Abstract

Caching appears to be an efficient way to reduce peak hour network traffic congestion by storing some content at the user's cache without knowledge of later demands. Recently, Maddah-Ali and Niesen proposed a two-phase, placement and delivery phase, coded caching strategy for centralized systems (where coordination among users is possible in the placement phase), and for decentralized systems. This paper investigates the same setup under the further assumption that the number of users is larger than the number of files. By using the same uncoded placement strategy of Maddah-Ali and Niesen, a novel coded delivery strategy is proposed to profit from the multicasting opportunities that arise because a file may be demanded by multiple users. The proposed delivery method is proved to be optimal under the constraint of uncoded placement for centralized systems with two files, moreover it is shown to outperform known caching strategies for both centralized and decentralized systems. Comment: 6 pages, 3 figures, submitted to ISIT 2016

Abstract

International audience; A deeply pipelined and parallel LDPC decoder architecture is proposed in this paper. The main feature of this architecture is the ∆-update scheme, which relaxes the data dependency requirement and allows for deeper pipelines than typical decoders. The proposed architecture also has the flexibility to handle a large number of codes. Frame error rate performance is shown for three codes with different quantization parameters. Finally, the impact of pipeline depth on processing time and on the energy-delay product (EDP) is evaluated from post-synthesis results. The results show that the ability to have deeper pipelines can lead to large reductions in EDP.