System Level Modeling and Optimization of the LTE Downlink

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1. Motivation and Scope of Workinto a combination of a link quality model and a link performance model, basedon the calculation of the post-equalization Signal to Interference and Noise Ratio(SINR) and Additive White Gaussian Noise (AWGN) Block Error Ratio (BLER)curves obtained from link level simulations.This chapter describes the functional separation of the L2S model into its two components:the link quality and the link performance model, which perform the followingfunctions:ˆ The link quality model encompasses the calculation of the post-equalization SINRbased on a Zero Forcing (ZF) receiver model on a per-subcarrier basis, thus incorporatingthe OFDM-based PHY and MIMO processing of LTE into its design. Itis in this stage of the modeling that a MIMO channel model and the network layoutis incorporated, the latter of which based on pathloss maps, space-correlatedshadow fading, antenna radiation patterns and the radiated transmit power.ˆ The link performance model, which takes as input the output of the link qualitymodel, compresses the subcarrier SINRs into a single value by means of MutualInformation Effective SINR Mapping (MIESM), thus quantifying the quality ofthe OFDM frequency-selective signal with a single AWGN-equivalent SINR value.This allows for the usage of a single set of link-level-obtained performance curves,independent of the channel. The link performance model finally outputs the linkthroughput and BLER.To further reduce run time complexity, part of the most computationally-intensiveprocessing necessary during system level simulations can be performed off-line onceand then reused in subsequent simulations:ˆ Link level AWGN BLER curves for each Modulation and Coding Scheme (MCS)need be produced once and are reused at every simulation. As MIESM enablesthe link performance model to be fading-insensitive, the same BLER curves canemployed independently of the channel type.ˆ As MU-MIMO is not in the scope of this model, it is possible with negligible loss ofprecision to precalculate the optimum precoder choice (shown in Appendix A) andstore it as fading parameters in a pregenerated channel trace. This offloads thecomputationally-intensive complex-valued matrix multiplications and inversionsrequired by the MIMO processing and SINR calculations and substitutes themwith simple scalar products at run-time.ˆ Network layouts as well as user spatial distributions can be cached and stored,thus reducing the need to re-generate commonly-employed simulation scenariosand enabling the reproduction of specific scenarios in a reproducible manner.However well-elaborated and sophisticated, any such link abstraction models needsto be compared to link level results, as the validity of performance evaluations4
1. Motivation and Scope of Workperformed via abstraction models is only as accurate as the abstraction model itselfis. In the second part of this chapter, the results of the link abstraction modelare compared to link level simulations, both at the simplest level (single-cell, singleuser), as well as in multi-cell setups.The following scenarios are considered for the link-to-system validation:ˆ A single-cell, single-user scenario, analogous to link level simulations over aSignal to Noise Ratio (SNR) range validates whether (i) with the only link levelinput of AWGN BLER curves, the throughput of time-and-frequency selectivechannels can be accurately modeled, (ii) the accuracy of the MIMO precoderprecalculation, and (iii) the accuracy of the system level feedback calculation.ˆ A multi-user scenario, comparing the multi-user gain observed at link level andat system level.Additionally, a brief complexity analysis is also provided, comparing the simulationrun-time of system level simulations compared to that of link level simulations, thushighlighting the advantages of employing a L2S model for more complex simulationscenarios.Related workThis chapter represents the basis of the LTE L2S model. Published work on whichthis chapter is based include [2], where the LTE MIMO link abstraction was presented.The creation of the model would not have been possible without the priorwork on LTE link level simulation, which was presented on [3]. A first validation oflink-to-system simulation results was first presented on [4], although for this thesis amore complex multi-cell scenario with different penetration losses has been additionallyconsidered. Additionally linked to this chapter are the contents of appendices A,B and D. While the contents of the multi-user gain analysis of the LTE downlink inAppendix D are contained in [5], the contents of appendices A and D are, as of thefinishing date of this thesis, not contained in any peer-reviewed publication.Chapter 4: Extensions to the L2S ModelIn addition to the LTE L2S model presented in Chapter 3, this chapter presents furtherenhancements to the link quality and link performance models that enable theL2S model to take into account imperfect channel knowledge and HARQ combining.In the first part of the chapter, an extension to the link performance model isintroduced. This extended model takes into account the gain introduced by theHARQ MAC layer retransmission scheme of LTE and is based on a separation ofthe HARQ gain into a coding gain and a repetition gain. A metric based on5
Page 1: DissertationSystem Level Modeling a
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4. Extensions to the L2S ModelBLER1
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6. Summary and Outlook6. Summary an
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6. Summary and Outlook6.2. OutlookW
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A. SNR-independence of the CLSM Pre
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B. Correlation Matrices for Shadow
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C. Taylor Expansion of the ZF MSEC.
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C. Taylor Expansion of the ZF MSEAp
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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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Abbreviations and AcronymsU-PlaneUT
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Abbreviations and AcronymsBibliogra
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Abbreviations and Acronymsdescripti
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Abbreviations and Acronyms[69] Tech
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Abbreviations and Acronymsfemto cel
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System Level Modeling and Optimization of the LTE Downlink

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