Mean Field Energy Games in Wireless Networks

This work tackles the problem of energy-efficient distributed power control in wireless networks with a large number of transmitters. The problem is modeled by a dynamic game. Each transmitter-receiver communication is characterized by a state given by the available energy and/or the individual channel state and whose evolution is governed by certain dynamics. Since equilibrium analysis in such a (stochastic) game is generally difficult and even impossible, the problem is approximated by exploiting the large system assumption. Under an appropriate exchangeability assumption, the corresponding mean field game is well defined and studied in detail for special cases. The main contribution of this work is to show how mean field games can be applied to the problem under investigation and provide illustrative numerical results. Our results indicate that this approach can lead to significant gains in terms of energy-efficiency at the resulting equilibrium.Comment: IEEE Proc. of Asilomar Conf. on Signals, Systems, and Computers, Nov. 2012, Pacific Grove, CA, US

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

Impact of Mobility on MIMO Green Wireless Systems

This paper studies the impact of mobility on the power consumption of wireless networks. With increasing mobility, we show that the network should dedicate a non negligible fraction of the useful rate to estimate the different degrees of freedom. In order to keep the rate constant, we quantify the increase of power required for several cases of interest. In the case of a point to point MIMO link, we calculate the minimum transmit power required for a target rate and outage probability as a function of the coherence time and the number of antennas. Interestingly, the results show that there is an optimal number of antennas to be used for a given coherence time and power consumption. This provides a lower bound limit on the minimum power required for maintaining a green network.Comment: Accepted for EUSIPCO conference. 5 page

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

Cross-Layer Design for Green Power Control

In this work, we propose a new energy efficiency metric which allows one to optimize the performance of a wireless system through a novel power control mechanism. The proposed metric possesses two important features. First, it considers the whole power of the terminal and not just the radiated power. Second, it can account for the limited buffer memory of transmitters which store arriving packets as a queue and transmit them with a success rate that is determined by the transmit power and channel conditions. Remarkably, this metric is shown to have attractive properties such as quasi-concavity with respect to the transmit power and a unique maximum, allowing to derive an optimal power control scheme. Based on analytical and numerical results, the influence of the packet arrival rate, the size of the queue, and the constraints in terms of quality of service are studied. Simulations show that the proposed cross-layer approach of power control may lead to significant gains in terms of transmit power compared to a physical layer approach of green communications.Comment: Presented in ICC 201

Optimal control for a mobile robot with a communication objective

In this paper, we design control strategies that minimize the time required by a mobile robot to accomplish a certain task (reach a target) while transmitting/receiving a message. To better illustrate the solution we consider a simple model for the robot dynamics. The message delivery is done over a wireless network, and we account for path-loss, i.e., the transmission rate depends on the distance to the wireless antenna. In this work, we consider only one wireless antenna and disregard any shadowing phenomena. To render the problem interesting from a practical point of view we assume that the robot cannot move with innite velocity. The general problem involves a switching control signal due to the complementarity of the objectives (message transmission can require to approach the antenna situated in the opposite direction of the nal target to reach). Our minimal-time control design is based on the use of Pontryagin maximum principle. A numerical example illustrates the theoretical results

Energy Efficient Communications in MIMO Wireless Channels: Information Theoretical Limits

ISBN : 978-1466501072This chapter is focused on defining and optimizing an energy-efficiency metric for MIMO systems. This metric, which expresses in bit per Joule, allows one to measure how much information is effectively transferred to the transmitter per unit cost of energy consumed at the transmitter. For a MIMO point-to-point communication (single user MIMO channels) this metric can be useful to determine what power level, precoding scheme, training length, or number of antennas have to be used for obtaining the maximum information that is effectively transferred per unit energy spent. Then, we move from a physical layer-type approach to a cross-layer design of energy-efficient power control by including the effects a queue with finite size at the transmitter. As a last step we study a distributed multiple user scenario (MIMO multiple access channels) where each user selfishly maximizes its energy-efficiency by choosing its best individual power allocation policy. Here, we present the most relevant results in this field in a concise and comprehensible manner