362 research outputs found
Introducing Hierarchy in Energy Games
In this work we introduce hierarchy in wireless networks that can be modeled
by a decentralized multiple access channel and for which energy-efficiency is
the main performance index. In these networks users are free to choose their
power control strategy to selfishly maximize their energy-efficiency.
Specifically, we introduce hierarchy in two different ways: 1. Assuming
single-user decoding at the receiver, we investigate a Stackelberg formulation
of the game where one user is the leader whereas the other users are assumed to
be able to react to the leader's decisions; 2. Assuming neither leader nor
followers among the users, we introduce hierarchy by assuming successive
interference cancellation at the receiver. It is shown that introducing a
certain degree of hierarchy in non-cooperative power control games not only
improves the individual energy efficiency of all the users but can also be a
way of insuring the existence of a non-saturated equilibrium and reaching a
desired trade-off between the global network performance at the equilibrium and
the requested amount of signaling. In this respect, the way of measuring the
global performance of an energy-efficient network is shown to be a critical
issue.Comment: Accepted for publication in IEEE Trans. on Wireless Communication
Spectrum Coordination in Energy Efficient Cognitive Radio Networks
Device coordination in open spectrum systems is a challenging problem,
particularly since users experience varying spectrum availability over time and
location. In this paper, we propose a game theoretical approach that allows
cognitive radio pairs, namely the primary user (PU) and the secondary user
(SU), to update their transmission powers and frequencies simultaneously.
Specifically, we address a Stackelberg game model in which individual users
attempt to hierarchically access to the wireless spectrum while maximizing
their energy efficiency. A thorough analysis of the existence, uniqueness and
characterization of the Stackelberg equilibrium is conducted. In particular, we
show that a spectrum coordination naturally occurs when both actors in the
system decide sequentially about their powers and their transmitting carriers.
As a result, spectrum sensing in such a situation turns out to be a simple
detection of the presence/absence of a transmission on each sub-band. We also
show that when users experience very different channel gains on their two
carriers, they may choose to transmit on the same carrier at the Stackelberg
equilibrium as this contributes enough energy efficiency to outweigh the
interference degradation caused by the mutual transmission. Then, we provide an
algorithmic analysis on how the PU and the SU can reach such a spectrum
coordination using an appropriate learning process. We validate our results
through extensive simulations and compare the proposed algorithm to some
typical scenarios including the non-cooperative case and the
throughput-based-utility systems. Typically, it is shown that the proposed
Stackelberg decision approach optimizes the energy efficiency while still
maximizing the throughput at the equilibrium.Comment: 12 pages, 10 figures, to appear in IEEE Transactions on Vehicular
Technolog
Stochastic Differential Games and Energy-Efficient Power Control
One of the contributions of this work is to formulate the problem of
energy-efficient power control in multiple access channels (namely, channels
which comprise several transmitters and one receiver) as a stochastic
differential game. The players are the transmitters who adapt their power level
to the quality of their time-varying link with the receiver, their battery
level, and the strategy updates of the others. The proposed model not only
allows one to take into account long-term strategic interactions but also
long-term energy constraints. A simple sufficient condition for the existence
of a Nash equilibrium in this game is provided and shown to be verified in a
typical scenario. As the uniqueness and determination of equilibria are
difficult issues in general, especially when the number of players goes large,
we move to two special cases: the single player case which gives us some useful
insights of practical interest and allows one to make connections with the case
of large number of players. The latter case is treated with a mean-field game
approach for which reasonable sufficient conditions for convergence and
uniqueness are provided. Remarkably, this recent approach for large system
analysis shows how scalability can be dealt with in large games and only relies
on the individual state information assumption.Comment: The final publication is available at
http://www.springerlink.com/openurl.asp?genre=article\&id=doi:10.1007/s13235-012-0068-
A Repeated Game Formulation of Energy-Efficient Decentralized Power Control
Decentralized multiple access channels where each transmitter wants to
selfishly maximize his transmission energy-efficiency are considered.
Transmitters are assumed to choose freely their power control policy and
interact (through multiuser interference) several times. It is shown that the
corresponding conflict of interest can have a predictable outcome, namely a
finitely or discounted repeated game equilibrium. Remarkably, it is shown that
this equilibrium is Pareto-efficient under reasonable sufficient conditions and
the corresponding decentralized power control policies can be implemented under
realistic information assumptions: only individual channel state information
and a public signal are required to implement the equilibrium strategies.
Explicit equilibrium conditions are derived in terms of minimum number of game
stages or maximum discount factor. Both analytical and simulation results are
provided to compare the performance of the proposed power control policies with
those already existing and exploiting the same information assumptions namely,
those derived for the one-shot and Stackelberg games.Comment: 25 pages, 5 figures, accepted for publication in IEEE Transaction on
Wireless Communicatio
Energy-Aware Competitive Power Allocation for Heterogeneous Networks Under QoS Constraints
This work proposes a distributed power allocation scheme for maximizing
energy efficiency in the uplink of orthogonal frequency-division multiple
access (OFDMA)-based heterogeneous networks (HetNets). The user equipment (UEs)
in the network are modeled as rational agents that engage in a non-cooperative
game where each UE allocates its available transmit power over the set of
assigned subcarriers so as to maximize its individual utility (defined as the
user's throughput per Watt of transmit power) subject to minimum-rate
constraints. In this framework, the relevant solution concept is that of Debreu
equilibrium, a generalization of Nash equilibrium which accounts for the case
where an agent's set of possible actions depends on the actions of its
opponents. Since the problem at hand might not be feasible, Debreu equilibria
do not always exist. However, using techniques from fractional programming, we
provide a characterization of equilibrial power allocation profiles when they
do exist. In particular, Debreu equilibria are found to be the fixed points of
a water-filling best response operator whose water level is a function of
minimum rate constraints and circuit power. Moreover, we also describe a set of
sufficient conditions for the existence and uniqueness of Debreu equilibria
exploiting the contraction properties of the best response operator. This
analysis provides the necessary tools to derive a power allocation scheme that
steers the network to equilibrium in an iterative and distributed manner
without the need for any centralized processing. Numerical simulations are then
used to validate the analysis and assess the performance of the proposed
algorithm as a function of the system parameters.Comment: 37 pages, 12 figures, to appear IEEE Trans. Wireless Commu
Cross-layer distributed power control: A repeated games formulation to improve the sum energy-efficiency
The main objective of this work is to improve the energy-efficiency (EE) of a
multiple access channel (MAC) system, through power control, in a distributed
manner. In contrast with many existing works on energy-efficient power control,
which ignore the possible presence of a queue at the transmitter, we consider a
new generalized cross-layer EE metric. This approach is relevant when the
transmitters have a non-zero energy cost even when the radiated power is zero
and takes into account the presence of a finite packet buffer and packet
arrival at the transmitter. As the Nash equilibrium (NE) is an
energy-inefficient solution, the present work aims at overcoming this deficit
by improving the global energy-efficiency. Indeed, as the considered system has
multiple agencies each with their own interest, the performance metric
reflecting the individual interest of each decision maker is the global
energy-efficiency defined then as the sum over individual energy-efficiencies.
Repeated games (RG) are investigated through the study of two dynamic games
(finite RG and discounted RG), whose equilibrium is defined when introducing a
new operating point (OP), Pareto-dominating the NE and relying only on
individual channel state information (CSI). Accordingly, closed-form
expressions of the minimum number of stages of the game for finite RG (FRG) and
the maximum discount factor of the discounted RG (DRG) were established. The
cross-layer model in the RG formulation leads to achieving a shorter minimum
number of stages in the FRG even for higher number of users. In addition, the
social welfare (sum of utilities) in the DRG decreases slightly with the
cross-layer model when the number of users increases while it is reduced
considerably with the Goodman model. Finally, we show that in real systems with
random packet arrivals, the cross-layer power control algorithm outperforms the
Goodman algorithm.Comment: 36 pages, single column draft forma
Transmitter Optimization in Multiuser Wireless Systems with Quality of Service Constraints
In this dissertation, transmitter adaptation for optimal resource allocation in wireless communication systems are investigated. First, a multiple access channel model is considered where many transmitters communicate with a single receiver. This scenario is a basic component of a. wireless network in which multiple users simultaneously access the resources of a wireless service provider. Adaptive algorithms for transmitter optimization to meet Quality-of-Service (QoS) requirements in a distributed manner are studied. Second, an interference channel model is considered where multiple interfering transmitter-receiver pairs co-exist such that a given transmitter communicates with its intended receiver in the presence of interference from other transmitters. This scenario models a wireless network in which several wireless service providers share the spectrum to offer their services by using dynamic spectrum access and cognitive radio (CR) technologies. The primary objective of dynamic spectrum access in the CR approach is to enable use of the frequency band dynamically and opportunistically without creating harmful interference to licensed incumbent users. Specifically, CR users are envisioned to be able to provide high bandwidth and efficient utilization of the spectrum via dynamic spectrum access in heterogeneous networks. In this scenario, a distributed method is investigated for combined precoder and power adaptation of CR transmitters for dynamic spectrum sharing in cognitive radio systems. Finally, the effect of limited feedback for transmitter optimization is analyzed where precoder adaptation uses the quantized version of interference information or the predictive vector quantization for incremental updates. The performance of the transmitter adaptation algorithms is also studied in the context of fading channels
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