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Cem Tekin

  1. Online Learning in Opportunistic Spectrum Access: A Restless Bandit Approach.

    Пнд, 10/04/2010 - 15:01 — SomNambul
    Authors: Mingyan Liu, Cem Tekin
    Subjects: Optimization and Control
    Abstract

    We consider an opportunistic spectrum access (OSA) problem where the
    time-varying condition of each channel (e.g., as a result of random fading or
    certain primary users' activities) is modeled as an arbitrary finite-state
    Markov chain. At each instance of time, a (secondary) user probes a channel and
    collects a certain reward as a function of the state of the channel (e.g., good
    channel condition results in higher data rate for the user).

  2. Online Algorithms for the Multi-Armed Bandit Problem with Markovian Rewards.

    Чт, 07/15/2010 - 15:01 — SomNambul
    Authors: Mingyan Liu, Cem Tekin
    Subjects: Optimization and Control
    Abstract

    We consider the classical multi-armed bandit problem with Markovian rewards.
    When played an arm changes its state in a Markovian fashion while it remains
    frozen when not played. The player receives a state-dependent reward each time
    it plays an arm. The number of states and the state transition probabilities of
    an arm are unknown to the player. The player's objective is to maximize its
    long-term total reward by learning the best arm over time.

  3. Spectrum Sharing as Network Congestion Games.

    Пнд, 12/21/2009 - 16:01 — SomNambul
    Authors: Mingyan Liu, Yunnan Wu, Jianwei Huang, Sahand Ahmad, Cem Tekin
    Subjects: Information Theory
    Abstract

    In this paper, we propose and analyze the properties of a new class of games
    - the network congestion game (NCG), which is a generalization of the classical
    congestion game (CG). In a classical congestion game,multiple users share the
    same set of resources and a users payoff for using any resource is a function
    of the total number of users sharing it. This game enjoys some very appealing
    properties, including the existence of a pure strategy Nash equilibrium (NE)
    and that every improvement path is finite and leads to such a NE (also called
    the finite improvement property or FIP).

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