Statistical QoS-Driven Power Allocation for WiFi Offloading Over Heterogeneous Wireless Networks
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2017 IEEE. To support the emerging next era of mobile wireless networks, researchers have made a great deal of efforts in 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 one of the 5G-promising techniques, the offloading technique has been demonstrated as the powerful approach to address the data explosion problem, alleviating the congestion in macrocells. Consequently, challenges have been imposed in applying the WiFi offloading scheme for maximizing the effective capacity under QoS constraints. To effectively overcome the above-mentioned challenges, we propose the statistical QoS-driven power allocation scheme through applying the WiFi offloading system over heterogeneous wireless networks. In particular, under the Nakagami-m fading channel model, we establish the communication model for WiFi offloading over heterogeneous wireless networks. Then, we propose the WiFi offloading methods. Given the statistical QoS constraints, we derive and analyze the effective capacity under our developed optimal power-allocation policies for the WiFi offloading scheme over heterogeneous wireless networks. Also conducted is a set of simulations which analyze the performance and the benefits of our proposed WiFi offloading scheme, compared to the schemes without WiFi offloading in terms of effective capacity under statistical QoS constraints over heterogeneous wireless networks.
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2017 51st Annual Conference on Information Sciences and Systems (CISS)
