Game theory and the design of self-configuring, adaptive wireless networks

Abstract

Game theory provides a wealth of tools that can be applied to the design and operation of communications systems. In this article, we provide a brief introduction to game theory. We then present applications of game theory to problems in random access and power control. In the case of random access, we examine the behavior of selfish users in a simplified Aloha system; surprisingly, rational selfish users do not implement the "always transmit" strategy that one might expect. In the case of power control, we show that game theoretic techniques can yield an optimal operating point without the intervention of an external controller.

A negotiation-based networking methodology to enable cooperation across heterogeneous co-located networks

“…To calculate the optimal set of network services, several negotiation approaches are possible based on methods such as game theory [16,17], selflearning approaches [18] or mathematical formulas. To illustrate the negotiation concepts, this section derives an example negotiation algorithm that uses a heuristic ILP formulation that can be applied to any number N participating networks, using the notations from Table 2.…”

Multi-Agent Design for the Physical Layer of a Distributed Base Station Network

“…That is, it converts a multi-dimensional problem into a one-dimensional quantity upon which decisions for actions are based. In spite of the fact that many frameworks attempt to provide mathematical support to derive such utility functions (such as game theory (Mackenzie & Wicker, 2001) or COIN theory (Tumer & Wolpert, 2004)), these frameworks mostly consider intelligent agents having the ability to learn (eventually using reinforcement learning techniques), which is not the nature of the proposed design. Ultimately, defining simple agent behavior to obtain an intended global behavior still relies on intuition and art such as in Conway's "game of life" (Elwyn R. Berlekamp et al, 1982), or with Wolfram's cellular automatons (Wolfram, 2002).…”

Distributed Relay Selection and Power Control for Multiuser Cooperative Communication Networks Using Buyer/Seller Game

“…In (11), p i represents the price per unit of power selling from relay node i to the source s, and P ri denotes how much…”

“…For game theory literature in the wireless networking, in [11], the behaviors of selfish nodes in the case of random access and power control were examined. In [12] static pricing policies for multipleservice networks were proposed to offer the needed incentives for each node to choose the service that best matched its needs, thereby discouraging over-allocation of resources and improving social welfare.…”