Statistical QoS-Driven Power Adaptation Over Q-OFDMA-Based Full-Duplex D2D 5G Mobile Wireless Networks
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abstract
2017 IEEE. To support the emerging next generation wireless networks, researchers have made a great deal of efforts in investigating promising techniques in multimedia services - the statistical quality-of-service (QoS) technique, which has been proved to be effective in statistically guaranteeing delay-bounded video transmissions over the time-varying wireless channels. On the other hand, as the two 5G-promising candidate techniques, the multiple-input and multiple-output (MIMO) based full-duplex (FD) and device-to-device (D2D) can also significantly enhance the performance of statistical QoS for time- sensitive traffics over the 5G mobile wireless networks. However, how to efficiently integrate these advanced techniques in supporting statistical QoS impose many new challenges not met before. To effectively overcome the difficulties, in this paper we propose the QoS-driven power adaptation scheme by applying Quadrature- OFDMA (Q-OFDMA) to implement MIMO FD D2D based multimedia services in 5G mobile wireless networks. In particular, under the Nakagami-m channel model, we establish the PHY-layer Q-OFDMA system model and FD D2D model. Given the statistical QoS constraint, we derive and analyze the effective capacity under our proposed optimal power adaptation policy over 5G mobile wireless networks. Also conducted is a set of simulations which show that our proposed scheme outperforms the other existing schemes in terms of self-interference cancellation to efficiently implement the statistical QoS over 5G mobile wireless networks.
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2017 IEEE Wireless Communications and Networking Conference (WCNC)
