Fundamental Limits of Wireless Caching Under Mixed Cacheable and Uncacheable Traffic

Hamdi Joudeh, Eleftherios Lampiris, Petros Elia, Giuseppe Caire

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)


We consider cache-aided wireless communication scenarios where each user requests both a file from an a-priori generated cacheable library (referred to as 'content'), and an uncacheable 'non-content' message generated at the start of the communication session. This scenario is easily found in real-world wireless networks, where the two types of traffic coexist and share limited radio resources. We focus our investigation on single-transmitter wireless networks with cache-aided receivers, where the wireless channel is modelled by a degraded Gaussian broadcast channel (GBC). For this setting, we study the (normalized) delay-rate trade-off, which characterizes the content delivery time and non-content communication rates that can be achieved simultaneously. We propose a scheme based on the separation principle, which isolates the coded caching problem from the physical layer transmission problem, and prove its information-theoretic order optimality up to a multiplicative factor of 2.01. A key insight emerging from our scheme is that substantial amounts of non-content traffic can be communicated while maintaining the minimum content delivery time, achieved in the absence of non-content messages; compliments of 'topological holes' arising from asymmetries in wireless channel gains.

Original languageEnglish
Title of host publication2020 IEEE International Symposium on Information Theory (ISIT)
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)978-1-7281-6432-8
Publication statusPublished - 24 Aug 2020
Externally publishedYes
Event2020 IEEE International Symposium on Information Theory, ISIT 2020 - Los Angeles, United States
Duration: 21 Jun 202026 Jun 2020


Conference2020 IEEE International Symposium on Information Theory, ISIT 2020
Country/TerritoryUnited States
CityLos Angeles


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