Hypergraph-Based Analysis of Clustered Cooperative Beamforming with Application to Edge Caching

The evaluation of the performance of clustered cooperative beamforming in cellular networks generally requires the solution of complex non-convex optimization problems. In this letter, a framework based on a hypergraph formalism is proposed that enables the derivation of a performance characterization of clustered cooperative beamforming in terms of per-user degrees of freedom (DoF) via the efficient solution of a coloring problem. An emerging scenario in which clusters of cooperative base stations (BSs) arise is given by cellular networks with edge caching. In fact, clusters of BSs that share the same requested files can jointly beamform the corresponding encoded signals. Based on this observation, the proposed framework is applied to obtain quantitative insights into the optimal use of cache and backhaul resources in cellular systems with edge caching. Numerical examples are provided to illustrate the merits of the proposed framework.Comment: 10 pages, 5 figures, Submitte

Many-to-Many Matching Games for Proactive Social-Caching in Wireless Small Cell Networks

In this paper, we address the caching problem in small cell networks from a game theoretic point of view. In particular, we formulate the caching problem as a many-to-many matching game between small base stations and service providers' servers. The servers store a set of videos and aim to cache these videos at the small base stations in order to reduce the experienced delay by the end-users. On the other hand, small base stations cache the videos according to their local popularity, so as to reduce the load on the backhaul links. We propose a new matching algorithm for the many-to-many problem and prove that it reaches a pairwise stable outcome. Simulation results show that the number of satisfied requests by the small base stations in the proposed caching algorithm can reach up to three times the satisfaction of a random caching policy. Moreover, the expected download time of all the videos can be reduced significantly

Cache-aware user association in backhaul-constrained small cell networks

International audienceAnticipating multimedia file requests via caching at the small cell base stations (SBSs) of a cellular network has emerged as a promising technique for optimizing the quality of service (QoS) of wireless user equipments (UEs). However, developing efficient caching strategies must properly account for specific small cell constraints, such as backhaul congestion and limited storage capacity. In this paper, we address the problem of devising a user-cell association, in which the SBSs exploit caching capabilities to overcome the backhaul capacity limitations and enhance the users' QoS. In the proposed approach, the SBSs individually decide on which UEs to service based on both content availability and on the data rates they can deliver, given the interference and backhaul capacity limitations. We formulate the problem as a one-to-many matching game between SBSs and UEs. To solve this game, we propose a distributed algorithm, based on the deferred acceptance scheme, that enables the players (i.e., UEs and SBSs) to self-organize into a stable matching, in a reasonable number of algorithm iterations. Simulation results show that the proposed cell association scheme yields significant gains, reaching up to 21% improvement compared to a traditional cell association techniques with no caching considerations

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