We study the role of caches in wireless networks. In particular, we focus on content caching and delivery across a Gaussian interference network, where both transmitters and receivers are equipped with caches. We provide a constant-factor approximation of the system's degrees of freedom (DoF), for arbitrary number of transmitters or receivers, content library size, receiver cache size, and transmitter cache size (as long as the transmitters combined can store the entire library among them). We demonstrate approximate optimality with respect to informationtheoretic bounds that do not impose any restrictions on the caching and delivery strategies. Our characterization reveals three key insights. First, the approximate DoF is achieved using a strategy that separates the physical and network layers. This separation architecture is thus approximately optimal. Second, we show that increasing transmitter cache memory beyond what is needed to exactly store the entire library between all transmitters does not provide more than a constant-factor benefit to the DoF. A consequence is that transmit zero-forcing is not needed for approximate optimality. Third, we derive an interesting trade-off between the receiver memory and the number of transmitters needed for approximately maximal performance. In particular, if each receiver can store a constant fraction of the content library, then only a constant number of transmitters are needed. In addition, solving the caching problem required formulating and solving a new communication problem, the symmetric multicast X-channel, for which we provide an exact DoF characterization. J. Hachem and S. Diggavi are with the
In REF , an orderoptimal approximation on the system performance for arbitrary number of transmitters and receivers was presented. But their analysis is limited to the case where the accumulated cache size at the transmitter side is large enough to cache all the files and only hybrid X-multicast channel is considered.
Degrees of Freedom of Cache-Aided Wireless Interference Networks
IEEE Transactions on Information Theory, vol. 64, pp. 5359 - 5380, July 2018
Mathematics Computer Science