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EE360: Lecture 7 Outline Adaptive CDMA Techniques Introduction CDMA with power control Adaptive techniques for interference reduction Rate and power adaptation Adaptive techniques to meet QOS
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Introduction Adaptive CDMA varies the rate and/or power of the signal relative to the channel and interference Traditional power control used to compensate for the near-far problem More sophisticated techniques vary rate and power to maximize throughput Adaptive techniques can be used to meet QOS constraints for different types of media
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Near-Far Problem and Traditional Power Control On uplink, users have different channel gains If all users transmit at same power (P i =P), interference from near user drowns out far user “Traditional” power control forces each signal to have the same received power Channel inversion: P i =P/h i Increases interference to other cells Decreases capacity Degrades performance of successive interference cancellation and MUD l Can’t get a good estimate of any signal h1h1 h2h2 h3h3 P2P2 P1P1 P3P3
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Adaptive Techniques for Interference Reduction Global Power Control (Bambos/Pottie) Power of all users is controlled such the each user’s SIR meets his required constraint There is no unique solution l Want all users to operate at minimum power Distributed algorithms converges to optimum Ideas used for call admission control Variable spreading codes Varying the spreading gain of a code varies the interference rejection P1P1 P2P2
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Rate and Power Adaptation * In CDMA the max. possible data rate depends on The required E b /N 0 for a given BER target (P b =f(E b /N 0,R)) The channel gains (G i )and powers (S i ) of all users Power and rate adaptation schemes Data rate fixed for G i > 0, transmit power adjusted to meet P b target. For G i < 0 power is fixed and data rate is adjusted to meet P b target. l Rate is adapted by varying the bit time: spreading code fixed. Can also truncate rate or power below cutoff 0 The cutoff avoids wasting power on bad channels l Significant power savings for given throughput target *S. Kim, 2000 Assumes interference modeled as AWGN
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CDMA Rate Adaptation Vary bit rate for binary modulation Use multiple codes per user Orthogonal or semiorthogonal Vary the constellation size Variable bit rate typically most effective Multicode with orthogonal codes equivalent Can optimize rate and power allocation to maximize total throughput for all these strategies Jafar/Goldsmith paper
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Power Control given Rate Requirements Mark/Zhu paper (Lola’s presentation) Multirate CDMA Power control to meet QOS (SIR) constraints Adaptation depends on spread BW, required data rates, and SIR requirements Rate and power allocation strategy proposed What about fairness Song/Mandayam paper (Tim’s presentation) Many algorithms will give more resources to user with the best channel: unfair resource allocation Incorporate fairness into resource allocation strategy using utility functions.
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Main Contributions (Student Paper Presentations) Adaptive WCDMA (Mark/Zhu) Power and rate adaptation More users make adaptation less useful Variations in traffic helps Raising power removes effect of errant interferers The “traffic demands” parameter l Rates times SIR per channel Utility functions in adaptive CDMA (Song/Mandayam ) Utility functions as a flexible tool to impose fairness Changing the SIR on each retransmission Separating computations between the mobile and base
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Real-time vs. Non Real-time * Adapting power and rate based on random channel variations may lead to large delays. Can devise adaptive strategies that transmits real-time data at a fixed rate Non real-time data transmitted at a variable rate based on channel conditions Similar to capacity analysis with minimum rate requirements. *S. Kim, 2000; Oh and Wasserman, 1999, others
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Summary There are multiple degrees of freedom in adaptive CDMA techniques Power, Rate, Spreading codes, QOS, etc. Adaptation techniques must be global Every user affects all other users Complex optimization problem Adaptive CDMA is an active research area as 3G systems have adopted a WCDMA standard
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