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FlashLinQ: A Clean Slate Design for Ad Hoc Networks

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  • asdfsadf
  • Disclaimers: asdfsadf
  • asdfsadf
  • Disclaimers: asdfsadf
  • The necessity of interference avoidance. Distributed scheduling. FDD P2P…?
  • CSMA/CA is the primary
  • Transcript

    • 1. FlashLinQ: A Clean Slate Design for Ad Hoc Networks Xinzhou Wu May. 4 th , 2010
    • 2. Qualcomm CR&D at Bridgewater
      • Flarion Technologies Inc founded in 2000 as a Bell Labs spin-off by Dr. Rajiv Laroia
      • Acquired by Qualcomm on January 18, 2006
      • Systems team lead by Dr. Tom Richardson, VP Eng.
      • Innovative workforce - enhancing Qualcomm patent portfolio
        • 53 patents awarded for OFDMA innovation
        • 315 additional patents filed and pending
      • 11 years of innovative OFDMA products and technologies
      • FLASH-OFDM® - first fully mobile commercial OFDMA system
      • Current major projects include:
        • Femtocell Station Modem (FSM) SoCs
        • FLASH-OFDM ®
        • FlashLinQ
    • 3. FlashlinQ – Direct Device-to-Device Communication Technology Over Licensed Spectrum Without Infrastructure Support
    • 4. Where We are Today
      • Wireless
        • WAN
          • 1G – Analog voice
          • 2G – Digital voice
          • 3G/4G – Broadband data/voice
          • No notion of physical location or proximity
        • LAN
          • WiFi
          • Bluetooth
          • Ad hoc networks (WiFi P2P mode)
      • Wired
        • Ethernet – local
        • Internet
          • Global
          • No notion of physical location or proximity
      We Are Social Beings That Interact With The Physical World Around Us
    • 5. QUALCOMM Proprietary and Confidential
    • 6. Proximate Internet QUALCOMM Proprietary and Confidential
    • 7. Autonomous Advertisements… Mobile Notary Public Courier: for Hire Local Seamstress School: Polling Place Taxi: for Hire -> Heading to NYC, need a ride? Grocer -> ½ off Salami QUALCOMM Proprietary and Confidential
    • 8. Discovering what one cares about nearby… Good to know Johnny is near home A Family out for the day A School Field Trip The “Neighborhood Watch” Cmte QUALCOMM Proprietary and Confidential
    • 9. Communicating with it… “ Multi-player” Neighborhood Gaming “ Media Swap” “ Proximate Context-aware Gaming” Mobile Social Network “Profile Matching” In-building Automation Control “ Vouch” – building 3 rd -party Trust Nets “ FlashPay” – eCash between eWallets QUALCOMM Proprietary and Confidential
    • 10. Applications of Proximate Internet
      • Social networking
        • Discover friends in the vicinity
        • Find people that share common interests
      • Mobile advertizing
        • Neighborhood stores – products & services
        • People offering services
      • Remotely control devices around you
    • 11. Need for Proximate Internet
      • Proximate Internet complements the Internet, does not replace it
      • Mobile/fixed ‘devices’ communicate with nearby mobile/fixed ‘devices’
        • Think of devices as ‘higher layer entities’ such as applications or services
      • Location based services over 3G networks
        • Mobile-to-fixed (could also be mobile-to-mobile)
      • Bluetooth based proximate services
        • File/content sharing – mobile-to-mobile
        • Local advertising – mobile-to-fixed
      • WiFi based in home services
        • Apple devices using Bonjour – mobile-to-fixed or fixed-to-fixed
    • 12. Requirement for Proximate Internet
      • Peer Discovery -- establishing need to communicate
        • Devices (application) discover all other devices within range (upto ~ mile)
          • Capable of discovering thousands of devices
          • Identify only authorized devices (privacy maintained)
        • Automatic power efficient discovery without human intervention
      • Paging – initiating communication
        • Link established through paging
      • Communication
        • Once link established, devices can securely communicate
        • All pairs that can coexist communicate simultaneously
          • Orthogonalization/reuse tradeoff - high system capacity
    • 13. Outline
      • Motivation: proximate internet – internet aware of the physical proximity
      • FlashLinQ peer discovery solution
        • PHY: 5x range improvement and 40x energy efficiency improvement over WiFi
        • MAC: greedy MAC protocol achieves close-to-optimal performance in dense deployment
      • FlashLinQ traffic scheduling slultion
        • Fully distributed SINR based scheduling protocol
        • 10x spectrum efficiency improvement over WiFi
    • 14. Technical Challenges in Peer Discovery Design
      • Autonomous and continuous: peer discovery should happen without manual intervention
      • Energy-efficient: low processing power to achieve decent stand-by time
        • Standby time for 802.11 is around 7 hours
      • Long range: each device need to discover peers far away
        • 802.11 transmissions can only reach 200m
      • Scalable: each device to monitor a large number of entities of interest in a dense network; graceful performance degradation as density increases
      • Spectrally-efficient : minimum signaling overhead to allow simultaneous advertisements by large number of devices
      • Many others: Secure, open and flexible, intelligent (application-defined timing and semantics) and dynamic (variation due to device mobility or user/application interactions)
    • 15. FlashLinQ Peer Discovery Solution – Operation
      • Synchronized peer discovery operation
        • All devices synchronize to an external time source ( e.g., CDMA 2000, MediaFLO, GPS)
        • Periodically, every device transmits its peer discovery signal and also listens to peer discovery signals of others to detect entities of interest in the proximity
        • Peer discovery occupies roughly 16 ms every one second
          • The system overhead is 1.6%
          • Standby time is 8.3 days!
      • Synchronicity is the key to improve energy efficiency!
    • 16. FlashLinQ Peer Discovery Solution – PHY
      • PHY signaling: single-tone OFDM signaling
        • Concentrating the transmit energy in small degrees of freedom ( +17 dB)
        • Taking advantage of good PAPR property of sinusoid signals ( +6 dB)
      • Caveats of single-tone signaling: half-duplexing and desensing
        • Miss other transmissions when transmitting due to half-duplexing
        • May not be able to hear all simultaneous transmissions due to desensing
        • Solution: hopping (Latin square)
            • Two Peer Discovery Resource IDs overlap in time at most once in 512 seconds
      • Single tone signaling is the key to increase range and be able to discover many at a time!
    • 17. FlashLinQ Peer Discovery Solution – MAC
      • Peer discovery resource is divided into 5600 logical channels that repeats every 8 seconds
      • Question: How to pick peer discovery resource (PDRID) in a distributed way?
      • Listen first and pick one which is not being used
      • What if all of them are used?
        • Happen when the number of users exceeds the number of PDRIDs in the system
        • Stadium scenario
      • Pick the one which is least congested
        • Measure the power at each PDRID and pick one with least power
          • A greedy distributed online protocol
      • How is the performance in the dense deployment?
        • Can be analyzed using a simple mathematical model
    • 18. Spatial coloring problem
      • n nodes uniformly distributed in a 2D space of unit area
      • K colors (PDRIDs) are available
      • Greedy coloring: pick a random coloring sequence and let each node picks color which maximizes the min distance
      • Study : the minimum distance between any two nodes with the same color
      Available Colors:
    • 19. Minimum Distance with One Color
      • Equivalent to the minimum distance between any two nodes out of n randomly placed nodes:
        • T. Richardson and E. Telatar
        • Much worse than the average
      • Can be proved using a balls-into-bins argument
        • Similar to the birthday problem
      • Our result: (Sigmetrics 2010, Ni-Srikant-Wu)
        • As number of colors increase, the minimum distance behaves more and more like mean.
    • 20. Main Result: K~log(n)/loglog(n)
      • Question: How many colors are required to obtain ?
      • Define to be the solution to . For any a>0,
        • If ,
        • If ,
    • 21. Main Result: K~log(n)
      • An upper bound is
      • When ,
      • Is it possible to make ?
        • Yes , we need
        • Also a tight result
        • Concentration effect
      If K is large enough, distributed coloring can maintain a minimum distance which is a constant factor away from the optimal coloring scheme
    • 22. Observations
      • Online distributed PDRID selection (greedy coloring) protocol is near-optimal in dense scenario, if
        • PDRID space is sufficiently large (~log(n) << n)
      • Distances between nodes sharing the same PDRID concentrate around the mean values
        • Tight hexagonal packing; WAN similar behavior
      • Performance for peer discovery in high density deployment is predictable
      • New system level ideas can be introduced to improve the performance
        • WAN interference management schemes like FFR can be introduced to peer discovery
    • 23. Outline
      • Motivation: proximate internet – internet aware of the physical proximity
      • FlashLinQ peer discovery solution
        • PHY: 5x range improvement and 40x energy efficiency improvement over WiFi
        • MAC: greedy MAC protocol achieves close-to-optimal performance in dense deployment
      • FlashLinQ traffic scheduling slultion
        • Fully distributed SINR based scheduling protocol
        • 10x spectrum efficiency improvement over WiFi
    • 24. Main Challenges in FlashLinQ Scheduling
      • When to listen and when to transmit?
        • All mobiles are half-duplex : while device is transmitting, it cannot monitor signals from other devices in the same band
        • Traditional TDD has a predetermined FL/RL partition in cellular networks
        • In FlashLinQ, TX and RX partition may not be fixed or determined a priori by a centralized controller
      • Which connections to schedule and what rates to use?
        • In WAN, scheduling units are the connections between a set of devices and their serving base station (intra-AR scheduling)
          • Scheduling is not a must, but a way to improve QoS and system capacity
          • Problems well formulated and studied in both academic and industry
        • In FlashLinQ, scheduling units are the connections between an arbitrary set of device pairs
          • Scheduling is a must to avoid deadlock
          • Not as many guidance from literature
      • How to make efficient scheduling decisions in a distributed fashion?
        • No central authority here to make decisions to everyone
        • Exchanging information between nodes can be expensive
      A B C D
    • 25. Carrier sensing: extend the wireline network to wireless
      • Wireless is also a shared medium for communications
        • Carrier sensing + collision avoidance to make sure the mobiles orthogonalize the channel use
    • 26. A caveat: hidden terminal problem
      • Wireless signal loses power much faster when it propagates in space, as compared to the wireline counterpart
        • Propagation loss
      • Hidden terminal: a corner case that carrier sense breaks down
        • A patch is needed: RTS/CTS
    • 27. 802.11 approach: Carrier sense and RTS/CTS
      • Carrier sensing and collision avoidance:
        • Senders (transmitters) are required to listen for DIFS
        • Exponentially backoff if collision detected
      • Optional RTS/CTS (virtual carrier sensing)
        • Include the information of the timed required to complete the data transmission
        • All nodes which decoded RTS or CTS not intended for them keep silent during the time interval specified in RTS/CTS
      A C B D
    • 28. Behavior of 802.11 scheduling: Hard spatial reuse
      • SNR based (hard) spatial reuse:
        • Orthogonalization enforced within the carrier sensing range, independent of the actual transmission distance
        • Unnecessary yielding enforced between transmitters
          • Exposed terminal
        • Try to mimic wireline network behavior by being heavily biased to orthogonalization
    • 29. FlashLinQ Traffic Solution -- Operation
      • Synchronous system
      • Connection scheduling happens every data slot
      • Rate scheduling gives SINR estimate of the surviving connections
        • No rate scheduling in 802.11
    • 30. Connection scheduling in FlashLinQ
      • Transmitters send out transmit requests (RTS)
      • Receivers hearing RTS from a higher priority connection should refrain from sending the CTS back.
        • Receiver yielding
      • Receivers send out receiver responses (CTS)
      • Transmitters hearing CTS from a higher priority pair should refrain from sending data in the current data segments
        • Transmitter yielding
      • Q: How to choose priority and how to make yielding decision?
      P1 P2 P3 P4
    • 31. Connection Scheduling Signaling
      • RTS/CTS signaling: All signals are single tone signals
        • Better range due to PAPR gain
        • More connections can compete the resource in a few symbols; small system overhead (224 CIDs, 18% system overhead)
        • A connection picks a connection ID which is locally unique when the connection is setup
        • Symbol/tone choice for RTS/CTS at a given time slot is pseudo random based on the CID
      • Priority is embedded in the position of the symbol/tone choice of a signal
        • “ Fair” sharing of the channel use
      • Both channel information and priority information are embedded by the position and power of the signals
      Tx (RTS) Rx (CTS)
    • 32. SINR Based Yielding
      • Receiver yielding: compare the signal strength from the intended transmitter to the signal strength from the interferer
        • Yield if the SINR (interference from higher priority connections) is below a certain threshold
      • Transmitter yielding: Receiver nodes do inverse power control to help SINR estimation at the transmitters
        • Yield if the SINR (interference from the initiator) of a higher priority connection is below a certain threshold
      • Inverse power scaling enables accurate SINR estimation
      Pt=P1 Pr=h11P1 Pt=1/h11P1 Pr=h21/h11P1 Tx1 Rx1 Tx2 Tx1 Tx2 Rx1 Rx2
    • 33. How to choose SINR threshold?
      • Simulation shows a value between [0,10]dB
      • A simple analysis: assume SINR threshold = x.
        • Translate into distance:
        • Number of pairs scheduled: inversely proportional to x^(2/alpha).
        • System capacity:
      dt di
    • 34. System Throughput vs. SINR Threshold
      • Optimal value between [0,10] dB
      • Agree with the simulation results
    • 35. FlashLinQ vs. 802.11
      • 802.11 is asynchronous
      • 802.11’s scheduling is mainly based on CSMA/CA and RTS/CTS
      • 802.11 signals are transmitted with maximum power
      • 802.11 does not have rate scheduling
      • FlashLinQ is synchronous
      • FlashLinQ relies on RTS/CTS type of mechanism only
        • No exposed terminal
        • No extended hidden terminal
      • FlashLinQ has both transmitter and receiver power scaling to maximize system spectrum efficiency and enable soft yielding decision
      • FlashLinQ does explicit rate scheduling
    • 36. Simulation scenario
      • 200m x 200m with wraparound
      • n bi-directional links dropped uniformly
      • Maximum communcation range 20m
      • Keenan Motley model used to model indoor environment
      • Compare performance between 802.11g and FlashLinQ
    • 37. Throughput comparison   System Sum Throughput (Mbps) System spetrum efficiency (bit/s/Hz) FlashLinQ 56 11.2 802.11g 31 1.55
    • 38. Delay comparison
      • WiFi makes hard reuse decision
        • each user is scheduled much less often, but gets high SINR when scheduled
      • FlashLinQ makes soft reuse decision
    • 39. System performance at different congestion levels
    • 40. Observations
      • Synchronous PHY of FlashLinQ makes it possible to design a distributed low-overhead, low-latency, spatial-efficient connection scheduling
      • Easily extendable to support QoS, maximal matching and MIMO
      • SIC?
      1 1 1/2 2
    • 41. Conclusions
      • Proximate internet combines the physical network and the internet
      • Current technology does not meet the requirements of proximate internet
        • Range, energy consumption, spectrum efficiency, etc.
      • FlashLinQ is a clean slate design for ad hoc networks which can enable proximate internet