Alternative bargaining solutions for the interference channel

In this paper, we address the problem of spectrum sharing where competitive operators coexist in the same frequency band. First, we model this problem as a strategic non-cooperative game where operators simultaneously share the spectrum according to the Nash Equilibrium (N.E). Given a set of channel realizations, several Nash equilibria exist which renders the outcome of the game unpredictable. For this reason, the spectrum sharing problem is reformulated as a Stackelberg game where the first operator is already being deployed and the secondary operator follows next. The Stackelberg equilibrium (S.E) is reached where the best response of the secondary operator is taken into account upon maximizing the primary operator's utility function. Finally, we assess the goodness of the proposed distributed approach by comparing its performance to the centralized approach.

IEEE Journal on Selected Areas in Communications, 2000

In this paper we discuss the use of cooperative game theory for analyzing interference channels. We extend our previous work, to games with N players as well as frequency selective channels and joint TDM/FDM strategies.

2008

A scenario consisting of two transmitter-receiver pairs coexisting in the same area and communicating using the same portion of the spectrum is considered. Decentralized coding strategies are employed at the transmitter side and no cooperation is assumed between the two systems. We investigate the structure of Nash equilibria corresponding to simultaneous water-filling solutions and propose a scheme that improves overall performance of systems with weak mutual interference. The resulting scheme provides a spectrum sharing rule in the form of a modified utility function. The conditions for optimality are presented and a numerical example illustrates the performance compared to a scheme employing the link rate as utility function.

Engineering Applications of Artificial Intelligence, 2013

This work proposes a dynamic and fair spectrum management strategy to be adopted by a service provider (SP). Here, we consider a scenario where multiple access networks (ANs) of different (not necessarily competing) technologies are owned by a single SP. We envisage that an SP employs an entity, called local spectrum controller (LSC), which manages a common pool of spectrum and is responsible for distributing the spectrum to individual ANs in a fair manner. Since the available spectrum is inadequate to satisfy the aggregate demand from all ANs simultaneously, LSC has to employ a dynamic spectrum allocation strategy. We have modeled the problem as an n-player cooperative bargaining game and have solved the problem with the help of solution techniques namely, Nash bargaining solution (NBS), Kalai-Smorodinsky bargaining solution (KSBS) and modified Thomson bargaining solution (MTBS). We have presented two novel heuristics to compute KSBS and MTBS. Moreover, a suitable utility function for the AN with respect to its received spectrum have been presented. We have also identified possible objectives of LSC (i.e., SP), namely minimizing overall dissatisfaction (MOD) of heterogeneous network, maintaining equality of distribution (MED) and maximizing proportional fairness (MPF). Finally, we have compared performances of above solutions with max-min fairness solution and Shapley value solution with respect to the above objectives of LSC.

2010 IEEE Global Telecommunications Conference GLOBECOM 2010, 2010

In this paper, we model the problem of dynamic spectrum access by a set of cognitive radio enabled nodes as an infinite horizon bargaining game. Each node (or, player) negotiates with its interfering nodes to obtain an agreeable sharing rule of the available channels. We investigate the subgame perfect equilibrium strategies of the bargaining game, abiding by which, each node can maximize its throughput against all its interfering nodes (opponents). We further study the issue of fairness in this model, in terms of the relative number of channels allocated to the nodes. Moreover, each node bargains with its interfering neighbors independently and in a distributed manner, making the system scalable.

IEEE Signal Processing Magazine, 2009

Most human activity is limited in one way or the other by the finite availability of resources. In communications engineering, the fundamental resources are bandwidth (spectrum) and power. Power is needed to overcome noise at the receiver, and it is basically limited because of regulations and due to limitations on storage (i.e., batteries). Spectrum is fundamentally in shortage, because the part of the EM spectrum where radio wave propagation behaves well is rather limited. As a result, licensed (dedicated) spectrum has become very expensive, as evidenced by the spectrum license auctions for 3G telephony, for example. At the same time, unlicensed spectrum has become overcrowded and at many locations so cluttered with interference that systems provide a very poor grade of service or even cease to work. One example of this can be seen in places where many wireless LAN base stations are placed too closely.

2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 2017

We consider the Gaussian interference channel as a non-cooperative game taking into account the cost of the transmission. We study the conditions of the existence of a pure Nash equilibrium. Particularly, for the many-user case we give sufficient conditions that lead to a Nash equilibrium, and for the two-user case we exhaustively describe the conditions of the existence and the uniqueness of a pure Nash equilibrium and we show the existence of best-response dynamics that converge to one of them.

IEEE Transactions on Cognitive Communications and Networking, 2015

Dynamic spectrum access (DSA) and MIMO communications are among the most promising solutions to address the ever increasing wireless traffic demand. An integration that successfully embraces the two is far from trivial due to the dynamics of spectrum opportunities as well as the requirement to jointly optimize both spectrum allocation and spatial/antenna pattern in a distributed fashion. Regardless of spectrum dynamics and heterogeneity, existing literature on channel/power allocation in MIMO DSA systems is only applicable to centralized cases. Our objective here is to design distributed algorithms that jointly allocate opportunistic channels to various links and to simultaneously optimize the MIMO precoding matrices so as to achieve fairness or maximize network throughput. For selfinterested DSA links, our distributed algorithm allows links to negotiate channel allocation based on Nash bargaining (NB) and configure the precoding matrices so that links' rate demands are guaranteed while the surplus resources (after meeting minimum rate demands) are fairly allocated. Next, we consider a network throughput maximization formulation (NET-MAX). Both the NB-based and NET-MAX problems are combinatorial with mixed variables. To tackle them, we first transform the original problems by incorporating the concept of timesharing. Using dual decomposition, we develop optimal distributed algorithms for timesharing case, which shed light on how to derive a distributed algorithm for the original problems. Our work fills a gap in the literature of channel allocation where a central controller is not available.

2008 42nd Asilomar Conference on Signals, Systems and Computers, Vols 1-4, 2008

We consider a scenario consisting of two transmit-receive pairs coexisting in the same area and communicating using the same portion of the spectrum. Applying a game theoretic framework, each pair is regarded as a player whose payoff function is the individual link rate and power is allocated using the iterative water-filling algorithm. We study the dynamics of such a game and find properties of the resulting Nash equilibria. For high interference scenarios, operating points admitting complete, partial or no overlap are possible and we present conditions under which the different Nash equilibria are achievable. Based on this analysis, a modified waterfilling algorithm is designed to increase the sum-rate of the communication links. Its performance is compared to that of the iterative water-filling algorithm by numerical simulations. Although we restrict the analysis to a two player game, analogous concepts can be used to design decentralized algorithms for scenarios with more players.

2011 IEEE International Symposium on Information Theory Proceedings, 2011

In a wireless OFDM communication system multiple players share the same spectrum while experiencing different channel realizations. Allocation algorithms exploit this feature and optimize the allocation of frequency bins according to various optimization criteria (e.g., weighted Max-Min, Nash Bargaining Solution (NBS), etc). These allocations do not allow players to transmit on the same frequency bin simultaneously. Thus, the communication channel is not fully utilized when the mutual interferences are weak. Here we propose a more general allocation scheme, called Partial Orthogonal Allocation (POA), where players can transmit simultaneously on some of the frequency bins, and maintain orthogonality of transmission on the other frequency bins. For this schema, the Nash Bargaining Solution is proposed and analyzed.