284 research outputs found
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
Space Division Multiple Access with a Sum Feedback Rate Constraint
On a multi-antenna broadcast channel, simultaneous transmission to multiple
users by joint beamforming and scheduling is capable of achieving high
throughput, which grows double logarithmically with the number of users. The
sum rate for channel state information (CSI) feedback, however, increases
linearly with the number of users, reducing the effective uplink capacity. To
address this problem, a novel space division multiple access (SDMA) design is
proposed, where the sum feedback rate is upper-bounded by a constant. This
design consists of algorithms for CSI quantization, threshold based CSI
feedback, and joint beamforming and scheduling. The key feature of the proposed
approach is the use of feedback thresholds to select feedback users with large
channel gains and small CSI quantization errors such that the sum feedback rate
constraint is satisfied. Despite this constraint, the proposed SDMA design is
shown to achieve a sum capacity growth rate close to the optimal one. Moreover,
the feedback overflow probability for this design is found to decrease
exponentially with the difference between the allowable and the average sum
feedback rates. Numerical results show that the proposed SDMA design is capable
of attaining higher sum capacities than existing ones, even though the sum
feedback rate is bounded.Comment: 29 pages; submitted to IEEE Transactions 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
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
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