394 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
Sum Rates, Rate Allocation, and User Scheduling for Multi-User MIMO Vector Perturbation Precoding
This paper considers the multiuser multiple-input multiple-output (MIMO)
broadcast channel. We consider the case where the multiple transmit antennas
are used to deliver independent data streams to multiple users via vector
perturbation. We derive expressions for the sum rate in terms of the average
energy of the precoded vector, and use this to derive a high signal-to-noise
ratio (SNR) closed-form upper bound, which we show to be tight via simulation.
We also propose a modification to vector perturbation where different rates can
be allocated to different users. We conclude that for vector perturbation
precoding most of the sum rate gains can be achieved by reducing the rate
allocation problem to the user selection problem. We then propose a
low-complexity user selection algorithm that attempts to maximize the high-SNR
sum rate upper bound. Simulations show that the algorithm outperforms other
user selection algorithms of similar complexity.Comment: 27 pages with 6 figures and 2 tables. Accepted for publication in
IEEE Trans. Wireless Comm
Linear Precoding in Cooperative MIMO Cellular Networks with Limited Coordination Clusters
In a cooperative multiple-antenna downlink cellular network, maximization of
a concave function of user rates is considered. A new linear precoding
technique called soft interference nulling (SIN) is proposed, which performs at
least as well as zero-forcing (ZF) beamforming. All base stations share channel
state information, but each user's message is only routed to those that
participate in the user's coordination cluster. SIN precoding is particularly
useful when clusters of limited sizes overlap in the network, in which case
traditional techniques such as dirty paper coding or ZF do not directly apply.
The SIN precoder is computed by solving a sequence of convex optimization
problems. SIN under partial network coordination can outperform ZF under full
network coordination at moderate SNRs. Under overlapping coordination clusters,
SIN precoding achieves considerably higher throughput compared to myopic ZF,
especially when the clusters are large.Comment: 13 pages, 5 figure
On the Throughput of Large-but-Finite MIMO Networks using Schedulers
This paper studies the sum throughput of the {multi-user}
multiple-input-single-output (MISO) networks in the cases with large but finite
number of transmit antennas and users. Considering continuous and bursty
communication scenarios with different users' data request probabilities, we
derive quasi-closed-form expressions for the maximum achievable throughput of
the networks using optimal schedulers. The results are obtained in various
cases with different levels of interference cancellation. Also, we develop an
efficient scheduling scheme using genetic algorithms (GAs), and evaluate the
effect of different parameters, such as channel/precoding models, number of
antennas/users, scheduling costs and power amplifiers' efficiency, on the
system performance. Finally, we use the recent results on the achievable rates
of finite block-length codes to analyze the system performance in the cases
with short packets. As demonstrated, the proposed GA-based scheduler reaches
(almost) the same throughput as in the exhaustive search-based optimal
scheduler, with substantially less implementation complexity. Moreover, the
power amplifiers' inefficiency and the scheduling delay affect the performance
of the scheduling-based systems significantly
Low-complexity user selection for rate maximization in MIMO broadcast channels with downlink beamforming
We present in this work a low-complexity algorithm to solve the sum rate maximization problem in multiuser MIMO broadcast
channels with downlink beamforming. Our approach decouples the user selection problem from the resource allocation problem
and its main goal is to create a set of quasiorthogonal users. The proposed algorithm exploits physical metrics of the wireless
channels that can be easily computed in such a way that a null space projection power can be approximated efficiently. Based on the
derived metrics we present a mathematical model that describes the dynamics of the user selection process which renders the user
selection problem into an integer linear program. Numerical results show that our approach is highly efficient to form groups of
quasiorthogonal users when compared to previously proposed algorithms in the literature. Our user selection algorithm achieves
a large portion of the optimum user selection sum rate (90%) for a moderate number of active users
User Selection and Precoding Techniques for Rate Maximization in Broadcast MISO Systems
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