12 research outputs found
Learning Equilibria with Partial Information in Decentralized Wireless Networks
In this article, a survey of several important equilibrium concepts for
decentralized networks is presented. The term decentralized is used here to
refer to scenarios where decisions (e.g., choosing a power allocation policy)
are taken autonomously by devices interacting with each other (e.g., through
mutual interference). The iterative long-term interaction is characterized by
stable points of the wireless network called equilibria. The interest in these
equilibria stems from the relevance of network stability and the fact that they
can be achieved by letting radio devices to repeatedly interact over time. To
achieve these equilibria, several learning techniques, namely, the best
response dynamics, fictitious play, smoothed fictitious play, reinforcement
learning algorithms, and regret matching, are discussed in terms of information
requirements and convergence properties. Most of the notions introduced here,
for both equilibria and learning schemes, are illustrated by a simple case
study, namely, an interference channel with two transmitter-receiver pairs.Comment: 16 pages, 5 figures, 1 table. To appear in IEEE Communication
Magazine, special Issue on Game Theor
Game Theory for Secure Critical Interdependent Gas-Power-Water Infrastructure
A city's critical infrastructure such as gas, water, and power systems, are
largely interdependent since they share energy, computing, and communication
resources. This, in turn, makes it challenging to endow them with fool-proof
security solutions. In this paper, a unified model for interdependent
gas-power-water infrastructure is presented and the security of this model is
studied using a novel game-theoretic framework. In particular, a zero-sum
noncooperative game is formulated between a malicious attacker who seeks to
simultaneously alter the states of the gas-power-water critical infrastructure
to increase the power generation cost and a defender who allocates
communication resources over its attack detection filters in local areas to
monitor the infrastructure. At the mixed strategy Nash equilibrium of this
game, numerical results show that the expected power generation cost deviation
is 35\% lower than the one resulting from an equal allocation of resources over
the local filters. The results also show that, at equilibrium, the
interdependence of the power system on the natural gas and water systems can
motivate the attacker to target the states of the water and natural gas systems
to change the operational states of the power grid. Conversely, the defender
allocates a portion of its resources to the water and natural gas states of the
interdependent system to protect the grid from state deviations.Comment: 7 pages, in proceedings of Resilience Week 201
Energy-Efficient Power Control for Contention-Based Synchronization in OFDMA Systems with Discrete Powers and Limited Feedback
This work derives a distributed and iterative algorithm by which mobile
terminals can selfishly control their transmit powers during the
synchronization procedure specified by the IEEE 802.16m and the 3GPP-LTE
standards for orthogonal frequency-division multiple-access technologies. The
proposed solution aims at maximizing the energy efficiency of the network and
is derived on the basis of a finite noncooperative game in which the players
have discrete action sets of transmit powers. The set of Nash equilibria of the
game is investigated, and a distributed power control algorithm is proposed to
achieve synchronization in an energy-efficient manner under the assumption that
the feedback from the base station is limited. Numerical results show that the
proposed solution improves the energy efficiency as well as the timing
estimation accuracy of the network compared to existing alternatives, while
requiring a reasonable amount of information to be exchanged on the return
channel
The 5G Cellular Backhaul Management Dilemma: To Cache or to Serve
With the introduction of caching capabilities into small cell networks
(SCNs), new backaul management mechanisms need to be developed to prevent the
predicted files that are downloaded by the at the small base stations (SBSs) to
be cached from jeopardizing the urgent requests that need to be served via the
backhaul. Moreover, these mechanisms must account for the heterogeneity of the
backhaul that will be encompassing both wireless backhaul links at various
frequency bands and a wired backhaul component. In this paper, the
heterogeneous backhaul management problem is formulated as a minority game in
which each SBS has to define the number of predicted files to download, without
affecting the required transmission rate of the current requests. For the
formulated game, it is shown that a unique fair proper mixed Nash equilibrium
(PMNE) exists. Self-organizing reinforcement learning algorithm is proposed and
proved to converge to a unique Boltzmann-Gibbs equilibrium which approximates
the desired PMNE. Simulation results show that the performance of the proposed
approach can be close to that of the ideal optimal algorithm while it
outperforms a centralized greedy approach in terms of the amount of data that
is cached without jeopardizing the quality-of-service of current requests.Comment: Accepted for publication at Transactions on Wireless Communication
Interference Coordination via Power Domain Channel Estimation
A novel technique is proposed which enables each transmitter to acquire
global channel state information (CSI) from the sole knowledge of individual
received signal power measurements, which makes dedicated feedback or
inter-transmitter signaling channels unnecessary. To make this possible, we
resort to a completely new technique whose key idea is to exploit the transmit
power levels as symbols to embed information and the observed interference as a
communication channel the transmitters can use to exchange coordination
information. Although the used technique allows any kind of {low-rate}
information to be exchanged among the transmitters, the focus here is to
exchange local CSI. The proposed procedure also comprises a phase which allows
local CSI to be estimated. Once an estimate of global CSI is acquired by the
transmitters, it can be used to optimize any utility function which depends on
it. While algorithms which use the same type of measurements such as the
iterative water-filling algorithm (IWFA) implement the sequential best-response
dynamics (BRD) applied to individual utilities, here, thanks to the
availability of global CSI, the BRD can be applied to the sum-utility.
Extensive numerical results show that significant gains can be obtained and,
this, by requiring no additional online signaling
CORASMA Program on Cognitive Radio for Tactical Networks: High Fidelity Simulator and First Results on Dynamic Frequency Allocation
International audienceThis paper reports some preliminary results of the "cognitive radio for dynamic spectrum management" (CORASMA) program that is dedicated to the evaluation of cognitive solutions for tactical wireless networks. It presents two main aspects of the program: the simulator and the the cognitive solutions proposed by the authors. The first part is dedicated to the simulator.We explain the rationale used to design its architecture, and how this architecture allows to assess and compare different cognitive solutions in an operational context. The second part addresses the dynamic frequency allocation topic that is part of the cognitive solutions tackled in the program CORASMA. We first give an overview of the challenges attached to this problem in the military context and then we expose the technical solutions studied by the authors for this purpose. Finally, we present some results obtained from the simulator as an illustration