Channel Access Competition in Linear Multihop DevicetoDevice Networks

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Channel Access Competition in Linear Multihop Device-to-Device Networks Vaggelis G. Douros Stavros Toumpis George

Channel Access Competition in Linear Multihop Device-to-Device Networks Vaggelis G. Douros Stavros Toumpis George C. Polyzos IWCMC @ Nicosia, 07. 08. 2014 1

Motivation (1) l 2 New communication paradigms will arise

Motivation (1) l 2 New communication paradigms will arise

Motivation (2) l l l 3 Proximal communication-D 2 D scenarios More devices…more interference

Motivation (2) l l l 3 Proximal communication-D 2 D scenarios More devices…more interference Our work: Channel access in such scenarios which device should transmit/receive data and when

Problem Description (1) l l l 4 1 2 3 4 5 6 Each

Problem Description (1) l l l 4 1 2 3 4 5 6 Each node in this linear D 2 D network either transmits to one of its neighbors or waits Node 3 transmits successfully to node 4 IFF none of the red transmissions take place If node 3 decides to transmit to node 4, then none of the green transmissions will succeed

Problem Description (2) l l 5 The problem: How can these autonomous nodes avoid

Problem Description (2) l l 5 The problem: How can these autonomous nodes avoid collisions? The (well-known) solution: maximal scheduling… is not enough/incentivecompatible We need to find equilibria! 1 2 3

Problem Description (3) l l l 6 This is a special type of game

Problem Description (3) l l l 6 This is a special type of game called graphical game Payoff depends on the strategy of nodes that are up to 2 hops away 1 -c: a successful transmission -c: a failed transmission 0: a node waits

On the Nash Equilibria (1) l l 7 How can we find a Nash

On the Nash Equilibria (1) l l 7 How can we find a Nash Equilibrium? The (well-known) solution: Apply a best response scheme… will not converge A naive approach: A distributed iterative randomized scheme, where nodes exchange feedback in a 2 -hop neighborhood to decide upon their new strategy 1 2 1 2

On the Nash Equilibria (2) l l l 8 Each node i has |Di|

On the Nash Equilibria (2) l l l 8 Each node i has |Di| neighbors and |Di|+1 strategies. Each strategy is chosen with prob. 1/(|Di|+1) A successful transmission is repeated in the next round Strategies that cannot be chosen increase the probability of Wait 1 2 3 4 5 This is a NE!

On the Nash Equilibria (3) l l 9 1 2 3 4 5 By

On the Nash Equilibria (3) l l 9 1 2 3 4 5 By studying the structure of the NE, we can identify strategy subvectors that are guaranteed to be part of a NE We propose a sophisticated scheme and show that it converges monotonically at a NE

On the Nash Equilibria (4) A sophisticated approach: A successful transmission is repeated IFF

On the Nash Equilibria (4) A sophisticated approach: A successful transmission is repeated IFF it is guaranteed that it will be part of a NE vector l Nodes exchange messages in a 3 -hop neighborhood l Is this faster than the 10 naive approach? l 1 2 3 4 5 This is a NE!

Performance Evaluation (1) l l 11 The sophisticated outperforms the naive scheme Even in

Performance Evaluation (1) l l 11 The sophisticated outperforms the naive scheme Even in big D 2 D networks, convergence at a NE is very fast

Performance Evaluation (2) l l 12 Convergence at a NE for the sophisticated scheme

Performance Evaluation (2) l l 12 Convergence at a NE for the sophisticated scheme is ~ proportional to the logarithm of the number of nodes of the topology In <10 rounds, most nodes converge at a local NE

Take-home Messages l Channel access for selfish D 2 D networks can lead to

Take-home Messages l Channel access for selfish D 2 D networks can lead to efficient NE with minimal cooperation – l Studying the structure of the NE is very useful towards the design of efficient schemes – – 13 stronger notion than maximal scheduling fast convergence without spending much energy

 Ευχαριστώ! Vaggelis G. Douros Mobile Multimedia Laboratory Department of Informatics School of Information

Ευχαριστώ! Vaggelis G. Douros Mobile Multimedia Laboratory Department of Informatics School of Information Sciences and Technology Athens University of Economics and Business douros@aueb. gr http: //www. aueb. gr/users/douros/ 14

Acknowledgement (1) l 15 Vaggelis G. Douros is supported by the HERAKLEITOS II Programme

Acknowledgement (1) l 15 Vaggelis G. Douros is supported by the HERAKLEITOS II Programme which is cofinanced by the European Social Fund and National Funds through the Greek Ministry of Education.

Acknowledgement (2) l 16 The research of Stavros Toumpis has been co-financed by the

Acknowledgement (2) l 16 The research of Stavros Toumpis has been co-financed by the European Union (European Social Fund ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF) Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.