2010/10/08 by Hesham El-Gamal, El-Gamal, Hesham, John Tadrous +3
Computer Science · Decision Sciences · Engineering · #Advanced MIMO Systems Optimization #Cognitive Radio Networks and Spectrum Sensing #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Information Theory (cs.IT) #Networking and Internet Architecture (cs.NI) #Personal Information Management and User Behavior #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1010.1800
openalex publication_date 2010/10/08 · openalex created_date 2022/10/04 · openalex updated_date 2026/07/28
This paper introduces the novel concept of proactive resource allocation in\nwhich the predictability of user behavior is exploited to balance the wireless\ntraffic over time, and hence, significantly reduce the bandwidth required to\nachieve a given blocking/outage probability. We start with a simple model in\nwhich the smart wireless devices are assumed to predict the arrival of new\nrequests and submit them to the network T time slots in advance. Using tools\nfrom large deviation theory, we quantify the resulting prediction diversity\ngain to establish that the decay rate of the outage event probabilities\nincreases linearly with the prediction duration T. This model is then\ngeneralized to incorporate the effect of prediction errors and the randomness\nin the prediction lookahead time T. Remarkably, we also show that, in the\ncognitive networking scenario, the appropriate use of proactive resource\nallocation by the primary users results in more spectral opportunities for the\nsecondary users at a marginal, or no, cost in the primary network outage.\nFinally, we conclude by a discussion of the new research questions posed under\nthe umbrella of the proposed proactive (non-causal) wireless networking\nframework.\n