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  • Spatial Modulation in aMassive MIMO Cellular SystemA signal processing investigation of spatial modulationMasters thesis in Embedded Electronic System Design

    DAVOR BARACEMIL LINDQVIST

    Department of Computer Science and EngineeringCHALMERS UNIVERSITY OF TECHNOLOGYUNIVERSITY OF GOTHENBURGGothenburg, Sweden 2016

  • Masters thesis 2016

    Design and Evaluation of a Modulator ADCUtilizing The Spatial Dimension

    An investigation of how the spatial dimension canbe used in a modulator to reduce the bandwidthrequirement in a receiver with hundreds of antennas

    DAVOR BARACEMIL LINDQVIST

    Department of Computer Science and EngineeringDivision of Computer Engineering

    Chalmers University of TechnologyUniversity of Gothenburg

    Gothenburg, Sweden 2016

  • Design and Evaluation of a Modulator ADC Utilizing The Spatial DimensionAn investigation of how the spatial dimension can be used in a modulator to reducethe bandwidth requirement in a receiver with hundreds of antennasDAVOR BARACEMIL LINDQVIST

    DAVOR BARAC, 2016. EMIL LINDQVIST, 2016.

    Supervisor: Lars Svensson, Department of Computer Science and EngineeringUlf Gustavsson, Ericsson

    Examiner: Per Larsson-Edefors, Department of Computer Science and Engineering

    Masters Thesis 2016Department of Computer Science and EngineeringDivision of Computer EngineeringChalmers University of TechnologyUniversity of GothenburgSE-412 96 GothenburgTelephone +46 31 772 1000

    Cover: Spatio-temporal modulator which can shape the quantization noise in space

    Typeset in LATEXGothenburg, Sweden 2016

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  • Design and Evaluation of a Modulator ADC Utilizing The Spatial DimensionAn investigation of how the spatial dimension can be used in a modulator to reducethe bandwidth requirement in a receiver with hundreds of antennasDAVOR BARACEMIL LINDQVISTDepartment of Computer Science and EngineeringChalmers University of TechnologyUniversity of Gothenburg

    Abstract

    In cellular networks, frequency channels are used to separate the users. However frequencyspectrum is an ever-decreasing resource as wireless units and applications increase. Thus,other means to separate the users are of interest. By using hundreds of antennas andbeamforming in the system, the users can be efficiently multiplexed in the spatial domain,while using the same time-frequency resource. The large amount of antennas howeverrequires extensive data processing and transport which is difficult and expensive to handle.Thus, an investigation of how to reduce the data bandwidth required in such a systemis of interest. This master thesis project evaluates the use of the spatial dimension in a modulator as part of the analog-to-digital conversion. It is put into the context ofbeamforming and evaluated.

    A simulator developed in MATLAB is utilized to show the properties and qualities ofdifferent modulator structures in a beamforming application. In particular, performanceat low converter speeds is evaluated.

    The results show that by using the spatial dimension in a modulator it is possible toreduce the bandwidth requirement, through reduction of sampling rate while still retainingthe signal quality. However, this is applicable only in one direction at a time, and thereare multiple implementation issues regarding the proposed design.

    The findings suggest that with the spatial dimension in a modulator there are possi-bilities to reduce the bandwidth requirement in antenna array systems but that there areconsiderable challenges to overcome.

    Keywords: sigma-delta modulation, spatial, multi-antenna array, signal processing, beam-forming, miso.

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  • Acknowledgements

    We would like to thank our supervisors Lars Svensson at Chalmers and Ulf Gustavsson atEricsson for an interesting, challenging and fun masters thesis project. Ulf Gustavssonhas provided very valuable insight into telecom systems and has been a bit of a walkingreference book. Lars Svensson has guided our work and kept things down-to-earth, butabove all he has inspired us in ways far beyond the scope of this masters thesis. It is trulyawesome to have a teacher and supervisor who loves what he does and actually cares; atrue role model in a lot of ways.

    Finally, we want to thank our families for being supportive and motivating us through allyears of studies.

    Davor & Emil, Gothenburg, June 2016

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  • Acronyms ADC - Analog-to-Digital Converter IC - Integrated Circuit SIMO - Single Input Multiple Output MISO - Multiple Input Single Output MIMO - Multiple Input Multiple Output MRC - Maximum Ratio Combining RMS - Root Mean Square STF - Signal Transfer Function NTF - Noise Transfer Function SNR - Signal-to-Noise Ratio OSR - Oversampling Ratio NMSE - Normalized Mean Square Error

  • Contents

    1 Introduction 1

    2 Theory 32.1 Wireless communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.2 Beamforming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

    2.2.1 Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.2.2 Spatial selectivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

    2.3 The temporal modulator . . . . . . . . . . . . . . . . . . . . . . . . . . 92.3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92.3.2 System models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92.3.3 Mathematical expressions . . . . . . . . . . . . . . . . . . . . . . . 112.3.4 Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

    2.4 The spatial modulator . . . . . . . . . . . . . . . . . . . . . . . . . . . 142.4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142.4.2 System models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142.4.3 Algebraic analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142.4.4 Second-order spatial modulator . . . . . . . . . . . . . . . . . . 16

    2.5 The spatio-temporal modulator . . . . . . . . . . . . . . . . . . . . . . 172.6 modulation in a beamforming application . . . . . . . . . . . . . . . . 18

    2.6.1 System model for beamforming . . . . . . . . . . . . . . . . . . . . 192.6.2 Temporal modulation . . . . . . . . . . . . . . . . . . . . . . . 202.6.3 Spatial modulation . . . . . . . . . . . . . . . . . . . . . . . . . 202.6.4 Spatio-temporal modulation . . . . . . . . . . . . . . . . . . . . 21

    3 Design 223.1 Simulation environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

    3.1.1 Model description . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223.1.2 Signals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233.1.3 The ADC designs . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263.1.4 Selection of simulation parameters . . . . . . . . . . . . . . . . . . . 273.1.5 Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

    3.2 The simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283.2.1 SNR vs. angle for a single user . . . . . . . . . . . . . . . . . . . . 283.2.2 Spatial distinction . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

    4 Results 324.1 Algebraic analysis of the modulators . . . . . . . . . . . . . . . . . . . 32

    4.1.1 Spatial modulator . . . . . . . . . . . . . . . . . . . . . . . . . 324.1.2 Spatio-temporal modulator . . . . . . . . . . . . . . . . . . . . 32

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  • 4.2 Evaluation of reconstruction SNR vs. input power . . . . . . . . . . . . . . 334.2.1 Temporal modulation . . . . . . . . . . . . . . . . . . . . . . . 334.2.2 Spatial modulation . . . . . . . . . . . . . . . . . . . . . . . . . 344.2.3 Spatio-temporal modulation . . . . . . . . . . . . . . . . . . . . 35

    4.3 Evaluation of reconstruction SNR vs. angle . . . . . . . . . . . . . . . . . . 364.3.1 Temporal modulation . . . . . . . . . . . . . . . . . . . . . . . 374.3.2 Spatial modulation . . . . . . . . . . . . . . . . . . . . . . . . . 394.3.3 Spatio-temporal modulation . . . . . . . . . . . . . . . . . . . . 43

    4.4 Comparison . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 454.4.1 SNR comparison for low OSR . . . . . . . . . . . . . . . . . . . . . 454.4.2 SNR comparison for high OSR . . . . . . . . . . . . . . . . . . . . . 464.4.3 SNR trend . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 474.4.4 Bandwidth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

    4.5 Multi-user analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484.5.1 Temporal modulation . . . . . . . . . . . . . . . . . . . . . . . 494.5.2 Spatial modulation . . . . . . . . . . . . . . . . . . . . . . . . . 504.5.3 Spatio-temporal modulation . . . . . . . . . . . . . . . . . . . . 51

    5 Discussion 525.1 Observations and findings . . . . . . . . . . . . . . . . . . . . . . . . . . . 525.2 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 535.3 Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

    6 Conclusion 55

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  • Chapter 1

    Introduction

    A recent trend in digital wireless communication systems is to use several antennas ateach end of a point-to-point connection. Current research focuses on very large arrayswith hundreds of antennas. The large number of antennas allows for what is commonlyreferred to as beamforming, which can focus the signal intended for a certain user inthe correct direction, for several users simultaneously [1]. Such antenna systems arecurrently being developed and evaluated for the coming 5G radio access networks [2]. Intodays wireless communication systems, beamforming