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The Approximate Sum Capacity of the Symmetric Gaussian K -User - - PowerPoint PPT Presentation

The Approximate Sum Capacity of the Symmetric Gaussian K -User Interference Channel Or Ordentlich Joint work with Uri Erez and Bobak Nazer July 5th, ISIT 2012 MIT, Cambridge, Massachusetts Ordentlich, Erez, Nazer Approx. Sum Capacity of the


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SLIDE 1

The Approximate Sum Capacity of the Symmetric Gaussian K-User Interference Channel

Or Ordentlich Joint work with Uri Erez and Bobak Nazer July 5th, ISIT 2012 MIT, Cambridge, Massachusetts

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 2

The symmetric Gaussian 2-user IC : channel model

w1 E1 x1 1 g w2 E2 x2 1 g z1 y1 z2 y2 D1 ˆ w1 D2 ˆ w2 yk = xk + gx¯

k + zk

Channel is static and real valued. Gaussian noises zk are of zero mean and variance 1. All users are subject to the power constraint xk2 ≤ nSNR. Define INR g2SNR and α log(INR)

log(SNR).

Channel is symmetric: sum capacity = 2 × symmetric capacity

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 3

GDoF of symmetric Gaussian 2-user IC

Symmetric capacity is known to within 1/2 bit (Etkin et al. 08). DoF for each user is 1/2. GDoF gives more refined view α 2 1

2 3 1 2

d(α) 1

2 3 1 2

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 4

Symmetric Gaussian 2-user IC

Noisy interference regime Treat interference as noise α 2 1

2 3 1 2

d(α) 1

2 3 1 2

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 5

Symmetric Gaussian 2-user IC

Weak interference regime Jointly decode intended message and part of interference (Han-Kobayashi). α 2 1

2 3 1 2

d(α) 1

2 3 1 2

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 6

Symmetric Gaussian 2-user IC

Strong interference regime Jointly decode intended message and interference α 2 1

2 3 1 2

d(α) 1

2 3 1 2

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 7

Symmetric Gaussian 2-user IC

Very strong interference regime Decode interference and then successively decode intended message α 2 1

2 3 1 2

d(α) 1

2 3 1 2

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 8

The symmetric Gaussian K-user IC : channel model

w1 E1 x1 1 g g w2 E2 x2 1 g g

. . . . . .

wK EK xK 1 g g z1 y1 z2 y2 zK yK D1 ˆ w1 D2 ˆ w2 DK ˆ wK yk = xk + g

  • m=k

xm + zk INR g2SNR and α log(INR)

log(SNR).

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-9
SLIDE 9

The symmetric Gaussian K-user IC: what do we know?

DoF is discontinuous at the rationals (Etkin and E. Ordentlich 09, Wu et al. 11). GDoF of the symmetric K-user IC is independent of K, except for discontinuity at α = 1 (Jafar and Vishwanath 10). α 2 1

2 3 1 2

d(α) 1

2 3 1 2 1 K

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 10

The symmetric Gaussian K-user IC: what do we know?

What about finite SNR? Adding interference cannot increase capacity → Outer bounds for K = 2 remain valid for K > 2.

10

−2

10 10

2

1 2 3 4 5 6 3−user IC @ SNR=35dB g symmetric rate[bits/channel use]

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 11

The symmetric Gaussian K-user IC: what do we know?

What about finite SNR? Can always use time-sharing → CSYM >

1 2K log(1 + KSNR). 10

−2

10 10

2

1 2 3 4 5 6 3−user IC @ SNR=35dB g symmetric rate[bits/channel use]

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 12

The symmetric Gaussian K-user IC: what do we know?

What about finite SNR? Can treat interference as noise → achieves the approximate capacity for noisy interference regime

10

−2

10 10

2

1 2 3 4 5 6 3−user IC @ SNR=35dB g symmetric rate[bits/channel use]

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 13

The symmetric Gaussian K-user IC: what do we know?

For the other regimes lattice codes are useful. Closed under addition = ⇒ K − 1 interferers folded to one effective interferer. Each receiver sees a K-user MAC yk = xk + g

  • m=k

xm + zk,

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 14

The symmetric Gaussian K-user IC: what do we know?

For the other regimes lattice codes are useful. Closed under addition = ⇒ K − 1 interferers folded to one effective interferer. Assume x1, . . . , xK ∈ Λ. = ⇒ Effective 2-user MAC at each receiver yk = xk + gxint,k + zk, where xint,k =

  • m=k

xm ∈ Λ.

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 15

The symmetric Gaussian K-user IC: what do we know?

For the other regimes lattice codes are useful. Closed under addition = ⇒ K − 1 interferers folded to one effective interferer. Assume x1, . . . , xK ∈ Λ. = ⇒ Effective 2-user MAC at each receiver yk = xk + gxint,k + zk, where xint,k =

  • m=k

xm ∈ Λ. How to decode xk?

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 16

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 17

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 18

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk xk 1 xint,k g z y

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 19

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk xk 1 xint,k g z y

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 20

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk xk 1 xint,k g z y Decode xint,k

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 21

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk xk 1 xint,k g z y Decode xint,k

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-22
SLIDE 22

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk xk 1 xint,k z y Cancel xint,k

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 23

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk xk 1 xint,k z y Decode xk

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-24
SLIDE 24

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk xk 1 xint,k z y Decode xk

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-25
SLIDE 25

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk xk 1 xint,k z y Decode xk

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 26

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk xk 1 xint,k z y Decode xk

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-27
SLIDE 27

The symmetric Gaussian K-user IC: what do we know?

For large g, can decode sum of interferences, subtract and decode desired codeword (Sridharan et al. 08) xint,k xk xk 1 xint,k z y Decode xk

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 28

The symmetric Gaussian K-user IC: what do we know?

What about finite SNR? Successive decoding is optimal in the very strong interference regime.

10

−2

10 10

2

1 2 3 4 5 6 3−user IC @ SNR=35dB g symmetric rate[bits/channel use]

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-29
SLIDE 29

The symmetric Gaussian K-user IC: strong interference

yk = xk + gxint,k + zk, xk, xint,k ∈ Λ Assume strong interference: g > 1 but not ≫ 1. For 2-user IC jointly decoding intended message and interference is

  • ptimal.

For K-user IC jointly decoding xk, xint,k seems like a good idea.

Question

What rates are achievable?

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-30
SLIDE 30

The symmetric Gaussian K-user IC: strong interference

yk = xk + gxint,k + zk, xk, xint,k ∈ Λ Assume strong interference: g > 1 but not ≫ 1. For 2-user IC jointly decoding intended message and interference is

  • ptimal.

For K-user IC jointly decoding xk, xint,k seems like a good idea. MAC capacity theorem does not hold when both transmitters use the same lattice codebook = ⇒ Need a new coding theorem.

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-31
SLIDE 31

MAC with same lattice code

What’s the problem with using the same lattice code? xint,k xk xk 1 xint,k 2 y Assume there is no noise at all

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 32

MAC with same lattice code

What’s the problem with using the same lattice code? xint,k xk xk 1 xint,k 2 y AMBIGUITY!

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 33

MAC with same lattice code: new decoder

Decoding the two lattice points directly is difficult. Instead...

New decoder based on compute-and-forward

Decode two equations with integer coefficients and solve for desired codeword. yk = xk + gxint,k + zk,

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 34

MAC with same lattice code: new decoder

Decoding the two lattice points directly is difficult. Instead...

New decoder based on compute-and-forward

Decode two equations with integer coefficients and solve for desired codeword. ˜ y1

k

˜ y2

k

  • =

a11 a12 a21 a22 xk xint,k

  • +

zeff,1 zeff,2

  • Ordentlich, Erez, Nazer
  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-35
SLIDE 35

MAC with same lattice code: new decoder

Decoding the two lattice points directly is difficult. Instead...

New decoder based on compute-and-forward

Decode two equations with integer coefficients and solve for desired codeword. ˜ y1

k

˜ y2

k

  • =

a11 a12 a21 a22 xk xint,k

  • +

zeff,1 zeff,2

  • Main result

We use this approach to obtain the approximate symmetric capacity region

  • f the K-user symmetric IC up to an outage set.

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 36

The symmetric Gaussian K-user IC: new inner bounds

10

−1

10 10

1

0.5 1 1.5 2 2.5 3 3.5 3−user IC @ SNR=20dB g symmetric rate[bits/channel use]

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-37
SLIDE 37

The symmetric Gaussian K-user IC: new inner bounds

10

−2

10 10

2

1 2 3 4 5 6 3−user IC @ SNR=35dB g symmetric rate[bits/channel use]

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-38
SLIDE 38

The symmetric Gaussian K-user IC: new inner bounds

10

−2

10 10

2

2 4 6 8 3−user IC @ SNR=50dB g symmetric rate[bits/channel use]

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-39
SLIDE 39

The symmetric Gaussian K-user IC: new inner bounds

10

−2

10 10

2

2 4 6 8 10 3−user IC @ SNR=65dB g symmetric rate[bits/channel use]

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-40
SLIDE 40

Main tool: compute-and-forward

Theorem - Nazer-Gastpar 11

For the channel y =

K

  • k=1

hkxk + z the equation

K

  • k=1

akxk with a = [a1 · · · aK] ∈ ZK can be decoded reliably as long as the rates of all users satisfy R < 1 2 log

  • SNR

SNRβh − a2 + β2

  • for some β ∈ R.

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-41
SLIDE 41

Main tool: compute-and-forward

Theorem - Nazer-Gastpar 11

For the channel y =

K

  • k=1

hkxk + z the equation

K

  • k=1

akxk with a = [a1 · · · aK] ∈ ZK can be decoded reliably as long as the rates of all users satisfy R < 1 2 log

  • SNR

SNRβh − a2 + β2

  • for some β ∈ R.

Use one channel output to decode two equations yk = xk + gxint,k + zk,

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-42
SLIDE 42

Main tool: compute-and-forward

Theorem - Nazer-Gastpar 11

For the channel y =

K

  • k=1

hkxk + z the equation

K

  • k=1

akxk with a = [a1 · · · aK] ∈ ZK can be decoded reliably as long as the rates of all users satisfy R < 1 2 log

  • SNR

SNRβh − a2 + β2

  • for some β ∈ R.

Use one channel output to decode two equations ˜ y1

k

˜ y2

k

  • =

a11 a12 a21 a22 xk xint,k

  • +

zeff,1 zeff,2

  • Ordentlich, Erez, Nazer
  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-43
SLIDE 43

Main tool: compute-and-forward

Decoding two equations is not very effective when channel gains are close to integers. This causes the notches in the achievable rate region. Fortunately, this rarely happens...

1 1.2 1.4 1.6 1.8 2 0.2 0.4 0.6 0.8 1 1.2 1.4 g Normalized Computation Rate First Equation Second Equation Sum

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 44

Main tool: compute-and-forward

PROMO

To hear more about this come to ”The Compute-and-Forward Transform” tomorrow at 15:20.

1 1.2 1.4 1.6 1.8 2 0.2 0.4 0.6 0.8 1 1.2 1.4 g Normalized Computation Rate First Equation Second Equation Sum

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 45

Compute-and-forward for the symmetric K-user IC

Transmit Equations Decoded by Receivers x1 a11x1 + a12

  • ℓ=1

xℓ a21x1 + a22

  • ℓ=1

xℓ x2 a11x2 + a12

  • ℓ=2

xℓ a21x2 + a22

  • ℓ=2

xℓ

. . . . . . . . .

xK a11xK + a12

  • ℓ=1

xℓ a21xK + a22

  • ℓ=1

xℓ From one real equation decode two linearly independent equations with integer coefficients. Corresponding computation rates are Rcomp,1, Rcomp,2.

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-46
SLIDE 46
  • Approx. symmetric capacity: strong interference regime

CSYM ≥ Rcomp,2 Rcomp,2 is the solution to an integer-least squares optimization problem. Inner bound can be found numerically and plotted.

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-47
SLIDE 47
  • Approx. symmetric capacity: strong interference regime

CSYM ≥ Rcomp,2 Rcomp,2 is the solution to an integer-least squares optimization problem. Inner bound can be found numerically and plotted.

10

1

1 2 3 4 5 3−user IC @ SNR=30dB g symmetric rate[bits/channel use] Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-48
SLIDE 48
  • Approx. symmetric capacity: strong interference regime

CSYM ≥ Rcomp,2 Rcomp,2 is the solution to an integer-least squares optimization problem. Inner bound can be found numerically and plotted.

Question

For c > 0 bits, what is the fraction of channel gains g for which

  • uter bound − inner bound > c bits?

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-49
SLIDE 49

Outage set

10

1

1 2 3 4 5 3−user IC @ SNR=30dB g symmetric rate[bits/channel use]

Strong interference regime

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-50
SLIDE 50

Outage set

10

1

1 2 3 4 5 3−user IC @ SNR=30dB g symmetric rate[bits/channel use]

c = 0.25 bits

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
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SLIDE 51

Outage set

48% outage for c = 0.25 bits

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-52
SLIDE 52

Outage set

22% outage for c = 0.5 bits

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-53
SLIDE 53

Outage set

11% outage for c = 0.75 bits

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-54
SLIDE 54
  • Approx. symmetric capacity: strong interference regime

Theorem - inner bound for the strong interference regime

The symmetric capacity of the symmetric Gaussian K-user IC is lower bounded by CSYM ≥ 1 4 log+(INR) − c 2 − 3 for all values of 1 ≤ g2 < SNR except for an outage set whose measure is a fraction of 2−c of the interval 1 ≤ |g| < √ SNR, for any c > 0.

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-55
SLIDE 55
  • Approx. symmetric capacity: strong interference regime

Theorem - inner bound for the strong interference regime

The symmetric capacity of the symmetric Gaussian K-user IC is lower bounded by CSYM ≥ 1 4 log+(INR) − c 2 − 3 for all values of 1 ≤ g2 < SNR except for an outage set whose measure is a fraction of 2−c of the interval 1 ≤ |g| < √ SNR, for any c > 0. Outage set approach appeared first in Niesen and Maddah-Ali 11 (next talk) The outage set phenomena seems inherent to the problem (Etkin and

  • E. Ordentlich 09).

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-56
SLIDE 56

Weak interference regime: Lattice Han-Kobayshi

Similar approach works for the weak interference regime. Just choose public and private codewords from lattice codebooks. Decoding is done using compute-and-forward. Achievable rate is the solution to integer least-squares optimization problem. Can be shown to be within a constant gap from outer bound (except for an outage set).

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-57
SLIDE 57

Summary: new inner bounds

New inner bound for strong interference regime.

◮ Constant gap from outer bound except for outage set.

10

−2

10 10

2

2 4 6 8 3−user IC @ SNR=50dB g symmetric rate[bits/channel use]

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-58
SLIDE 58

Summary: new inner bounds

New inner bound for moderately weak interference regime.

◮ Constant gap from outer bound except for outage set.

10

−2

10 10

2

2 4 6 8 3−user IC @ SNR=50dB g symmetric rate[bits/channel use]

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC
slide-59
SLIDE 59

Summary: new inner bounds

New inner bound for weak interference regime.

◮ Constant gap from outer bound for all channel gains.

10

−2

10 10

2

2 4 6 8 3−user IC @ SNR=50dB g symmetric rate[bits/channel use]

Ordentlich, Erez, Nazer

  • Approx. Sum Capacity of the Symmetric Gaussian K-User IC