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Reliable Physical Layer Network Coding
When two or more users in a wireless network transmit simultaneously, their
electromagnetic signals are linearly superimposed on the channel. As a result,
a receiver that is interested in one of these signals sees the others as
unwanted interference. This property of the wireless medium is typically viewed
as a hindrance to reliable communication over a network. However, using a
recently developed coding strategy, interference can in fact be harnessed for
network coding. In a wired network, (linear) network coding refers to each
intermediate node taking its received packets, computing a linear combination
over a finite field, and forwarding the outcome towards the destinations. Then,
given an appropriate set of linear combinations, a destination can solve for
its desired packets. For certain topologies, this strategy can attain
significantly higher throughputs over routing-based strategies. Reliable
physical layer network coding takes this idea one step further: using
judiciously chosen linear error-correcting codes, intermediate nodes in a
wireless network can directly recover linear combinations of the packets from
the observed noisy superpositions of transmitted signals. Starting with some
simple examples, this survey explores the core ideas behind this new technique
and the possibilities it offers for communication over interference-limited
wireless networks.Comment: 19 pages, 14 figures, survey paper to appear in Proceedings of the
IEE
Reliable Packet Streams with Multipath Network Coding
With increasing computational capabilities and advances in robotics, technology is at the verge of the next industrial revolution. An growing number of tasks can be performed by artificial intelligence and agile robots. This impacts almost every part of the economy, including agriculture, transportation, industrial manufacturing and even social interactions. In all applications of automated machines, communication is a critical component to enable cooperation between machines and exchange of sensor and control signals.
The mobility and scale at which these automated machines are deployed also challenges todays communication systems. These complex cyber-physical systems consisting of up to hundreds of mobile machines require highly reliable connectivity to operate safely and efficiently. Current automation systems use wired communication to guarantee low latency connectivity. But wired connections cannot be used to connect mobile robots and are also problematic to deploy at scale. Therefore, wireless connectivity is a necessity. On the other hand, it is subject to many external influences and cannot reach the same level of reliability as the wired communication systems.
This thesis aims to address this problem by proposing methods to combine multiple unreliable wireless connections to a stable channel. The foundation for this work is Caterpillar Random Linear Network Coding (CRLNC), a new variant of network code designed to achieve low latency. CRLNC performs similar to block codes in recovery of lost packets, but with a significantly decreased latency. CRLNC with Feedback (CRLNC-FB) integrates a Selective-Repeat ARQ (SR-ARQ) to optimize the tradeoff between delay and throughput of reliable communication. The proposed protocol allows to slightly increase the overhead to reduce the packet delay at the receiver. With CRLNC, delay can be reduced by more than 50 % with only a 10 % reduction in throughput. Finally, CRLNC is combined with a statistical multipath scheduler to optimize the reliability and service availability in wireless network with multiple unreliable paths. This multipath CRLNC scheme improves the reliability of a fixed-rate packet stream by 10 % in a system model based on real-world measurements of LTE and WiFi.
All the proposed protocols have been implemented in the software library NCKernel. With NCKernel, these protocols could be evaluated in simulated and emulated networks, and were also deployed in several real-world testbeds and demonstrators.:Abstract 2
Acknowledgements 6
1 Introduction 7
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.2 Use Cases and Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.3 Opportunities of Multipath . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.4 Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2 State of the Art of Multipath Communication 19
2.1 Physical Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.2 Data Link Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3 Network Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.4 Transport Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.5 Application Layer and Session Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.6 Research Gap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3 NCKernel: Network Coding Protocol Framework 27
3.1 Theory that matters! . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.2 Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.3 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.3.1 Socket Buffers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.3.2 En-/Re-/Decoder API . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.3.3 Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.3.4 Timers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.3.5 Tracing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.4 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.5 Protocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4 Low-Latency Network Coding 35
4.1 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
4.2 Random Linear Network Coding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
4.3 Low Latency Network Codes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.4 CRLNC: Caterpillar Random Linear Network Coding . . . . . . . . . . . . . . . . . . 38
4.4.1 Encoding and Packet Format . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
4.4.2 Decoding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.4.3 Computational Complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4.5 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
4.5.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
4.5.2 Simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.5.3 Packet Loss Probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
4.5.4 Delay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
4.5.5 Window Size Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
5 Delay-Throughput Tradeoff 55
5.1 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.2 Network Coding with ARQ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
5.3 CRLNC-FB: CRLNC with Feedback . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
5.3.1 Encoding and Packet Format . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
5.3.2 Decoding and Feedback . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
5.3.3 Retransmissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
5.4 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
5.4.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
5.4.2 Simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
5.4.3 Systematic Retransmissions . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
5.4.4 Coded Packet Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
5.4.5 Comparison with other Protocols . . . . . . . . . . . . . . . . . . . . . . . . 67
5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
6 Multipath for Reliable Low-Latency Packet Streams 73
6.1 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
6.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
6.3 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.3.1 Traffic Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.3.2 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.3.3 Channel Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
6.3.4 Reliability Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
6.4 Multipath CRLNC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
6.4.1 Window Size for Heterogeneous Paths . . . . . . . . . . . . . . . . . . . . . 77
6.4.2 Packet Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
6.5 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
6.5.1 Simulator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
6.5.2 Preliminary Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
6.5.3 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
6.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
7 Conclusion 94
7.1 Results and Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
7.2 Future Research Topics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Acronyms 99
Publications 101
Bibliography 10
Compute-and-Forward: Harnessing Interference through Structured Codes
Interference is usually viewed as an obstacle to communication in wireless
networks. This paper proposes a new strategy, compute-and-forward, that
exploits interference to obtain significantly higher rates between users in a
network. The key idea is that relays should decode linear functions of
transmitted messages according to their observed channel coefficients rather
than ignoring the interference as noise. After decoding these linear equations,
the relays simply send them towards the destinations, which given enough
equations, can recover their desired messages. The underlying codes are based
on nested lattices whose algebraic structure ensures that integer combinations
of codewords can be decoded reliably. Encoders map messages from a finite field
to a lattice and decoders recover equations of lattice points which are then
mapped back to equations over the finite field. This scheme is applicable even
if the transmitters lack channel state information.Comment: IEEE Trans. Info Theory, to appear. 23 pages, 13 figure
A Novel Network Coded Parallel Transmission Framework for High-Speed Ethernet
Parallel transmission, as defined in high-speed Ethernet standards, enables
to use less expensive optoelectronics and offers backwards compatibility with
legacy Optical Transport Network (OTN) infrastructure. However, optimal
parallel transmission does not scale to large networks, as it requires
computationally expensive multipath routing algorithms to minimize differential
delay, and thus the required buffer size, optimize traffic splitting ratio, and
ensure frame synchronization. In this paper, we propose a novel framework for
high-speed Ethernet, which we refer to as network coded parallel transmission,
capable of effective buffer management and frame synchronization without the
need for complex multipath algorithms in the OTN layer. We show that using
network coding can reduce the delay caused by packet reordering at the
receiver, thus requiring a smaller overall buffer size, while improving the
network throughput. We design the framework in full compliance with high-speed
Ethernet standards specified in IEEE802.3ba and present solutions for network
encoding, data structure of coded parallel transmission, buffer management and
decoding at the receiver side. The proposed network coded parallel transmission
framework is simple to implement and represents a potential major breakthrough
in the system design of future high-speed Ethernet.Comment: 6 pages, 8 figures, Submitted to Globecom201
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