Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   consider the problem of maximiz- ing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission pors for each connection so as to maximize the number of connections for which this threshold is met.  believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking.  study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms.  also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission pors) as ll as discrete aspects (i.e. which connections should be supported). Our results are:   show that maximizing the number of supported connec- tions is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming.   present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections.   examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero por.  show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections.  also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008. I. INTRODUCTION
['Matthew Andrews', 'Michael Dinitz']
I am writing a research paper on a idea Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory
[{"from": "human", "value": "I am writing a research paper on a idea Maximizing Capacity in Arbitrary Wireless Networks in the SINR Model: Complexity and Game Theory"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   consider the problem of maximiz- ing the number of supported connections in arbitrary wireless networks where a transmission is supported if and only if the signal-to-interference-plus-noise ratio at the receiver is greater than some threshold. The aim is to choose transmission pors for each connection so as to maximize the number of connections for which this threshold is met.  believe that analyzing this problem is important both in its own right and also because it arises as a subproblem in many other areas of wireless networking.  study both the complexity of the problem and also present some game theoretic results regarding capacity that is achieved by completely distributed algorithms.  also feel that this problem is intriguing since it involves both continuous aspects (i.e. choosing the transmission pors) as ll as discrete aspects (i.e. which connections should be supported). Our results are: \u0081  show that maximizing the number of supported connec- tions is NP-hard, even when there is no background noise. This is in contrast to the problem of determining whether or not a given set of connections is feasible since that problem can be solved via linear programming. \u0081  present a number of approximation algorithms for the problem. All of these approximation algorithms run in polynomial time and have an approximation ratio that is independent of the number of connections. \u0081  examine a completely distributed algorithm and analyze it as a game in which a connection receives a positive payoff if it is successful and a negative payoff if it is unsuccessful while transmitting with nonzero por.  show that in this game there is not necessarily a pure Nash equilibrium but if such an equilibrium does exist the corresponding price of anarchy is independent of the number of connections.  also show that a mixed Nash equilibrium corresponds to a probabilistic transmission strategy and in this case such an equilibrium always exists and has a price of anarchy that is independent of the number of connections. This work was supported by NSF contract CCF-0728980 and was performed while the second author was visiting Bell Labs in Summer, 2008. I. INTRODUCTION"}]