35 research outputs found
The role of asymptotic functions in network optimization and feasibility studies
Solutions to network optimization problems have greatly benefited from
developments in nonlinear analysis, and, in particular, from developments in
convex optimization. A key concept that has made convex and nonconvex analysis
an important tool in science and engineering is the notion of asymptotic
function, which is often hidden in many influential studies on nonlinear
analysis and related fields. Therefore, we can also expect that asymptotic
functions are deeply connected to many results in the wireless domain, even
though they are rarely mentioned in the wireless literature. In this study, we
show connections of this type. By doing so, we explain many properties of
centralized and distributed solutions to wireless resource allocation problems
within a unified framework, and we also generalize and unify existing
approaches to feasibility analysis of network designs. In particular, we show
sufficient and necessary conditions for mappings widely used in wireless
communication problems (more precisely, the class of standard interference
mappings) to have a fixed point. Furthermore, we derive fundamental bounds on
the utility and the energy efficiency that can be achieved by solving a large
family of max-min utility optimization problems in wireless networks.Comment: GlobalSIP 2017 (to appear
Joint Beamforming and Power Control in Coordinated Multicell: Max-Min Duality, Effective Network and Large System Transition
This paper studies joint beamforming and power control in a coordinated
multicell downlink system that serves multiple users per cell to maximize the
minimum weighted signal-to-interference-plus-noise ratio. The optimal solution
and distributed algorithm with geometrically fast convergence rate are derived
by employing the nonlinear Perron-Frobenius theory and the multicell network
duality. The iterative algorithm, though operating in a distributed manner,
still requires instantaneous power update within the coordinated cluster
through the backhaul. The backhaul information exchange and message passing may
become prohibitive with increasing number of transmit antennas and increasing
number of users. In order to derive asymptotically optimal solution, random
matrix theory is leveraged to design a distributed algorithm that only requires
statistical information. The advantage of our approach is that there is no
instantaneous power update through backhaul. Moreover, by using nonlinear
Perron-Frobenius theory and random matrix theory, an effective primal network
and an effective dual network are proposed to characterize and interpret the
asymptotic solution.Comment: Some typos in the version publised in the IEEE Transactions on
Wireless Communications are correcte
Improving Resource Efficiency with Partial Resource Muting for Future Wireless Networks
We propose novel resource allocation algorithms that have the objective of
finding a good tradeoff between resource reuse and interference avoidance in
wireless networks. To this end, we first study properties of functions that
relate the resource budget available to network elements to the optimal utility
and to the optimal resource efficiency obtained by solving max-min utility
optimization problems. From the asymptotic behavior of these functions, we
obtain a transition point that indicates whether a network is operating in an
efficient noise-limited regime or in an inefficient interference-limited regime
for a given resource budget. For networks operating in the inefficient regime,
we propose a novel partial resource muting scheme to improve the efficiency of
the resource utilization. The framework is very general. It can be applied not
only to the downlink of 4G networks, but also to 5G networks equipped with
flexible duplex mechanisms. Numerical results show significant performance
gains of the proposed scheme compared to the solution to the max-min utility
optimization problem with full frequency reuse.Comment: 8 pages, 9 figures, to appear in WiMob 201
Characterization of the weak Pareto boundary of resource allocation problems in wireless networks -- Implications to cell-less systems
We establish necessary and sufficient conditions for a network configuration
to provide utilities that are both fair and efficient in a well-defined sense.
To cover as many applications as possible with a unified framework, we consider
utilities defined in an axiomatic way, and the constraints imposed on the
feasible network configurations are expressed with a single inequality
involving a monotone norm. In this setting, we prove that a necessary and
sufficient condition to obtain network configurations that are efficient in the
weak Pareto sense is to select configurations attaining equality in the
monotone norm constraint. Furthermore, for a given configuration satisfying
this equality, we characterize a criterion for which the configuration can be
considered fair for the active links. We illustrate potential implications of
the theoretical findings by presenting, for the first time, a simple
parametrization based on power vectors of achievable rate regions in modern
cell-less systems subject to practical impairments.Comment: Accepted at IEEE ICC 202
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