Communication over Bidirectional Links

1
Communication over Bidirectional Links

• A. Khoshnevis, D. Dash, C Steger, A. Sabharwal
• TAP/WARP retreat
• May 11, 2006

2
Wireless Networks

• Higher throughput
• TAP 400 Mbps
• WiMax/Mesh
• 4G

3
Network of Unknowns
Interference
Topology
Channel
Battery
4
Medium Access Example

• If S1 knows q2 and S2 knows q1
• No need for handshaking
• TDMA scheduling
• No collision
• As load increases
• Probability of queue empty reduces
• Network utility increases
• Having the knowledge about
• Queue states, increases the utilization

5
How to learn about unknowns

• There is gain in knowing unknown parameters
• The information can be gathered
• Directly
• Feedback
• Training
• Dedicated link, information sharing
• Indirectly
• Overhearing
• Passive sensing

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Need for Bidirectional links

• Indirect
• Limited
• Highly depends on the topology and availability
• Direct
• Amount of information can be controlled
• An explicit sharing of information requires flow
  of information in both directions among all
  communicating nodes, hence
• Communication over Bidirectional Links

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Cost-Benefit of learning the unknowns

• Catch
• We dont care about the unknown
• Only care about sending data
• Time varying in nature
• Periodic measurements
• Spend resources for non-data
• If considering the true cost of knowing the
  unknown,
• is there still any gain left?

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Our research

• Unknown Channel
• Chris, Farbod, Ashu, Behnaam
• Allerton05, ISIT06, JSAC06
• Resource allocation algorithm
• Uncertainty of noise
• Farbod, Dash, Ashu
• CTW06, Asilomar06
• Coding scheme
• Randomness of source
• Upcoming NSF proposal
• Access mechanism

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Multiple Access Channel MAC

• The system is modeled by
• Information theory answers
• What is the maximum rate (R1,R2) at which X1 and
  X2 can transmit
• with arbitrary small probability of error

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Standard solution method

• Finding an achievable upper bound
• Achievability proof
• Converse proof
• Typical solution to MAC

R2
R1
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MAC with Bidirectional links

• Time is slotted
• Forward channel multiple access
• Reverse channel feedback from receiver
• Superposition coding

Un-decoded
New Information
Tx
Decodable
From Feedback
Decoded
Un-decodable
Rx
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Our model
j,l I,k
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Contribution and results

• Considering resources in feedback
• Time
• Power (Pf)
• Coding scheme to compress the feedback
  information
• Pf / eP

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Interpretation of result

• In second timeslot
• Both user help to resolve uncertainty
• Co-operation induced by feedback

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Cooperative link

• Anticipate the exponential feedback power is
  resolved
• Under investigation
• Rate region
• Coding strategies

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What if

• Receiver has information for senders
• Superimpose feedback information with its own
  information

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Achievable rate region

• A ? 0
• Only Broadcast
• B ? 1
• Only MAC

B
A
R3
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Channel state vs. data feedback

• So far, receiver sends back unresolved
  information
• In fading environment using channel state
• Power / rate control increases the throughput
• Feedback can be used to send back channel state
  information

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Randomness of source

• Challenges
• K is random
• Under delay constraint
• Access mechanism is required
• Each node needs to know the number of active users

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Recap

• Ongoing work
• Gaining information about the unknowns increases
  the throughput
• Obtaining information is best when it is explicit
  and direct
• Requires resources (power and time) to be
  allocated to unknowns
• Requires bidirectional communication link
• Capacity of MAC increases with realistic
  feedback
• Power in the feedback link is large
• Up coming
• Cooperative link
• Channel state vs. data feedback
• Randomness of the source