'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
With the popularity of social network-based services,
the unprecedented growth of mobile date traffic has
brought a heavy burden on the traditional cellular networks.
Device-to-device (D2D) communication, as a promising solution
to overcome wireless spectrum crisis, can enable fast content
delivery based on user activities in social networks. In this paper,
we address the content delivery problem related to optimization
of peer discovery and resource allocation by combining both the
social and physical layer information in D2D underlay networks.
The social relationship, which is modeled as the probability of
selecting similar contents and estimated by using the Bayesian
nonparametric models, is used as a weight to characterize the
impact of social features on D2D pair formation and content
sharing. Next, we propose a three-dimensional iterative matching
algorithm to maximize the sum rate of D2D pairs weighted by
the intensity of social relationships while guaranteeing the quality
of service (QoS) requirements of both cellular and D2D links
simultaneously. Moreover, we prove that the proposed algorithm
converges to a stable matching and is weak Pareto optimal,
and also provide the theoretical complexity. Simulation results
show that the algorithm is able to achieve more than 90% of
the optimum performance with a computation complexity one
thousand times lower than the exhaustive matching algorithm.
It is also demonstrated that the satisfaction performance of D2D
receivers can be increased significantly by incorporating social
relationships into the resource allocation design.peerReviewe