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Optimal Random Access in Networks with TwoWay Traffic
"... We consider a random access network in which the nodes need to optimize their channel access rates. The nodes are assumed to be rational and interested in their performance seen as a transmitter as well as a receiver. By casting this problem as a noncooperative game, we derive conditions for the Na ..."
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We consider a random access network in which the nodes need to optimize their channel access rates. The nodes are assumed to be rational and interested in their performance seen as a transmitter as well as a receiver. By casting this problem as a noncooperative game, we derive conditions for the Nash equilibrium. We also show the existence of a Nash equilibrium when the nodes are constrained by their battery power (for this case, the constraints on the access rates of the nodes become coupled). For the special case where all nodes are each other's neighbors, we find that the equilibrium is given by the solution of a system of linear equations. An adaptive distributed scheme is then proposed for learning this equilibrium and its convergence is studied numerically.
Social Security, 1999a, Opportunity for All: Tackling Poverty and Social Exclusion, Cm4445. London: The Stationary Office
 C. Kostis and O. Spaniol (Eds.), Mobile and Wireless Systems, LNCS
, 2005
"... Abstract. Wireless Adhoc networks are expected to be made up of energy aware entities (nodes) interested in their own perceived performance. We consider a simple random access model for a wireless ad hoc network to address problems of finding an optimal channel access rate and providing incentive f ..."
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Abstract. Wireless Adhoc networks are expected to be made up of energy aware entities (nodes) interested in their own perceived performance. We consider a simple random access model for a wireless ad hoc network to address problems of finding an optimal channel access rate and providing incentive for cooperation to forward other nodes ’ traffic. By casting these problems as noncooperative games, we derive conditions for the Nash equilibrium and provide distributed algorithms to learn the Nash equilibrium.
A gametheoretic look at throughput and stability in random access
 in Proc. Military Commun. Conf
, 2006
"... We address the problem of noncooperative random access of two transmitter nodes to a single receiver. We assume infinite buffer capacities and consider a general multipacket reception channel that allows packet capture in the presence of multiple simultaneous transmissions. For the separate cases ..."
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We address the problem of noncooperative random access of two transmitter nodes to a single receiver. We assume infinite buffer capacities and consider a general multipacket reception channel that allows packet capture in the presence of multiple simultaneous transmissions. For the separate cases of saturated or possibly emptying queues, we specify the random access transmission strategies in cooperative and noncooperative equilibrium to optimize the achievable or stable throughput rates, transmission energy and delay costs. We follow a gametheoretic approach to compare the noncooperative performance of selfish nodes with full cooperation in random or scheduled access. Finally, we present extensions to random access with arbitrary number of transmitters and receivers. I.
Stochastic Learning Solution for Constrained Nash Equilibrium Throughput in Non Saturated Wireless Collision Channels
"... We consider finite number of users, with infinite buffer storage, sharing a single channel using the aloha medium access protocol. This is an interesting example of a non saturated collision channel. We investigate the uplink case of a cellular system where each user will select a desired throughput ..."
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We consider finite number of users, with infinite buffer storage, sharing a single channel using the aloha medium access protocol. This is an interesting example of a non saturated collision channel. We investigate the uplink case of a cellular system where each user will select a desired throughput. The users then participate in a non cooperative game wherein they adjust their transmit rate to attain their desired throughput. We show that this game, in contrast to the saturated case, either has no Nash Equilibrium or has infinitely many Nash Equilibria. Further, we show that the region of NE coincides with an appropriate ’stability region’. We also discuss the efficiency of the equilibria in term of energy consumption and congestion rate. Next, we propose two learning algorithms using a stochastic iterative procedure that converges to the best Nash equilibrium. For instance, the first one needs partial information (transmit rates of other users during the last slot) whereas the second is an information less and fully distributed scheme. We approximate the control iterations by an equivalent ordinary differential equation in order to prove that the proposed stochastic learning algorithm converges to a Nash equilibrium even in the absence of any coordination or extra information. Extensive numerical examples and simulations are provided to validate our results.
Throughput of slotted aloha with encoding rate optimization and multipacket reception
 in INFOCOM 2009, IEEE. IEEE
"... AbstractThis paper considers a slotted ALOHA random access system where users send packets to a common receiver with multipacket reception capability. A collection of m users access the shared medium independently of each other with probability p and, upon access, they choose an encoding rate. A c ..."
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AbstractThis paper considers a slotted ALOHA random access system where users send packets to a common receiver with multipacket reception capability. A collection of m users access the shared medium independently of each other with probability p and, upon access, they choose an encoding rate. A collision occurs when the sum of the rates of all the users exceeds the capacity of the channel. We analytically characterize as a function of m and p the encoding rate which maximizes the expected global thoughput of the system. It is shown that for any value of p the throughput converges to one when m tends to infinity, hence there is no loss due to packet collisions. This is in striking contrast with the well known behavior of slotted ALOHA systems in which users cannot adjust the encoding rate. In that case the throughput decreases to zero as the number of users increases. Finally, assuming that users are selfish, we characterize the encoding rate which maximizes the expected individual throughput of each user, and show that the corresponding Nash equilibrium is not globally optimum.