1. Scheduling for Wireless Networks with Users’ Satisfaction and Revenue Management Leonardo Badia*, Michele Zorzi + Speaker: Andrea Zanella + {lbadia, zorzi}@ing.unife.it *Dept. of Engineering, University of Ferrara + Dept. of Information Eng., University of Padova

2. Outline Users’ Satisfaction Model for the RRM Scheduling Algorithms Framework Case Study: UMTS HSDPA Numerical Results Conclusions

3. Allocation problem of the RRM General problem: assignment of a scarce resource. Radio Resource Management. Efficient resource usage and multiple access for different users.

4. Allocation problem of the RRM Micro-economic concept of utility (dep. on allocated resource g) Target: welfare maximisation (?) Constraints on the availability of the resource (band)

5. User’s Satisfaction Concept High performance peaks are useless when a low assignment is satisfactory. Target of the operator: to satisfy the customers and to have high profit. Another trade-off: total welfare vs. total earned revenue.

6. Price effect introduction Price p i impacts on the revenue. In this work we focus on two different pricing policies: p i (g i ) = p,  admitted user (flat price) p i (g i ) = kg i,  user (linear price) The appreciation of the service depends on the paid price.

7. Price effect introduction Our proposal is to consider an Acceptance-probability A i dependent on both price and utility. A possible choice (coherent with the properties of such a probability):

8. Price effect introduction This model allows a direct revenue evaluation as: Two different optimisation goals can be identified:

9. Our Scheduling Algorithm Start with a “trial” solution. The starting solution is similar but not equal to the CS scheduler. This overcomes fairness problems. A further Local Search is performed. The Local Search is aimed at increasing the revenue at each iteration.

10. Wireless Networks Scheduling The starting solution is based on the marginal utility u ’(g) equal to a given threshold. This avoids over-assignments which are instead present with the CS scheduler. Performance metrics: revenue, admission rate.

11. High Speed Downlink Packet Access UMTS - release 5 New Shared Channel (High Speed – Downlink Shared CHannel – HS DSCH) Fast scheduling (MAC – High Speed, located in the Node B) Downlink side, asymmetric traffic

12. Simulation parameters No. of cells3 X 3, hexagonal wrapped Cell radius250 m Orth. factor0.3 Propagation β = 3.5,  = 4 dB, f d =2Hz UtilitiesSigmoid-shaped curves Marg.utility thr.  Parameters for Ai(ui,pi) C = 0.5,  = 2.0,  = 4.0

13. Results

15. Conclusions Microeconomic theory considerations (utility and pricing trade-off) Consequences on operator’s revenue and users’ service appreciation Good results with LC strategy (local search aimed at revenue maximisation): revenue is improved up to 20-30% for 200 users. Possibilities of price tuning and more aware choice of the RRM parameters

16. Future work Parameter optimisation. Different traffic mixtures. More complex pricing strategies, suited to the form of the utility functions. Possibility of adopting the acceptance-probability as a sorting metric directly into the scheduler.