Sum-Capacity of Ergodic Fading Interference and Compound Multiaccess Channels

The problem of resource allocation is studied for two-sender two-receiver fading Gaussian interference channels (IFCs) and compound multiaccess channels (C-MACs). The senders in an IFC communicate with their own receiver (unicast) while those in a C-MAC communicate with both receivers (multicast). The instantaneous fading state between every transmit-receive pair in this network is assumed to be known at all transmitters and receivers. Under an average power constraint at each source, the sum-capacity of the C-MAC and the power policy that achieves this capacity is developed. The conditions defining the classes of strong and very strong ergodic IFCs are presented and the multicast sum-capacity is shown to be tight for both classes.Comment: Proceedings of the 2008 IEEE International Symposium on Information Theory, Toronto, ON, Canada, July 6 - 11, 200

Implicit Coordination in Two-Agent Team Problems; Application to Distributed Power Allocation

The central result of this paper is the analysis of an optimization problem which allows one to assess the limiting performance of a team of two agents who coordinate their actions. One agent is fully informed about the past and future realizations of a random state which affects the common payoff of the agents whereas the other agent has no knowledge about the state. The informed agent can exchange his knowledge with the other agent only through his actions. This result is applied to the problem of distributed power allocation in a two-transmitter $M-$band interference channel, $M\geq 1$, in which the transmitters (who are the agents) want to maximize the sum-rate under the single-user decoding assumption at the two receivers; in such a new setting, the random state is given by the global channel state and the sequence of power vectors used by the informed transmitter is a code which conveys information about the channel to the other transmitter.Comment: 6 pages, appears as WNC3 2014: International Workshop on Wireless Networks: Communication, Cooperation and Competition - International Workshop on Resource Allocation, Cooperation and Competition in Wireless Network

A Non-Cooperative Power Control Game for Multi-Carrier CDMA Systems

In this work, a non-cooperative power control game for multi-carrier CDMA systems is proposed. In the proposed game, each user needs to decide how much power to transmit over each carrier to maximize its overall utility. The utility function considered here measures the number of reliable bits transmitted per joule of energy consumed. It is shown that the user's utility is maximized when the user transmits only on the carrier with the best "effective channel". The existence and uniqueness of Nash equilibrium for the proposed game are investigated and the properties of equilibrium are studied. Also, an iterative and distributed algorithm for reaching the equilibrium (if it exists) is presented. It is shown that the proposed approach results in a significant improvement in the total utility achieved at equilibrium compared to the case in which each user maximizes its utility over each carrier independently.Comment: To appear in Proceedings of the 2005 IEEE Wireless Communications and Networking Conference, New Orleans, LA, March 13 - 17, 200

Minimizing the impact of EV charging on the electricity distribution network

The main objective of this paper is to design electric vehicle (EV) charging policies which minimize the impact of charging on the electricity distribution network (DN). More precisely, the considered cost function results from a linear combination of two parts: a cost with memory and a memoryless cost. In this paper, the first component is identified to be the transformer ageing while the second one corresponds to distribution Joule losses. First, we formulate the problem as a non-trivial discrete-time optimal control problem with finite time horizon. It is non-trivial because of the presence of saturation constraints and a non-quadratic cost. It turns out that the system state, which is the transformer hot-spot (HS) temperature here, can be expressed as a function of the sequence of control variables; the cost function is then seen to be convex in the control for typical values for the model parameters. The problem of interest thus becomes a standard optimization problem. While the corresponding problem can be solved by using available numerical routines, three distributed charging policies are provided. The motivation is threefold: to decrease the computational complexity; to model the important scenario where the charging profile is chosen by the EV itself; to circumvent the allocation problem which arises with the proposed formulation. Remarkably, the performance loss induced by decentralization is verified to be small through simulations. Numerical results show the importance of the choice of the charging policies. For instance, the gain in terms of transformer lifetime can be very significant when implementing advanced charging policies instead of plug-and-charge policies. The impact of the accuracy of the non-EV demand forecasting is equally assessed.Comment: 6 pages, 3 figures, keywords: electric vehicle charging, electricity distribution network, optimal control, distributed policies, game theor

A game-theoretic approach to transmitter covariance matrix design for broadband MIMO Gaussian interference channels

A game-theoretic approach to transmitter covariance matrix design for broadband MIMO Gaussian interference channels Anandkumar, A.J.G. Lambotharan, S. Chambers, J.A. Dept of Electron. & Electr. Eng., Loughborough Univ., Loughborough, UK This paper appears in: Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on Publication Date: Aug. 31 2009-Sept. 3 2009 On page(s): 301 - 304 E-ISBN: 978-1-4244-2711-6 Location: Cardiff ISBN: 978-1-4244-2709-3 INSPEC Accession Number:10961923 Digital Object Identifier: 10.1109/SSP.2009.5278580 Current Version Published: 2009-10-06 Abstract A game-theoretic approach to the maximization of the information rates of broadband multi-input-multi-output (MIMO) Gaussian interference channels is proposed. The problem is cast as a strategic noncooperative game with the MIMO links as players and the information rates as payoff functions. The Nash equilibrium solution of this game is a waterfilling operation and sufficient conditions for its existence and uniqueness are presented. A distributed algorithm which requires no cooperation among the users is presented along with conditions for guaranteed global convergence of the proposed algorithm. The efficacy of the proposed scheme is confirmed through a design example

Alternating-Offer Bargaining Games over the Gaussian Interference Channel

This paper tackles the problem of how two selfish users jointly determine the operating point in the achievable rate region of a two-user Gaussian interference channel through bargaining. In previous work, incentive conditions for two users to cooperate using a simple version of Han-Kobayashi scheme was studied and the Nash bargaining solution (NBS) was used to obtain a fair operating point. Here a noncooperative bargaining game of alternating offers is adopted to model the bargaining process and rates resulting from the equilibrium outcome are analyzed. In particular, it is shown that the operating point resulting from the formulated bargaining game depends on the cost of delay in bargaining and how bargaining proceeds. If the associated bargaining problem is regular, a unique perfect equilibrium exists and lies on the individual rational efficient frontier of the achievable rate region. Besides, the equilibrium outcome approaches the NBS if the bargaining costs of both users are negligible.Comment: 8 pages, 6 figures, to appear in Proceedings of Forty-Eighth Annual Allerton Conference on Communication, Control, and Computin