Beyond Cut-Set Bounds -The Approximate Capacity of D2D Networks

Abstract-Device-to-Device (D2D) communication is emerging as a viable solution for alleviating the severe capacity crunch in content-centric wireless networks. D2D encourages backhaulfree communication directly between devices with similar content requirements grouped into clusters. In this work, a self-sustaining D2D network is considered, where a set of commonly requested files are completely stored within the collective devices memories in a cluster and file requests from devices are serviced by local inter-device multicast transmissions. For such a network, new information theoretic converse results are developed, in the form of a lower bound on the minimum D2D multicast rate as a function of the storage per device. The proposed converse is then used to characterize the approximate tradeoff between the device storage and D2D multicast rate to within a constant multiplicative gap of 8

Fundamental Limits of Caching in Wireless D2D Networks

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 work, we consider a D2D ``infrastructure-less'' 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, 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 can provide an improved scaling law. Somewhat counterintuitively, we show that these gains do not cumulate (in terms of throughput scaling law).Comment: 45 pages, 5 figures, Submitted to IEEE Transactions on Information Theory, This is the extended version of the conference (ITW) paper arXiv:1304.585

Adaptive Video Streaming for Wireless Networks with Multiple Users and Helpers

We consider the optimal design of a scheduling policy for adaptive video streaming in a wireless network formed by several users and helpers. A feature of such networks is that any user is typically in the range of multiple helpers. Hence, in order to cope with user-helper association, load balancing and inter-cell interference, an efficient streaming policy should allow the users to dynamically select the helper node to download from, and determine adaptively the video quality level of the download. In order to obtain a tractable formulation, we follow a "divide and conquer" approach: i) Assuming that each video packet (chunk) is delivered within its playback delay ("smooth streaming regime"), the problem is formulated as a network utility maximization (NUM), subject to queue stability, where the network utility function is a concave and componentwise non-decreasing function of the users' video quality measure. ii) We solve the NUM problem by using a Lyapunov Drift Plus Penalty approach, obtaining a scheme that naturally decomposes into two sub-policies referred to as "congestion control" (adaptive video quality and helper station selection) and "transmission scheduling" (dynamic allocation of the helper-user physical layer transmission rates).Our solution is provably optimal with respect to the proposed NUM problem, in a strong per-sample path sense. iii) Finally, we propose a method to adaptively estimate the maximum queuing delays, such that each user can calculate its pre-buffering and re-buffering time in order to cope with the fluctuations of the queuing delays. Through simulations, we evaluate the performance of the proposed algorithm under realistic assumptions of a network with densely deployed helper nodes, and demonstrate the per-sample path optimality of the proposed solution by considering a non-stationary non-ergodic scenario with user mobility, VBR video coding.Comment: final version to appear in IEEE Transactions on Communication

Coded caching: Information theoretic bounds and asynchronism

Caching is often used in content delivery networks as a mechanism for reducing network traffic. Recently, the technique of coded caching was introduced whereby coding in the caches and coded transmission signals from the central server were considered. Prior results in this area demonstrate that carefully designing the placement of content in the caches and designing appropriate coded delivery signals from the server allow for a system where the delivery rates can be significantly smaller than conventional schemes. However, matching upper and lower bounds on the transmission rate have not yet been obtained. In the first part of this thesis we derive tighter lower bounds on the coded caching rate than were known previously. We demonstrate that this problem can equivalently be posed as a combinatorial problem of optimally labeling the leaves of a directed tree. Our proposed labeling algorithm allows for significantly improved lower bounds on the coded caching rate. Furthermore, we study certain structural properties of our algorithm that allow us to analytically quantify improvements on the rate lower bound for general values of the problem parameters. This allows us to obtain a multiplicative gap of at most four between the achievable rate and our lower bound. The original formulation of the coded caching problem assumes that the file requests from the users are synchronized, i.e., they arrive at the server at the same time. Several subsequent contributions work under the same assumption. Furthermore, the majority of prior work does not consider a scenario where users have deadlines. In the second part of this thesis we formulate the asynchronous coded caching problem where user requests arrive at different times. Furthermore, the users have specified deadlines. We propose a linear program for obtaining its optimal solution. However, the size of the LP (number of constraints and variables) grows rather quickly with the number of users and cache sizes. To deal with this problem, we explore a dual decomposition based approach for solving the LP under consideration. We demonstrate that the dual function can be evaluated by equivalently solving a number of minimum cost network flow algorithms. Moreover, we consider the asynchronous setting where the file requests are revealed to the server in an online fashion. We propose a novel online algorithm for this problem building on our prior work for the offline setting (where the server knows the request arrival times and deadlines in advance). Our simulation results demonstrate that our proposed online algorithm allows for a natural tradeoff between the feasibility of the schedule and the rate gains of coded caching