# Social-Aware Peer Selection for Device-to-Device Communications in Dense Small-Cell Networks
## 1 Introduction and Contribution  
Over the last decade, there has been tremendous growth in the demand for data and other network applications and services, largely arising from mobile devices. This has led to a scarcity of spectrum and capacity in cellular systems. Despite the revolution in radio access and networking technologies, the current cellular system is becoming heavily loaded [1]--if this trend continues, the scarcity will worsen--it is projected to increase seven-fold in 2016-2021 [2]. This has motivated researchers to find new mechanisms to offload traffic from cellular base stations (BS) and fulfill ever-increasing customer demands. Network densification through small-cell networks (SCNs) is a promising solution to the aforementioned issue. The main concept of SCN is to overlay several small-cell base stations (SCBSs) within an existing legacy cellular system. This can efficiently reuse the spectrum and improve both coverage and capacity, particularly in densely populated urban areas. However, the SCN model has certain challenges, such as resource allocation, interference mitigation, and backhaul network management that need to be addressed separately [3; 4]. Similarly, device-to-device (D2D) communications is another exciting approach that has received substantial research attention. This communication system can offload traffic from legacy macro-cell base stations (MCBS) by allowing proximate user equipments (UEs) to communicate directly [5]. Moreover, it can improve the coverage, capacity, and spectrum utilization of a cellular system by efficiently reusing resources and mitigating spectrum congestion. Both D2D and SCN are expected to be integral parts of future 5G cellular communication systems [4; 6]. As these twoparadigms aim to provide short-range communications with low-cost and power, they can be merged to provide more efficient D2D communications. The combined model can significantly facilitate D2D peer selection, link establishment, and communication. Before establishing a D2D link, D2D user equipment (DUE) has to discover and select a suitable peer that both has the required services, and is willing to serve the requesting UE. This process can be performed either with or without the assistance of the MCBS. The former method can improve the peer discovery process at the cost of higher signaling overhead. Conversely, the latter approach can achieve scalability and out-of-coverage discovery but lacks synchronization and collision avoidance [5], SCN-based D2D communications can acquire the merits of both designs and overcome some of their individual challenges [4]. D2D communications rely on the cooperation between the UEs where a target UE will serve the requesting UE with its desired data or application. This involves the use of resources of the serving UE, which may not be possible due to users' selfish nature. Consequently, users may not always be willing to provide resources to unknown fellow users. To overcome this issue, many recent works have combined users' social parameters with their physical parameters. This has significantly improved users' willingness to  
scenario in which the peer selection process increased the burden on the MCBS in terms of signaling and social information management. [PERSON] et al. proposed a user-pairing scheme based on resource sharing between cellular and D2D users [PERSON] et al. (2018). This method aimed to improve resource utilization by selecting a suitable D2D partner for each cellular user equipment (CUE) using a bipartite graph. Similarly, [PERSON] et al. [PERSON] et al. (2018) utilized a Voronoi diagram to propose a scheme for UE pairing in D2D communications. Users located in an adjacent area in the diagram were allowed to establish a D2D connection. Power consumption and interference were reduced as the scheme permitted short-range D2D communications between neighboring UEs. However, neither of the methods in [PERSON] et al. (2018) and [PERSON] et al. (2018) integrated the SCN paradigm.