5 research outputs found
Spatial and Social Paradigms for Interference and Coverage Analysis in Underlay D2D Network
The homogeneous Poisson point process (PPP) is widely used to model spatial
distribution of base stations and mobile terminals. The same process can be
used to model underlay device-to-device (D2D) network, however, neglecting
homophilic relation for D2D pairing presents underestimated system insights. In
this paper, we model both spatial and social distributions of interfering D2D
nodes as proximity based independently marked homogeneous Poisson point
process. The proximity considers physical distance between D2D nodes whereas
social relationship is modeled as Zipf based marks. We apply these two
paradigms to analyze the effect of interference on coverage probability of
distance-proportional power-controlled cellular user. Effectively, we apply two
type of functional mappings (physical distance, social marks) to Laplace
functional of PPP. The resulting coverage probability has no closed-form
expression, however for a subset of social marks, the mark summation converges
to digamma and polygamma functions. This subset constitutes the upper and lower
bounds on coverage probability. We present numerical evaluation of these bounds
on coverage probability by varying number of different parameters. The results
show that by imparting simple power control on cellular user, ultra-dense
underlay D2D network can be realized without compromising the coverage
probability of cellular user.Comment: 10 pages, 10 figure
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Intracell interference characterization and cluster interference for D2D communication
The homogeneous spatial Poisson point process (SPPP) is widely used for spatial modeling of mobile terminals (MTs). This process is characterized by a homogeneous distribution, complete spatial independence, and constant intensity measure. However, it is intuitive to understand that the locations of MTs are neither homogeneous, due to inhomogeneous terrain, nor independent, due to homophilic relations. Moreover, the intensity is not constant due to mobility. Therefore, assuming an SPPP for spatial modeling is too simplistic, especially for modeling realistic emerging device-centric frameworks such as device-to-device (D2D) communication. In this paper, assuming inhomogeneity, positive spatial correlation, and random intensity measure, we propose a doubly stochastic Poisson process, a generalization of the homogeneous SPPP, to model D2D communication. To this end, we assume a permanental Cox process (PCP) and propose a novel Euler-Characteristic-based approach to approximate the nearest-neighbor distribution function. We also propose a threshold and spatial distances from an excursion set of a chi-square random field as interference control parameters for different cluster sizes. The spatial distance of the clusters is incorporated into a Laplace functional of a PCP to analyze the average coverage probability of a cellular user. A closed-form approximation of the spatial summary statistics is in good agreement with empirical results, and its comparison with an SPPP authenticates the correlation modeling of D2D nodes