2,473 research outputs found
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
Robust Linear Precoder Design for Multi-cell Downlink Transmission
Coordinated information processing by the base stations of multi-cell
wireless networks enhances the overall quality of communication in the network.
Such coordinations for optimizing any desired network-wide quality of service
(QoS) necessitate the base stations to acquire and share some channel state
information (CSI). With perfect knowledge of channel states, the base stations
can adjust their transmissions for achieving a network-wise QoS optimality. In
practice, however, the CSI can be obtained only imperfectly. As a result, due
to the uncertainties involved, the network is not guaranteed to benefit from a
globally optimal QoS. Nevertheless, if the channel estimation perturbations are
confined within bounded regions, the QoS measure will also lie within a bounded
region. Therefore, by exploiting the notion of robustness in the worst-case
sense some worst-case QoS guarantees for the network can be asserted. We adopt
a popular model for noisy channel estimates that assumes that estimation noise
terms lie within known hyper-spheres. We aim to design linear transceivers that
optimize a worst-case QoS measure in downlink transmissions. In particular, we
focus on maximizing the worst-case weighted sum-rate of the network and the
minimum worst-case rate of the network. For obtaining such transceiver designs,
we offer several centralized (fully cooperative) and distributed (limited
cooperation) algorithms which entail different levels of complexity and
information exchange among the base stations.Comment: 38 Pages, 7 Figures, To appear in the IEEE Transactions on Signal
Processin
Dynamic Radio Cooperation for Downlink Cloud-RANs with Computing Resource Sharing
A novel dynamic radio-cooperation strategy is proposed for Cloud Radio Access
Networks (C-RANs) consisting of multiple Remote Radio Heads (RRHs) connected to
a central Virtual Base Station (VBS) pool. In particular, the key capabilities
of C-RANs in computing-resource sharing and real-time communication among the
VBSs are leveraged to design a joint dynamic radio clustering and cooperative
beamforming scheme that maximizes the downlink weighted sum-rate system utility
(WSRSU). Due to the combinatorial nature of the radio clustering process and
the non-convexity of the cooperative beamforming design, the underlying
optimization problem is NP-hard, and is extremely difficult to solve for a
large network. Our approach aims for a suboptimal solution by transforming the
original problem into a Mixed-Integer Second-Order Cone Program (MI-SOCP),
which can be solved efficiently using a proposed iterative algorithm. Numerical
simulation results show that our low-complexity algorithm provides
close-to-optimal performance in terms of WSRSU while significantly
outperforming conventional radio clustering and beamforming schemes.
Additionally, the results also demonstrate the significant improvement in
computing-resource utilization of C-RANs over traditional RANs with distributed
computing resources.Comment: 9 pages, 6 figures, accepted to IEEE MASS 201
Adaptive Bit Partitioning for Multicell Intercell Interference Nulling with Delayed Limited Feedback
Base station cooperation can exploit knowledge of the users' channel state
information (CSI) at the transmitters to manage co-channel interference. Users
have to feedback CSI of the desired and interfering channels using
finite-bandwidth backhaul links. Existing codebook designs for single-cell
limited feedback can be used for multicell cooperation by partitioning the
available feedback resources between the multiple channels. In this paper, a
new feedback-bit allocation strategy is proposed, as a function of the delays
in the communication links and received signal strengths in the downlink.
Channel temporal correlation is modeled as a function of delay using the
Gauss-Markov model. Closed-form expressions for bit partitions are derived to
allocate more bits to quantize the stronger channels with smaller delays and
fewer bits to weaker channels with larger delays, assuming random vector
quantization. Cellular network simulations are used to show that the proposed
algorithm yields higher sum-rates than an equal-bit allocation technique.Comment: Submitted to IEEE Transactions on Signal Processing, July 201
Cooperative Multi-Cell Block Diagonalization with Per-Base-Station Power Constraints
Block diagonalization (BD) is a practical linear precoding technique that
eliminates the inter-user interference in downlink multiuser multiple-input
multiple-output (MIMO) systems. In this paper, we apply BD to the downlink
transmission in a cooperative multi-cell MIMO system, where the signals from
different base stations (BSs) to all the mobile stations (MSs) are jointly
designed with the perfect knowledge of the downlink channels and transmit
messages. Specifically, we study the optimal BD precoder design to maximize the
weighted sum-rate of all the MSs subject to a set of per-BS power constraints.
This design problem is formulated in an auxiliary MIMO broadcast channel (BC)
with a set of transmit power constraints corresponding to those for individual
BSs in the multi-cell system. By applying convex optimization techniques, this
paper develops an efficient algorithm to solve this problem, and derives the
closed-form expression for the optimal BD precoding matrix. It is revealed that
the optimal BD precoding vectors for each MS in the per-BS power constraint
case are in general non-orthogonal, which differs from the conventional
orthogonal BD precoder design for the MIMO-BC under one single sum-power
constraint. Moreover, for the special case of single-antenna BSs and MSs, the
proposed solution reduces to the optimal zero-forcing beamforming (ZF-BF)
precoder design for the weighted sum-rate maximization in the multiple-input
single-output (MISO) BC with per-antenna power constraints. Suboptimal and
low-complexity BD/ZF-BF precoding schemes are also presented, and their
achievable rates are compared against those with the optimal schemes.Comment: accepted in JSAC, special issue on cooperative communications on
cellular networks, June 201
Outage Efficient Strategies for Network MIMO with Partial CSIT
We consider a multi-cell MIMO downlink (network MIMO) where base-stations
(BS) with antennas connected to a central station (CS) serve
single-antenna user terminals (UT). Although many works have shown the
potential benefits of network MIMO, the conclusion critically depends on the
underlying assumptions such as channel state information at transmitters (CSIT)
and backhaul links. In this paper, by focusing on the impact of partial CSIT,
we propose an outage-efficient strategy. Namely, with side information of all
UT's messages and local CSIT, each BS applies zero-forcing (ZF) beamforming in
a distributed manner. For a small number of UTs (), the ZF beamforming
creates parallel MISO channels. Based on the statistical knowledge of these
parallel channels, the CS performs a robust power allocation that
simultaneously minimizes the outage probability of all UTs and achieves a
diversity gain of per UT. With a large number of UTs (),
we propose a so-called distributed diversity scheduling (DDS) scheme to select
a subset of \Ks UTs with limited backhaul communication. It is proved that
DDS achieves a diversity gain of B\frac{K}{\Ks}(M-\Ks+1), which scales
optimally with the number of cooperative BSs as well as UTs. Numerical
results confirm that even under realistic assumptions such as partial CSIT and
limited backhaul communications, network MIMO can offer high data rates with a
sufficient reliability to individual UTs.Comment: 26 pages, 8 figures, submitted to IEEE Trans. on Signal Processin
- …