperform traditional techniques such as maximum-ratio combining
because minimization of interference power is more critical than maximization
of signal power in the multiple antenna downlink. Analysis is provided to
quantify the feedback savings, and the technique is seen to work well with user
selection and is also robust to receiver estimation error.Comment: Submitted to IEEE Trans. Wireless Communications April 2007. Revised
August 200
Eigen-Based Transceivers for the MIMO Broadcast Channel with Semi-Orthogonal User Selection
This paper studies the sum rate performance of two low complexity
eigenmode-based transmission techniques for the MIMO broadcast channel,
employing greedy semi-orthogonal user selection (SUS). The first approach,
termed ZFDPC-SUS, is based on zero-forcing dirty paper coding; the second
approach, termed ZFBF-SUS, is based on zero-forcing beamforming. We first
employ new analytical methods to prove that as the number of users K grows
large, the ZFDPC-SUS approach can achieve the optimal sum rate scaling of the
MIMO broadcast channel. We also prove that the average sum rates of both
techniques converge to the average sum capacity of the MIMO broadcast channel
for large K. In addition to the asymptotic analysis, we investigate the sum
rates achieved by ZFDPC-SUS and ZFBF-SUS for finite K, and show that ZFDPC-SUS
has significant performance advantages. Our results also provide key insights
into the benefit of multiple receive antennas, and the effect of the SUS
algorithm. In particular, we show that whilst multiple receive antennas only
improves the asymptotic sum rate scaling via the second-order behavior of the
multi-user diversity gain; for finite K, the benefit can be very significant.
We also show the interesting result that the semi-orthogonality constraint
imposed by SUS, whilst facilitating a very low complexity user selection
procedure, asymptotically does not reduce the multi-user diversity gain in
either first (log K) or second-order (loglog K) terms.Comment: 35 pages, 3 figures, to appear in IEEE transactions on signal
processin
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