network alignment: treating networks as wireless interference channel

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Network Alignment: Treating Networks as Wireless Interference Channel Chun Meng Univ. of California, Irvine

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Network Alignment: Treating Networks as Wireless Interference Channel. Chun Meng Univ. of California, Irvine. Outline. Motivation: Network ≈ Wireless Interference Channel Approaches: N A in the middle, Precoding -Based NA PBNA Feasibility of PBNA Conclusion. State of the Art - I. - PowerPoint PPT Presentation

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Page 1: Network Alignment: Treating Networks as Wireless Interference Channel

Network Alignment: Treating Networks as Wireless Interference Channel

Chun MengUniv. of California, Irvine

Page 2: Network Alignment: Treating Networks as Wireless Interference Channel

o Motivation:Network ≈ Wireless Interference Channel

o Approaches:NA in the middle, Precoding-Based NA

o PBNAFeasibility of PBNA

o Conclusion

2

Outline

Page 3: Network Alignment: Treating Networks as Wireless Interference Channel

Intra-Session NC Achievable rate = min-cut[1,2]

LP-formulation[3]

Code design: RNC[4], deterministic[5]

3

State of the Art - I

[1] R. Ahlswede, et al, “Network information flow”[2] R. Koetter and M. M edard, “An algebraic approach to network coding”′[3] Z. Li, et al, “On Achieving Maximum Multicast Throughput in Undirected Networks”[4] T. Ho, et al, “A random linear network coding approach to multicast”[5] S. Jaggi, et al, “Polynomial Time Algorithms for Multicast Network Code Construction”

Page 4: Network Alignment: Treating Networks as Wireless Interference Channel

Inter-Session NC Only approximation of bounds [1]

Exponential number of variables

Code design: NP-hard[5]

LP, evolutionary approach

4

State of the Art - II

[1] N. Harvey, et al, “On the Capacity of Information Networks”[2] A. R. Lehman and E. Lehman, “Complexity classification of network information flow problems”[3] D. Traskov, et al, “Network coding for multiple unicasts: An approach based on linear optimization”[4] M. Kim, et al, “An evolutionary approach to inter-session network coding”

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Restrictive Framework𝑋 1

𝑋 2

𝑋 3

𝑍 2

𝑍1

𝑍 3

R. Koetter and M. M edard, “An algebraic approach to network coding”′

Interference must be canceled out

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Network vs. Wireless Channel - I

Network with multiple unicasts SISO

Channel gain: introduced by nature

𝑋 1

𝑋 2

𝑋 3

𝑍 2

𝑍1

𝑍 3

𝑥1

𝑥2

𝑥3

𝑦 1

𝑦 2

𝑦 3

Transfer function: introduced by network

Min-cut = 1

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7

Networks vs. Wireless Channel - II

Network with multiple unicasts MIMO

𝐗1

𝐗2

𝐗3

𝐙2

𝐙1

𝐙3

𝐱1

𝐱 2

𝐱 3

𝐲 1

𝐲 2

𝐲 3

Min-cut > 1

Transfer matrix Channel matrix

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8

Interference AlignmentCommon problem:

Too MANY unknowns!

Solution: Align interferences to reduce the number of

unknowns

V. Cadambe and S. Jafar, “Interference Alignment and Degrees of Freedom of the K-User Interference Channel”

Benefit: Everyone gets one half of the cake

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9

Brief Intro of IAo Originally introduced by Cadambe & Jafar

o Approaches:• Asymptotic alignment, • Ergodic alignment, • Lattice alignment, • Blind alignment

o Applications• K-user wireless interference channel, • K-user MIMO interference channel, • Cellular networks, • Multi-hop interference networks, • Exact repair in distributed storage

Syed A. Jafar, “Interference Alignment — A New Look at Signal Dimensions in a Communication Network”

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Network Is NOT Wireless Channel

o symbols from finite field

o : polynomial of coding variables

o real & complex numbers

o : structureless

Page 11: Network Alignment: Treating Networks as Wireless Interference Channel

o Motivation:Network ≈ Wireless Interference Channel

o Approaches:NA in the middle, Precoding-Based NA

o PBNAFeasibility of PBNA

o Conclusion

11

Outline

Page 12: Network Alignment: Treating Networks as Wireless Interference Channel

12

NA in the Middle𝑋 1

𝑋 2

𝑋 3 𝑍 31

𝑍 21

𝑍11

t=1 𝑋 1

𝑋 2

𝑋 3 𝑍 32

𝑍 22

𝑍12t=

2

≠ = =NA in the middle:

B. Nazer, et al, "Ergodic Interference Alignment"

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NA in the Middle: Pros & ConsPros:

Achieve ½ in exactly 2 time slots

Cons:Finding code is NOT easy

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14

Precoding-Based NA - IS1

S2

S3

D1

D2

D3

2n+1 uses of networkor 2n+1 symbol extensionx1

x2

x3

n+1

n

n

y1=V1x1

y2=V2x2

y3=V3x3

2n+1

2n+1

2n+1

V. R. Cadambe and S. A. Jafar, "Interference Alignment and Degrees of Freedom of the K-User Interference Channel“

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15

Precoding-Based NA - II

M11V1x1

M12V2x2

M13V3x3

M22V2x2

M21V1x1

M23V3x3

M33V3x3

M32V2x2

M31V1x1

Align interferences

Page 16: Network Alignment: Treating Networks as Wireless Interference Channel

16

Precoding-Based NA - III

Alignment conditions

Rank conditions

Page 17: Network Alignment: Treating Networks as Wireless Interference Channel

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Precoding-Based NA - Advantages

• Achievable rate ½ min-cut[1]

• Code design is simpleEncoding & decoding are predetermined regardless of topology

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18

Get a Better Understanding

V1 can NOT be chosen freely!

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Reformulated Feasibility Cond.

Condensed alignment cond.

Reformulated rank cond.

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Algebraic Formulation - I

is not constant. V1 can NOT be arbitrary matrix

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Algebraic Formulation - II

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22

Algebraic Formulation - III

is full rank

Linearly independent

Page 23: Network Alignment: Treating Networks as Wireless Interference Channel

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Algebraic Formulation - IV is achievable via PBNA if

If is not constant, is asymptotically achievable via PBNA if

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Algebraic Formulation - V is constant. Setting AB=C, V1 can be arbitrary matrix

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25

Algebraic Formulation - VI

If is constant, is asymptotically achievable via PBNA if

pi(x) is not constant

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Summarizationo If is not constant, is asymptotically achievable via PBNA

if

o If is constant, is asymptotically achievable via PBNA if

pi(x) is not constant

Page 27: Network Alignment: Treating Networks as Wireless Interference Channel

o Motivation:Network ≈ Wireless Interference Channel

o Approaches:NA in the middle, Precoding-Based NA

o PBNAFeasibility of PBNA

o Conclusion

27

Outline

Page 28: Network Alignment: Treating Networks as Wireless Interference Channel

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Unfriendly Networks - I If is constant, is asymptotically achievable via PBNA if

pi(x) is not constant

𝑋 1

𝑋 2

𝑋 3

𝑍 2

𝑍1

𝑍 3

𝑒

Page 29: Network Alignment: Treating Networks as Wireless Interference Channel

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Unfriendly Networks - IIIf is not constant, is asymptotically achievable via PBNA if

𝑋 1

𝑋 2

𝑋 3

𝑍 3

𝑍1

𝑍 2

𝑒1

𝑒2

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30

Coupling Relations

network for which the relation holds, it is realizable

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31

Coupling Relations are Mostly Bad

Bad guys

Good guy

𝑋 1

𝑋 2

𝑋 3

𝑍 2

𝑍1

𝑍 3𝑒1

𝑒2

Arbitrary precoding matrix V1 is OK

Page 32: Network Alignment: Treating Networks as Wireless Interference Channel

32

Networks vs. Wireless Channel

Have structures

Coupling relations

Feasibility conditions are violated

Structureless

Can change independently

IA is always feasible

Page 33: Network Alignment: Treating Networks as Wireless Interference Channel

33

NOT All Coupling Relations are Realizable

Max degree of xee’ ≤ 2 Max degree of xee’ ≥ 3

Q1: Which coupling relations are realizable?

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34

Topology and Coupling Relations

Q2: What is the network topology for ?

𝑋 1

𝑋 2

𝑋 3

𝑍 2

𝑍1

𝑍 3

𝑋 1

𝑋 2

𝑋 3

𝑍 3

𝑍1

𝑍 2

Page 35: Network Alignment: Treating Networks as Wireless Interference Channel

35

How About Other Precoding Matrices?

Q3: If can not be used, how about others?

The ONLY one ?

Page 36: Network Alignment: Treating Networks as Wireless Interference Channel

36

Answer to Q1Q1: Which coupling relations are realizable?

Answer:

Page 37: Network Alignment: Treating Networks as Wireless Interference Channel

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Answer to Q3

Answer:

Q3: If can not be used, how about others?

NO !

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38

Combining the Answers to Q1 & Q3If is not constant, is asymptotically achievable via PBNA if and only if

Page 39: Network Alignment: Treating Networks as Wireless Interference Channel

39

Key Idea Behind Q-1Graph-related properties

𝜎 1 𝜏1𝑒1

𝑒4

𝑒2𝑒3

𝑒5

𝑒6

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40

Graph-Related Properties - IHow to check pi(x) is not constant?

1 2

1 3

1 2

1 3

1 2

1 3

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41

Graph-Related Properties - IILinearization Property

Assign values to x

Max degree = 1

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42

Graph-Related Properties - IIIIntuition behind Linearization Property

1

1

3

2

ee’

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43

Graph-Related Properties - IVSquare-Term Property

Implication:

Assign values to x

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44

Graph-Related Properties - VIntuition behind Square-Term Property

1 2

1 3

e

e’

1 3

1 2

e

e’

Page 45: Network Alignment: Treating Networks as Wireless Interference Channel

45

Finding Realizable Coupling Relations - I

Objective:

Step I

Assign values to x

Max degree of f(z) and g(z) = 1

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46

Finding Realizable Coupling Relations - II

Step II

Define

No square term in the numerator

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47

Finding Realizable Coupling Relations - III

Step III

[1] J. Han, et al, “Analysis of precoding-based intersession network coding and the corresponding 3-unicast interference alignment scheme”

Unrealizable

Page 48: Network Alignment: Treating Networks as Wireless Interference Channel

48

How to Answer Q3 ?Q3: If can not be used, how about others?

How to construct V1 ?

Page 49: Network Alignment: Treating Networks as Wireless Interference Channel

49

Example: Construct V1

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50

All Precoding Matrices Are Equivalent

can not be used to coupling relation Any V1 cannot be used

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51

Topology of Coupling Relations - IQ2: What is the network topology for ?

1

1

3

2

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52

Topology of Coupling Relations - II

1

1

2

3

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53

Topology of Coupling Relations - III

𝑋 1

𝑋 2

𝑋 3

𝑍 3

𝑍1

𝑍 2

Page 54: Network Alignment: Treating Networks as Wireless Interference Channel

54

Trivial Case is constant and T is identity matrix

Perfectly aligned

If is constant, can be achieved via PBNA in exactly two time slots if and only if

pi(x) is not constant

Page 55: Network Alignment: Treating Networks as Wireless Interference Channel

55

Trivial Case - Example

1

2

3

2

1

3𝑒1

𝑒2

Page 56: Network Alignment: Treating Networks as Wireless Interference Channel

o Motivation:Network ≈ Wireless Interference Channel

o Approaches:NA in the middle, Precoding-Based NA

o PBNAFeasibility of PBNA

o Conclusion

56

Outline

Page 57: Network Alignment: Treating Networks as Wireless Interference Channel

57

Conclusion

o How to apply interference alignment to networks?o Q1: Which coupling relations are realizable?o Q2: What is the network topology for ?

o Q3: If can not be used, how about others?

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58

Open Questions

o Is it possible to achieve in limited number of time slots ?

o How about other IA schemes ?o In what condition does IA behave better than routing ?

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59

http://odysseas.calit2.uci.edu/doku.php/public:publication

Thank you ! Questions ?