The capacity of next generation of cellular networks using femtocaches is studied when multihop communications and decentralized cache placement are considered. We show that the storage capability of future network User Terminals (UT) can be effectively used to increase the capacity in random decentralized uncoded caching. We further propose a random decentralized coded caching scheme which achieves higher capacity results than the random decentralized uncoded caching. The result shows that coded caching which is suitable for systems with limited storage capabilities can improve the capacity of cellular networks by a factor of log(n) where n is the number of nodes served by the femtocache.
The femtocaching network model is proposed in @cite_17 @cite_23 and the capacity improvement for single-hop communication is computed. In @cite_15 , the authors considered a femtocaching D2D network with multihop relaying of information from the helper to the UTs. They proposed a solution based on index coding in which the helper is utilizing the side information in the UTs to create index codes which are to be multicasted to the UTs. This way, they reduce bandwidth utilization by grouping multiple unicast transmissions into multicast transmission. However, that paper does not consider the case of coded side information and also it assumes that the relayed message from the helper cannot be changed based on the information in the relaying UTs.
@cite_15 @cite_23 @cite_17
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The next generation of cellular networks deploying wireless distributed femtocaching infrastructure proposed by is studied. By taking advantage of multihop communications in each cell, the number of required femtocaching helpers is significantly reduced. This reduction is achieved by using underutilized storage and communication capabilities in user terminals, which results in reducing the deployment costs of distributed femtocaches. A multihop index coding technique is proposed to code the cached contents in helpers to achieve order-optimal capacity gains. As an example, we consider a wireless cellular system in which contents have a popularity distribution and demonstrate that our approach can replace many unicast communications with multicast communication. We will prove that simple heuristic linear index code algorithms based on graph coloring can achieve order-optimal capacity under Zipfian content popularity distribution. We study a distributed antenna system where L antenna terminals (ATs) are connected to a central processor (CP) via digital error-free links of finite capacity R0, and serve K user terminals (UTs). This model has been widely investigated both for the uplink (UTs to CP) and for the downlink (CP to UTs), which are instances of the general multiple-access relay and broadcast relay networks. We contribute to the subject in the following ways: 1) For the uplink, we consider the recently proposed compute and forward (CoF) approach and examine the corresponding system optimization at finite SNR. 2) For the downlink, we propose a novel precoding scheme nicknamed reverse compute and forward (RCoF). 3) In both cases, we present low-complexity versions of CoF and RCoF based on standard scalar quantization at the receivers, that lead to discrete-input discrete-output symmetric memoryless channel models for which near-optimal performance can be achieved by standard single-user linear coding. 4) We provide extensive numerical results and finite SNR comparison with other state of the art information theoretic techniques, in scenarios including fading and shadowing. The proposed uplink and downlink system optimization focuses specifically on the ATs and UTs selection problem. In both cases, for a given set of transmitters, the goal consists of selecting a subset of the receivers such that the corresponding system matrix has full rank and the sum rate is maximized. We present low-complexity ATs and UTs selection schemes and demonstrate through Monte Carlo simulation that the proposed schemes essentially eliminate the problem of rank deficiency of the system matrix and greatly mitigate the noninte We consider a wireless device-to-device (D2D) network where communication is restricted to be single-hop. Users make arbitrary requests from a finite library of files and have pre-cached information on their devices, subject to a per-node storage capacity constraint. A similar problem has already been considered in an infrastructure setting, where all users receive a common multicast (coded) message from a single omniscient server (e.g., a base station having all the files in the library) through a shared bottleneck link. In this paper, we consider a D2D infrastructureless version of the problem. We propose a caching strategy based on deterministic assignment of subpackets of the library files, and a coded delivery strategy where the users send linearly coded messages to each other in order to collectively satisfy their demands. We also consider a random caching strategy, which is more suitable to a fully decentralized implementation. Under certain conditions, both approaches can achieve the information theoretic outer bound within a constant multiplicative factor. In our previous work, we showed that a caching D2D wireless network with one-hop communication, random caching, and uncoded delivery (direct file transmissions) achieves the same throughput scaling law of the infrastructure-based coded multicasting scheme, in the regime of large number of users and files in the library. This shows that the spatial reuse gain of the D2D network is order-equivalent to the coded multicasting gain of single base station transmission. It is, therefore, natural to ask whether these two gains are cumulative, i.e., if a D2D network with both local communication (spatial reuse) and coded multicasting