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.  Queue Network of Unknowns Interference Topology Channel Battery

4. q1 S1 l1 D q2 l2 S2 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. W X Y + H Q(H) S1 D S2 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

6. 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

7. Cost-Benefit of learning the unknowns • Catch • We don’t 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?

8. S1 D S2 S1 h D Our research • Unknown Channel • Chris, Farbod, Ashu, Behnaam • Allerton’05, ISIT’06, JSAC’06 • Resource allocation algorithm • Uncertainty of noise • Farbod, Dash, Ashu • CTW’06, Asilomar’06 • Coding scheme • Randomness of source • Upcoming NSF proposal • Access mechanism

9. X1 Y X2 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

10. Standard solution method • Finding an achievable upper bound • Achievability proof • Converse proof • Typical solution to MAC R2 R1

11. 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

12. Our model j,l I’,k’

13. Contribution and results • Considering resources in feedback • Time • Power (Pf) • Coding scheme to compress the feedback information • Pf/ eP

14. Interpretation of result • In second timeslot • Both user help to resolve uncertainty Co-operation induced by feedback

15. X1 Y X2 Cooperative link • Anticipate the exponential feedback power is resolved • Under investigation • Rate region • Coding strategies

16. What if… • Receiver has information for senders • Superimpose feedback information with its own information

17. Achievable rate region • A:  = 0 • Only Broadcast • B:  = 1 • Only MAC B A R3

18. h2 h1 h2 h1 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

19. X2 X1 X3 X4 Randomness of source • Challenges: • K is random • Under delay constraint • Access mechanism is required • Each node needs to know the number of active users

20. 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