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Opportunistic Large Arrays. By Anna Scaglione and Yao-Win Hong. Introduction . The reach back problem Issues and limitations Cooperative transmission of Ad Hoc nodes to remote receiver otherwise not reachable – Opportunistic Large Arrays

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opportunistic large arrays

Opportunistic Large Arrays

By Anna Scaglione and Yao-Win Hong

IEEE ISWC 2002

introduction
Introduction
  • The reach back problem
  • Issues and limitations
  • Cooperative transmission of Ad Hoc nodes to remote receiver otherwise not reachable –Opportunistic Large Arrays
    • OLAas the avalanche of cheers by spectators in a stadium
  • OLA distributed modem, adaptive receiver and characteristic features
  • Conclusions and future work

IEEE ISWC 2002

related work
Related Work
  • Increasing Capacity with Mobility
    • M. Grossglauser, D. Tse, “Mobility Increases the Capacity of Ad-Hoc Wireless Networks,” IEEE Proc. INFOCOM 2001
    • Richard H. Frenkiel, B. R. Badrinath, Joan Borras, and Roy D. Yates, “The Infostations Challenge: Balancing Cost and Ubiquity in Delivering Wireless Data,” IEEE Personal Comm., April 2000
  • Cooperative Diversity
    • J.N. Laneman, G.W. Wornell, D.N.C. Tse,“An Efficient Protocol for Realizing Cooperative Diversity in Wireless Networks”, ISIT 2001

IEEE ISWC 2002

reach back problem
Reach Back Problem
  • Problem:
    • Design a scheme that allows two-way transmission from a set of asynchronous transmitters, with low battery life and low peak power, to a remote destination with which they cannot individually exchange data reliably
  • Cooperative Transmission Technique
    • Is cooperation possible through the network connectivity?
    • How can we enforce scalability and adaptability?

IEEE ISWC 2002

bottleneck inter node communications
Bottleneck: Inter-node Communications
  • Signaling is necessary to form a Phased array or do Space-Time Coding
  • Throughput per node vanishes in the limit as the number of nodes diverges [Gupta-Kumar]
    • Obstacle in coordinating large scale networks to perform any form of synchronized activity
  • Is this an insurmountable obstacle?
  • In the uplink network connectivity should not be used to support the bandwidth consuming inter-node signaling

IEEE ISWC 2002

new approach
New approach
  • How can we impress coordination if the nodes responses are asynchronous?
    • Idea: Generate avalanches of signals
  • Opportunistic Large Array (OLA)
    • Formed by firing signals in response to signals fired by special nodes (leaders)
  • Issues:
    • Diversity under the OLA configuration
    • Signal Estimation and Receiver Training

IEEE ISWC 2002

how it works
How it works:
  • Leader triggers transmission.
  • Avalanche effect from Ad Hoc nodes (like the OLA in a stadium)

IEEE ISWC 2002

does it work for large networks
Does it work for large networks?
  • Basis: experimental evidence of neural communications
    • The communication of any neuron pair is almost entirely lost
    • The avalanche of pulses fired by the neurons provide coordination, redundancy for reliability, stability, robustness and all sorts of desirable properties
  • Bio-Inspired Communication Networks

IEEE ISWC 2002

system model
System Model
  • Let leader trigger with a pulse pm(t):

where An is the complex fading coefficient, n(t) is AWGN with variance N0, and τn is the delay of node n.

  • Spread Spectrum System
    • BW=1/Tp>>1/Ts=Rate
  • Multipath Fading Problem
    • Delay Spread >> Tp
    • Frequency Selective Fading

IEEE ISWC 2002

ola structure
OLA Structure
  • Let where c is the speed of light.
    • Assume smaller than radius of transmission.
  • Let Nk = # of nodes in ring Dk.
    • If N sufficiently large, sm(kTp) is Gaussian with variance

IEEE ISWC 2002

ola structure11
OLA Structure
  • Parameters that affect the transmitter alphabet
    • Distribution of the nodes in the network
    • Nodes modulation technique
    • Leader selection
    • Pulse-width of symbol waveform
    • Size of network
  • Spatial distribution of nodes provide diversity in the most non-artificial way

IEEE ISWC 2002

ola modulations i
OLA Modulations I
  • Linear Modulations
    • Let sm be the complex symbol for an M-ary constellation (QAM, ASK, PSK),

p(t) = pulse shape at each node

g(t) = effective aggregated pulse shape.

Signal Processing perspective:

OLA is like a multi-path channel with positive gain!

    • Sample at every Tp,
    • ML receiver: assuming (sme+n) is Gaussian,

IEEE ISWC 2002

ola modulations ii
OLA Modulations II
  • Orthogonal Modulations.
    • Frequency Shift Keying
      • When Tp is large enough, s.t. all pulses overlap

then no need for training with incoherent detection

    • Pulse Position Modulation – UWB applications
      • OLA using UWB generates signals that are still nearly orthogonal.

IEEE ISWC 2002

ola modulations iii
OLA Modulations III
  • Leader Position Modulation
    • Choose leaders to be at positions sufficiently apart.
    • The waveform generated by the Mth leader or group of leaders represent the Mth symbol waveform.

where An is reordered,

and τn is reassigned.

    • Advantage:
      • Nodes need only to transmit one type of pulse.
      • Need not decode symbols, just react to the received power variation.

IEEE ISWC 2002

ola modulations iv
OLA Modulations IV
  • Leader Position Modulation

IEEE ISWC 2002

adaptive receiver with training i
Adaptive Receiver with Training I
  • Let

where r(i)=[r(iTs), r(iTs+Tp), …, r(iTs+kmaxTp)]T, sm is the sampled symbol waveform, and n(i) the sampled noise.

  • M.L. Estimation of the OLA signatures
    • Mean Square Estimation Error contributes to the received noise
    • Use pseudo-noise sequences during training for Low Probability of Detection

IEEE ISWC 2002

adaptive receiver with training ii
Adaptive Receiver with Training II
  • Adaptive LMMSE Estimator
    • To minimize ,
  • Decision directed mode
    • as in memory and learning each decision updates the OLA set of waveforms
  • Problem:
    • Training for newly setup nodes
    • Solution Blind Estimation

IEEE ISWC 2002

adaptive receiver with blind estimate
Adaptive Receiver with Blind Estimate
  • Constant Modulus Algorithm [Godard ‘80]
      • To minimize ,
  • Subspace Method
      • Assume si a white process
      • Estimated with
      • Find noise subspace eigenvectors ud:
      • The equivalent channel is the null space of noise subspace.

IEEE ISWC 2002

intra ola communication
Intra-OLA Communication
  • Flooding network with the data from one source
  • Using exact same receiver structure for both nodes and remote receiver
    • Each parameter different for every node i.
    • Communication between OLA “coalitions”
  • Compressing the joint information of each node while distributing data through the network

IEEE ISWC 2002

performance analysis i
Performance Analysis I
  • Error performance between joint transmission and individual transmission
  • Effect of estimation error

IEEE ISWC 2002

performance analysis i21
Performance Analysis I
  • Robustness toward Moving nodes or Unfriendly nodes

IEEE ISWC 2002

ola downlink distributed receiver
OLA Downlink - Distributed Receiver
  • Many faulty receivers = One good receiver
  • The nodes share with close by nodes their detections, compress and detect jointly the data as they travel through the network (distributed detection for ad-hoc networks)

IEEE ISWC 2002

conclusion
Conclusion
  • OLA introduces the concept of cooperative communication systems
  • Advantages in terms of diversity and robustness
  • Easily constructed on top of existing systems
  • Suitable for applications such as security, maintenance, control signal etc.

IEEE ISWC 2002