Hardware Impairments in Large-scale MISO Systems: Energy Efficiency, Estimation, and Capacity Limits

Hardware Impairments in Large-scale MISO SystemsEmil Bjrnson*, Jakob Hoydis, Marios Kountouris, and Mrouane Debbah

Alcatel-Lucent Chair on Flexible Radio and Department of Telecommunications, Suplec, FranceBell Laboratories, Alcatel-Lucent, Stuttgart, Germany*Signal Processing Lab, KTH Royal Institute of Technology, Sweden

2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)1Energy Efficiency, Estimation, and Capacity Limits

2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)2IntroductionChallenge of Network Traffic GrowthData Dominant Era66% annual traffic growthExponential increase!

Is this Growth Sustainable?User demand will increaseIncreased traffic supply only ifnetwork revenue is sustained!

Continuous Network EvolutionWhat will be the next step?2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)3

Source: Cisco Visual Networking IndexWhat Will Be Next Steps?More Frequency SpectrumScarcity in conventional bands: Use mmWave, cognitive radioJoint optimization of current networks (Wifi, 2G/3G/4G)

Improved Spectral EfficiencyMore antennas/km2 (space division multiple access)

What Limits the Spectral Efficiency?Propagation losses and transmit powerChannel capacityChannel estimation accuracy (inter-user interference)Signal processing complexity2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)4Our Focus:New Paradigm: Large Antenna ArraysRemarkable New Network ArchitectureDeploy large arrays at macro base stations

Everything Seems to Become Better [1]Large array gain (improves channel conditions)Higher capacity (more antennas more users)Orthogonal channels (little inter-user interference)Linear processing optimal (low complexity)

Properties Proved by Asymptotic AnalysisAre conventional models applicable?

[1] F. Rusek, D. Persson, B. Lau, E. Larsson, T. Marzetta, O. Edfors, F. Tufvesson, Scaling up MIMO: Opportunities and challenges with very large arrays, IEEE Signal Process. Mag., 2013.2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)5

Transceiver Hardware ImpairmentsPhysical Hardware is Non-IdealOscillator phase noiseAmplifier non-linearityIQ imbalance in mixers, etc.

Impact of Hardware ImpairmentsMismatch between the intended and emitted signalDistortion of received signalLimits capacity in high-SNR regime [2]

[2]: E. Bjrnson, P. Zetterberg, M. Bengtsson, B. Ottersten, Capacity Limits and Multiplexing Gains of MIMO Channels with Transceiver Impairments, IEEE Communications Letters, 20132013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)6What happens in many-antennas regime?Will everything still get better?2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)7Channel Model with Hardware Impairments Our Focus: Point-to-Point Channel2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)8

Generalized Channel ModelReceived Downlink Signal

[3]: T. Schenk, RF Imperfections in High-Rate Wireless Systems: Impact and Digital Compensation. Springer, 20082013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)9

Data Signal:Noise:

Transmitter DistortionReceiver DistortionDistortion Noise per AntennaProportional to transmitted/received signal power4 Prop. Constants: BS or UT, transmit or receive

Uplink:AnalogousgeneralizationInterpretation of Distortion ModelGaussian Distortion NoiseIndependent between antennasDepends on beamformingStill uncorrelated directivity Little in the signal dimension

Error Vector Magnitude (EVM)

Quality of transceivers:

LTE requirements: 0EVM0.17 (smaller higher rates)Distortion will not vanish at high SNR!2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)10

2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)11Main ContributionContribution 1: Channel Estimation2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)12

New InsightsLow SNR: Small differenceHigh SNR: Error floorError floor for i.i.d. channels:

Characterized by impairments!Very different MSE but noneed to change estimator

Contribution 2: Capacity LimitsExplicit Capacity BoundsUpper: Channel is knownLower: LMMSE estimatorAsymptotic limits:2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)13

Contribution 3: Energy Efficiency2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)14

New InsightsPower reduction from array gainSame as with ideal hardware!Capacity lower bounded by

EE grows without bound!

2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)15Conclusions & OutlookConclusions2013-06-01International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)162013-06-0117International Conference on Digital Signal Processing (DSP 2013): Emil Bjrnson (Suplec and KTH)Thank You for Listening!

Questions?

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