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Q1: What makes CDMA work for my smartphone ?

Q1: What makes CDMA work for my smartphone ? . Mung Chiang Networks: Friends, Money, and Bytes . Take a look at your smartphone. Networks (wireless, Internet, web…) Chip, touch screen, battery, software, business model… Data applications Measured in bps Networking Radio air interface

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Q1: What makes CDMA work for my smartphone ?

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  1. Q1: What makes CDMA work for my smartphone? Mung Chiang Networks: Friends, Money, and Bytes

  2. Take a look at your smartphone • Networks (wireless, Internet, web…) • Chip, touch screen, battery, software, business model… • Data applications • Measured in bps • Networking • Radio air interface • Core and backhaul

  3. History of wireless • 1940s: terrestrial wireless communications • 1970s – now: cellular networks • 1G, 2G, 2.5G, 3G, 4G, LTE… • 1990s – now: WiFi networks • More on this later… • What is a cellular network?

  4. Basic terminologies

  5. The air • Electromagnetic spectrum • Licensed vs. unlicensed bands • Signal attenuation • Frequency reuse factor • Interference • Cocktail party

  6. Resource allocation • Orthogonal • TDMA • FDMA • Ideal CDMA • Non-orthogonal • CDMA • Starting in 1989, then IS-95 in 2G • Spread spectrum technique

  7. Interference • Our first example of negative externality • Famous special case: near-far problem • Simple solution by Qualcomm: feedback control • Transmit power control • Received signal power equalization • But what if you need to achieve a target signal quality?

  8. Uplink interference

  9. SIR • Signal-to-Interference-noise-Ratio:

  10. Distributed power control • An iterative, distributed algorithm:

  11. DPC • Simple • in communication • in computation • in configuration • Intuitive • Equilibrium looks good • Convergence sounds plausible

  12. A general theme • Individual behaviors driven by self-interest • Aggregate into a (fair and efficient) state across all users • Helped by feedback signals

  13. View 1: Optimization • Objective: power minimization • Constraints: achieve target SIRs for all users • Variables: transmit powers • Constants: channels, noise, target SIRs

  14. Pictorially

  15. Symbolically • Minimize • Subject to • Variables

  16. Linear programming • Minimize a linear function subject to linear constraints • How to prove convergence of DPC algorithm to a solution of this optimization?

  17. Terminology

  18. View 2: Game • Power control is a competition • Games are models for • Competition • Cooperation • There’s a formal (mathematical) language for games

  19. A game • A set of players • A strategy space for each player • A payoff (utility) or cost function for each player

  20. Prisoner’s dilemma • 2-user game

  21. Strategies • Strategies • Best response • Dominant

  22. Equilibrium • Equilibrium • Socially optimal? • Pareto optimal? • Exist? • Unique?

  23. Coordination game • Another 2-user game

  24. Nash equilibrium • Best response strategies “match”

  25. Power control game • Let’s identify • Players • Strategy spaces • Payoff functions • DPC is just the best response strategy! • Monotonicity of strategy space -> convergence of algorithm

  26. Example Target SIRs: 2, 2.5, 1.5, 2 Noise level: 0.1 mW

  27. Iteration 0 • Initialize all power levels to be 1 mW • Let’s calculate the corresponding SIRs

  28. Iteration 1 • Let’s calculate power levels • Let’s calculate SIRs

  29. Convergence in powers

  30. Convergence in SIRs

  31. Two control loops

  32. In practice • Asynchronous and discrete • Frequency: 800 – 1500 • Granularity: 0.1 dB, 0.2 dB, 0.5 dB • Power control + handoff made all 3G standards work • How to make cellular speed even faster?

  33. Summary • Different users’ signals interfere with each other in the air • Feasible SIR region with a Pareto-optimal boundary • Interference coordination in CDMA uses DPC with feedback • Solves an optimization problem in the form of LP • Or modeled as a non-cooperative game

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