Analysis of optimal relay selection in IEEE 802.16 multihop relay networks
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Joint base station and relay station placement for IEEE 802.16j networks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Uplink capacity of multi-class IEEE 802.16j relay networks with adaptive modulation and coding
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Recipient maximization routing scheme for multicast over IEEE 802.16j relay networks
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Modeling and resource allocation for mobile video over WiMAX broadband wireless networks
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Wireless Communications
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By introducing the relay capability, the IEEE 802.16j standard is developed to improve the WiMAX performance. Under the transparent mode, existing studies aim at improving network throughput by increasing the transmission rates of mobile stations (MSs). However, we show that using higher rates will let MSs consume more energy. In the paper, we define an energy-conserved uplink resource allocation (EURA) problem in 802.16j networks under the transparent mode, which asks how to arrange the uplink resource to 1) satisfy MSs' requests and 2) minimize their energy consumption. Objective 1 is necessary while objective 2 should be achieved when objective 1 is met. The above bi-objective problem is especially important when the network is non-saturated. The EURA problem is NP-hard and we propose a heuristic with two key designs. First, we exploit relay stations to allow more concurrent uplink transmissions to fully use the frame space. Second, we reduce MSs' transmission powers by adjusting their rates and paths. Simulation results show that our heuristic can save up to 80% of MSs' energy as compared with existing work.