Decoding 802.11 Collisions Shyamnath Gollakota Dina Katabi.

Slides:



Advertisements
Similar presentations
1 Retransmission Repeat: Simple Retransmission Permutation Can Resolve Overlapping Channel Collisions Li (Erran) Li Bell Labs, Alcatel-Lucent Joint work.
Advertisements

SoftCast+ Scalable Robust Mobile Video
Chorus: Collision Resolution for Efficient Wireless Broadcast Xinyu Zhang, Kang G. Shin University of Michigan 1.
Opportunistic Routing Is Missing Its Opportunities! Sachin Katti & Dina Katabi.
Symbol Level Network Coding By Sachin Katti, Dina Katabi, Hari Balakrishnan, Muriel Medard Sigcomm 2008.
Interference Alignment and Cancellation EE360 Presentation Omid Aryan Shyamnath Gollakota, Samuel David Perli and Dina Katabi MIT CSAIL.
Analog Network Coding Sachin Katti Shyamnath Gollakota and Dina Katabi.
Medium Access Issues David Holmer
Physical Layer Security Made Fast and Channel-Independent Shyamnath Gollakota Dina Katabi.
MIMO As a First-Class Citizen in Kate C.-J. Lin Academia Sinica Shyamnath Gollakota and Dina Katabi MIT.
– Wireless PHY and MAC Stallings Types of Infrared FHSS (frequency hopping spread spectrum) DSSS (direct sequence.
Strider : Automatic Rate Adaptation & Collision Handling Aditya Gudipati & Sachin Katti Stanford University 1.
Network Coding Testbed Using Software-Defined Radio Abstract In current generation networks, network nodes operate by replicating and forwarding the packets.
SUCCESSIVE INTERFERENCE CANCELLATION IN VEHICULAR NETWORKS TO RELIEVE THE NEGATIVE IMPACT OF THE HIDDEN NODE PROBLEM Carlos Miguel Silva Couto Pereira.
U NIVERSITY OF M ASSACHUSETTS, A MHERST Department of Computer Science Leveraging Interleaved Signal Edges for Concurrent Backscatter by Pan Hu, Pengyu.
Living with Interference in Unmanaged Wireless Environments David Wetherall, Daniel Halperin and Tom Anderson Intel Research & University of Washington.
Collision Aware Rate Adaptation (CARA) Bob Kinicki Computer Science Department Computer Science Department Advanced Computer.
Hidden Terminal based Attack, Diagnosis and Detection Yao Zhao, Leo Zhao, Yan Chen Lab for Internet & Security Tech, Northwestern Univ.
5-1 Data Link Layer r Today, we will study the data link layer… r This is the last layer in the network protocol stack we will study in this class…
Dynamic Rate Adaptation in IEEE WLANs Bob Kinicki PEDS March 26, 2007 PEDS March 26, 2007.
SourceSync: A Distributed Architecture for Sender Diversity Hariharan Rahul Haitham Hassanieh Dina Katabi.
Combating Cross-Technology Interference Shyamnath Gollakota Fadel Adib Dina Katabi Srinivasan Seshan.
Overcoming the Antennas-Per-AP Throughput Limit in MIMO Shyamnath Gollakota Samuel David Perli and Dina Katabi.
Z IG Z AG D ECODING : C OMBATING H IDDEN T ERMINALS IN W IRELESS N ETWORKS Shyamnath Gollakota and Dina Katabi MIT CSAIL SIGCOMM 2008 Presented by Paul.
Diagnosing Wireless Packet Losses in : Separating Collision from Weak Signal Shravan Rayanchu, Arunesh Mishra, Dheeraj Agrawal, Sharad Saha, Suman.
RCTC: Rapid Concurrent Transmission Coordination in Full Duplex Wireless Networks Wenjie Zhou, Kannan Srinivasan, Prasun Sinha Department of Computer Science.
Wireless Networking & Mobile Computing CS 752/852 - Spring 2012 Tamer Nadeem Dept. of Computer Science Lec #7: MAC Multi-Rate.
Harnessing Mobile Multiple Access Efficiency with Location Input Wan Du * and Mo Li School of Computer Engineering Nanyang Technological University, Singapore.
Wireless Medium Access. Multi-transmitter Interference Problem  Similar to multi-path or noise  Two transmitting stations will constructively/destructively.
Link Layer: Wireless Mesh Networks Capacity Y. Richard Yang 11/13/2012.
Full-duplex Backscatter for
Understanding the Real-World Performance of Carrier Sense MIT Computer Science and Artificial Intelligence Laboratory Networks and Mobile Systems
AutoMAC : Rateless Wireless Concurrent Medium Access Aditya Gudipati, Stephanie Pereira, Sachin Katti Stanford University.
Network Coding Testbed Jeremy Bergan, Ben Green, Alex Lee.
Automatic Rate Adaptation Aditya Gudipati & Sachin Katti Stanford University 1.
Next Generation n Dina Katabi Jointly with Kate Lin and Shyamnath Gollakota.
MZig: Enabling Multi-Packet Reception in ZigBee Linghe Kong, Xue Liu McGill University MobiCom 2015.
CSE 461 University of Washington1 Topic How do nodes share a single link? Who sends when, e.g., in WiFI? – Explore with a simple model Assume no-one is.
Sunghwa Son Introduction Time-varying wireless channel  Large-scale attenuation Due to changing distance  Small-scale fading Due to multipath.
Revisiting the Contract Between Layers Sachin Katti Dina Katabi, Hari Balakrishnan, Muriel Medard.
Achieving Spectrum Efficiency Lili Qiu University of Texas at Austin 1.
Securing Wireless Medical Implants Shyamnath Gollakota Haitham Hassanieh Benjamin Ransford Dina Katabi Kevin Fu.
ECE 256: Wireless Networking and Mobile Computing
Efficient Control Plane Design in Wireless Networks Presented by Xiaoyu JI 23, June, 2013.
PPR: Partial Packet Recovery for Wireless Networks Kyle Jamieson and Hari Balakrishnan MIT Computer Science and Artificial Intelligence Laboratory.
Introduction to Wireless Networks Dina Katabi & Sam Madden MIT – – Spring 2014.
Cross-Layer Approach to Wireless Collisions Dina Katabi.
mZig: Enabling Multi-Packet Reception in ZigBee
2012 1/6 NSDI’08 Harnessing Exposed Terminals in Wireless Networks Mythili Vutukuru, Kyle Jamieson, and Hari Balakrishnan MIT Computer Science and Artificial.
Why PHY Really Matters Hari Balakrishnan MIT CSAIL August 2007 Joint work with Kyle Jamieson and Ramki Gummadi.
PPR: Partial Packet Recovery Brad Karp UCL Computer Science CS 4038 / GZ06 23 rd January, 2008.
CRMA: Collision Resistant Multiple Access Lili Qiu University of Texas at Austin Joint work with Tianji Li, Mi Kyung Han, Apurv Bhartia, Eric Rozner, Yin.
Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project Collision Helps! Algebraic Collision Recovery for Wireless Erasure Networks.
Bringing Life to Dead Spots Grace Woo Pouya Kheradpour, Dawei Shen, and Dina Katabi.
FD-MMAC: Combating Multi-channel Hidden and Exposed Terminals Using a Single Transceiver Yan Zhang, Loukas Lazos, Kai Chen, Bocan Hu, and Swetha Shivaramaiah.
On the Performance Characteristics of WLANs: Revisited S. Choi, K. Park and C.K. Kim Sigmetrics 2005 Banff, Canada Presenter - Bob Kinicki Presenter -
Wireless Communication
Wireless Communication
Wireless Communication
Xors in the air Sachin Katti, Hariharan Rahul, Wenjun Hu, Dina Katabi, Muriel Medard, Jon Crowcroft.
CS 457 – Lecture 6 Ethernet Spring 2012.
and Hidden Terminals Y. Richard Yang 2/3/2009.
CS434/534: Topics in Networked (Networking) Systems Wireless Foundation: Wireless Mesh Networks Yang (Richard) Yang Computer Science Department Yale.
Colorado School of Mines
Hidden Terminal Decoding and Mesh Network Capacity
Goal Control the amount of traffic in the network
Network Coding Testbed
CSMA/CN: Carrier Sense Multiple Access with Collision Notification
Decoding Collisions Shyamnath Gollakota Dina Katabi.
Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project Collision Helps! Algebraic Collision Recovery for Wireless Erasure Networks.
Presentation transcript:

Decoding Collisions Shyamnath Gollakota Dina Katabi

The Hidden Terminals Problem Collision! Alice Bob

The Hidden Terminals Problem Alice Bob More Collisions! Retransmissions Can’t get any useful connections

Can we take two collisions and produce the two packets? PaPa PbPb PaPa PbPb Yes, we can!

ZigZag Exploits ’s behavior Retransmissions  Same packets collide again Senders use random jitters  Collisions start with interference-free bits ∆1 ∆2 PaPa PbPb PaPa PbPb Interference-free Bits

How Does ZigZag Work? ∆1 ∆2 Find a chunk that is interference-free in one collisions and has interference in the other 1 1 ∆1 ≠∆2 Decode and subtract from the other collision 1 1

∆ ∆1 How Does ZigZag Work? Find a chunk that is interference-free in one collisions and has interference in the other ∆1 ≠∆2 Decode and subtract from the other collision

∆ ∆1 How Does ZigZag Work? 3 3 Find a chunk that is interference-free in one collisions and has interference in the other ∆1 ≠∆2 Decode and subtract from the other collision

∆ ∆1 How Does ZigZag Work? Find a chunk that is interference-free in one collisions and has interference in the other ∆1 ≠∆2 Decode and subtract from the other collision

∆ ∆1 How Does ZigZag Work? Find a chunk that is interference-free in one collisions and has interference in the other ∆1 ≠∆2 Decode and subtract from the other collision

∆ ∆1 How Does ZigZag Work? Find a chunk that is interference-free in one collisions and has interference in the other ∆1 ≠∆2 Decode and subtract from the other collision

∆ ∆1 How Does ZigZag Work? Find a chunk that is interference-free in one collisions and has interference in the other ∆1 ≠∆2 Decode and subtract from the other collision

∆ ∆1 How Does ZigZag Work? Find a chunk that is interference-free in one collisions and has interference in the other ∆1 ≠∆2 Decode and subtract from the other collision Delivered 2 packets in 2 timeslots As efficient as if the packets did not collide Delivered 2 packets in 2 timeslots As efficient as if the packets did not collide

ZigZag A receiver design that decodes collisions As efficient as if the colliding packets were sent in separate time slots Experimental results shows that it reduces hidden terminal losses from 72% to 0.7%

How does the AP know it is a collision and where the second packet starts? Time AP received a collision signal ∆

Detecting Collisions and the Value of ∆ Time AP received signal Packets start with known preamble AP correlates known preamble with signal Correlation Time Correlate ∆ Preamble Correlation Detect collision and the value of ∆ Works despite interference because correlation with an independent signal is zero Preamble Correlation Detect collision and the value of ∆ Works despite interference because correlation with an independent signal is zero

How Does the AP Subtract the Signal? Channel’s attenuation or phase may change between collisions Can’t simply subtract a chunk across collisions Alice’s signal in first collision Alice’s signal in second collision

Subtracting a Chunk Decode chunk into bits – Removes effects of channel during first collision Re-modulate bits to get channel-free signal Apply effect of channel during second collision – Use correlation to estimate channel despite interference Now, can subtract!

What if AP Makes a Mistake?

∆1 ∆ Bad News: Errors can propagate 3 3 Can we deal with these errors? What if AP Makes a Mistake?

∆1 ∆2 What if AP Makes a Mistake? Good News: Temporal Diversity A bit is unlikely to be affected by noise in both collisions Get two independent decodings

Errors propagate differently in the two decodings For each bit, AP picks the decoding that has a higher PHY confidence [JB07, WKSK07] Which decoded value should the AP pick? ∆1 ∆ AP Decodes Backwards as well as Forwards

ZigZag Generalizes

∆1 ∆ Flipped order

Different packet sizes ZigZag Generalizes ∆1 ∆

ZigZag Generalizes Flipped order Different packet sizes Multiple colliding packets

ZigZag Generalizes Flipped order Different packet sizes Multiple colliding packets Capture effect – Subtract Alice and combine Bob’s packet across collisions to correct errors ∆1 ∆2 P a1 PbPb P a2 PbPb 3 packets in 2 time slots  better than no collisions

Performance

Implementation USRP Hardware GNURadio software Carrier Freq: GHz BPSK modulation

USRPs Testbed 10% HT, 10% partial HT, 80% perfectly sense each other Each run randomly picks an AP and two clients Co-located a nodes to find out about HTs and created the same collision patterns by the USRPs a

Throughput Comparison Throughput CDF of concurrent flow pairs

Throughput Comparison Throughput CDF of concurrent flow pairs Hidden Terminals Partial Hidden Terminals Perfectly Sense

Throughput Comparison ZigZag Throughput CDF of concurrent flow pairs Hidden Terminals get high throughput

Throughput Comparison ZigZag Throughput CDF of concurrent flow pairs ZigZag Exploits Capture Effect ZigZag improved average Throughput by 25%

Throughput Comparison ZigZag Throughput CDF of concurrent flow pairs Improved hidden terminals loss rate from 72% to 0.7% Hidden Terminals

Is ZigZag as efficient as if the colliding packets were sent in separate slots? For every SNR, Check that ZigZag can match the BER of collision-free receptions

Is ZigZag as efficient as if packets were collision-free Receptions? SNR in dB Bit Error Rate (BER)

Collision-Free Receptions Is ZigZag as efficient as if packets were collision-free Receptions? SNR in dB Bit Error Rate (BER)

Collision-Free Receptions Is ZigZag as efficient as if packets were collision-free Receptions? ZigZag-Decoded Collisions SNR in dB Bit Error Rate (BER) ZigZag is as efficient as if the colliding packets were sent separately

Three Colliding Senders Collision! Alice Bob Chris Nodes picked randomly from testbed

Three Colliding Senders ZigZag extends beyond two colliding senders CDF of runs Per-Sender Throughput Alice Bob Chris

Related Work RTS-CTS – Excessive Overhead; Administrators turn it off Interference Cancellation – Unsuitable for because of bit rate adaptation Interference cancelation operates on one collision  Undecodable Alice’s Info Rate Bob’s Info Rate Rmax

Related Work RTS-CTS – Excessive Overhead; Administrators turn it off Interference Cancellation – Unsuitable for because of bit rate adaptation ZigZag operates on two collisions  Can decode Alice’s Info Rate Bob’s Info Rate Rmax

Conclusion ZigZag is a receiver design that resolves collisions It is as efficient as if the colliding packets were sent in separate time slots It reduces hidden terminal losses from 72% to 0.7% It enables aggressive MAC  More concurrency