• Invited talk @ITA-2018: Adding one transmitter can double the effective gains of coded caching Details
  • Tutorial@ITW-2018. Coded Caching & Distributed Computing: Opportunities and Challenges. (with A. Ramamoorthy) Details
  • Welcome Emanuele Parinello - New PhD student (topic - caching, distributed computing, distributed machine learning). Details
  • Welcome Ayse Unsal - New Postdoctoral researcher (topic - information theory and feedback, index coding). Details
  • Chair of ICC workshop on Advanced Caching for Wireless Networks (co-organized with Georgios Paschos and Mari Kobayashi), ICC Paris, May 2017. Details
  • Awarded ERC Consolidator Grant (DUALITY) 2017-2022. Details
  • Tutorial @ 5G Wireless Summer School: Advanced Wireless Caching (P.Elia), Dresden, Sept 20th. Details
  • Invited talk on Caching at Tyrrhenian Int. Workshop. Livorno - Sept 12th. Details
  • Tutorial@Sigmetrics-16: Caching in Wireless Networks (P. Elia and G. Paschos). Details
  • Tutorial@ICC-2016: Wireless caching for 5G: network coding and PHY. (P. Elia) Details
  • Awarded LABEX Postdoc Grant (information theory for surveillance). Details
  • Awarded Jeunes Chercheurs Grand (ECOLOGICAL-BITS-AND-FLOPS). Details


My research focuses mainly on wireless communications, information theory and coding theory, and lately on the intersection of caching and advanced wireless communications, exploring a broad spectrum of aspects that include:

  1. Fundamental limits of memory-aided (cache-aided) communications
  2. Fundamental limits of distributed computing and distributed machine learning
  3. Caching as a means for altering the structure of networks
  4. The use of memory in advanced communication paradigms such as massive MIMO, ultra high frequency communications, cloud-based communications (cloud RAN)
  5. Practical implementation and prototyping of novel memory aided algorithms.

The elusive tradeoff between memory, performance, complexity and feedback:

We are interested in the elusive tradeoff between memory, performance, complexity and feedback, where roughly speaking

`memory’ = GBytes of storage

performance = achievable rates and reliability

complexity = flops (computational complexity) or implementation complexity

feedback = learn the network, and disseminate learned info around the network.

This meaningful tradeoff (memory, performance, complexity and feedback are intimately intertwined) stands to define future research and practice in communication networks. In deriving the fundamental properties of these intertwined relationship leads to fascinating links with different areas such as

  • combinatorial design, projective geometry, resolvability of affine plances
  • discrete mathematics, statistical physics
  • as well as information theory, complexity theory, lattices, optimization theory and many others.

Other work: Other work includes:

  • design of multiuser communications with imperfect (and delayed) feedback
  • MIMO transceivers
  • complexity of communication* isolation and connectivity in dense networks
  • queueing theory and cross-layer design
  • coding theory (association schemes and algebraic combinatoris)
  • cooperative communications
  • soft-biometrics and surveillance systems.



Ayse Unsal

Interference management for environmental-friendly networks,

Index coding, Information theoretic coded caching

Eleftherios Lampiris

Feedback and complexity in wireless communications,

Information theoretic caching, Combinatorial designs, Coding.

Emanuele Parrinello

Information theoretic caching, distributed computing, and distributed machine learning