Overcoming the Antennas-Per-AP Throughput Limit in MIMO Shyamnath Gollakota Samuel David Perli and Dina Katabi.

Slides:



Advertisements
Similar presentations
Wireless Networks Should Spread Spectrum On Demand Ramki Gummadi (MIT) Joint work with Hari Balakrishnan.
Advertisements

1 Retransmission Repeat: Simple Retransmission Permutation Can Resolve Overlapping Channel Collisions Li (Erran) Li Bell Labs, Alcatel-Lucent Joint work.
Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)
Chorus: Collision Resolution for Efficient Wireless Broadcast Xinyu Zhang, Kang G. Shin University of Michigan 1.
VSMC MIMO: A Spectral Efficient Scheme for Cooperative Relay in Cognitive Radio Networks 1.
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.
Interference Alignment By Motion Swarun Kumar Fadel Adib, Omid Aryan, Shyamnath Gollakota and Dina Katabi.
Fine-grained Channel Access in Wireless LAN SIGCOMM 2010 Kun Tan, Ji Fang, Yuanyang Zhang,Shouyuan Chen, Lixin Shi, Jiansong Zhang, Yongguang Zhang.
BBN: Throughput Scaling in Dense Enterprise WLANs with Blind Beamforming and Nulling Wenjie Zhou (Co-Primary Author), Tarun Bansal (Co-Primary Author),
Secure In-Band Wireless Pairing Shyamnath Gollakota Nabeel Ahmed Nickolai Zeldovich Dina Katabi.
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.
© 2004 Qualcomm Flarion Technologies 1 + Lessons Unlearned in Wireless Data Rajiv Laroia Qualcomm Flarion Technologies.
Network Coding Testbed Using Software-Defined Radio Abstract In current generation networks, network nodes operate by replicating and forwarding the packets.
Living with Interference in Unmanaged Wireless Environments David Wetherall, Daniel Halperin and Tom Anderson Intel Research & University of Washington.
Successive Interference Cancellation: A Back of the Envelope Perspective Souvik Sen, Naveen Santhapuri, Romit Roy Choudhury, Srihari Nelakuditi I have.
Turbocharging Ambient Backscatter Communication Aaron Parks Angli Liu Shyamnath Gollakota Joshua R. Smith 1.
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.
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.
RCTC: Rapid Concurrent Transmission Coordination in Full Duplex Wireless Networks Wenjie Zhou, Kannan Srinivasan, Prasun Sinha Department of Computer Science.
RobinHood: Sharing the Happiness in a Wireless Jungle Tarun Bansal, Wenjie Zhou, Kannan Srinivasan and Prasun Sinha Department of Computer Science and.
Multiple Input Multiple Output
Link Layer: Wireless Mesh Networks Capacity Y. Richard Yang 11/13/2012.
Full-duplex Backscatter for
AutoMAC : Rateless Wireless Concurrent Medium Access Aditya Gudipati, Stephanie Pereira, Sachin Katti Stanford University.
Network Coding Testbed Jeremy Bergan, Ben Green, Alex Lee.
Symphony: Orchestrating Collisions in Enterprise Wireless Networks Tarun Bansal (Co-Primary Author), Bo Chen (Co-Primary Author), Prasun Sinha and Kannan.
Next Generation n Dina Katabi Jointly with Kate Lin and Shyamnath Gollakota.
1 Wireless Collisions: From Avoidance, to Recovery, to Creation Erran Li Aug
Support WiFi and LTE Co-existence
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.
BBN: Throughput Scaling in Dense Enterprise WLANs with Blind Beamforming and Nulling Wenjie Zhou (Co-Primary Author), Tarun Bansal (Co-Primary Author),
Infrastructure Mobility: A What-If Analysis Mahanth Gowda Nirupam Roy Romit Roy Choudhury.
Omid Abari Hariharan Rahul, Dina Katabi and Mondira Pant
Decoding Collisions Shyamnath Gollakota Dina Katabi.
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.
Doc.: IEEE /1421r0 Submission November 2013 Philip Levis, Stanford UniversitySlide 1 STR Radios and STR Media Access Date: Authors:
Introduction to Wireless Networks Dina Katabi & Sam Madden MIT – – Spring 2014.
Cross-Layer Approach to Wireless Collisions Dina Katabi.
Wi-Fi. Basic structure: – Stations plus an access point – Stations talk to the access point, then to outside – Access point talks to stations – Stations.
Presented by Abhijit Mondal Haritabh Singh Suman Mondal
Multipe-Symbol Sphere Decoding for Space- Time Modulation Vincent Hag March 7 th 2005.
MIMO: Challenges and Opportunities Lili Qiu UT Austin New Directions for Mobile System Design Mini-Workshop.
Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project Collision Helps! Algebraic Collision Recovery for Wireless Erasure Networks.
August 13, 1999 TXAA Feedback Channel 1. August 13, 1999 TXAA Feedback Channel 2 Contents  Introduction  TXAA and Feedback Channel Description  Generation.
Bringing Life to Dead Spots Grace Woo Pouya Kheradpour, Dawei Shen, and Dina Katabi.
1 A Coordinate-Based Approach for Exploiting Temporal-Spatial Diversity in Wireless Mesh Networks Hyuk Lim Chaegwon Lim Jennifer C. Hou MobiCom 2006 Modified.
The Importance of Being Opportunistic Sachin Katti Dina Katabi, Wenjun Hu, Hariharan Rahul, and Muriel Medard.
Wireless Communication
Interference Alignment By Motion
Wireless Communication
and Hidden Terminals Y. Richard Yang 2/3/2009.
MIMO III: Channel Capacity, Interference Alignment
Howard Huang, Sivarama Venkatesan, and Harish Viswanathan
CS434/534: Topics in Networked (Networking) Systems Wireless Foundation: Wireless Mesh Networks Yang (Richard) Yang Computer Science Department Yale.
Interference Avoidance and Control
Hidden Terminal Decoding and Mesh Network Capacity
Network Coding Testbed
Evaluation on blind detection for
CSMA/CN: Carrier Sense Multiple Access with Collision Notification
Decoding Collisions Shyamnath Gollakota Dina Katabi.
MIMO I: Spatial Diversity
Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project Collision Helps! Algebraic Collision Recovery for Wireless Erasure Networks.
MIMO II: Physical Channel Modeling, Spatial Multiplexing
Further discussion on Hybrid Multiple Access for
Presentation transcript:

Overcoming the Antennas-Per-AP Throughput Limit in MIMO Shyamnath Gollakota Samuel David Perli and Dina Katabi

MIMO LANs Today, MIMO delivers as many concurrent packets as the antennas on the AP Talk presents a practical technique to double the concurrent packets in MIMO LANs

MIMO Primer AP Bob Antenna 1 Antenna 2 h ij is the channel from antenna i to antenna j

AP AP receives the sum of these vectors MIMO Primer Bob

AP AP projects on a direction orthogonal to interference p2 p2 p1 p1 How does the AP decode each packet? Current MIMO decodes as many concurrent packets as there are antennas per AP Current MIMO decodes as many concurrent packets as there are antennas per AP MIMO Primer Bob

Can We Get More Concurrent Packets? Bob AP p3 p3 p3 p3 No direction is orthogonal to all interference  AP can’t decode All current MIMO LANs are limited by number of antennas-per-AP Alice

Let the APs Coordinate Over the Ethernet Naive solution: Emulate 4-antenna AP by sending every signal sample over Ethernet

Let the APs Coordinate Over the Ethernet Impractical Overhead, Naive solution: Emulate 4-antenna AP by sending every signal sample over Ethernet p3 p3 Raw samples E.g., a 3 or 4-antenna system needs 10’s of Gb/s Can we leverage the Ethernet with minimal overhead?

p1 p1 Bob AP1 p3 p3 p3 p3 Align P3 with P2 at AP1 AP1 broadcasts P1 on Ethernet AP2 subtracts/cancels P1  decodes P2, P3 p1p1 p2p2 p3p3 AP2 Alice  AP1 decodes P1 to its bits Interference Alignment and Cancellation (IAC) IAC overcomes the antennas-per-AP throughput limit In IAC, a packet is decoded, then broadcasted once on the Ethernet  minimal overhead IAC overcomes the antennas-per-AP throughput limit In IAC, a packet is decoded, then broadcasted once on the Ethernet  minimal overhead

Contributions First MIMO LAN to overcome the antennas-per-AP limit IAC synthesizes interference alignment and cancellation Proved that IAC almost doubles MIMO throughput Implemented IAC in software radios showing practical throughput gains

How to Change Packet Direction?

Client AP

How to Change Packet Direction? Client AP Sender controls packet direction by multiplying with a vector

How Do We Align? Bob AP1 Alice AP2

How Does Alignment Work in Presence of Modulation? Real Imaginary Modulated samples are complex numbers with different phases Real Imaginary Sample in P3 Sample in P2 Alignment is in the antenna domain not the modulation domain Antenna 1 Antenna 2 Alignment works independent of modulation phases

How Does AP2 Subtract Interference from P1? Can’t subtract the bits in packet Need to subtract interference signal as received by AP2 Solution AP2 Re-modulate P1’s bits AP2 estimate and apply the channel P1 traversed to itself on modulated signal – Channel estimation in the presence of interference as in [ZigZag, SIGCOMM’08] Subtract!

How Does IAC Generalize to M-Antenna MIMO?

Theorem In a M- antenna MIMO system, IAC delivers 2M concurrent packets on uplink max{2M-2, 3M/2} concurrent packets on downlink How Does IAC Generalize to M-Antenna MIMO? E.g., M=2 antennas 4 packets on uplink 3 packets on downlink

Theorem In a M- antenna MIMO system, IAC delivers 2M concurrent packets on uplink max{2M-2, 3M/2} concurrent packets on downlink How Does IAC Generalize to M-Antenna MIMO? E.g., M=10 antennas 20 packets on uplink 18 packets on downlink For a large M, IAC doubles MIMO throughput For a large M, IAC doubles MIMO throughput

What if There is a Single Client? Client AP1 Current MIMO exploits diversity and pick best of two APs Can’t have more than 2 concurrent packets, but … IAC can pick the best antenna pair across APs AP2 IAC provides higher diversity than Current MIMO Diversity gain applies to one or more clients IAC provides higher diversity than Current MIMO Diversity gain applies to one or more clients

IAC MAC Requirements Allow concurrent packets Clients are oblivious to each other Works even when channel changes (i.e., the matrix H changes)

IAC MAC Leverages PCF mode Clients are simple: APs compute v vectors and send them to clients in the Grant message IAC adapts to changing channels because APs get a new channel estimate from each ACK packet CF- End Contention-free Contention Downlink Uplink..... ACKs P4 P5 P6 P1 P2 P3 Time

Performance

Implementation GNURadio software 2-antenna MIMO USRP nodes Carrier Freq: 2.4GHz

Testbed 20-node testbed All nodes within radio range of each other Each run randomly picks APs and clients

Gain = Client throughput in IAC Client throughput in current MIMO Metric

Uplink Gain CDF of Runs Per-Client Throughput Gain

Uplink Gain CDF of Runs Per-Client Throughput Gain On uplink, IAC’s median gain is 2.1x Gain is partially due to diversity but more to concurrency On uplink, IAC’s median gain is 2.1x Gain is partially due to diversity but more to concurrency

Downlink Gain CDF of Runs Per-Client Throughput Gain On downlink, IAC’s median gain is 1.5x

Gains as a Function of SNR

SNR in dB Uplink Throughput Gain IAC is beneficial across the operational range of SNRs

Related Work Interference Alignment [AMK’08,JS’08] Interference Cancellation [GC’80,HWA’08] MU-MIMO [NJ’06] IAC provably provides more throughput, and doubles the number of concurrent packets

Conclusion First MIMO LAN to overcome the antennas-per-AP limit IAC synthesizes interference alignment and cancellation Proved that IAC almost doubles MIMO throughput Implemented IAC in software radios showing that it works in practice

IAC MAC Leverages PCF mode APs compute and send v vectors in Grant  Clients are oblivious to each other APs can track channels, i.e., H, from using ACKs CF- End Contention-free Contention Downlink Uplink..... ACKs P4 P5 P6 P1 P2 P3 Time

Uplink: for M=2 antennas, IAC delivers 2M=4 packets Clients APs p1p1 p2p2 p4 p3

APs Clients p1p1 p2p2 p3p3 Downlink: - Clients can’t coordinate over Ethernet - For M=2 antennas, IAC delivers 3M/2 = 3 packets

IAC’s concurrency increases capacity bound C = d log(SNR) + o(log(SNR)) IAC increases degrees of freedom d is degrees of freedom Interference cancellation does not increase degrees of freedom but provides a better use of them