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Bridging the Gap: A Deterministic Model for Wireless Links David Tse Wireless Foundations U.C. Berkeley NSF Wireless Networks Workshop Aug 27, 2007 TexPoint.

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Presentation on theme: "Bridging the Gap: A Deterministic Model for Wireless Links David Tse Wireless Foundations U.C. Berkeley NSF Wireless Networks Workshop Aug 27, 2007 TexPoint."— Presentation transcript:

1 Bridging the Gap: A Deterministic Model for Wireless Links David Tse Wireless Foundations U.C. Berkeley NSF Wireless Networks Workshop Aug 27, 2007 TexPoint fonts used in EMF: AAA A AA A A A A A A A

2 Key Features of Wireless Channels broadcast interference high dynamic range in channel strengths between different nodes Basic PHY layer model- additive Gaussian channel:

3 Gaussian Model: Basis for PHY-Layer Advances Many PHY-layer advances in past decade based on the Gaussian model. Examples: MIMO, interference cancellation, superposition coding Advances in the context of point-to-point, many- to-one, and one-to-many settings. Hard to use to reason about more complex wireless network configurations. Capacity of simple networks with single-relay or two interfering point-to-point links are open problems for eons.

4 Common Channel Models for Wireless Networks 0/1 connectivity models packet collision models SINR based model: treating interference as noise These models do not capture key properties of wireless medium constrains the design of innovative communication schemes

5 Bridging the Gap More research needed in model building. As an example we discuss a deterministic channel model which : captures several key aspects of the wireless medium is scalable to complex wireless networks

6 Point-to-Point Link Rx observes  most-significant bits of the transmitted signal.  is proportional to the SNR on the dB scale.

7 Broadcast user 2 user 1 Users with higher SNR see more bits of the transmitted signal. Implemented by superposition coding at the PHY layer.

8 Multiple Access user 2 user 1 mod addition More significant bits of strong user observed cleanly. Collision with weak user at the less significant bits. Implemented by interference cancellation at the PHY layer.

9 Application to Relay Networks What is the capacity of this network from a single source S to a single destination D?

10 Max-Flow Min-Cut Theorem Theorem: where Generalization of Ford-Fulkerson Theorem for wireline networks.

11 Conclusion PHY layer higher layers simple wireless channel model


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