Integration of WiMAX and WiFi Optimal Pricing for Bandwidth Sharing Dusit Niyato and Ekram Hossain, TRLabs and University of Manitoba IEEE Communications Magazine May 2007 報告者：李宗穎

2 Outline Introduction Major Research Issues and The Related Approaches Pricing for Bandwidth Sharing in An Integrated WIMAX/WIFI Network Conclusions

3 An integrated WiMAX/WiFi network

4 Protocol Adaptation and QoS Support e –unsolicited granted service –polling service –best effort service e –low-priority traffic –high-priority traffic

5 QoS support in an integrated WiMAX/WiFi network per-flow approach –guarantee QoS for individual flows –complexity is high aggregate approach –reduce this overhead by grouping multiple flows with similar QoS requirements together and servicing them as a single traffic class

6 Pricing pricing issue relates to the control of radio resource usage from an economic point of view –Optimization-Based Pricing –Game-Theory-Based Pricing

7 Optimization-Based Pricing Goal : maximize utility –the wired network to maximize system utility the rate is a function of price –price-based distributed algorithm for rate adaptation in wireless networks both rate and reliability performances Disadvantage –may not satisfy all the related entities individually

8 Game-Theory-Based Pricing (1/2) game-theoretic formulation aims at providing individually optimal solutions –suitable for systems with multiple entities –service providers want to maximize their profit –users want to achieve their best QoS performance

9 Game-Theory-Based Pricing (2/2) Three major components –the players –the strategies of the players –the payoffs for the players Nash equilibrium –no player can increase his/her payoff by choosing a different strategy

10 System Description the WiMAX BSs and WiFi routers are operated by different service providers the WiMAX service provider charges the WiFi networks with adjustable pricing bandwidth sharing and pricing model uses a genetic algorithm for learning to choose the best strategy

11 Revenue and Elastic Demand (1/3) WiMAX BS charges different prices to different WiFi APs/routers depending on the bandwidth demand from WiFi clients D(λ i,b i (s) ) : queuing delay λ i : traffic arrival rate b i (s) : allocated bandwidth N SS : total number of SSs a i : indicates the fixed revenue e i : decreasing rate of revenue due to the queuing delay

12 Revenue and Elastic Demand (2/3) a linear demand function expressed as follows The revenue of the WiFi network k is obtained b j (P k (r) ) = c j – d j P k (r) ) b j (P k (r) ) : the bandwidth demand of node j P k (r) : the price charged at WiFi AP/router k c j : the fixed bandwidth demand d j : elasticity of the demand function

13 Revenue and Elastic Demand (3/3) Finally, the cost is calculated from P k (bs) : the price charged by the WiMAX BS to the WiFi AP/router k N k (r) : the number of WiFi nodes served by router k F k (r) : a fixed cost for a WiFi router

14 Stackelberg Game and Profit Maximization (1/2) The players –The WiMAX BS and WiFi APs/routers The strategies –WiMAX BS : the price P k (bs) charged to the WiFi APs –WiFi APs : the required bandwidth The payoffs –WiMAX BS and WiFi APs/routers, the payoffs are the corresponding profits

15 Stackelberg Game and Profit Maximization (2/2) Given the price charged by the WiMAX BS P k (bs), the profit of AP k is WiMAX BS can adjust the price P k (bs) charged to router k to achieve the highest payoff π k (r) = R k (r) – C k (r)

16 Genetic algorithm for Stackelberg game for bandwidth sharing

17 Simulation Parameter BS TypeTDMA/TDD Frame duration5ms Bandwidth20MHz ModulationQPSK (1/2) SS number10 WiFi Router Serve Number4 + 6

18 Profit function of the WiMAX BS

19 Price and bandwidth sharing at the equilibrium under different traffic loads at the subscriber stations.

20 Price and bandwidth sharing at the equilibrium under different numbers of WiFi nodes served by WiFi router two

21 Conclusions Game theory has been used to analyze and obtain the optimal pricing for bandwidth sharing between a WiMAX BS and WiFi APs/routers