Digitale Kommunikationssysteme


Cloud Radio-Access Networks, Caching


In recent years, mobile usage characteristics in wireless networks have changed profoundly from conventional connection-centric to content-centric behaviors. This shift is mainly driven by the rapid growth in multimedia content, particularly by video.

In this context, integrating content caching in heterogeneous networks (HetNet) represents a viable solution for highly content-centric, next generation (5G) mobile networks. Specifically, when caching the most popular contents in edge nodes, e.g., eNBs and relays, alleviates backhaul traffic,
reduces latency and ameliorates quality of service of mobile users.

In particular, we are interested in

  • joint cache placement and file delivery design
  • memory-latency tradeoff
  • centralized cloud processing vs. edge processing
  • Fog computing

and their optimality with respect to fundamental bounds. For instance, the delivery time per bit (DTB), which measures the incurred network time for downloading arbitrary files from transmitting nodes, is one of several metrics used in some of our work to prove optimality.

In the following illustration, the fundamental limits on the delivery time for the depicted cloud and cache-aided HetNet is studied on the basis of the DTB. The HetNet consists of a Home eNB (HeNB) and a macro eNB which serve two users – U1 and U2 – over a Z-shaped wireless channel. For this network, two distinct cloud-edge transmission policies are feasible. In the first policy, the so-called serial policy, the cloud transmission terminates before the wireless transmission initiates, whereas in the second policy, the so-called parallel policy, cloud and wireless transmissions are executed simultaneously.

The results are quite interesting. In particular, we are able to identify channel regimes for which edge caching and cloud processing can provide nontrivial synergistic and non-synergistic performance gains.  

By modifiying the maximum fronthaul capacity nF and per-link (wireless) capacities ndm,  m {1,2,3},  you can see the effect on the optimal DTB over the fractional cache size µ.

The parameters, setup and the results are discussed in more details here.

Our contributions


Author / Editor / Organization Titel Year Download / Bibtex
2017
1 J. Kakar , A. Alameer , A. Chaaban , A. Sezgin , Arogyaswami Paulraj Delivery Time Minimization in Edge Caching: Synergistic Benefits of Subspace Alignment and Zero Forcing Link
BibTeX
2 J. Kakar , S. Gherekhloo , A. Sezgin Fundamental Limits on Delivery Time in Cloud- and Cache-Aided Heterogeneous Networks Link
BibTeX
3 S. Gherekhloo , A. Sezgin Latency-Limited Broadcast Channel with Cache-Equipped Helpers BibTeX
4 A. Alameer , A. Sezgin Resource Cost Balancing with Caching in C-RAN Link
BibTeX
5 J. Kakar , S. Gherekhloo , A. Sezgin Fundamental Limits on Latency in Transceiver Cache-Aided HetNets Link
BibTeX
2016
1 J. Kakar , S. Gherekhloo , Z. Awan , A. Sezgin Fundamental Limits on Latency in Cloud- and Cache-Aided HetNets Link
BibTeX
2 A. Alameer , A. Sezgin Joint beamforming and network topology optimization of green cloud radio access networks Link
BibTeX
3 Y. Ugur , Z. Awan , A. Sezgin Cloud Radio Access Networks with Coded Caching Link
BibTeX
2015
1 Z. Awan , A. Sezgin Fundamental Limits of Caching in D2D Networks With Secure Delivery Download
BibTeX