System Level Modeling and Optimization of the LTE Downlink

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1. Motivation and Scope of WorkAs shown in Table 1.1, wireless standards have been steadily evolving, improvingthe achievable throughput, improving latency [4], and utilizing larger spetra moreefficiently with each evolutionary step.Table 1.1.: Evolution of the maximum download throughput and latency for several 3GPPstandards, as defined by their respective maximum mobile equipment capabilities(2000-2010)Year Max. DL speed Latency SpectrumUMTS 2000 0.384 Mbit/sHSDPARel’5 2002 14 Mbit/sRel’7 2007 28 Mbit/sRel’8 2009 42.2 Mbit/sRel’9 2010 84.4 Mbit/s∼70 ms∼25 ms5 MHz10 MHzLTE Rel’8 2009 300 Mbit/s 15 ms-20 ms 20 MHzWith the addition of Adaptive Modulation and Coding (AMC) and Multiple-InputMultiple-Output (MIMO) spatial multiplexing [5], the last iteration of 3GPP cellularwireless systems, named Long Term Evolution (LTE), is capable of reaching aspectral efficiency of up to 15 bit/s/Hz.This thesis is motivated by the need of modeling the performance of LTE networks,which feature a new Physical (PHY) layer based on Orthogonal Frequency-DivisionMultiplexing (OFDM) [6], as opposed to the Wideband Code Division MultipleAccess (W-CDMA) PHY of UMTS-based systems [7].The new PHY offers a higher number of degrees of freedom that can be exploited,which albeit offering a more flexible system, increase the complexity of feedbackand resource allocation. Scheduling is performed over time and frequency, and dynamicallyadjusts the per-user allocated physical resources according to the receivedchannel quality (CQI) and MIMO feedback (PMI and RI). All in order to furtherincrease the spectral efficiency improvements of the PHY with a more efficientexploitation of multi-user gain.In order to evaluate the opportunities offered by the combination of the LTE PHYand Medium Access Control (MAC) layers, complex scenarios consisting of multipleeNodeBs and users need to be simulated, which unless proper modeling of the PHYlayer is applied, is computationally very costly or very inaccurate if over-simplifiedscenarios are employed.The main objective of this thesis is to describe a link abstraction model, also alternativelyreferred to as Link-to-System (L2S) model or L2S interface, for LTE Release8, with particular focus on the MIMO capabilities of the PHY. It aims at accuratelymodeling link performance without the need to simulate all of the involved PHY2
1. Motivation and Scope of Worklayer procedures, thus significantly decreasing simulation complexity and enablingthe simulation of more complex scenarios and the evaluation of Multi-User (MU)gain at the network level.The proposed model serves as basis for a Matlab-implemented LTE system levelsimulation tool [8], openly available for free for academic, non-commercial use, whichenables the reproducibility of the results in this thesis, as well as the prior work onwhich it is based upon.1.1. OutlineThe main sections of this thesis, which span Chapters 2 to 5, comprise a descriptionof the relevant aspects of LTE necessary for L2S modeling, a description andvalidation of the proposed model, extensions for imperfect channel knowledge andHARQ, and finally an application of the L2S model to evaluate the performance ofFractional Frequency Reuse (FFR) jointly with scheduling in LTE networks.A short summary of each of the core sections of this thesis, as well as its relation tothe publications listed in Section 1.2, can be found in the subsections below.Chapter 2: 3GPP Long Term EvolutionIn the first chapter, heavily based on the contribution in [1], a very brief overview ofthe reasons behind the creation of the LTE standard is given, as well as an overviewof the network structure LTE defines. The bulk of the chapter is devoted to thedescription of the PHY and MAC layers, with special attention to the followingtopics, relevant for L2S modeling:ˆ Structure of the OFDM-based PHY layer.ˆ Defined MIMO transmit modes, as well as the feedback required for each of them.ˆ Channel coding and Hybrid Automatic Repeat reQuest (HARQ) procedures.ˆ Degrees of freedom at the scheduler level to exploit multi-user diversity and adaptto the channel conditions: frequency, time, AMC, as well as spatial multiplexing.Chapter 3: Physical Layer Modeling and LTE System Level SimulationIn this section, the importance of system level simulations is highlighted, as it allowsfor simulation of scenarios where rather than that of a single link, the performanceof a complex network layout can be evaluated. It begins by, based on the Bit-Interleaved Coded Modulation (BICM) model, modeling a single LTE TX-RX linkwith the structure presented in Chapter 2. The link model is progressively developed3
Page 1: DissertationSystem Level Modeling a
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D. Evaluation of Multi-User GainD.
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D. Evaluation of Multi-User GainAvg
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Abbreviations and AcronymsAbbreviat
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Abbreviations and AcronymsKPILLRL2S
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System Level Modeling and Optimization of the LTE Downlink

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