Successive Interference Cancellation: A Back of the Envelope Perspective Souvik Sen, Naveen Santhapuri, Romit Roy Choudhury, Srihari Nelakuditi I have.

Slides:



Advertisements
Similar presentations
A DISTRIBUTED CSMA ALGORITHM FOR THROUGHPUT AND UTILITY MAXIMIZATION IN WIRELESS NETWORKS.
Advertisements

Nick Feamster CS 4251 Computer Networking II Spring 2008
1 Message In Message (MIM): A Case for Reordering Transmissions in Wireless Networks Naveen Santhapuri, Srihari Nelakuditi University of South Carolina.
Towards Collision Detection in Wireless Networks Souvik Sen, Naveen Santhapuri, Romit Roy Choudhury, Srihari Nelakuditi.
Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)
Multiuser Detection for CDMA Systems
Successive Interference Cancellation: A Back of the Envelope Perspective Souvik Sen, Naveen Santhapuri, Romit Roy Choudhury, Srihari Nelakuditi.
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.
Analog Network Coding Sachin Katti Shyamnath Gollakota and Dina Katabi.
BBN: Throughput Scaling in Dense Enterprise WLANs with Blind Beamforming and Nulling Wenjie Zhou (Co-Primary Author), Tarun Bansal (Co-Primary Author),
Pushing the Envelope of Indoor Wireless Spatial Reuse using Directional Access Points and Clients Xi Liu 1, Anmol Sheth 2, Konstantina Papagiannaki 3,
Strider : Automatic Rate Adaptation & Collision Handling Aditya Gudipati & Sachin Katti Stanford University 1.
1 Link Layer Multicasting with Smart Antennas: No Client Left Behind Souvik Sen, Jie Xiong, Rahul Ghosh, Romit Roy Choudhury Duke University.
Asymptotic Throughput Analysis of Massive M2M Access
Living with Interference in Unmanaged Wireless Environments David Wetherall, Daniel Halperin and Tom Anderson Intel Research & University of Washington.
Noise Cancelation for MIMO System Prepared by: Heba Hamad Rawia Zaid Rua Zaid Supervisor: Dr.Yousef Dama.
Topology Control for Effective Interference Cancellation in Multi-User MIMO Networks E. Gelal, K. Pelechrinis, T.S. Kim, I. Broustis Srikanth V. Krishnamurthy,
Authors: Andrea Zanella, Michele Zorzi Presenter: Nicola Bui Analysis of the Capture Probability in Wireless Systems with Multi-Packet.
5/21/20151 Mobile Ad hoc Networks COE 549 Capacity Regions Tarek Sheltami KFUPM CCSE COE
1 DOA-ALOHA: Slotted ALOHA for Ad Hoc Networking Using Smart Antennas Harkirat Singh & Suresh Singh Portland State University, OR, USA.
Discussion on The Receiver Behavior for DSC/CCAC with BSS Color
Simulation of VoIP traffic in n networks Aya Mire Niv Tokman Oren Gur-Arie.
Outline What is an ad hoc network Smart Antenna Overview
Doc.: IEEE /0861r0 SubmissionSayantan Choudhury Impact of CCA adaptation on spatial reuse in dense residential scenario Date: Authors:
Doc.: IEEE /1227r3 SubmissionSlide 1 OFDMA Performance Analysis Date: Authors: Tianyu Wu etc. MediaTek Sept 2014 NameAffiliationsAddressPhone .
Overcoming the Antennas-Per-AP Throughput Limit in MIMO Shyamnath Gollakota Samuel David Perli and Dina Katabi.
Wireless Networking & Mobile Computing CS 752/852 - Spring 2012 Tamer Nadeem Dept. of Computer Science Lec #7: MAC Multi-Rate.
RobinHood: Sharing the Happiness in a Wireless Jungle Tarun Bansal, Wenjie Zhou, Kannan Srinivasan and Prasun Sinha Department of Computer Science and.
Link Layer: Wireless Mesh Networks Capacity Y. Richard Yang 11/13/2012.
AutoMAC : Rateless Wireless Concurrent Medium Access Aditya Gudipati, Stephanie Pereira, Sachin Katti Stanford University.
Network Coding Testbed Jeremy Bergan, Ben Green, Alex Lee.
Wireless Networking & Mobile Computing CS 752/852 - Spring 2012 Tamer Nadeem Dept. of Computer Science Lec #5: Advanced MAC Schemes Dual Busy Tone & Collision.
Naveen Santhapuri, Srihari Nelakuditi and Romit Roy Choudhury University of South Carolina Duke University WCNC 2008.
Infrastructure Mobility: A What-If Analysis Mahanth Gowda Nirupam Roy Romit Roy Choudhury.
TRANSMISSION POWER CONTROL FOR AD HOC WIRELESS NETWORKS: THROUGHPUT, ENERGY AND FAIRNESS Lujun Jia; Xin Liu; Noubir, G.; Rajaraman, R.; Wireless Communications.
Pushing the Limits of Wireless Networks Prof. Dina Katabi Jan 9, 2006.
Sunghwa Son Introduction Time-varying wireless channel  Large-scale attenuation Due to changing distance  Small-scale fading Due to multipath.
Packet Dispersion in IEEE Wireless Networks Mingzhe Li, Mark Claypool and Bob Kinicki WPI Computer Science Department Worcester, MA 01609
Versatile Low Power Media Access for Wireless Sensor Networks Sarat Chandra Subramaniam.
ECE 256: Wireless Networking and Mobile Computing
Doc.: IEEE /0523r0 Submission April 2014 Imad Jamil (Orange)Slide 1 MAC simulation results for Dynamic sensitivity control (DSC - CCA adaptation)
X. Li, W. LiuICC May 11, 2003A Joint Layer Design Smart Contention Resolution Random Access Wireless Networks With Unknown Multiple Users: A Joint.
Tackling Exposed Node Problem in IEEE Mac Deepanshu Shukla ( ) Guide: Dr. Sridhar Iyer.
Cross-Layer Approach to Wireless Collisions Dina Katabi.
Presented by Abhijit Mondal Haritabh Singh Suman Mondal
No Time to Countdown: Migrating Backoff to the Frequency Domain Souvik Sen, Romit Roy Choudhury, Srihari Nelakuditi - Twohsien
報告人 : 陳柏偉.  INTRODUCTION  MODELS AND SCENARIOS  METHODOLOGY  RESULTS  CONCLUSION 2.
1 WELCOME Chen. 2 Simulation of MIMO Capacity Limits Professor: Patric Ö sterg å rd Supervisor: Kalle Ruttik Communications Labortory.
Optimization Problems in Wireless Coding Networks Alex Sprintson Computer Engineering Group Department of Electrical and Computer Engineering.
1 Effectiveness of Physical and Virtual Carrier Sensing in IEEE Wireless Ad Hoc Networks Fu-Yi Hung and Ivan Marsic WCNC 2007.
PAC: Perceptive Admission Control for Mobile Wireless Networks Ian D. Chakeres Elizabeth M. Belding-Royer.
Link Layer Multicasting with Smart Antennas: No Client Left Behind Souvik Sen, Jie Xiong, Rahul Ghosh, and Romit Roy Choudhury Dept. of Electrical and.
The Importance of Being Opportunistic Sachin Katti Dina Katabi, Wenjun Hu, Hariharan Rahul, and Muriel Medard.
PHY + MAC: The Whole is Greater than the Sum Romit Roy Choudhury Associate Professor 1.
Bridging the Gap: A Deterministic Model for Wireless Links David Tse Wireless Foundations U.C. Berkeley NSF Wireless Networks Workshop Aug 27, 2007 TexPoint.
1 Wireless Networking Understanding the departure from wired networks, Case study: IEEE (WiFi)
Wireless Communication
Xiaohua (Edward) Li and Juite Hwu
Interference Avoidance and Control
Hidden Terminal Decoding and Mesh Network Capacity
Network Coding Testbed
OFDMA Performance Analysis
Self Organized Networks
AccuRate: Constellation Aware Rate Estimation in Wireless Networks
CSMA/CN: Carrier Sense Multiple Access with Collision Notification
No Time to Countdown: Backing Off in Frequency Domain
<month year> <doc.: IEEE doc> January 2013
<month year> <doc.: IEEE doc> January 2013
Potential of Modified Signal Detection Thresholds
Presentation transcript:

Successive Interference Cancellation: A Back of the Envelope Perspective Souvik Sen, Naveen Santhapuri, Romit Roy Choudhury, Srihari Nelakuditi I have inserted some text in the text box below for the first few slides. This should help in getting started with the flow of the talk. Also, some suggestions for modifications are inserted in these yellow post-it notes. Make those changes. I have also reduced the mentioning of “holes”... we were bringing it up too much. I have inserted some text in the text box below for the first few slides. This should help in getting started with the flow of the talk. Also, some suggestions for modifications are inserted in these yellow post-it notes. Make those changes. I have also reduced the mentioning of “holes”... we were bringing it up too much.

2 Simple Case of Wireless Transmission Decoding successful if: AP Signal = Noise SNR = T1 Bigger fonts Write “Threshold” Do so for next 2 slides Bigger fonts Write “Threshold” Do so for next 2 slides

3 Interferer What if parallel transmissions? Decoding successful only if: Signal = Interference + Noise SINR = T1 AP T2

4 Collision Decoding fails because: Signal = Interference + Noise SINR = Interferer T1 AP T2

5 Successive Interference Cancellation Interferer T1 AP T2 - = 3. Decode as if simple transmission 1. Decode strongest signal first 1. Decode strongest signal first 2. Model and subtract 2. Model and subtract Thus, it is as if SIC can “uncollide” signals, resulting in two successful transmissions Correct the animation. Make the 3 boxes come with the corresponding picture. See the text in the lower panel so you know how to explain it.

6 SIC Capacity SNR = R blue = S blue noise log 1 + SINR = R* green = S green S blue + noise log 1+ T1 T2 Interferer AP R SIC = S blue + S green noise log 1+ Rate of green signal far less Rate of blue signal remains same Strong signal penalized, weak signal gets all the benefits

7 Channel Capacity w/o SIC SNR = R blue = S blue noise log 1 + T1 T2 Interferer AP SNR = S green R green = noise log 1 + R SIC = S blue + S green noise log 1+ R woSIC = max( R blue, R green ) Gain sic =

8 SIC PHY Capacity Gain

9 Max SIC gain when equal signal strengths

We were tempted to schedule packet transmissions of similar signal strengths... As protocol designers... Our interpretation was that... maximizing SIC capacity will maximize throughput

This paper studies the SIC implications on throughput on two types of scenarios 1. Two transmitters transmitting to a common receiver 2. Two transmitters transmitting to distinct receivers

12 SIC: MAC Layer Packet Perspective Weaker blue packet can be at a high rate Stronger green packet has to be at low rate MAC Layer throughput can actually suffer T1 T2 Interferer AP HOLE Packet Transmission Time Rate Make first bullet come with green box, then second bullet with blue box. Correct hole animation Make first bullet come with green box, then second bullet with blue box. Correct hole animation

13 Mathematically... T1 T2 Interferer AP HOLE Packet Transmission Time Time sic = Time woSIC = Packet Transmission Time L R blue L R* green max, = L R blue L R green + = Gain SIC = The “=” sign is also animated. Remove

14 SIC Throughput Gain

15 SIC Throughput Gain Max throughput gain when signal strengths are 2:1

16 Capacity Vs. Throughput We expected:  Maximizing SIC capacity will maximize throughput Reality:  Equal signal strengths maximize capacity  Disparate signal strengths (2:1) maximize throughput Capacity Draw a single double-sided arrow to depict capacity... then explain throughput.

by reducing size of the hole... Can’t we improve MAC layer throughput with SIC

18 (1) Power Control Reduce power of blue Tx such that SINR* green = R green R blue = 2 * Reduce

19 (2) Client Pairing T1T2T3 R green R blue Make 2 pairs

20 (2) Client Pairing T1T2T3 R green R blue R green R red

21 (3) MultiRate Packetization Multirate Packetization  Send the strong packet at high rate after weak packet has finished R* green R blue R green R blue

22 (4) Packet Packing Packet Packing  Send multiple packets to fill up the hole  Hard because stronger signal modeling becomes difficult R* green R blue

- Perform Monte Carlo Simulations How Does Adaptation Help?

24 Considerable Improvement with Adaptation Performance with MAC Modifications

25 SIC Capacity: Two Tx same Rx T1 T2 Interferer AP How does SIC perform for different receivers?

26 SIC MAC: Two Transmitter Different Receiver Various Topologies No SICSIC at R 2 SIC at R 1 SIC at R 1 and R 2

- Perform Monte Carlo Simulations How often such topologies occur and what is the relative gain?

28 Gain with SIC in less than 10% of the cases Two Tx Different Rx: Monte Carlo Simulation

29 Not many topologies offer gain even with MAC modifications Not many topologies offer gain even with MAC modifications Does MAC Adaptation Help?

30 SIC Benefit in Different Wireless Architectures Enterprise Wireless LAN  Upload Traffic: Considerable SIC gain with 2 clients to 1 AP  Download Traffic: Two AP to one client, not beneficial  Download Traffic: Two AP to diff. clients, same as 2 tx diff. rx Residential Wireless LAN  Upload same as EWLAN  Download topologies provide a bit more opportunity than EWLAN

31 Conclusion SIC may not be promising to improve wireless throughput  Bitrate selection is reaching optimality  SIC constraint: Stronger Tx needs to be decoded under interference SIC has promising gain in upload scenarios Interference cancellation useful when interfering tx known  No bitrate constraint like SIC: ANC, ZigZag, CSMA/CN

Questions, comments? Thank you Duke SyNRG Research Group

33 Successive Interference Cancellation Received signal is the sum of interfering and own signal Decode strong interfering signal Subtract it from total signal Decode own (weaker) signal  Its implementation is in time domain Cancellation: - = Next Decode: SIC can decode both packets even though they are received simultaneously

34 Successive Interference Cancellation Received signal is the sum of interfering and own signal Decode strong interfering signal Subtract it from total signal Decode own (weaker) signal  Its implementation is in time domain Cancellation: - = Next Decode: SIC can decode both packets even though they are received simultaneously

35 Can we “Uncollide” Packets? But> Signal = Interference + Noise SINR = The interfering transmission can be decoded Interferer T1 AP T2

Note to Protocol Designers: To maximize throughput with SIC schedule transmissions of equal strength - Lets verify that!

37 Why is This Happening? T1 T2 Interferer AP = HOLE R green R blue

38 Why is This Happening? Maximizing capacity does not maximize throughput HOLE Capacity Throughput = + + +

39 SIC Throughput Gain R green R blue This happens because Max throughput gain when signal strengths are 2:1

40 Improving MAC Throughput: Power Control Rate of strong Tx depends on signal strength of weak Tx Reduce power of blue Tx such that SINR green = HOLE R green R blue SINR* green = R green R blue = 2 *