15 research outputs found
Optimality Properties, Distributed Strategies, and Measurement-Based Evaluation of Coordinated Multicell OFDMA Transmission
The throughput of multicell systems is inherently limited by interference and
the available communication resources. Coordinated resource allocation is the
key to efficient performance, but the demand on backhaul signaling and
computational resources grows rapidly with number of cells, terminals, and
subcarriers. To handle this, we propose a novel multicell framework with
dynamic cooperation clusters where each terminal is jointly served by a small
set of base stations. Each base station coordinates interference to neighboring
terminals only, thus limiting backhaul signalling and making the framework
scalable. This framework can describe anything from interference channels to
ideal joint multicell transmission.
The resource allocation (i.e., precoding and scheduling) is formulated as an
optimization problem (P1) with performance described by arbitrary monotonic
functions of the signal-to-interference-and-noise ratios (SINRs) and arbitrary
linear power constraints. Although (P1) is non-convex and difficult to solve
optimally, we are able to prove: 1) Optimality of single-stream beamforming; 2)
Conditions for full power usage; and 3) A precoding parametrization based on a
few parameters between zero and one. These optimality properties are used to
propose low-complexity strategies: both a centralized scheme and a distributed
version that only requires local channel knowledge and processing. We evaluate
the performance on measured multicell channels and observe that the proposed
strategies achieve close-to-optimal performance among centralized and
distributed solutions, respectively. In addition, we show that multicell
interference coordination can give substantial improvements in sum performance,
but that joint transmission is very sensitive to synchronization errors and
that some terminals can experience performance degradations.Comment: Published in IEEE Transactions on Signal Processing, 15 pages, 7
figures. This version corrects typos related to Eq. (4) and Eq. (28
Massive MIMO and Small Cells: Improving Energy Efficiency by Optimal Soft-Cell Coordination
To improve the cellular energy efficiency, without sacrificing
quality-of-service (QoS) at the users, the network topology must be densified
to enable higher spatial reuse. We analyze a combination of two densification
approaches, namely "massive" multiple-input multiple-output (MIMO) base
stations and small-cell access points. If the latter are operator-deployed, a
spatial soft-cell approach can be taken where the multiple transmitters serve
the users by joint non-coherent multiflow beamforming. We minimize the total
power consumption (both dynamic emitted power and static hardware power) while
satisfying QoS constraints. This problem is proved to have a hidden convexity
that enables efficient solution algorithms. Interestingly, the optimal solution
promotes exclusive assignment of users to transmitters. Furthermore, we provide
promising simulation results showing how the total power consumption can be
greatly improved by combining massive MIMO and small cells; this is possible
with both optimal and low-complexity beamforming.Comment: Published at International Conference on Telecommunications (ICT
2013), 6-8 May 2013, Casablanca, Morocco, 5 pages, 4 figures, 2 tables. This
version includes the Matlab code necessary to reproduce the simulations; see
the ancillary files. This version also corrects errors in Table 1 and in the
simulations, which affected Figs. 3-
Coordination and Antenna Domain Formation in Cloud-RAN systems
We study here the problem of Antenna Domain Formation (ADF) in cloud RAN
systems, whereby multiple remote radio-heads (RRHs) are each to be assigned to
a set of antenna domains (ADs), such that the total interference between the
ADs is minimized. We formulate the corresponding optimization problem, by
introducing the concept of \emph{interference coupling coefficients} among
pairs of radio-heads. We then propose a low-overhead algorithm that allows the
problem to be solved in a distributed fashion, among the aggregation nodes
(ANs), and establish basic convergence results. Moreover, we also propose a
simple relaxation to the problem, thus enabling us to characterize its maximum
performance. We follow a layered coordination structure: after the ADs are
formed, radio-heads are clustered to perform coordinated beamforming using the
well known Weighted-MMSE algorithm. Finally, our simulations show that using
the proposed ADF mechanism would significantly increase the sum-rate of the
system (with respect to random assignment of radio-heads).Comment: 7 pages, IEEE International Conference on Communications 2016 (ICC
2016
A New Look at Cell-Free Massive MIMO: Making It Practical With Dynamic Cooperation
This paper takes a new look at Cell-free Massive MIMO (multiple-input
multiple-output) through the lens of the dynamic cooperation cluster framework
from the Network MIMO literature. The purpose is to identify and address
scalability issues that appear in prior work. We provide distributed algorithms
for initial access, pilot assignment, cluster formation, precoding, and
combining that are scalable in the sense of being implementable with
arbitrarily many users. Interestingly, the suggested precoding and combining
outperform conjugate beamforming and matched filtering, respectively, while
also being fully distributed.Comment: To appear at the 2019 IEEE International Symposium on Personal,
Indoor and Mobile Radio Communications (IEEE PIMRC 2019), 6 pages, 5 figure
Pareto Characterization of the Multicell MIMO Performance Region With Simple Receivers
We study the performance region of a general multicell downlink scenario with
multiantenna transmitters, hardware impairments, and low-complexity receivers
that treat interference as noise. The Pareto boundary of this region describes
all efficient resource allocations, but is generally hard to compute. We
propose a novel explicit characterization that gives Pareto optimal transmit
strategies using a set of positive parameters---fewer than in prior work. We
also propose an implicit characterization that requires even fewer parameters
and guarantees to find the Pareto boundary for every choice of parameters, but
at the expense of solving quasi-convex optimization problems. The merits of the
two characterizations are illustrated for interference channels and ideal
network multiple-input multiple-output (MIMO).Comment: Published in IEEE Transactions on Signal Processing, 6 pages, 6
figure
Multicell Coordinated Beamforming with Rate Outage Constraint--Part I: Complexity Analysis
This paper studies the coordinated beamforming (CoBF) design in the
multiple-input single-output interference channel, assuming only channel
distribution information given a priori at the transmitters. The CoBF design is
formulated as an optimization problem that maximizes a predefined system
utility, e.g., the weighted sum rate or the weighted max-min-fairness (MMF)
rate, subject to constraints on the individual probability of rate outage and
power budget. While the problem is non-convex and appears difficult to handle
due to the intricate outage probability constraints, so far it is still unknown
if this outage constrained problem is computationally tractable. To answer
this, we conduct computational complexity analysis of the outage constrained
CoBF problem. Specifically, we show that the outage constrained CoBF problem
with the weighted sum rate utility is intrinsically difficult, i.e., NP-hard.
Moreover, the outage constrained CoBF problem with the weighted MMF rate
utility is also NP-hard except the case when all the transmitters are equipped
with single antenna. The presented analysis results confirm that efficient
approximation methods are indispensable to the outage constrained CoBF problem.Comment: submitted to IEEE Transactions on Signal Processin