Resource Allocation in Wireless Communication Networks

1. Resource Allocation in Wireless Communication Networks Xin Liu Computer Science Dept. University of California, Davis

2. Wireless Communication Networks • Cellular networks • WiFi, WiMAX • Ad hoc networks • Mesh/community networks • Wireless sensor networks • …

3. Resource Management • Scarce radio resource • Timing-varying and location-dependent channel conditions • Limited battery power • Sharedmedium • Mobility

4. Research Topics • Opportunistic scheduling • Spectrum-agile communication • Wireless sensor networks

5. Opportunistic Scheduling • Objective • Efficient spectrum utilization • QoS provisioning • Motivation • Scarce radio resource • Timing-varying channel conditions • Multi-user diversity

6. Channel Conditions • Decides transmission performance • Determined by • Strength of desired signal • Noise level • Interference from other transmissions • Background noise • Time-varying and location-dependent.

7. Interference and Noise

8. Propagation Environment

9. Time-varying Channel Conditions • Due to users’ mobility and variability in the propagation environment, both desired signal and interference are time-varying and location-dependent • A measure of channel quality: SINR (Signal to Interference plus Noise Ratio)

10. Illustration of Channel Conditions

11. Performance vs. Channel Condition • Voice users: better voice quality at high SINR for a fixed transmission rate; • Data users: higher transmission rate at high SINR for a given bit error rate; • Adaptation techniques are specified in 3G standards. • TDMA: adaptive coding and modulation • CDMA: variable spreading and coding

12. Multi-user Diversity Scheduling question: given this channel condition, which user should transmit at a given time?

13. A Greedy Scheduling Scheme • Always choose the user with the best channel condition to transmit • Improve the spectrum efficiency • Unfairness among users Starvation

14. Opportunistic Scheduling • Basic idea: schedule users in a way that exploits variability in channel conditions • Opportunistic: choose a user to transmit when its channel condition is good. • Fairness/QoS requirements: opportunism cannot be too myopic. • Each scheduling decision depends on • channel conditions • fairness or QoS requirements • Select the “relatively-best” user

15. System Model • Time-slotted systems • Each user has a certain requirement • TDMA or time-slotted CDMA systems (e.g., IS-856)

16. Notion of Utility • Uik: data rate of user iat time k • If time slot k is assigned to user i, useri will receive a throughput of Uik. • Measures the worth of the time slot to user i. • Generalize to the notion of utility: • throughput • throughput – cost of power consumption • {Uik, k=1,2,3…} is a stochastic process. • Utility values are comparable and additive.

17. A Framework for Scheduling • Objective: Maximize the sum of all users’ throughput while satisfying the QoS requirements of users. • Scheduling decision depends on: • Channel conditions • QoS/fairness requirements

18. A Case Study: Temporal Fairness Scheduling

19. Objective Maximize average system throughput subject to the fairness constraints ri. System utility: • is the indicator function

20. Scheduling Problem Formulation • Optimal scheduling problem where  is the set of all policies. • No channel model assumed • No assumption on utility functions • General distributions of • Users’ utility values can be arbitrarily correlated across time and among users.

21. An Optimal Scheduling Policy • Choose the ``relatively-best'' user to transmit • vi*: “off-sets” used to achieve the fairness requirement.

22. Parameter Estimation • We estimate vi* based on measurements of the channel using stochastic approximation. • Consider the root-finding algorithm for each threshold vi*: • vik → vi* with appropriately chosen • However,

23. Parameter Estimation (Cont'd) • vik → vi* w.p.1 under appropriate conditions (e.g., ak=1/k). • Simulation results show the estimation works well.

24. Scheduling Algorithm

25. Case 1: Simulation of a Wireless System • Fair sharing: ri=1/N, N is number of active users • Non-opportunistic scheme: round-robin • Concentrate on the downlink. Reuse factor is 3. • Consider co-channel interference from first-ring neighbor cells; • Consider path loss (Lee's model) and log-normal shadowing; • Each user moves in the cell with a certain speed and its direction, which can change periodically; • 25 users/cell with exponentially distributed on-off periods.

26. Utility Values • Step function - user 1-2; • Linear function - user 3-4; • S-shape function -user 5-8;

27. System Performance

28. Conclusions on Opportunistic Scheduling • Traditional setting: performance of system depends on average channel conditions. • Opportunistic setting: performance of system depends on peak channel conditions. • Opportunistic gain increases with • channel variability (over time) • number of users • channel independence (across users). • Current and Future wireless systems: • exploit opportunistic methods (IS-856).

29. Where do We Stand? • History: a successful story, a $$$$$$ industry • Current • Rapid proliferation • Policy evolution • Future: • More spectrum • Advanced DSP and radio technologies • Cool applications An Exciting Area, a Long Way to Go!

30. Recruitment • I am looking for students • Self-motivation • Welcome background in algorithms, optimization, probability, etc. Thank You!