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Energy and Bursty Packet Loss Tradeoff Over Fading Channels: A System-Level Model

Energy efficiency and quality of service (QoS) guarantees are the key design goals for the 5G wireless communication systems. In this context, we discuss a multiuser scheduling scheme over fading channels for loss tolerant applications. The loss tolerance of the application is characterized in terms of different parameters that contribute to quality of experience for the application. The mobile users are scheduled opportunistically such that a minimum QoS is guaranteed. We propose an opportunistic scheduling scheme and address the cross layer design framework when channel state information is not perfectly available at the transmitter and the receiver. We characterize the system energy as a function of different QoS and channel state estimation error parameters. The optimization problem is formulated using Markov chain framework and solved using stochastic optimization techniques. The results demonstrate that the parameters characterizing the packet loss are tightly coupled and relaxation of one parameter does not benefit the system much if the other constraints are tight. We evaluate the energy-performance trade-off numerically and show the effect of channel uncertainty on the packet scheduler design.
- Trinity College Dublin Ireland
- University of Glasgow United Kingdom
- Dresden University of Technology Germany
- Qatar University Qatar
- Qatar University Qatar
FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), Markov chain, radio resource allocation, opportunistic scheduling, Cross-layer design, 003, green communications, energy efficiency
FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT), Markov chain, radio resource allocation, opportunistic scheduling, Cross-layer design, 003, green communications, energy efficiency
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).6 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
