Border Games in Cellular Networks

Abstract

Abstract-In each country today, cellular networks operate on carefully separated frequency bands. This careful separation is imposed by the regulators of the given country to avoid the interference between these networks. But, the separation is only valid for the network operators within the borders of their country, hence the operators are left on their own to resolve cross-border interference of their cellular networks. In this paper, we focus on the scenario of two operators, who want to fine-tune the emitting power of the pilot signals (i.e., beacon signals) of their base stations. This operation is crucial, because the pilot signal power determines the number of users they can attract and hence the revenue they can obtain. In the case of no power costs, we show that operators should be strategic in their borders, meaning to fine-tune the emitting power of their pilot signals. In addition, we study Nash equilibrium conditions in an empirical model and show the efficiency of the Nash equilibria for different user densities. Finally, we modify our game model to take power costs into account. In the model with power costs, the players should still be strategic, but their strategic behavior results in a well-known Prisoner's Dilemma and hence in a sub-optimal Nash equilibrium.

Correlated Anarchy in Overlapping Wireless Networks

“…So, given that the payoff is a function of the aggregate bet b, it would seem that users would have to be informed of every other user's bet, a prospect that downright shatters the unregulated premises of our setting. However, a more careful consideration of (6) reveals that it suffices for users to know the distribution of users among the nodes, something which is small enough to be broadcasted by the nodes along with the signal m. 12 So, let us consider a sequence ω(t) of instances of G to model the game's t th iteration (t = 0, 1, 2 . .…”

“…11 The rescaling factor 1 M has been introduced because significant rewards should come only after checking a strategy against at least O(M) signals. 12 Actually, the signal itself could be the user distribution of the previous stage. This was discussed in [20] where the distinction between real and fake memory is seen to have a negligible impact on the game's performance.…”

“…For example, game-theoretic techniques were used to optimize transmission probabilities in [2] and to calculate the optimal power allocation [3]- [6] or the optimal transmitting carrier in [7]. The authors of [8] and [9] studied the possibility of connecting to several access points using a single WLAN card; the selfish behavior of service providers was analyzed in [10]- [12] and, recently, even the effects of pricing were examined in [13]- [16] using game theory. The scenario that we consider is an unregulated network where a large number of N heterogeneous users (e.g.…”

Security and cooperation in wireless networks: thwarting malicious and selfish behavior in the age of ubiquitous computing

“…Little attention has been devoted so far to the problem of cooperation between wireless sensor network operators; the interested reader can find a slightly different approach in [132]. Section 11.2 is derived from a paper by Felegyhazi et al [134]. Power control has been extensively studied in the context of cellular networking.…”

“…Additional material, such as slide shows (in pdf or PowerPoint 3 formats) will be progressively posted there. Lausanne -Budapest, 2004-2007 3 Trademark of Microsoft Inc. …”