Allerton 2015 Paper Abstract


Paper ThC3.5

Muppirisetty, L. Srikar (Chalmers University of Technology), Tadrous, John (The Ohio State University), Eryilmaz, Atilla (Ohio State University), Wymeersch, Henk (Chalmers University of Technology)

On Proactive Caching with Demand and Channel Uncertainties

Scheduled for presentation during the Regular Session "Wireless Communication Systems II" (ThC3), Thursday, October 1, 2015, 14:50−15:10, Butternut

53rd Annual Allerton Conference on Communication, Control, and Computing, Sept 29-Oct 2, 2015, Allerton Park and Retreat Center, Monticello, IL, USA

This information is tentative and subject to change. Compiled on December 5, 2021

Keywords Wireless Communication Systems, Performance Analysis, Pricing and Congestion Control


Mobile data traffic has surpassed to voice to become the main component of the system load of today’s wireless networks. Recent studies indicate that the data demand patterns of mobile users are predictable. Moreover, the channel quality of mobile users along their navigation paths is predictable by exploiting their location information. This work aims at fusing the statistically predictable demand and channel patterns in devising proactive caching strategies that alleviate network congestion. Specifically, we establish a fundamental bound on the minimum possible cost achievable by any proactive scheduler under time-invariant demand and channel statistics as a function of their prediction uncertainties, and develop an asymptotically optimal proactive service policy that attains this bound as the prediction window grows. In addition, the established bound yields insights on how the demand and channel statistics affect proactive caching decisions. We reveal some of these insights through numerical investigations.



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