摘要
Recently, applications of real-time polling service (rtPS) in IEEE 802.16 wireless networks have gained considerable popularity. These applications generate large amounts of real time traffic in the network and thus maintaining the quality of service (QoS) such as packet delay requirement in rtPS dominant networks is critical. Existing dimensioning methodology does not consider QoS parameters of rtPS in network dimensioning. Moreover, exhaustive and time-consuming simulations are required to evaluate the performance and QoS of rtPS. To overcome this problem, we propose an improved radio network dimensioning framework which considers QoS parameters of rtPS in network dimensioning. In this framework, an analytical model is developed to evaluate the capacity and performance of rtPS in IEEE 802.16 wireless networks. The proposed framework provides a fast and accurate means of finding the trade-off between system load and packet delay, thus providing network operators with an analytical tool that jointly considers coverage, capacity and QoS requirements for obtaining the minimum number of sites required. The accuracy of the proposed model is validated through simulations.
Recently, applications of real-time polling service (rtPS) in IEEE 802.16 wireless networks have gained considerable popularity. These applications generate large amounts of real time traffic in the network and thus maintaining the quality of service (QoS) such as packet delay requirement in rtPS dominant networks is critical. Existing dimensioning methodology does not consider QoS parameters of rtPS in network dimensioning. Moreover, exhaustive and time-consuming simulations are required to evaluate the performance and QoS of rtPS. To overcome this problem, we propose an improved radio network dimensioning framework which considers QoS parameters of rtPS in network dimensioning. In this framework, an analytical model is developed to evaluate the capacity and performance of rtPS in IEEE 802.16 wireless networks. The proposed framework provides a fast and accurate means of finding the trade-off between system load and packet delay, thus providing network operators with an analytical tool that jointly considers coverage, capacity and QoS requirements for obtaining the minimum number of sites required. The accuracy of the proposed model is validated through simulations.
