CAP: A ContAct based Proximity service via opportunistic device-to-device relay

Abstract

The research progress of 5G has brought a number of novel technologies to meet the multi-dimensional demands. Device-to-Device (D2D) communication is a way to no longer treat the User Equipments (UEs) as terminal, but rather as a part of network (known as helpers) for service provisioning. Such a way potentially increases the coverage and also expands the capacity of cellular network. In this paper, we propose a generic framework for Proximity as a Service (PaaS) with demands of service continuity, namely ContAct based Proximity (CAP) via opportunistic D2D communication. Mainly, fruitful contact information (e.g., contact duration, frequency and interval) is captured as a key metric, to handle an ubiquitous and PaaS through the optimal selection of helpers. The nature of CAP is evaluated under the Helsinki city scenario, with key factors influencing the service demands (e.g., success ratio, disruption duration and frequency). Simulation results show the advantage of CAP, in both success ratio and continuity of the service. This work is the first one to evaluate LTE-Direct and WiFi-Direct in opportunistic proximity services.

Proximity as a Service for the Use Case of Access Enhancement Via Cellular Network-Assisted Mobile Device-to-Device

“…The maximal transmission range of in-band D2D air interface (LTE-Direct) is designed to be 500 m [30] because a dedicated in-band D2D technique can use its own bands which are suitable for longer transmit range without interference. However, with the consideration of shadow loss, multi-path effects, and restricted battery life, the transmission range of LTE-Direct implemented in phones in urban areas cannot reach 500 m. Therefore, in this paper, the maximum D2D transmission range is set as 150 m [12].…”

“…Success ratio [12] cannot be used as a sole means of evaluating the connectivity of the system, because the requesters being satisfied always generate more access requests afterwards, consequently bringing more access requests. The increase in access requests may result in increasing uncompleted access requests.…”

“…We proposed [12] a use case of proximal service by which some (appropriately selected) UEs, named helpers [13], are eligible to opportunistically provide services for other UEs (as service requesters) as requested. Key techniques developed involve the design of the system model, appropriate knowledge of human mobility, energy-efficient D2D handling for specific services requirements (with a limited number of requesters a helper can serve simultaneously), and potential security issues (limited number of selected helpers), etc.…”

Survey on cooperatively V2X downloading for intelligent transport systems

“…Literature [22] put forward the urban area, area and street mobility model (city area, street unit mobility models) with the traffic theory [22]. The metropolitan mobility model proposed by Li [23] is a hierarchy of mobility model, and three models focus on mobility at different regional levels: obstacle mobility model [24], in which obstacles such as buildings are modelled; graph‐based mobility model [25] uses graphs to model the restrictions imposed by environmental facilities on node movement; virtual track‐based group mobility model [26] is modelled using a virtual path.…”