2,096 research outputs found
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
MIMO Interference Alignment Over Correlated Channels with Imperfect CSI
Interference alignment (IA), given uncorrelated channel components and
perfect channel state information, obtains the maximum degrees of freedom in an
interference channel. Little is known, however, about how the sum rate of IA
behaves at finite transmit power, with imperfect channel state information, or
antenna correlation. This paper provides an approximate closed-form
signal-to-interference-plus-noise-ratio (SINR) expression for IA over
multiple-input-multiple-output (MIMO) channels with imperfect channel state
information and transmit antenna correlation. Assuming linear processing at the
transmitters and zero-forcing receivers, random matrix theory tools are
utilized to derive an approximation for the post-processing SINR distribution
of each stream for each user. Perfect channel knowledge and i.i.d. channel
coefficients constitute special cases. This SINR distribution not only allows
easy calculation of useful performance metrics like sum rate and symbol error
rate, but also permits a realistic comparison of IA with other transmission
techniques. More specifically, IA is compared with spatial multiplexing and
beamforming and it is shown that IA may not be optimal for some performance
criteria.Comment: 21 pages, 7 figures, submitted to IEEE Transactions on Signal
Processin
Joint Wireless Information and Energy Transfer with Reduced Feedback in MIMO Interference Channels
To determine the transmission strategy for joint wireless information and
energy transfer (JWIET) in the MIMO interference channel (IFC), the information
access point (IAP) and energy access point (EAP) require the channel state
information (CSI) of their associated links to both the information-decoding
(ID) mobile stations (MSs) and energy-harvesting (EH) MSs (so-called local
CSI). In this paper, to reduce th e feedback overhead of MSs for the JWIET in
two-user MIMO IFC, we propose a Geodesic energy beamforming scheme that
requires partial CSI at the EAP. Furthermore, in the two-user MIMO IFC, it is
proved that the Geodesic energy beamforming is the optimal strategy. By adding
a rank-one constraint on the transmit signal covariance of IAP, we can further
reduce the feedback overhead to IAP by exploiting Geodesic information
beamforming. Under the rank-one constraint of IAP's transmit signal, we prove
that Geodesic information/energy beamforming approach is the optimal strategy
for JWIET in the two-user MIMO IFC. We also discuss the extension of the
proposed rank-one Geodesic information/energy beamforming strategies to general
K-user MIMO IFC. Finally, by analyzing the achievable rate-energy performance
statistically under imperfect partial CSIT, we propose an adaptive bit
allocation strategy for both EH MS and ID MS.Comment: accepted to IEEE Journal of Selected Areas in Communications (IEEE
JSAC), Special Issue on Wireless Communications Powered by Energy Harvesting
and Wireless Energy Transfe
Downlink SDMA with Limited Feedback in Interference-Limited Wireless Networks
The tremendous capacity gains promised by space division multiple access
(SDMA) depend critically on the accuracy of the transmit channel state
information. In the broadcast channel, even without any network interference,
it is known that such gains collapse due to interstream interference if the
feedback is delayed or low rate. In this paper, we investigate SDMA in the
presence of interference from many other simultaneously active transmitters
distributed randomly over the network. In particular we consider zero-forcing
beamforming in a decentralized (ad hoc) network where each receiver provides
feedback to its respective transmitter. We derive closed-form expressions for
the outage probability, network throughput, transmission capacity, and average
achievable rate and go on to quantify the degradation in network performance
due to residual self-interference as a function of key system parameters. One
particular finding is that as in the classical broadcast channel, the per-user
feedback rate must increase linearly with the number of transmit antennas and
SINR (in dB) for the full multiplexing gains to be preserved with limited
feedback. We derive the throughput-maximizing number of streams, establishing
that single-stream transmission is optimal in most practically relevant
settings. In short, SDMA does not appear to be a prudent design choice for
interference-limited wireless networks.Comment: Submitted to IEEE Transactions on Wireless Communication
On the capacity of MIMO broadcast channels with partial side information
In multiple-antenna broadcast channels, unlike point-to-point multiple-antenna channels, the multiuser capacity depends heavily on whether the transmitter knows the channel coefficients to each user. For instance, in a Gaussian broadcast channel with M transmit antennas and n single-antenna users, the sum rate capacity scales like Mloglogn for large n if perfect channel state information (CSI) is available at the transmitter, yet only logarithmically with M if it is not. In systems with large n, obtaining full CSI from all users may not be feasible. Since lack of CSI does not lead to multiuser gains, it is therefore of interest to investigate transmission schemes that employ only partial CSI. We propose a scheme that constructs M random beams and that transmits information to the users with the highest signal-to-noise-plus-interference ratios (SINRs), which can be made available to the transmitter with very little feedback. For fixed M and n increasing, the throughput of our scheme scales as MloglognN, where N is the number of receive antennas of each user. This is precisely the same scaling obtained with perfect CSI using dirty paper coding. We furthermore show that a linear increase in throughput with M can be obtained provided that M does not not grow faster than logn. We also study the fairness of our scheduling in a heterogeneous network and show that, when M is large enough, the system becomes interference dominated and the probability of transmitting to any user converges to 1/n, irrespective of its path loss. In fact, using M=αlogn transmit antennas emerges as a desirable operating point, both in terms of providing linear scaling of the throughput with M as well as in guaranteeing fairness
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