Downlink Scheduling With Economic Considerations to Future Wireless

Networks

Bader Al-Manthari, Nidal Nasser, and Hossam Hassanein

IEEE Transactions on Vehicular Technology, Vol.58, No.2, FEBRUARY 2009

報告人：李宗穎

2

Outline

Introduction & Related Work System and Packet Scheduler Model Centralized Downlink Packet Scheduler Performance Evaluation Conclusion

3

Introduction (1/2)

Future wireless cellular systems (HSDPA : high-speed downlink packet access) offer high data rates that are beyond the capabilities of 3G systems

A key component of radio-resource management is packet scheduling, which is responsible for distributing the shared radio resources among the mobile users

4

Introduction (2/2)

The packet scheduling scheme should track the instantaneous channel conditions of the connections and select for transmission those that are experiencing good channel conditions to maximize system capacity

5

Research Goal

This paper design CDPS (centralized downlink packet scheduler) to balance between the requirements of connections (throughput & fairness) and the requirements of service providers (revenues)

6

Related Work

maximum carrier-to-interference ratio (Max CIR) [5] Max CIR tends to maximize the system’s capacity by serving

the connections with the best channel quality proportional fairness (PF) [6]

PF tries to increase the degree of fairness among connections by selecting those with the largest relative channel quality

[5] S. Borst, “User-level performance of channel-aware scheduling schemes in wireless data networks,” in Proc. IEEE Conf. Comput. Commun. INFOCOM, Mar. 2003, vol. 1, pp. 321–331.[6] A. Jalali, R. Padovani, and R. Pankaj, “Data throughput of CDMA-HDR a high efficiency-high date

rate personal communication wireless system,” in Proc. IEEE VTC, May 2000, pp. 1854–1858.

7

Contributions

This paper propose a novel centralized downlink packet scheduler (CDPS) scheme CDPS tries to balance between the user connection’s

preferences (as perceived by the service provider) and the fairness by formulating an optimization problem that can be solved in real time

the service provider can choose the degree of fairness of the CDPS

CDPS can be configured to reduce to the Max CIR and PF schemes

8

System and Packet Scheduler Model

Assumption Only one connection is scheduled for transmissi

on at each frame Scheduling scheme will equally work if more th

an one connection is scheduled These PDUs are stored in the transmission queu

e of the corresponding connection in a first-in–first-out fashion

9

Packet scheduler model

Each connection regularly informs the base station the size of the transport block that the base

station should send to the connection number of simultaneous channel codes, and the

type of modulation and coding schemes

10

Centralized Downlink Packet Scheduler The proposed scheme (CDPS) employs practical

economic models through the use of utility and opportunity cost functions First, outlining the general formulation of CDPS Second, provide a definition for a possible utility

function, an opportunity cost function, and a fairness measure

Finally, mathematically show that our defined utility function for CDPS reduces to the Max CIR and PF scheduling schemes

11

General formulation of CDPS

Xi1(t), . . . , Xim−1(t) are the chosen quantitative measures (ex: data rate, average delay…)

Xim(t) is a fairness measure that represents how fair the scheduling scheme is to the user connection

OCi(t) is the opportunity cost of serving connection i at time t

K is a predefined constant value

12

Opportunity cost function opportunity cost is how much data rate the system would c

ompromise if connection i is selected for transmission given that there is a connection j with a higher current data rate

Ri(t) is the current data rate for connection i at time t, which depends on its channel condition

maxj Rj(t) is the maximum current data rate of all connections at time t

13

Cobb–Douglas functional form of production functions

Y = ALαKβ

Y = total production L = labor input K = capital input A = total factor productivity α and β These values are constants determined by a

vailable technology α + β = 1 (constant) α + β < 1 (decreasing) α + β > 1 (increasing)

14

Cobb-Douglas Utility Function Assuming m = 2 in our formulation of CDPS, the Cobb–

Douglas utility function is expressed as

Xi1 be any performance metric that the service provider wants to optimize

Xi2 be a fairness measure that increases as the connection’s or system’s perception of fairness increases

c and d is constant value

15

Definition of Xi1(t) and Xi2(t)

The utility of connection i being served increases as Ri(t) increases

γi is used to control the shape of Xi2(t) αi(t) = Si(t)/ (maxj Sj(t))

Si(t) is the average throughput for connection i up to time t

maxj Sj(t) is the maximum average throughput achieved among all connections up to time t

16

αi(t) and γi in Xi2(t)

the larger the value of γi, the higher the rate of decrease in Xi2

(t) (dynamically changed as needed by the service provider) the scheduling scheme to be fairer to the connections with low

α values (i.e., low average throughputs compared with connections with high average throughputs)

17

CDPS decision rule

CDPS will find the connection that would maximize the following objective function:

a solution can be found by choosing connection i for transmission such that

18

Properties of CDPS Efficiency

CDPS makes efficient use of the bandwidth by relatively favoring connections with good channel conditions

Fairness CDPS also consider average throughputs compared with the

maximum average throughput User satisfaction

using both the instantaneous channel condition and the user’s connection relative fairness

Flexibility flexibility to choose the degree of fairness and thereby control the

capacity–fairness tradeoff and effect the obtained revenues

19

Flexibility of CDPS

Max CIR If K is set to 0, then the CDPS reduces to the M

ax CIR scheme PF schemes

If c is set to 0, d is set to 1, then the CDPS reduces to the PF scheme

20

Simulation Model

User Download FTP data (50Mb)

Each connection sendsa request for one FTP file

Using NS2 + Enhanced UMTS Radio Access Network Extensions

21

Throughput

Cell throughput Cell throughput with different values of K

25 user connections

22

User Satisfaction

User satisfaction with minimum throughput of 128 kb/s with different values of K

23

Conclusion

CDPS scheme for future wireless cellular systems that is based on a utility function to represent the satisfactions of the mobile users as perceived by the service provider