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Wireless Network Design: Optimization Models and Solution ...

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318 Hang Jin <strong>and</strong> Li Guo<br />

1. Guarantee the packet delay for users with real-time service: VoIP <strong>and</strong> gaming<br />

2. Guarantee the throughput of FTP <strong>and</strong> Web users to be within the max. service<br />

rate <strong>and</strong> sustain rate defined by the service level of each individual user.<br />

So the basic procedure of the radio resource allocation is:<br />

1. First allocate radio resource to Gaming <strong>and</strong> VoIP users to ensure the packet delay<br />

requirement;<br />

2. Allocated radio resource to FTP <strong>and</strong> Web users, whose user throughput is less<br />

than the sustain rate defined in his service level;<br />

3. Finally, allocate the remaining resource to those users whose throughput is lesser<br />

than the max. service rate but larger than the sustain rate.<br />

In this experiment, 200 active users are simulated. The fairness metric defined in<br />

IEEE 802.16j [10] is employed in the experiment. In IEEE 802.16j, the fairness is<br />

defined as the reciprocal of the st<strong>and</strong>ard deviation of the normalized throughput<br />

with the mean throughput ¯x = 1<br />

K<br />

F =<br />

K<br />

∑<br />

k=1<br />

� K<br />

K<br />

∑ (<br />

k=1<br />

xk<br />

− 1)2<br />

¯x<br />

xk . This metric grows with larger fairness, <strong>and</strong><br />

is not bounded. The output of the experiment shows that the fairness of 200 users is<br />

1.53, which is slightly better than Fair-Time scheduler.<br />

From the above experiments, we can see that through proper design of radio resource<br />

allocation scheme in WiMax system, we can satisfy the various performance<br />

requirements.<br />

13.6 Conclusion<br />

In this chapter, we have discussed the optimization problem for radio resource management<br />

in OFDMA-based WiMax systems. Radio resource allocation in WiMax is<br />

a classic optimization problem with multiple factors. Various optimization solutions<br />

exist with different metrics <strong>and</strong> tradeoff between complexity <strong>and</strong> performance exist<br />

among those solutions. The dynamic features in most of the aspects of OFDMAbased<br />

WiMax systems impose difficulty on the optimization solution of a radio resource<br />

allocation problem. A Particular performance metric <strong>and</strong> requirement needs<br />

to be considered in the design of each radio resource allocation algorithm.

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