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Submission doc.: IEEE 802.11-16/0317r0 March 2016 R.W. Yeung & S. Yang, CUHKSlide 1 BATS: Network Coding for Wireless Relay Networks Date: 2016-03-14 Authors:

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1 Submission doc.: IEEE 802.11-16/0317r0 March 2016 R.W. Yeung & S. Yang, CUHKSlide 1 BATS: Network Coding for Wireless Relay Networks Date: 2016-03-14 Authors:

2 Submission doc.: IEEE 802.11-16/0317r0 Highlights BATS code stands for ‘BATched Sparse code’ The most advanced network coding technology for wireless networks Significantly improves the multi-hop relay throughput, and/or reduces delay Throughput benefits in the following applications: Multi-hop transmission Multicast Content distribution Internet of things Slide 2R.W. Yeung & S. Yang, CUHK March 2016

3 Submission doc.: IEEE 802.11-16/0317r0 Outline Introduction to BATS Code Protocol Design Implementations Applications in Wireless Relay Networks Slide 3R.W. Yeung & S. Yang, CUHK March 2016

4 Submission doc.: IEEE 802.11-16/0317r0 1. Introduction to BATS code March 2016 R.W. Yeung & S. Yang, CUHKSlide 4

5 Submission doc.: IEEE 802.11-16/0317r0 Loss & Relay are Inevitable WLAN has more and more interference in both 2.4GHz and 5GHz  Higher loss due to interference Higher frequency in millimeter wave spectrum, e.g., 60 GHz to be adopted in 802.11AD and 5G  Higher loss due to obstacles  Relay for non-line-of-sight transmission Low power transmission in IoT  Higher loss due to power constraints  Relay for long distance transmission Slide 5R.W. Yeung & S. Yang, CUHK March 2016

6 Submission doc.: IEEE 802.11-16/0317r0 Multi-hop Networks with Packet Loss Slide 6R.W. Yeung & S. Yang, CUHK March 2016 STR1R1 R2R2 R3R3 All links have a packet loss rate 10% Intermediate OperationMaximum Rate Forwarding0.9 n Network coding0.9 n is number of hops.

7 Submission doc.: IEEE 802.11-16/0317r0 Random Linear Network Coding High encoding/decoding complexity High intermediate node caching/recoding complexity High coefficient vector overhead Slide 7R.W. Yeung & S. Yang, CUHK March 2016

8 Submission doc.: IEEE 802.11-16/0317r0 Low Complexity Linear Network Coding BATS codes [YY11, YY14] Combine fountain codes with random linear network coding Rateless codes Coding-based chunked codes [Tang12, MAB12, YT14] Using LDPC codes to construct random linear network coding Fixed-rate codes Modified fountain codes for network coding [PFS05, CHKS09, GS08, TF11] Network coding changes the degree distribution Cannot reduce coefficient vector overhead Slide 8R.W. Yeung & S. Yang, CUHK March 2016

9 Submission doc.: IEEE 802.11-16/0317r0 BATS Code in a Nutshell A BATS code includes an outer code and an inner code The outer code is a matrix fountain code at the source node The inner code consists of random linear network coding at the intermediate network nodes March 2016 R.W. Yeung & S. Yang, CUHKSlide 9

10 Submission doc.: IEEE 802.11-16/0317r0 Outer Code 1.Obtain a degree d by sampling a degree distribution Ψ 2.Pick d distinct input packets randomly 3.Generate a batch of M coded packets using the d packets Slide 10R.W. Yeung & S. Yang, CUHK March 2016 b1b1 b2b2 b7b7 b3b3 b4b4 b5b5 b6b6 X1X1 X2X2 X3X3 Encoding of batches: X i = B i G i

11 Submission doc.: IEEE 802.11-16/0317r0 Inner Code The batches traverse the network. Encoding at the intermediate nodes forms the inner code. Linear network coding is applied in a causal manner within a batch. Slide 11R.W. Yeung & S. Yang, CUHK March 2016 ST Network with linear network coding Transmission of batches: Y i = X i H i …, X 3, X 2, X 1 …, Y 3, Y 2, Y 1

12 Submission doc.: IEEE 802.11-16/0317r0 Belief Propagation Decoding Slide 12R.W. Yeung & S. Yang, CUHK March 2016 1.Find a check node i with degree i = rank(G i H i ) 2.Decode the ith batch 3.Update the decoding graph. Repeat 1. b1b1 b2b2 b7b7 b3b3 b4b4 b5b5 b6b6 G1H1G1H1 G2H2G2H2 Associated with a batch is a system of linear equations: Y i = X i H i = B i G i H i = B i G i H i Associated with a batch is a system of linear equations: Y i = X i H i = B i G i H i = B i G i H i G3H3G3H3

13 Submission doc.: IEEE 802.11-16/0317r0 Multi-Hop Transmission Slide 13R.W. Yeung & S. Yang, CUHK March 2016 10 Mbps 9 Mbps 8.1Mbps 7.3 Mbps 6.6 Mbps Fountain Code 10% loss 10 Mbps BATS Code 10% loss Traditional approaches accumulate packet loss in multi-hop transmission, while BATS code compensates packet loss hop-by-hop.

14 Submission doc.: IEEE 802.11-16/0317r0 Comparison of BATS and Fountain Slide 14R.W. Yeung & S. Yang, CUHK March 2016 For a network of L hops each with loss rate e, throughput of BATS =1-e, vs throughput of Fountain =(1-e) L.

15 Submission doc.: IEEE 802.11-16/0317r0 BATS vs RLNC Much lower computation complexity (99.9% lower) Much smaller coding overhead (98% smaller) Slide 15R.W. Yeung & S. Yang, CUHK March 2016 Coding overhead Encoding complexity Decoding complexity Intermediate node caching BATSO(1) RLNCO(K) O(K 2 )O(K) * RLNC stands for Random Linear Network Coding ** For transmitting 1000 packets of size 1K bytes

16 Submission doc.: IEEE 802.11-16/0317r0 Achievable Rates of BATS Codes Slide 16R.W. Yeung & S. Yang, CUHK March 2016

17 Submission doc.: IEEE 802.11-16/0317r0 Analysis of BATS Codes Asymptotic analysis provides An approach to characterize the achievable rates of BATS codes An approach to optimize the degree distribution Finite-length analysis enables Exact characterization of BP/inactivation decoding performance Fine-tuning of the degree distributions Slide 17R.W. Yeung & S. Yang, CUHK March 2016

18 Submission doc.: IEEE 802.11-16/0317r0 Inactivation Decoding Inactivation decoding can significantly reduce the coding overhead for BATS code with short block lengths Slide 18R.W. Yeung & S. Yang, CUHK March 2016 No. of Packets Coding overheadNo. of Inactivation Ave.MaxMinAve.MaxMin 16002.041609411972 80006.30770215.5268179 1600026.5810890352.2379302 Simulation results of inactivation decoding (M=32, q=256)

19 Submission doc.: IEEE 802.11-16/0317r0 Inner Code Design Systematic adaptive recoding Reduce computation cost Increase the achievable rate with the same batch size Interleaved transmission Improve the performance with burst loss No delay accumulation at intermediate nodes Slide 19R.W. Yeung & S. Yang, CUHK March 2016

20 Submission doc.: IEEE 802.11-16/0317r0 2. Protocol Design March 2016 R.W. Yeung & S. Yang, CUHKSlide 20

21 Submission doc.: IEEE 802.11-16/0317r0 BATS Protocol March 2016 R.W. Yeung & S. Yang, CUHKSlide 21 PHY BATS enabled MAC BATS enabled IP BATS enabled TCP BATS encoding BATS decoding Batch forwarding Input file output file BATS enabled APP Existing MAC Existing IP Existing TCP

22 Submission doc.: IEEE 802.11-16/0317r0 3. Implementation March 2016 R.W. Yeung & S. Yang, CUHKSlide 22

23 Submission doc.: IEEE 802.11-16/0317r0 BATS Code Implementations BATS recoding has been implemented using low-end wireless routers. 10 Mbps can be achieve using a single core Using a particular CPU, >500Mbps decoding throughput can be achieved. Gbps throughput can be achieved using CPU, GPU or hardware accelerator. Slide 23R.W. Yeung & S. Yang, CUHK March 2016

24 Submission doc.: IEEE 802.11-16/0317r0 March 2016 R.W. Yeung & S. Yang, CUHKSlide 24

25 Submission doc.: IEEE 802.11-16/0317r0 4. Applications in Wireless Relay Networks March 2016 R.W. Yeung & S. Yang, CUHKSlide 25

26 Submission doc.: IEEE 802.11-16/0317r0 Application: Multi-hop Networks Satellite Video/signal relays for automobiles Video relays for traffic surveillance Wireless access point extender HDMI repeater March 2016 R.W. Yeung & S. Yang, CUHKSlide 26

27 Submission doc.: IEEE 802.11-16/0317r0 Application: Multicast Delivery Shared video in conference rooms Shared video in concerts/sport games/classrooms TV broadcasting with relays March 2016 R.W. Yeung & S. Yang, CUHKSlide 27

28 Submission doc.: IEEE 802.11-16/0317r0 Application: Internet of Things Device-to-device networks Sensor networks Mobile networks Wireless relays for drones March 2016 R.W. Yeung & S. Yang, CUHKSlide 28

29 Submission doc.: IEEE 802.11-16/0317r0 References [YY11] S. Yang and R. W. Yeung, “Coding for a network coded fountain,” ISIT 2011. [YY14] S. Yang and R. W. Yeung, “Batched sparse codes,” IEEE Trans. Inform. Theory, vol. 60, no. 9, Sep. 2014. [Tang12] B. Tang, S. Yang, Y. Yin, B. Ye and S. Lu, “Expander graph based overlapped chunked codes,” ISIT 2012. [YT14] S. Yang and B. Tang, “From LDPC to chunked network codes,” ITW 2014. [YZ15] S. Yang and Q. Zhou, “Tree Analysis of BATS Codes," IEEE Comm. Letters 2016. [NY13] T-C Ng and S. Yang, “Finite-Length Analysis of BATS Codes,” NetCod 2013. [YNY15] S. Yang, T-C Ng and R.W. Yeung, “Finite-Length Analysis of BATS Codes,” ArXiv 2016. [Huang14] Q. Huang, K. Sun, X. Li, and D. O. Wu, “Just fun: A joint fountain coding and network coding approach to loss- tolerant information spreading,” Mobile Ad Hoc 2014. [YYCY14] S. Yang, R. W. Yeung, H. F. Cheung, and H. H. Yin, “BATS: Network coding in action,” Allerton 2014. [XGGC14] X. Xu, P. K. M. Gandhi, Y. L. Guan, and P. H. J. Chong, “Two-phase cooperative broadcasting based on batched network code,” arXiv 2015. Slide 29R.W. Yeung & S. Yang, CUHK March 2016

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