1. Network Coding for Wireless Networks
Wireless Communication Project
by Group 2
Shang Shang Ma Rong
Yang Yang Wang Chen

2. Network Coding for Wireless Networks
INTRODUCTION 1
COPE DESCRIPTION 2
COPE IMPLEMENTATION 3 分工
ANALOG NETWORK CODING 4

3. Introduction
Why?
Network
Coding
What?
Definitions

4. Definitions Max-flow Min-cut Theory Unicast, Multicast Through- put 12
Unicast, Multicast 3
Through-
put
The main advantage for network coding, as an original
purpose of this topic, is its high transmission capacity with the
max-flow, which means by employing network coding, the theoretical
upper bound of transmission rate can be achieved by
the sender. Due to the fact that all sessions do not need to have
the same distribution trees according to some coding algorithm
in transmission, the multisession IP can provide effective
network resource utilization[1]. Besides, network coding has
an effect on load balance and bandwidth saving , which also
provide an alternative method as traffic engineering[4]. Using
linear programming formulations, the maximum throughput
that a multicast application can achieve with network coding
in unreliable ad hoc networks is 65% higher than conventional
multicast[5].
Another advantage for network coding is its superior performance
in reducing the number of retransmissions in lossy networks
compared to end-to-end automatic repeat request(ARQ)
in both low-loss and high-loss regimes. We hypothesize that
network coding achieves a logarithmic reliability gain with
respect to multicast group size compared to a simple ARQ
scheme[6].

5. Max-Flow Min-Cut Theorem
(From Wiki) The max-flow min-cut theorem is a statement in optimization theory about maximal flows in flow networks
The maximal amount of flow is equal to the capacity of a minimal cut.
The maximum flow in a network is dictated by its bottleneck.
[1] S.-Y. R. Li, R. W. Yeung, and N. Cai, “Linear network Coding”, IEEE Trans.

6. Graph Graph G(V,E): consists of a set and a set V of vertices
V consists of sources, sinks, and other nodes
A member e(u,v) of E has a to send information from u to v
V of vertices
E of edges.
capacity c(u,v) S A B D C T A B 3 2 4 S T D C

7. Min-Cuts and Max-Flows
Cuts: Partition of vertices into two sets
Size of a Cut = Total Capacity Crossing the Cut
Min-Cut: Minimum size of Cuts = 5
Max-Flows from S to T
Min-Cut = Max-Flow S A D 3 2 B C T 4 S A B D C T 3 2 4 3 2 3 2 3 2 1

8. Unicast | Multicast | Broadcast
Multicast communication is one-to-many.
Unicast communication is one-to-one.
Broadcast communication is one-to-all.
Broadcast
Multicast
Unicast

9. Throughput
The amount of data transferred from one place to another or processed in a specified amount of time.
Data transfer rates for disk drives and networks are measured in terms of throughput. Typically, throughputs are measured in kbps, Mbps and Gbps.

10. Wire vs Wireless Wire vs Wireless WIRE WIRELESS Traffic Pattern
An edge between two nodes means that the two nodes are physically connected.
Multicast communication is studied while network coding
of multiple unicast flows remains a largely unknown territory.
The traffic rate (or distribution) is predetermined and
do not change.
The channel of one particular edge is actually shared by other neighboring edge.
Unicast communication is the dominate traffic pattern.
Traffic rates are varies over time rather than constant.
Network Modeling
Wire:
1) Network Modeling
Currently, when we want to translate a real network
environment into a math model, we just translate the
network into a graph where an edge between two nodes
means that the two nodes are physically connected(or
the radio range allows the two nodes to communicate).
2) Traffic Pattern
Multicast communication is studied with network coding
of multiple unicast flows remains a largely unknown
territory. Moreover, the sender and receiver are fixed and
given.
3) Traffic Rate
The traffic rate (or distribution) is predetermined and
do not change.
Wireless:
1) Broadcast is a nature characteristic for wireless communications,
which means when the nodes are transmitting,
all the nodes that have direct edge linking with it are
affected. The channel of one particular edge is actually
shared by other neigbhoring edge. So the math model
of wireless network have more restriction than its wired
counterpart.
2) Unicast communication is the dominate traffic pattern. In
a random wireless environment, there are actually multiple
unicast session with different senders and receivers.
They do not signal their desire to communicate, but just
start sending packets.
3) Traffic rate are bursty and varies over time rather than
constant.
4) Connectivity in a wireless network is highly variable
due to changing channel and medium conditions. This
unpredictable nature makes the wireless network even
harder for modeling.
Traffic Pattern
Traffic Rate

11. Introduction
Definitions
Network
Coding
Why?
What?

12. What is NETWORK CODING
Network Coding is a field of information theory and coding theory and is a method of attaining maximum information flow in a network.
Network Coding Theory points out that it is necessary to consider encoding/decoding data on nodes in network in order to achieve optimal throughput.

13. Multicast Problem Butterfly Networks: Each edge’s capacity is 1.
Max-Flow from A to D = 2
Max-Flow from A to E = 2
Multicast Max-Flow from A to D and E = 1.5
Max-Flow for each individual connection is not achieved. A B C F G D E 1 1
0.5 1
0.5 1 1 1 1
0.5
0.5 1 1

14. With network coding, every sink obtains the maximum flow.
Ahlswede et al. (2000)
With network coding, every sink obtains the maximum flow. b1 b2 B C b1 b2 F
b1+b2
b1+b2 G D E
[2] Rudolf Ahlswede, Ning Cai, Shuo-Yen Robert Li, and Raymond W. Yeung. Network information flow.

15. COPE
COPE is an opportunistic approach to network coding to increase the throughput of wireless mesh networks.
COPE inserts a coding layer between the IP and MAC layers, which identifies coding opportunities and benefits from them by forwarding multiple packets in a single transmission.
[3] S. Katti, D. Katabi, W. Hu, and R. Hariharan, “The importance of being opportunistic: Practical network coding for wireless environments

16. An information exchange scenario
Relay
Alice
Bob
Bob’s packet
Alice’s packet
Alice’s packet
Bob’s packet
Multi-hop unicast requires 4 transmissions
Can we do better?

17. Can Network Coding help - An idea
XOR =
Relay
Alice
Bob
Bob’s packet
Alice’s packet
Alice’s packet
Bob’s packet
3 transmissions instead of 4
Saves bandwidth & power
33% throughput increase

18. Analog Network Coding
Analog network coding mixes signals instead of bits.
Wireless routers forward signals instead of packets. It achieves significantly higher throughput than both traditional wireless routing and prior work on wireless network coding(COPE).
Traditionally, interference is considered harmful. Wireless networks
strive to avoid scheduling multiple transmissions at the same time
in order to prevent interference. This paper adopts the opposite approach;
it encourages strategically picked senders to interfere. Instead
of forwarding packets, routers forward the interfering signals.
The destination leverages network-level information to cancel the interference
and recover the signal destined to it. The result is analog
network coding because it mixes signals not bits.
So, what if wireless routers forward signals instead of packets?
Theoretically, such an approach doubles the capacity of the canonical
2-way relay network. Surprisingly, it is also practical. We implement
our design using software radios and show that it achieves
significantly higher throughput than both traditional wireless routing
and prior work on wireless network coding.

19. Introduction
Definitions
Network
Coding
What?
Why?

20. Why is NETWORK CODING 1 2 3 Improve network throughput
Superior performance in reducing the number of retransmissions in lossy networks
The main advantage for network coding, as an original
purpose of this topic, is its high transmission capacity with the
max-flow, which means by employing network coding, the theoretical
upper bound of transmission rate can be achieved by
the sender. Due to the fact that all sessions do not need to have
the same distribution trees according to some coding algorithm
in transmission, the multisession IP can provide effective
network resource utilization[1]. Besides, network coding has
an effect on load balance and bandwidth saving , which also
provide an alternative method as traffic engineering[4]. Using
linear programming formulations, the maximum throughput
that a multicast application can achieve with network coding
in unreliable ad hoc networks is 65% higher than conventional
multicast[5].
Another advantage for network coding is its superior performance
in reducing the number of retransmissions in lossy networks
compared to end-to-end automatic repeat request(ARQ)
in both low-loss and high-loss regimes. We hypothesize that
network coding achieves a logarithmic reliability gain with
respect to multicast group size compared to a simple ARQ
scheme[6].
network coding
improves the robustness of the system and is able to smoothly
handle extreme situations where the server and nodes leave
the system 3
Is able to smoothly handle extreme situations where the server and nodes leave the system

21. Wireless Communication Project by Group 2
COPE
Wireless Communication Project
by Group 2

22. Opportunistic listening Opportunistic routing
Contents
General idea 1
Opportunistic listening 2
Opportunistic coding 3
Opportunistic routing 4

23. General idea of cope What is cope?
Cope is an opportunistic approach to network coding to increase throughput of wireless mesh networks.
The main characteristic of COPE is opportunism.
What is opportunism?

24. Opportunistic routing
General idea of cope
Opportunistic listening
Opportunistic coding
Opportunistic routing

25. General idea of cope A C B E D

26. Opportunistic Listening
1.Nodes have opportunities to hear packets even when they are not the intended receiver.
2.Nodes store all the packets they hear within a limited time slot T.
3.Nodes send reception reports to their neighbors, helping to create more coding opportunities.

27. E1:B to E A1:D to A pool A Que A B E D C B E Output E1 E2 E3 pool D

28. E1:B to E A1:D to A pool A Que A B E D E1 C B E E1 Output E2 E3 pool

29. E1:B to E A1:D to A pool E1 A Que A B E D C B E E1 Output E2 E3 pool

30. E1:B to E A1:D to A pool E1 I have E1 A Que E1 A B E D C B E Output E2

31. E1:B to E A1:D to A pool E1 A Que E1 A B E D C B E Output E2 E3 pool D

32. E1:B to E A1:D to A pool E1 A Que E1 A B E D C B E Output E2 E3 pool

33. E1:B to E A1:D to A pool E1 A Que E1 A B E D C B A1 E A1 A1 Output E2

34. E1:B to E A1:D to A pool E1 A Que E1 A1 A B E D C B E I have A1 Output

35. E1:B to E A1:D to A Node A have packet E1 Node A want packet A1
So I can give Node A
E1+A1
Coding
opportunity
Node E have packet A1
Node E want packet E1
So I can give Node E
E1+A1
pool E1 A
Que E1 A1 A B E D C B E
Output E2 E3
pool A1
E1:B to E
A1:D to A D
Output A2 A3

36. E1:B to E A1:D to A Coding opportunity pool E1 A Que E1 A1 A B E D E1
Output E2 E3
pool A1
E1:B to E
A1:D to A D
Output A2 A3

37. E1:B to E A1:D to A Coding opportunity pool E1 A Que A E1 B E A1 D
Output E2 E3
pool A1
E1:B to E
A1:D to A D
Output A2 A3

38. E1:B to E A1:D to A pool E1 A Que A E1 B E A1 D E1+A1 E1+A1 C B E
Output E2 E3
pool A1
E1:B to E
A1:D to A D
Output A2 A3

39. E1:B to E A1:D to A pool E1 E1+(E1+A1)=A1 A1 received! E1+A1 A Que A
Output E2 E3
pool A1
A1+(E1+A1)=E1 E1 received!
E1:B to E
A1:D to A D
Output A2 A3

40. Opportunistic Coding
How can the node decide which packets needed to XOR together?
Each node should answer this question based on local information and without consulting with other nodes.
Each node has several options to decide which packets to XOR together to gain the maximum throughput.

41. Opportunistic Coding C A B D

42. Opportunistic Coding Packets Next Hops B’s queue Node P1 A P4 P3 P2 P1

43. Opportunistic Coding P1----- A P2-----B P3----- C P4----- D + = =
Packet node
P A
P2-----B
P C
P D P1 + = P2 P4 P1 P4 P3 P2 P1 C A B P4 P3 D = P1 + P2 P3 P1
Bad coding decision

44. Opportunistic Coding P1----- A P2-----B P3----- C P4----- D + = =
Packet node
P A
P2-----B
P C
P D P1 + = P3 P4 P1 P4 P3 P2 P1 C A B P4 P3 D = P1 + P3 P3 + = P1 P3 P1
Better coding decision

45. Opportunistic Coding P1----- A P2-----B P3----- C P4----- D + + =
Packet node
P A
P2-----B
P C
P D P4 + P1 + = P3 P4 P1 P4 P3 P2 P1 C A B P1 + P3 + = P4 P4 P3 D P4 + P3 + = P1 = P1 + P3 + P4 P3 P1
Best coding decision

46. Opportunistic Coding
Theory:
To transmit n packets, p1,…,pn, to n receivers, r1,…,rn, a node can XOR the n packets together only if each intended receiver ri has all n-1 packets pj for j not equals to i.

47. ri Opportunistic Coding P1…Pi-1,Pi+1…Pn ri-1 :XOR P1 to Pn Pi-1 Pi P3
rn-2 P2
Pn-1
P1…Pi-1,Pi+1…Pn
P1…Pi-2,Pi…Pn r2
rn-1 P1 Pn r1 rn
:XOR P1 to Pn

48. Opportunistic Coding
Whenever a node has a chance to transmit a packet, it tries to find the largest n that satisfies the above rule.
The node tries to maximize the number of packets delivered in a single transmission.

49. Opportunistic Routing
Can we further reduce the
number of transmissions?
1.The path is stored in the packet itself.
2.Check the path, find the opportunities to routing.

50. Opportunistic Routing
Path: SABD
Reception
report
Destination
source A S B D

51. Conclusion Main idea of cope: 1.Overhear on the medium.
2.Learn the status of its neighbors.
3.Detect coding opportunities.
4.Code as long as the receivers can decode.

52. COPE IMPLEMENTATION & PERFORMANCE

53. Agenda Data Structure for each node Pseudo broadcast mechanism
COPE layer
COPE header
Gain

54. DATA STRUCTURE

55. A SCENARIO Packet Delivery RR Reception report P IP packet AckB P RR
Reception report C P P P P D P P P
IP packet
Ack G
IP acknowledge E F P P

56. A SCENARIO(II) Packet acknowledge RR Reception report P IP packet AckB
Ack RR
Reception report C
Ack D P
IP packet
Ack G
IP acknowledge E
Ack
Ack F

57. A SCENARIO(III) Reception Report RR Reception report P IP packet AckB RR RR RR
Reception report C RR RR RR RR D P RR RR
IP packet
Ack G
IP acknowledge RR RR E RR RR RR F RR RR

58. DATA STRUCTURE RR Reception report P IP packet Ack IP acknowledge A BF G RR
Reception report P
IP packet
Ack
IP acknowledge

59. DATA STRUCTURE In Node C Output Queue： Retransmission pool：
Upper Layer
Output Queue： P6 P5 P4 P3 P2 P1 P1
Retransmission pool： RR
Packet Transmitted
Reception report
IP packet
Ack
IP acknowledge

60. DATA STRUCTURE In Node C Output Queue： Retransmission pool：
Upper Layer
Output Queue：
Ack P6 P5 P4 P3 P2
Retransmission pool：
P1 can be deleted
Ack Received RR P1 P1
Reception report
If ack is not received after a long time
P1 returns to Output Queue to wait
another transmission opportunity
IP packet
IP acknowledge

61. DATA STRUCTURE In Node C Output Queue： Retransmission pool：
Upper Layer
Output Queue： Px P6 P5 P4 P3 P2 P1
Retransmission pool：
Px is head for node D
Not C.
Reception report
Opportunity Listening Queue：
RR：a,b,c,d,x
IP packet Pa Pb Pc Pd
Ack
If node C receive a neighbor’s packet whose destination is not C,
Node C just put the packet into the above queue.
Periodical,Each node inform its neighbor about what they’ve got in its Opportunity Listenning Queue. That is , Reception Report
IP acknowledge

62. DATA STRUCTURE In Node C …… ………………………… Output Queue：
RR from A
Upper Layer
Output Queue： P6 P5 P4 P3 P2 P1
Retransmission pool：
Reception report
Opportunity Listening Queue：
IP packet Pa Pb Pc Pd Px
Neighbors’ virtual Queue：
A queue
B queue
D queue ……
…………………………
Ack
IP acknowledge

63. DATA STRUCTURE In Node C …… ………………………… Output Queue：
Upper Layer
Output Queue： P6 P5 P4 P3 P2 P1
Retransmission pool：
Used for decoding
Reception report
Opportunity Listening Queue：
IP packet Pa Pb Pc Pd Px
Neighbors’ virtual Queue：
A queue
B queue
D queue ……
…………………………
Ack
Used for Coding
IP acknowledge
RR from A
RR from B
RR from D

64. DATA STRUCTURE
LOGIC
Packet headed to the same destination can never be coded together
It is not necessary to code a packet in opportunity listening queue
It is not necessary to transmit a packet when it is received again from its destination
A node can decode a packet which is coded with one of the packet he once send

65. DATA STRUCTURE Output Queue： Retransmission pool：
Upper Layer
Output Queue： P6 P5 P4 P3 P2 P1 P1 P1
Retransmission pool：
Opportunity Listening Queue：

66. DATA STRUCTURE 4 PARTS: Output Queue Retransmission Pool
Opportunity Listening Queue
Neighbor’s Virtual Queue

67. PSEUDO BROADCAST MECHANISM
Laptop2
Both laptop2 and laptop3 are the intended
Receiver of packet from laptop1
Laptop3
Laptop1
[4] Katti S, Rahul H, Hu WJ, Katabi D, Muriel M, Crowcroft J. XORs in the air: Practical wireless networking.

68. PSEUDO BROADCAST Current WLAN medium access mechanism 802.11 MAC:
DCF CSMA/CA(mandatory)
-Distributed Foundation Wireless MAC
-Collision avoidance via randomized back-off
-ACK packet for acknowledgement(not for broad cast)
DCF RTS/CTS(optional)
-avoids hidden terminal and exposed terminal
Point Coordination Function(infrastructure mode)
How to apply COPE? Opportunistic Listenning?
Multiple intended receiver?
All neighbors can receive?
BROADCAST

69. PSEUDO BROADCAST 802.11 Broadcast mode: POOR RELIABILITY 802.11 MAC:
DCF CSMA/CA? Yes
Back off? No
DCF RTS/CTS? No
ACK? No
POOR RELIABILITY

70. PSEUDO BROADCAST PSEUDO BROADCAST SOLUTION?
MAC:
Develop a brand-new MAC access protocol
which is suitable for COPE broadcast
Hard to implement…..Unrealistic….
WLAN MAC already pervasive
PSEUDO BROADCAST
Add a new layer on top the current
MAC layer to make link-to-link broadcast
reliable.
Feasible!

71. PSEUDO BROADCAST Reliability 1. ACK 2. Retransmission(ACK timeout)
3. Multiple Intended Receiver
DIFS& backoff
Multi receiver
One receiver
SIFS
SIFS
Synchronous Acknowledgement does not work!
Receiver can send ACK packet asynchronously
Packet
Packet
ACK
ACK
We can treat Ack packet as a normal packet, ACK packets
from different Receivers also go through the DIFS and back off
procedure to avoid collision
2. Or we can piggy back on packet travelling in the reverse direction
ACK
ACK
ACK
ACK
Collision!

72. PSEUDO BROADCAST What should be contained in COPE packet?
1. XORed(coded) packet with multiple receivers
2. uncoded packet with multiple receivers(all neighbors)
3. Reception Report with multiple receivers (all neighbors)
4. Packet Acknowledge with certain receiver
Later on we will give a detailed description about the COPE packet format

73. COPE LAYER Where does cope layer lies in? Network layer and MAC layer.
COPE layer is a very slim layer lies between
Network layer and MAC layer.
Network Layer
COPE layer
MAC layer
COPE layer process the network layer packets before
they are send to MAC layer
COPE layer process the MAC layer frames before they
Are send to Network layer
It is the COPE layer where the
four data structure:
Output Queue,
Retransmission pool,
Opportunistic listening pool
And neighbors’ virtual queue lies in.

74. COPE LAYER Sender side Get a packet from network layer Network Layer
MAC layer
Get a packet from network layer
Add the packet into Output Queue
Encode if possible

75. COPE LAYER Sender side Get a packet from network layer
Add the packet into Output Queue
Encode if possible
Network Layer
COPE layer
MAC layer
Yes
Encoded?
Add packet to Retransmission pool No
Piggy back Reception Report
If the packet is not encoded, then the destination MAC address will be the receiver MAC address, and the ACK-retransmission mechanism will be cared about by MAC layer.
If the packet is encoded, which means it has many intended receivers, the destination MAC address will be FFFF.FFFF.FFFF, which is a broadcast frame in MAC layer, as mentioned before, MAC layer broadcast have no retransmission mechanism, we will need COPE layer to concern about the asynchronous retransmission so as to guarantee the reliable transmission.
Piggy back asynchronous acknowledge
To MAC layer

76. COPE LAYER receiver side Yes Add to opportunity listening pool
Am I the next hop?
Network Layer
COPE layer
MAC layer No
Record RR in neighbors’ virtual queue
Extract Reception Report
If there is any
Delete correponding packets in retransmission pool
Extract acks for me
If there is any
Get a packet from MAC

77. COPE LAYER receiver side Send into Output Queue
Deliver to Network layer
Network Layer
COPE layer
MAC layer No
Yes
Am I destination?
Decode and schedule Ack No
Yes
This packet is encoded?
Decodable?
Yes
I am the next hop

78. COPE HEADER MAC header Encoded Packet ID Encoded packet number
Reception
Report(Packet ID)
Asynchronous ACK
Encoded packet number
Enocded packet IDs
Intended receiver s
COPE header
Number of packets received
Packets ID
IP header
Received packets’ ID
ACK receiver
Data Frame

79. Coding Gain
[3] S. Katti, D. Katabi, W. Hu, and R. Hariharan, “The importance of being opportunistic: Practical network coding for wireless environments

80. Coding Gain
[4] Katti S, Rahul H, Hu WJ, Katabi D, Muriel M, Crowcroft J. XORs in the air: Practical wireless networking.

81. Coding Gain
[4] Katti S, Rahul H, Hu WJ, Katabi D, Muriel M, Crowcroft J. XORs in the air: Practical wireless networking.

82. ANALOG NETWORK CODING

83. Alice-Bob topology
[5] Katti S, Gollakota S, Katabi D: Embracing Wireless Interference: Analog Network Coding

84. Traditional Approach Alice transmits Bob transmits Router forwards
Time slot 1
Time slot 2
Time slot 3
Time slot 4

85. Digital Network Coding
Alice transmits
Bob transmits
Router forwards
Alice
Router
Bob
Time slot 1
Time slot 2
Time slot 3

86. Analog Network Coding Alice & Bob transmits Router forwards Alice
Time slot 1
Time slot 2

87. How can we do it?
Alice
Bob

88. How can we do it?(Cont.)
Alice
REC
Alice
SND

89. How can we do it?(Cont.) What will Alice do?
Demodulate and do some signal processing
Note the starting bit for interferenced signal
Do XOR for interferenced signal

90. How can we do it?(Cont.) Smart Alice!
She must learn the characters of the wireless channel
She must store the packets which already sent by herself
She may do the XOR job effectively

91. MSK Easier? Choose the right modulation method
Some experiments are already done by using Software Defined Radios (SDR).
Successful results showed that we got significant throughput gains compared to COPE and traditional ways.

92. Future investigation is still needed ! ! !
Drawbacks
Vulnerable to noises
Difficult to use in more complex topology networks
Future investigation is still needed ! ! !

93. What we may learn from ANC?
Think differently
Electrical engineer & computer scientist
PHY layer & MAC layer & Network layer

94. Wireless Communication Project by Group 2
Thanks for enjoying!
Wireless Communication Project
by Group 2

95. Wireless Communication Project by Group 2
Q&A
Wireless Communication Project
by Group 2