135,048 research outputs found
UAV-Assisted and Intelligent Reflecting Surfaces-Supported Terahertz Communications
In this letter, unmanned aerial vehicles (UAVs) and intelligent reflective surface (IRS) are utilized to support terahertz (THz) communications. To this end, the joint optimization of UAV's trajectory, the phase shift of IRS, the allocation of THz sub-bands, and the power control are investigated to maximize the minimum average achievable rate of all users. An iteration algorithm based on successive Convex Approximation with the Rate constraint penalty (CAR) is developed to obtain UAV's trajectory, and the IRS phase shift is formulated as a closed-form expression with introduced pricing factors. Simulation results show that the proposed scheme significantly enhances the rate performance of the whole system
Commodity Market Dynamics and the Joint Executive Committee (1880-1886)
Using weekly spot and future commodity prices in Chicago and New York, we construct expected transportation rates for grain between these two cities, expected inventory levels in New York, and realized errors in the expectations of such variables. We incorporate these exogenous com- modity market dynamics into Porter’s (1983) structural modeling of the Joint Executive Committee Railroad Cartel. As in Porter, we model mar- ginal cost as a parametric function of (instrumented) output, among other factors. Unlike Porter, we model pricing over marginal cost as a nonparamet- ric function of a set of variables, which include expectations of deterministic demand cycles and cartel stability. We estimate the pricing and demand equation simultaneously and semiparametrically. Our estimated weekly markups during periods of cartel stability are shown to reflect optimal collu- sive pricing over deterministic business cycles, as modeled in Haltiwanger and Harrington (1991). Periods of cartel instability are proven to be triggered by realized mistakes in expectations of New York grain prices
Energy-Efficient Resource Allocation in Wireless Networks: An Overview of Game-Theoretic Approaches
An overview of game-theoretic approaches to energy-efficient resource
allocation in wireless networks is presented. Focusing on multiple-access
networks, it is demonstrated that game theory can be used as an effective tool
to study resource allocation in wireless networks with quality-of-service (QoS)
constraints. A family of non-cooperative (distributed) games is presented in
which each user seeks to choose a strategy that maximizes its own utility while
satisfying its QoS requirements. The utility function considered here measures
the number of reliable bits that are transmitted per joule of energy consumed
and, hence, is particulary suitable for energy-constrained networks. The
actions available to each user in trying to maximize its own utility are at
least the choice of the transmit power and, depending on the situation, the
user may also be able to choose its transmission rate, modulation, packet size,
multiuser receiver, multi-antenna processing algorithm, or carrier allocation
strategy. The best-response strategy and Nash equilibrium for each game is
presented. Using this game-theoretic framework, the effects of power control,
rate control, modulation, temporal and spatial signal processing, carrier
allocation strategy and delay QoS constraints on energy efficiency and network
capacity are quantified.Comment: To appear in the IEEE Signal Processing Magazine: Special Issue on
Resource-Constrained Signal Processing, Communications and Networking, May
200
Energy-Efficient Resource Allocation in Wireless Networks with Quality-of-Service Constraints
A game-theoretic model is proposed to study the cross-layer problem of joint
power and rate control with quality of service (QoS) constraints in
multiple-access networks. In the proposed game, each user seeks to choose its
transmit power and rate in a distributed manner in order to maximize its own
utility while satisfying its QoS requirements. The user's QoS constraints are
specified in terms of the average source rate and an upper bound on the average
delay where the delay includes both transmission and queuing delays. The
utility function considered here measures energy efficiency and is particularly
suitable for wireless networks with energy constraints. The Nash equilibrium
solution for the proposed non-cooperative game is derived and a closed-form
expression for the utility achieved at equilibrium is obtained. It is shown
that the QoS requirements of a user translate into a "size" for the user which
is an indication of the amount of network resources consumed by the user. Using
this competitive multiuser framework, the tradeoffs among throughput, delay,
network capacity and energy efficiency are studied. In addition, analytical
expressions are given for users' delay profiles and the delay performance of
the users at Nash equilibrium is quantified.Comment: Accpeted for publication in the IEEE Transactions on Communication
Final report: Workshop on: Integrating electric mobility systems with the grid infrastructure
EXECUTIVE SUMMARY:
This document is a report on the workshop entitled “Integrating Electric Mobility
Systems with the Grid Infrastructure” which was held at Boston University on November 6-7
with the sponsorship of the Sloan Foundation. Its objective was to bring together researchers
and technical leaders from academia, industry, and government in order to set a short and longterm research agenda regarding the future of mobility and the ability of electric utilities to meet
the needs of a highway transportation system powered primarily by electricity. The report is a
summary of their insights based on workshop presentations and discussions. The list of
participants and detailed Workshop program are provided in Appendices 1 and 2.
Public and private decisions made in the coming decade will direct profound changes in
the way people and goods are moved and the ability of clean energy sources – primarily
delivered in the form of electricity – to power these new systems. Decisions need to be made
quickly because of rapid advances in technology, and the growing recognition that meeting
climate goals requires rapid and dramatic action. The blunt fact is, however, that the pace of
innovation, and the range of business models that can be built around these innovations, has
grown at a rate that has outstripped our ability to clearly understand the choices that must be
made or estimate the consequences of these choices. The group of people assembled for this
Workshop are uniquely qualified to understand the options that are opening both in the future of
mobility and the ability of electric utilities to meet the needs of a highway transportation system
powered primarily by electricity. They were asked both to explain what is known about the
choices we face and to define the research issues most urgently needed to help public and
private decision-makers choose wisely. This report is a summary of their insights based on
workshop presentations and discussions.
New communication and data analysis tools have profoundly changed the definition of
what is technologically possible. Cell phones have put powerful computers, communication
devices, and position locators into the pockets and purses of most Americans making it possible
for Uber, Lyft and other Transportation Network Companies to deliver on-demand mobility
services. But these technologies, as well as technologies for pricing access to congested
roads, also open many other possibilities for shared mobility services – both public and private –
that could cut costs and travel time by reducing congestion. Options would be greatly expanded
if fully autonomous vehicles become available. These new business models would also affect
options for charging electric vehicles. It is unclear, however, how to optimize charging
(minimizing congestion on the electric grid) without increasing congestion on the roads or
creating significant problems for the power system that supports such charging capacity.
With so much in flux, many uncertainties cloud our vision of the future. The way new
mobility services will reshape the number, length of trips, and the choice of electric vehicle
charging systems and constraints on charging, and many other important behavioral issues are
critical to this future but remain largely unknown. The challenge at hand is to define plausible
future structures of electric grids and mobility systems, and anticipate the direct and indirect
impacts of the changes involved. These insights can provide tools essential for effective private ... [TRUNCATED]Workshop funded by the Alfred P. Sloan Foundatio
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