Power Efficient MIMO Techniques for 3GPP LTE and Beyond

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Centre for Communications Research Power Efficient MIMO Techniques for 3GPP LTE and Beyond K. C. Beh, C. Han, M. Nicolaou, S. Armour, A. Doufexi
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Power Efficient MIMO Techniques for 3GPP LTE and Beyond. K. C. Beh, C. Han, M. Nicolaou, S. Armour, A. Doufexi. Green Radio. 4 billion mobile phone users worldwide Telecommunication industry responsible for 183 million tons of CO2 - PowerPoint PPT Presentation

Transcript of Power Efficient MIMO Techniques for 3GPP LTE and Beyond

  • Green Radio 4 billion mobile phone users worldwide

    Telecommunication industry responsible for 183 million tons of CO2

    MVCE framework (Core 5): Deliver high data rate services with a 100-fold reduction in power consumption

  • Green Radio and LTELTE next major step in mobile radio communications

    Aim to reduce delays, improve spectrum flexibility, reduce cost of operators and end users

    MIMO transmission techniques improve system reliability and performance

    LTE support of a MIMO scheduling and precoding method with improved interface between PHY and DLC

  • Green Radio and LTEExamine performance of proposed MIMO-OFDMA scheme

    Consider the capabilities of MIMO-OFDMA precoding in reducing Tx. Power from Base Station (BS)

    Theoretical analysis and simulation results

    Maintain QoS levels with reduced Tx. Power

  • System and Channel ModelSpatial Channel Model Extension (SCME) Urban Macro

    Low spatially correlated channel for all users

    2x2 MIMO architecture (analysis is readily extendible to higher MIMO orders)

    Perfect CQI estimation and feedback

    Ideal Link Adaptation based on 6 Modulation and Coding Schemes (MCS)

  • System and Channel Model

  • System and Channel Model

  • Random and Layered Random BeamformingRandom Unitary Matrix applied to frequency sub-carriers on Physical Resource Block (PRB) basisLinear MMSE Receiver with interference suppression capabilityMIMO channels can be decomposed into separate spatial layersESINR feedback for resource allocationRandom Beamforming: All spatial layers to a single userLayered Random Beamforming: Spatial layers assigned to different users Higher Diversity

  • Unitary Codebook Based BeamformingPre-defined set of antenna beamsPre-coders based on Fourier basis for uniform sector coverageVariable codebook size G, consisting of the unitary matrix setLarge Codebook: Higher Spatial Granularity, Increased FeedbackSmall Codebook: Low Spatial Granularity, Lower FeedbackSingle-User MIMO (SU-MIMO) and Multi-User MIMO (MU-MIMO) capability

  • Feedback ConsiderationsFull Feedback: CQI for all precoding matricesPartial Feedback: CQI on preferred beamsSuboptimal performance for MU-MIMO with partial feedbackCodebook size G=2 assumed

  • Theoretical AnalysisPrecoding schemes achieve varying degrees of Multiuser Diversity (MUD) (K=5)A target spectral efficiency achieved at different SNR levels for different schemes

  • Theoretical AnalysisTarget Spectral Efficiency 3bps/HzSingle User SISO BenchmarkHigher benefits for increasing numbers of usersK=10, MU-MIMO, Gain= 5dB

  • Simulation ResultsAnalysis based on ideal Adaptive Modulation and Coding (AMC)Throughput = R(1-PER),Results consistent with theoretical analysis

  • Simulation ResultsSimulation performance predicts even higher gains Actual performance PER dependent. MU-MIMO and LRB eliminate deep fades that cause severe link degradationsMU-MIMO gain @ K=10: 7dB SFBC suffers from inherent inability to exploit MUD

  • Power Efficiency and FairnessPower Efficiency associated with a cost metric and a corresponding Power Fairness Index (PFI)

    Low cost metric implies high power efficiency

  • Power Efficiency and FairnessPFI indication of how fairly power is allocated to different users with respect to their achieved ratesUplink improvementsSchemes utilising the additional spatial layer, achieve an overall higher power allocation fairness, with PFI values consistently closer to unity.

  • Conclusions and Future WorkMultiuser Diversity schemes exploiting temporal, spectral and spatial domain achieve notable performance gains. Performance gains can be translated to a power saving at the BSTheoretical Analysis consistent with simulation resultsImproved consistency in cost metricImproved power allocation fairnessPower savings of up to 10dB can be achieved with no QoS compromise