On Proactive Caching with Demand and Channel Uncertainties
Paper in proceeding, 2016

Mobile data traffic has surpassed that of 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.


Srikar Muppirisetty

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

John Tadrous

Rice University

Atilla Eryilmaz

Ohio State University

Henk Wymeersch

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

53rd Annual Allerton Conference on Communication, Control, and Computing


Areas of Advance

Information and Communication Technology

Subject Categories

Communication Systems



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