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Dirty RF Impact on Interference Alignment

Per Zetterberg

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Outline

• Goal• Approach• Interference-alignment and CoMP• Implementation• Results• Impairment-modeling (closening the gap

theory-simulation)• Conclusion

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Goal

TestbedMeasurements(USRP)

Impairment-modeling

FEREVMSINRMatch!

Detailedsimulation

New interesting and challenging techniques

Assumption: Results are general.

Channels

Robust approaches

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Approach

Transmitter Spectrum analyzer

Test-bedMeasurements(USRP)

Impairment-modeling

Basic simulation

PC

Impairment model

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Interference alignment

K-transmitters and K-receivers, K-links:K/2 simultaneous interference-free links.Requires coding over multiple channel realizations.Global channel knowledge required.

Cadambe/Jafar, ”Interference Alignment and Degrees of Freedom of the K-User Interference Channel”,IEEE Trans, Information Theory 2008.

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Interference-alignment incarnations

In frequency-domain:Something new –will be studied later.

In antenna-domain:Co-ordinated beam-forming.

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Co-ordinated Multi-Point CoMP

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Implementation IA

BS 1

BS 2

BS 3

MS 1

MS 2

MS 3

Feedback:Wired ethernet

𝒗 1

𝒗 2

𝒗 3

𝒖1

𝒖2

𝒖3

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Implementation: CoMP

BS 1

BS 2

BS 3

MS 1

MS 2

MS 3

Feedback:Wired ethernet

𝒗 1

𝒗 2

𝒗 3

𝒖1

𝒖2

𝒖3

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Beamformer

SNIR𝑘=𝒖𝑘

∗𝑯 𝑘 ,𝑘𝒗𝑘𝒗𝑘∗𝑯 𝑘 ,𝑘

∗ 𝒖𝑘

∑𝑛 ≠𝑘

𝒖𝑘∗𝑯 𝑘 ,𝑛 𝒗𝑛𝒗𝑛

∗𝑯 𝑘,𝑛∗ 𝒖𝑘

=¿

“Approaching the Capacity of Wireless Networks through Distributed Interference Alignment", by Krishna Gomadam, Viveck R. Cadambe and Syed A. Jafar.

Formulate virtual uplink SINR. Iterate

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Frames

Payload10 OFDM symbols

Payload10 OFDM symbols

CSI referencesignals

Demodulation reference signals

38 subcarriers, 312.5kHz carrier-spacingQPSK, …., 256QAM0.25, 0.5, 0.75 –rate LDPC codes

• MS feed-back CSI to BS1.• BS1 calculate beam-formers.• BS1 sends weights to BS2,

BS3.• BS1-BS3 frequency locked.

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Preliminary Results

16QAM, 0.75 rate coded. 432 frames transmitted.

FER IA CoMP

Uncoded 63% 9%

Coded 19% 0%

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How far from ideal ?

0 5 10 15 20 25 30 35-5

0

5

10

15

20

25

30

35

Receiver estimated SNR

Act

ual S

NR

IA

0 5 10 15 20 25 30 350

5

10

15

20

25

30

35

Receiver estimated SNR

Act

ual S

NR

CoMP

d

e

P

P100EVM%

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Power-Amplifier Non-linearity

OFDM signals:

+𝑠 (𝑡 )

n

y+n(t)

Modeled as noise:

D Dardari, V. Tralli, A Vaccari “A theoretical characterization of nonlinear distortion effects in OFDM systems“, IEEE Trans. Comm., Oct 2000.

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MIMO case

OFDM signals:

+𝑠1 (𝑡 )

n

(t)

OFDM signals:

+

n

(t)

𝑠2 (𝑡 )

Correlation ?

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Phase-noise

A/D

ttfjt RX2expLO

LPFBPF LNA

y(t)

Modeled as additive noise + CPE

CPE: Slowly varying between symbols

R. Corvaja, E. Costa, and S. Pupolin, “M-QAM-OFDM system performance in the presence of a nonlinear amplifier and phase noise, IEEE Trans. Comm. 2002.

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CoMP Results

0 5 10 15 20 25 30 350

10

20

30

40

0 5 10 15 20 25 30 350

10

20

30

40

Withoutimpairmentmodel

Withimpairmentmodel

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IA Results

0 5 10 15 20 25 30 35-10

0

10

20

30

40

0 5 10 15 20 25 30 35-10

0

10

20

30

40

Withoutimpairmentmodel

Withimpairmentmodel

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Conclusion: What will be answered?

• How much worse is IA practice than in theory?• What practical impairments need to be modeled?

(==> can lead to improved robust designs)• Is IA still worthwhile with impairments compared to

base-lines ?

Other outputs• Software environments that can be re-used

(commodity hardware)• Increased understanding of software and hardware

issues and implementations in our research community and our PhDs in particular.

• Course-work for the above.

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Structure of model

TX TX

RX TX

RX

RX

Channel

TX- impairment

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Our Hardware

PC

Linux

Gbit-Ethernet

USRP N210Sample-rate: 100MHzStreaming: 25MHz

We have 18 USRPs

GPS

PPS,10MHz

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The 4Multi Software FrameWork(Multi-Antenna, Multi-User, Multi-Cell, Multi-Band)

• Send data in small bursts (relaxes computational load)• Nodes synchronized by external trigering (PPS)• The implementor (basically) only need to program three functions node::init, node::process and node::end_of_run.• Simulate the system using “simulate” generic function.• Everything that can be compiled with gcc can run (e.g IT++)• Toolbox with coding&modulation.• Store _all_ received signals for post-processing.

Vision: “The coding should be as easy as performing ordinary

(but detailed) desktop simulations”