1,056 research outputs found
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
Bit Allocation Law for Multi-Antenna Channel Feedback Quantization: Single-User Case
This paper studies the design and optimization of a limited feedback
single-user system with multiple-antenna transmitter and single-antenna
receiver. The design problem is cast in form of the minimizing the average
transmission power at the base station subject to the user's outage probability
constraint. The optimization is over the user's channel quantization codebook
and the transmission power control function at the base station. Our approach
is based on fixing the outage scenarios in advance and transforming the design
problem into a robust system design problem. We start by showing that uniformly
quantizing the channel magnitude in dB scale is asymptotically optimal,
regardless of the magnitude distribution function. We derive the optimal
uniform (in dB) channel magnitude codebook and combine it with a spatially
uniform channel direction codebook to arrive at a product channel quantization
codebook. We then optimize such a product structure in the asymptotic regime of
, where is the total number of quantization feedback
bits. The paper shows that for channels in the real space, the asymptotically
optimal number of direction quantization bits should be times
the number of magnitude quantization bits, where is the number of base
station antennas. We also show that the performance of the designed system
approaches the performance of the perfect channel state information system as
. For complex channels, the number of magnitude and
direction quantization bits are related by a factor of and the system
performance scales as as .Comment: Submitted to IEEE Transactions on Signal Processing, March 201
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
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
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