Topology Control for Effective Interference Cancellation in Multi-User MIMO Networks

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Topology Control for Effective Interference Cancellation in Multi-User MIMO Networks. E. Gelal, K. Pelechrinis , T.S. Kim, I. Broustis Srikanth V. Krishnamurthy, B. Rao IEEE INFOCOM 2010. Problem Motivation & Contributions. MIMO communications are becoming prevalent - PowerPoint PPT Presentation

Text of Topology Control for Effective Interference Cancellation in Multi-User MIMO Networks

  • Topology Control for Effective Interference Cancellation in Multi-User MIMO Networks

    E. Gelal, K. Pelechrinis, T.S. Kim, I. Broustis Srikanth V. Krishnamurthy, B. Rao

    IEEE INFOCOM 2010

  • Problem Motivation & ContributionsMIMO communications are becoming prevalentMultiple antenna elements robust links802.11n utilizes MIMO PHYCSMA/CA no exploitation of MIMO capabilitiesAt most one transmission each time instance

    How can we realize multi-user MIMO communications?Precoding techniques can be usedAccurate channel estimation, feedback from receiver.

    * Successive Interference Cancellation

  • Problem Motivation & Contributions

    We design MUSIC (Multi-User MIMO with Successive Interference Cancellation)Uses SIC for enabling Multi-user MIMO communicationsCentralized and distributed approachesEvaluation on a variety of settingsOur approach scales and the decoding error probability is boundedMUSIC outperforms DoF approaches.

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  • RoadmapProblem motivation & ContributionsBackgroundSICProblem formulationOur approachEvaluationsConclusions

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  • Background

    Multi-user MIMOPrecoding techniquesTx sends pilot signalsRx receives pilot signals channel coefficients estimationRx feedbacks channel coefficients to Tx Tx assigns weights at the antennas Successive Interference Cancellation (SIC)Receiver iteratively extracts high interfering signalsSINR requirement should be satisfied for every interferer. *

  • Background

    Selective diversity at TxFeedback from Rx to Tx for the best transmission elementOne element used for subsequent transmissionFeedback is required less often than with precoding

    Degrees of Freedom = k #antenna elements = kk simultaneous transmissions are possible

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  • RoadmapProblem motivation & ContributionsBackgroundSICProblem formulationOur approachEvaluationsConclusions

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  • SIC*SIC tries to remove first the stronger interferers and then decode the weaker intended signal.

  • Models

    Selection diversity and SICTwo kinds of interferersStrong: signal strength higher than the intendedWeak: signal strength weaker than the intendedPath loss and multipath

    htr follows Rayleigh distribution, is the path exponent, P the transmission power

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  • Dealing with Weak InterferersMaximum weak interference tolerated on link (u,v):

    We want to assure that:

    Assuming all interferers at the same distance as of the strongest one Aggregate weak interference follows Erlang distribution with parametersn: number of intreferers: variance of the Rayleigh distributed variable h

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  • Dealing with Strong Interferers*dBmStrongest interferer P1P1/(N+P2+P3+.+Pk) > Second strongest interferer P2Intended signal ((k-1) strongest) Pk-1k stronger interferer (weak) PkP2/(N+P3+P4+.+Pk) > Pk-1/(N+Pk) > SUCCESFUL DECODING !!Compact rule: Iteratively for correct decoding on link (y,z), there must be at most one interferer u, with the following interfering power:

  • Problem Formulation

    Interference Graph,Directed, edge and vertex weightedV : set of links, with weight the mean value of the received signal strengthE : set of directed edges among the links/vertices, with weight the mean value of interference among the links connected. *

  • Problem Formulation*Time Slot 1 V1 linksTime Slot 2 V2 linksTime Slot m Vm links NP - Hard

  • RoadmapProblem motivation & ContributionsBackgroundSICProblem formulationOur approachEvaluationsConclusions

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  • C-MUSIC

    The centralized algorithm is iterative.Global knowledge of the topologyMain stepsPriority to links not scheduledInclude links that do not require SIC for decodingAdd links that can be decoded with SICTry to pack more links among those already scheduled*

  • C-MUSICTwo interfering links cannot belong to the same sub-topology if:The weak interferer causes more interference than the weak interference budgetThe strong interference cannot be removed The two links have the same transmitter (selection diversity) A node is the transmitter for one of the links and a receiver for the other.

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  • D-MUSIC*Transmitter Receiver

    Overhearing Nodes

  • RoadmapProblem motivation & ContributionsBackgroundSICProblem formulationOur approachEvaluationsConclusions

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  • Simulation Set UpOPNET simulationsTraffic load: 10-30 pkt/sec, 1500 bytes packetsPath loss (=4) and Rayleigh fadingSimulations with different Node density, SINR requirement, number of antenna elementsMetrics of interest:Number of time slots, average decoding success probability, throughputComparison with:Optimal (small topologies), DoF based topology control *

  • Evaluation resultsMUSIC is efficient in terms of number of time slots formed

    Density does not significantly decrease the probability of successful decoding

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    OptimalC-MUSICD-MUSIC7.839.189.64

  • Evaluation resultsDoF based link activation cannot effectively exploit the benefits of multi-user MIMODoF-based link activation leads to more decoding errors

    MUSIC provides better throughput as compared with DoF *

  • RoadmapProblem motivation & ContributionsBackgroundSICProblem formulationOur approach: C-MUSICEvaluationsConclusions

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  • Conclusions

    Identify the conditions for SIC to allow multi-packet reception in multi-user MIMO settings.Design a framework for exploiting SICDemonstrate through simulations the applicability of our approach

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