284 research outputs found
Semi-orthogonal user selection for MISO systems with quantized feedback
2008 International ITG Workshop on Smart Antennas, WSA 2008; Darmstadt; Germany; 26 February 2008 through 27 February 2008For MISO multi-user downlink wireless communication system with precoding at the transmission, the channel state information at the transmitter can provide tremendous capacity gains. However, the amount of feedback data increases with the number of users in the cell and the number of transmit antennas. In this paper, we study on different algorithms and criteria in order to significantly reduce the amount of feedback data. We associate the classical norm criterion with a criterion based on the orthogonality between the user channels. Without cooperation between the users, we only allow users that are semi-orthogonal to feedback their channel information (CQI and CDI) to the base station. The feedback CDI is quantized using a local grassmanian packing. We show that the proposed combined criterion with a finite feedback rate gives better performance compared to the norm criterion. Furthermore we show that the performance is not affected by CQI quantization
Feedback Allocation For OFDMA Systems With Slow Frequency-domain Scheduling
We study the problem of allocating limited feedback resources across multiple
users in an orthogonal-frequency-division-multiple-access downlink system with
slow frequency-domain scheduling. Many flavors of slow frequency-domain
scheduling (e.g., persistent scheduling, semi-persistent scheduling), that
adapt user-sub-band assignments on a slower time-scale, are being considered in
standards such as 3GPP Long-Term Evolution. In this paper, we develop a
feedback allocation algorithm that operates in conjunction with any arbitrary
slow frequency-domain scheduler with the goal of improving the throughput of
the system. Given a user-sub-band assignment chosen by the scheduler, the
feedback allocation algorithm involves solving a weighted sum-rate maximization
at each (slow) scheduling instant. We first develop an optimal
dynamic-programming-based algorithm to solve the feedback allocation problem
with pseudo-polynomial complexity in the number of users and in the total
feedback bit budget. We then propose two approximation algorithms with
complexity further reduced, for scenarios where the problem exhibits additional
structure.Comment: Accepted to IEEE Transactions on Signal Processin
Reduced Feedback Designs for SDMA-OFDMA Systems
IEEE International Conference on Communications, ICC 2009; Dresden; Germany; 14 June 2009 through 18 June 2009In SDMA-OFDMA wireless communication systems, the feedback load increases with the number of users, subcarriers and antennas in the cell. In this paper, we propose two efficient reduced feedback algorithms by selecting the clusters at the user side. For each cluster, we select the users according to their norm and their orthogonality. We evaluate the performance of the user selection algorithms considering the quantization effect. We also design a specific codebook design to quantize CSI for the proposed criterion
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
Improved Rate-Energy Trade-off For SWIPT Using Chordal Distance Decomposition In Interference Alignment Networks
This paper investigates the simultaneous wireless information and power
transfer (SWIPT) precoding scheme for K-user multiple-input-multiple-output
(MIMO) interference channels (IC), for which interference alignment (IA)
schemes provide optimal precoders to achieve full degrees-of-freedom (DoF)
gain. However, harvesting RF energy simultaneously reduces the achievable DoFs.
To study a trade-off between harvested energy and sum rate, the transceiver
design problem is suboptimally formulated in literature via convex relaxations,
which is still computationally intensive, especially for battery limited nodes
running on harvested energy. In this paper, we propose a systematic method
using chordal distance (CD) decomposition to obtain the balanced precoding,
which improves the trade-off. Analysis shows that given the nonnegative value
of CD, the achieved harvested energy for the proposed precoder is higher than
that for perfect IA precoder. Moreover, energy constraints can be achieved,
while maintaining a constant rate loss without losing DoFs via tuning the CD
value and splitting factor. Simulation results verify the analysis and add that
the IA schemes based on max-SINR or mean-squared error are better suited for
SWIPT maximization than subspace or leakage minimization methods
Limited Feedback Design for Interference Alignment on MIMO Interference Networks with Heterogeneous Path Loss and Spatial Correlations
Interference alignment is degree of freedom optimal in K -user MIMO
interference channels and many previous works have studied the transceiver
designs. However, these works predominantly focus on networks with perfect
channel state information at the transmitters and symmetrical interference
topology. In this paper, we consider a limited feedback system with
heterogeneous path loss and spatial correlations, and investigate how the
dynamics of the interference topology can be exploited to improve the feedback
efficiency. We propose a novel spatial codebook design, and perform dynamic
quantization via bit allocations to adapt to the asymmetry of the interference
topology. We bound the system throughput under the proposed dynamic scheme in
terms of the transmit SNR, feedback bits and the interference topology
parameters. It is shown that when the number of feedback bits scales with SNR
as C_{s}\cdot\log\textrm{SNR}, the sum degrees of freedom of the network are
preserved. Moreover, the value of scaling coefficient C_{s} can be
significantly reduced in networks with asymmetric interference topology.Comment: 30 pages, 6 figures, accepted by IEEE transactions on signal
processing in Feb. 201
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