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Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, 2009. WiOPT 2009. 7th International Symposium on

Date 23-27 June 2009

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  • [Title page]

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  • WiOpt - general chair's message

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  • WiOpt - message from the TPC co-chairs

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  • Conference committee

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  • Wireless scheduling

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  • Recent progress in multiuser information theory with correlated sources

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  • Self-X RAN: Autonomous self organizing radio access networks

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  • Cooperation at the network level

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  • Coding for cooperation and relaying

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  • Lifting the curse of dimensionality: a random matrix-theoretic approach

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  • Survey on spiked models and their application to wireless commcunications

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  • Time and space averages in large wireless networks [SpaSWiN Workshop]

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    Summary form only given, as follows. In this talk, we will discuss some problems related to cooperative spectrum sensing, and show how random matrix theory can help to address them. We will propose a simple test for frequency band sensing in wireless networks. The test is based on the analysis of the ratio of the extreme eigenvalues related to the gain matrix of the channel. The novelty relies in the fact that the test does not require the knowledge of the noise statistics. Large random matrix results allow us to build the threshold for the test, and also to study its type II error. This in particular enables us to compare this test with a different although popular test already proposed in the literature. We will show that our test is uniformly more powerful. View full abstract»

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  • Using redundancy to enable interactive communication for moving vehicles

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  • Where is the action in information theory

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  • Table of contents

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  • Transmission schedule optimization for half-duplex multiple-relay networks

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (6094 KB) |  | HTML iconHTML  

    Half duplex devices are widely used in today's wireless networks. These devices can only send or receive, but not do both at the same time. In this paper, we use cooperative decode-forward relay strategies to increase the throughput of half-duplex wireless networks. Due to the half duplex constraint, relays need to carefully choose their transmission states in order to maximize the throughput. We show that the transmission schedule optimization can be formulated as a linear programming problem. Although the number of possible states grows exponentially as the number of relays increases, only a small subset of these states needs to be used in the optimal transmission schedule. This observation allows us to use heuristic algorithms to solve for near-optimal schedule in large networks. Our numerical results show that the decode-forward strategy can provide nearly 3 times more throughput than the traditional multi-hop relaying strategy in half duplex wireless networks. View full abstract»

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  • On models for multi-user Gaussian channels with fading

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1806 KB) |  | HTML iconHTML  

    An analytically tractable model for Gaussian multiuser channels with fading is studied, and the capacity region of this model is found to be a good approximation of the capacity region of the original Gaussian network. This work extends the existing body of work on deterministic models for Gaussian multiuser channels to include the physical phenomenon of fading. In particular, it generalizes these results to a unicast, multiple node network setting with fading. View full abstract»

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  • Natural selection of message forwarding algorithms in Multihop wireless networks

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4921 KB) |  | HTML iconHTML  

    The need for self-managing multihop MANETs (mobile ad hoc networks) arose recently, where the network rapidly adapts to the changes of the environment without any central control. One of the challenges is how to spread the information fast and resource-effectively in the network. This paper presents a novel adaptive framework, which utilizes natural selection for choosing the adequate message forwarding algorithms for changing environments. The survival of the competing algorithms depends on their efficiency, while the fitness evaluation is made locally without overhead generating performance feedback. Performance evaluations were carried out in our simulation platform tailored to a self-managing MANET environment, to analyze the performance measures of different message forwarding algorithms. View full abstract»

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  • Multi-sensor event detection under temporal correlations with renewable energy sources

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    Sensor networks have major applications in environmental monitoring, relief operations, surveillance, health-care and defense. Future sensor networks would comprise of sensing devices with energy harvesting capabilities from renewable energy sources such as solar power. Multiple sensor nodes deployed in the region of interest would collaborate to achieve a global objective, such as detection of application specific events. This paper focuses on the design of efficient algorithms for multi-sensor activation in order to optimize the overall event detection probability. The recharge-discharge dynamics of the individual rechargeable sensor nodes, along with temporally correlated nature of event occurrences makes the optimal multi-sensor event detection question very challenging. We formulate the dynamic multi-sensor event detection question in a stochastic optimization framework, and design efficient sensor activation algorithms. Particularly, we analyze certain classes of threshold activation policies and show that they achieve near-optimal performance when the threshold is chosen carefully. Specifically, we show that a time-invariant threshold policy, which attempts to maintain a fixed number (appropriately chosen) of sensors active at all times, is optimal in absence of temporal correlations. Moreover, the same energy-balancing time-invariant threshold policy approaches optimality in presence of temporal correlations as well, albeit under certain limiting assumptions. Through simulation studies, we compare the performance of this time-invariant policy with energy-balancing correlation-dependent policies, and observe that although the latter perform better, the performance difference is rather small. View full abstract»

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  • Mathematical analysis of throughput bounds in random access with ZIGZAG decoding

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4795 KB) |  | HTML iconHTML  

    We investigate the throughput improvement that ZIGZAG decoding (Gollakota and Katabi (2008)) can achieve in multi-user random access systems. ZIGZAG is a recently proposed 802.11 receiver design that allows successful reception of packets despite collision. Thus, the maximum achievable throughput of a wireless LAN can be significantly improved by using ZIGZAG decoding. We analyze the throughput bounds in three different idealized slotted multi-access system models for the case when ZIGZAG decoding is used. We also provide results for the Aloha and CSMA models where exact closed form solutions are infeasible to calculate. Our analysis and simulation results show that ZIGZAG decoding can significantly improve the maximum throughput of the random access system. View full abstract»

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  • Joint resource allocation and admission control in wireless mesh networks

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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1994 KB) |  | HTML iconHTML  

    Many next generation applications (such as video flows) are likely to have associated minimum data rate requirements to ensure satisfactory quality as perceived by end-users. While there have been prior approaches on supporting quality-of-service (QoS) in mesh networks, they have largely ignored the issues that arise due to self-interference, the interference between different link layer transmissions of a single flow along a multi-hop path. In this paper, we develop a framework to address the problem of maximizing the aggregate utility of traffic flows in wireless mesh networks, with constraints imposed both due to self-interference and minimum rate requirements. The output of our framework is a schedule that dictates which links are to be activated simultaneously, and provides specifications of the resources associated with each of those links. Utilizing the proposed framework as a basis, we build an admission control module that intelligently manages the resources among the flows in the network and admits as many new flows as possible without violating the QoS of the existing flows. We provide numerical results to demonstrate the efficacy of our framework. View full abstract»

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  • Joint load balancing, scheduling, and interference mitigation in multi-cell and multi-carrier wireless data systems

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    We consider the problem of maximizing the weighted sum data rate in multi-cell and multi-carrier wireless data systems in the presence of interference. We present a scheme that jointly considers load balancing, user scheduling, and interference mitigation to improve the system performance. Our proposed scheme iteratively applies two processes. The first process solves the sub-problem of load balancing and user scheduling while fixing the power allocation of each BS (and thus fixing the interference). We prove that this sub-problem is NP-hard, and devise a 1/2-approximation algorithm to solve the problem. We also consider an extended model capturing finite queue size and propose a 1/2-approximation algorithm under this model. The second process solves the problem of interference mitigation assuming fixed load balancing and user scheduling. We develop a local-improvement based algorithm to solve this problem. Via simulations, we demonstrate that our joint scheme improves both average system throughput and fairness significantly. Compared to the scheme with fixed user-BS association and 1/3 frequency reuse, the lowest 10% cell-edge users obtain more than 60% performance improvement and 90%of users enjoy more than 30%throughput improvement. View full abstract»

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  • Jamming in wireless networks under uncertainty

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    The problem of jamming plays an important role in ensuring the quality and security of wireless communications, especially at this moment when wireless networks are quickly becoming ubiquitous. Since jamming can be considered as a game in which jammer is playing against the user (transmitter) who would like to transmit signal with good quality and at the same time with a reasonable amount of energy, game theory is an appropriate tool for dealing with jamming. Here we investigate the effect of partially available information and correlation among sub-carriers on the user behavior. Specifically, to do so we deal with the scenario when the user does not know how jamming efforts are distributed among sub-carriers and the user does not know the fading channels' gains with certainty. As an object function for the user we consider SINR. We consider zero-sum games, so all of them can also be viewed as a minimax problem for the user playing against the nature. We study independent fading channel gains scenario as well as dependent fading channel gains scenario, both in discrete and continuous versions. We show that in all the scenarii the jammers equalize the quality of the best sub-carriers for the transmitter on as low level as their power constraints allow. Meanwhile the transmitter distributes his power among these jamming sub-carriers. We find the equilibrium strategies in closed form and specify the range of sub-carriers where the transmitter can expect the jamming attack. Also, we show for independent plot these strategies depend only on the expected value of the transmitters channel gains meanwhile for the dependent plot they depend on the whole spectra of these gains. Thus, for independent plot the behaviour of the jammer is less fine tuned under environment since it works with the expected gains. The user for both scenarios has to take the whole spectra of the jamming gains but, of course, for the independent scenario he is less specific because of the jammer. View full abstract»

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  • Identifying RFID tag categories in linear time

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    Given a large set of RFID tags, we are interested in determining the categories of tags that are present in the shortest time possible. Since there can be more than one tag present in a particular category, pure randomized strategies that rely on resolving individual tags are very inefficient. Instead, we rely on a pseudo-random strategy that utilizes a uniform hash function to accurately identify all t categories present among a given set of psi tags with high probability. We propose two algorithms: (a) a single frame algorithm that determines the optimal frame size, and (b) a probabilistic version where the frame size is fixed, and we select the probability to minimize the number of frames needed for identification. Both of these algorithms run in time linear to the number of categories present, t. We show that our approach significantly outperforms existing algorithms for category identification. The performance of our algorithms is within a constant factor of the lower bound. View full abstract»

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