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BBN: Throughput Scaling in Dense Enterprise WLANs with B lind B eamforming and N ulling

BBN: Throughput Scaling in Dense Enterprise WLANs with B lind B eamforming and N ulling. Wenjie Zhou (Co-Primary Author), Tarun Bansal (Co-Primary Author), Prasun Sinha and Kannan Srinivasan The Ohio State University. Changes in Uplink Traffic. Traditionally, WLAN traffic:

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BBN: Throughput Scaling in Dense Enterprise WLANs with B lind B eamforming and N ulling

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  1. BBN: Throughput Scaling in Dense Enterprise WLANs with Blind Beamforming and Nulling WenjieZhou (Co-Primary Author), Tarun Bansal (Co-Primary Author), PrasunSinha and KannanSrinivasan The Ohio State University

  2. Changes in Uplink Traffic • Traditionally, WLAN traffic: • downlink heavy • less attention to uplink traffic • Recently, uplink traffic increased rapidly: • mobile applications Cloud Computing Online Gaming Code Offloading VoIP, Video Chat Sensor Data Upload

  3. Can we scale the uplink throughput with the number of clients?

  4. Network MIMO Exchange raw samples AP1 AP2 AP3 C1 C2 C3 Huge bandwidth consumption

  5. MegaMIMO1 Does not apply to uplink : Clients do not share a backbone network [1] Rahul, H., Kumar, S., and Katabi, D. MegaMIMO: Scaling Wireless Capacity with User Demand. In Proc. of ACM SIGCOMM 2012.

  6. Interference Alignment1 AP1 AP2 C1 C2 C3 AP3 • 4 packets, 3 slots • Enough time slots, everyone gets half the cake • Exponential slots of transmissions, not suitable for mobile clients • Heavy coordination between clients [1] Cadambe, V. R., and Jafar, S. A. Interference Alignment and the Degrees of Freedom for the K User Interference Channel. IEEE Transactions on Information Theory (2008).

  7. Existing interference alignment and beamforming techniques are not suitable to mobile uplink traffic. How can we bring the benefits of beamforming to uplink traffic?

  8. AP Density in Enterprise WLANs (140,0.5) BBN leverages the high density of access points

  9. Omniscient TDMA Single Collision Domain Time Slot: 2 Time Slot: 1 Time Slot: 3 AP1 AP2 Switch AP3 AP4 C1 C2 C3 x1 x2 x3 Three Packets received in Three Slots Only one AP is in use

  10. Blind Beamforming and NullingSingle Collision Domain Time Slot: 1 h(1)11x1 + h(1)21x2 + h(1)31x3 h(1)12x1 + h(1)22x2 + h(1)32x3 AP1 AP2 Switch h(1)14x1 + h(1)24x2 + h(1)34x3 h(1)13x1+h(1)23x2+h(1)33x3 AP3 AP4 C1 C2 C3 h(1)33 h(1)13 h(1)23 x1 x2 x3

  11. Blind Beamforming and NullingSingle Collision Domain Time Slot: 2 Receives: a11x1 + s1h(1)21x2 + s1h(1)31x3 Receives: a12x1 + a22x2 + a32x3 AP1 AP2 Switch AP3 AP4 Transmits: (h(1)13x1 + h(1)23x2 + h(1)33x3) Transmits: v4(h(1)14x1 + h(1)24x2 + h(1)34x3) v3

  12. Blind Beamforming and NullingSingle Collision Domain Slot 1: h(1)11x1 + h(1)21x2+ h(1)31x3 Slot 1: h(1)12x1 + h(1)22x2 + h(1)32x3 Slot 2: a11x1 + s1h(1)21x2 + s1h(1)31x3 Slot 2: a11x1+ s1h(1)21x2+ s1h(1)31x3 Slot 2: a12x1+ a22x2 + a32x3 (s1h(1)11-a11)x1 AP1 AP2 Switch AP3 AP4 • Three Packets received in Two Slots

  13. Number of APs Required • In a network with APs, APs in BBN can receive N uplink packets in two slots • 3 clients, 4 APs • 4 clients, 7 APs • 10 clients, 46 APs

  14. Throughput Improvement • Previous Example Topology • APs in BBN receive three packets in two slots: an improvement of 50% • General Topology • Uplink throughput in BBN scales with the number of clients (N/2 packets per slot). • Half of the cake as in Interference Alignment • Always two slots • No coordination between clients

  15. BBN Highlights • Leverages the high density of access points • All computation and design complexity shifted to APs • APs only need to exchange decoded packets over the backbone instead of raw samples

  16. Further Optimizations to Improve SNR x2, x3 x1 AP2 AP1 Receivers • Which subset of APs act as transmitters and which subset as receivers? • Which AP decodes which packet? AP4 Switch Transmitters AP3 C1 C2 C3 BBN Approach: xi is decoded at the APj where it is expected to have highest SNR

  17. Challenge 1/4: Synchronization of APs • To perform accurate beamforming, APs need to be tightly synchronized with each other • Solution: • SourceSync (Rahul et al., SIGCOMM 2010): synchronizes APs within a single collision domain • Vidyut(Yenamandraet al., SIGCOMM 2014): uses power line to synchronize APs in the same building

  18. Challenge 2/4 : MultiCollision Domain • Not all APs may be able to hear each other directly • Solution: Make smaller groups where all APs in a single group can hear each other.

  19. Distributed System • Within a group, all APs can hear each other • When one group is communicating, neighboring groups remain silent Group Head Group Head

  20. Challenge 3/4 : Inconsistency in the AP density • Number of APs may be less than • Solution: Appropriate MAC layer algorithm that restricts the number of participating clients

  21. MAC Timeline Keep Silent – Allow neighboring groups to transmit Uplink Uplink Downlink Uplink Time Slot 1 Time Slot 2 ....... ....... ....... Time Poll Approve A, B and C Compute pre-coding vectors in the background Notification Period

  22. Challenge 4/4 : Robustness • Nulling is not always perfect. Can’t Subtract x1 Decoding Error x1, x2 , x3 x1 AP1 AP2 C1 C2 C3 Switch AP4 AP5 x1 x2 x3

  23. Challenge 4/4 : Robustness • What if we have extra APs x1 x1, x2 , x3 x1 AP5 AP1 AP2 Switch AP7 AP3 AP4 AP6 C1 C2 C3 x1 x2 x3

  24. Experiments Intended Signal = x1 Interference from x2,x3 x2, x3 AP1 AP2 USRP N210 Switch AP3 AP4 C1 C2 C2 x2 x3 x1

  25. Throughput 1.48X BBN provides 1.48x throughput compared to TDMA

  26. Trace-Driven Simulation • Over multiple collision domains (divided into groups) • Field Size: 500m X 500m • Number of clients: 1000 • Vary the number of APs • Residual interference distribution from experiment • Other algorithms simulated • Omniscient TDMA • IEEE 802.11

  27. Throughput BBN • 2000 APs • 4.6X throughput gain • ~76 APs near each client

  28. Fairness BBN • BBN achieves higher fairness • Beamforming increased SINR of clients that are far away

  29. Summary and Future Work • BBN leverages the high density of APs to scale the uplink throughput for single antenna systems • Throughput scales linearly with the number of clients • All computational and design complexity shifted to APs • Future Work • Coexist with legacy network • Data rate selection Thank you

  30. Backup Slides

  31. Long Term Results

  32. Frequency Accuracy w/ out : 25 ppb Frequency Accuracy with GPS Lock : <1 ppb PPS Accuracy with GPS Lock : 50 ns OctoClock-G Vidyut: approximately 225 ns

  33. Multiple Antenna AP • Assume each AP has K antennas • For N clients, APs required • For M APs, clients

  34. Estimate SNR of C1 at AP2 SNR of C1 at AP2 is low AP1 AP2 No path with high SNR Switch AP3 AP4 C1

  35. Estimate SNR of C1 at AP1 SNR of C1 at AP1 is high AP1 AP2 One path with high SNR Switch AP3 AP4 C1 • C1 should be decoded by AP1 • AP1 should act as a receiver in slot 2

  36. Blind Nulling in BBN

  37. MAC Layer: Phase 1 Approve IACS IACS IACS AP1 : C1 : AC1 Packet 1 C2 : AC2 Packet 2 C3 : Packet 3 AC3

  38. MAC Layer: Phase 2 SIFS SIFS SIFS BIFS AP1 : AC1 AP2: AC2 AP3 : AC3 AP4 : v4* Samples4 AP5 : v5* Samples5 AP6: v6* Samples6 AP7 : v7* Samples7

  39. Experiments Setup • Performed using USRP N210 Radio • Testbed of 4 APs and 3 clients • Modulation Scheme: OFDM with BPSK • Channel: Central Frequency 400 Mhz, Bandwith set to 500 KHz

  40. Existing Schemes • Interference Alignment • Existing IA schemes perform alignment over exponential number of time slots [Cadambeet al., IEEE Transactions on Information Theory 2007] • MU-MIMO (Multi User MIMO) • Requires transmitters to exchange each other’s data before transmission • MU-MIMO (Multi User MIMO) in EWLAN • All APs together act as a single AP with multiple antennas • Requires APs to exchange samples over the backbone which is cost-prohibitive [Gollakotaet al., SIGCOMM 2009; Gowdaet al., INFOCOM 2013]

  41. Existing Schemes • Interference Alignment • Existing IA schemes require each transmitter to transmit exponential amount of data [Cadambeet al., IEEE Transactions on Information Theory 2007] • MU-MIMO • All APs together act as a single AP with multiple antennas • Requires APs to exchange samples over the backbone which is cost-prohibitive [Gollakotaet al., SIGCOMM 2009]

  42. Related Work (contd.) • Interference Alignment • Existing IA schemes work over exponential number of time slots [Cadambeet al., IEEE Transactions on Information Theory 2007] • Or, work only for downlink [Suhet al., IEEE Transactions on Communications 2011] • Or, require multiple antennas at clients [Gollakotaet al., SIGCOMM 2009] • Or, require APs to exchange samples over backbone [Annapureddyet al., IEEE Transactions on Information Theory 2012]

  43. Related Work • Backbone Usage • MegaMIMO (Rahulet al., SIGCOMM 2012): Works only for downlink • Symphony (Bansal et al., MobiCom 2013): Works only in multiple collision domain

  44. Related Work (contd.) • Wireless Relays • Use special relay nodes to assist high speed communication between specific transmitters and receivers • Existing algorithms do not make use of the backbone • BBN leverages the backbone to improve throughput • BBN can extend to multiple rounds to decode packets with low SNR

  45. BBN Highlights • Leverages the high density of access points • Uplink throughput scales with the number of clients in the network • All computational and design complexity shifted to APs • APs only need to exchange decoded packets over the backbone

  46. Example Topology: What we ideally want x1 x2 x3 AP1 AP2 AP3 • Works! But can we make the requirements less strict? Switch C1 C2 C3 AP4 AP5 AP6 AP7 x1 x2 x3

  47. Matching in BBN AP1 AP2 • Find the Maximum Weight Matching • Which AP decodes which packet. • Which AP transmits in the second slot. AP3 Edge Weight = Expected SINR of C2 at AP3 AP4 C1 C2 C3 AP5 AP6 AP7

  48. Number of APs Required: Example Topology • Two packets (x2 and x3) need to be nulled at AP1 • One packet (x3) needs to be nulled at AP2 • Three transmitting APs required • Guarantee non degenerate solution: Four APs required x3 x1 x2

  49. AP Density in Enterprise WLANs • Can we leverage the high density of APs to scale the uplink throughput? CDF of number of APs observed (Measurements conducted at Ohio State University campus)

  50. Enterprise Wireless LAN Internet AP AP AP AP AP AP

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