Cattoni, Andrea Fabio

Da Costa, Gustavo Wagner Oliveira

Garcia, Luis Guilherme Uzeda

Mogensen, Preben

Pedersen, Klaus

English

	The 2nd Workshop of COST Action IC0902 Cognitive Radio and Networking for Cooperative Coexistence of Heterogeneous Wireless NetworksOctober 6–7, 2011Castelldefels, Barcelona-SpainContribution to Working Group 2 - Definition of cooperation-based cognitive algorithms, that take advantage of information exchange at a local level Comparison of Selfish versus Altruistic Strategies in Dynamic Spectrum Allocation for Cognitive FemtocellsGustavo W.O. da Costa, Luis G.U. Garcia, Andrea F. Cattoni – Aalborg UniversityKlaus I. Pedersen, Preben E. Mogensen – Nokia Siemens Networks DenmarkGustavo W.O. da Costa/Andrea F. Cattoni – Aalborg UniversityDynamic spectrum sharing is of increasing relevance due to the scarce availability of spectrum, and its importance is further increasing due to the massive growth of traffic demand. In particular, dense femtocell deployment is expected to take off during the next years in order to meet the demand.Distributed autonomous spectrum sharing approaches are preferred for the large scale deployment of femtocells. Yet, designing efficient, stable, fair and scalable distributed algorithms is no easy feat, especially if the cells in a wireless network tend to act selfishly and independently.  We investigated a practical solution, which consists in letting neighbor Cognitive-enabled femtocells (CFemto) to establish mutual non-aggression agreements. Under some policies it is possible to devise efficient distributed channel allocation rules which smoothly reallocate the spectrum.Game Theory is a powerful toolbox which models the interaction of autonomous agents. In this contribution we would like to introduce a game theoretic model for a dynamic spectrum sharing framework recently proposed for femtocells ‎[1]. Using Game theory and, particularly, elements of Network Formation Games, we modeled the establishment of such agreements as a dynamic game. In addition to that, several strategies for this game were proposed ranging from purely egoistic to selfless.Our analysis includes cases where femtocells compete for spectrum as well as cooperative cases towards a common goal. In particular, we considered equal rights dynamic spectrum sharing among closed-subscriber group (CSG) CFemtos. We investigate only the intra-tier interference avoidance ‎[2] and the macrocells are assumed to operate in a separate band. The CFemto Access Point (FAP) coordinates the spectrum allocation with the served User Equipments (UEs). Hence, the spectrum decisions are done on a cell basis. Each FAP is then considered a player of the allocation game.The utility of the players is affected not only by the mutual agreements between pair of players, but also by the way the channels are re-distributed when new players join the game. Ultimately, these two elements will define the component carrier allocation of each femtocell and the actual SINR in each channel.The reader interested in the details of the channel allocation algorithm may refer to ‎[1].  In, ‎[1] the spectrum allocation policy states that a new entrant can request coordination at most to two active players. The analysis in ‎[1] shows that coordinating with two other players is enough to provide considerable gains, while avoiding spectrum fragmentation and reducing the need for signaling. In dynamic games, strategies are essentially a contingent plan of how to play the game on each possible information set. Rational players are typically assumed to select their strategies on a purely selfish manner. Based on examples from society ‎[3] and nature ‎[4] we are interested in challenging the selfishness assumption and identify what are the desirable strategies for dynamic spectrum sharing in femtocells.  In this contribution we consider four different ways of selecting strategies:Selfish: All players select their strategies according to the canonical GT assumptions, optimizing only their own instantaneous throughput.Selfless new entrant: The new entrant intends to protect the existing players and it is completely selfless. Other players still play selfishly. Max-min: a pair of players will choose to cooperate if this is of benefit of the player with lowest incoming BIM.Max-sum: A pair of players will coordinate transmissions if this decision increases their sum capacity compared to uncoordinated transmissions.The performance was evaluated through semi-static system level simulations. We derive our results from a Monte Carlo performance evaluation and thousands of snapshots have been simulated to ensure statistical reliability. The scenario consists of a single 5x5 grid of houses assuming CSG femtocells. Each house contains 4 rooms where both FAPs and UEs are randomly located. Yet, there is at most one femtocell per house. The indoor propagation is modeled according to the WINNER A1 indoor home scenario ‎[5]. Furthermore, if the UE and the FAP are located in the same room, we assume line-of-sight propagation and non-line-of-sight otherwise.  The transmit power of femtocells was set to 24dBm. Look-up tables map the SINR to corresponding throughput values according to a modified Shannon's formula from ‎[6]. The system bandwidth is divided into 6 channels of 15 MHz each. More details and results are available in ‎[7].The system level simulation results show that each femtocell should strive for a balance between selfishness and altruism. It is possible to use this balance in favor of the overall network throughput or in favor of achieving a minimum performance for each cell. In conclusion, theoretical assumptions should guide the design of practical solutions, but they should not be a limiting factor. References[1]	L. Garcia, G. Costa, A. Cattoni, K. Pedersen, and P. Mogensen, “Self organizing coalitions for conflict evaluation and resolution in femtocells,” in GLOBECOM 2010, 2010 IEEE Global Telecommunications Conference, 2010, pp. 1 –6.[2]	V. Chandrasekhar, J. Andrews, and A. Gatherer, “Femtocell networks: a survey,” Communications Magazine, IEEE, vol. 46, no. 9, pp. 59–67, 2008.[3]	R. M. Nelissen, D. S. van Someren, and M. Zeelenberg, “Take it or leave it for something better? Responses to fair offers in ultimatum bargaining,” Journal of Experimental Social Psychology, vol. 45, no. 6, pp. 1227 – 1231, 2009.[4]	C. Stephens, “Modelling reciprocal altruism,” The British Journal for the Philosophy of Science, vol. 47, no. 4, pp. 533–551, 1996.[5]	P. et al.. Kysti, “IST-WINNER D1.1.2 , ”WINNER II Channel Models”, ver 1.1,” Winner II, Tech. Rep., 2007. [Online]. Available: https://www.ist-winner.org/WINNER2-Deliverables/D1.1.2v1.1.pdf (​https:​/​​/​www.ist-winner.org​/​WINNER2-Deliverables​/​D1.1.2v1.1.pdf​)[6]	P. E. Mogensen et al., “LTE Capacity Compared to the Shannon Bound,” in VTC Spring, April 2007.[7]	Gustavo W. O. Costa et al., Dynamic Spectrum Sharing in Femtocells: a Comparison of Selfish versus Altruistic Strategies, in VTC Fall, September 2011.[8]	PAGE  1Action IC0902 – WG2-2011-Doc_YY

Comparison of Selfish versus Altruistic Strategies in Dynamic Spectrum Allocation for Cognitive Femtocells

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Comparison of Selfish versus Altruistic Strategies in Dynamic Spectrum Allocation for Cognitive Femtocells

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