3,681 research outputs found
A Stochastic Geometric Analysis of Device-to-Device Communications Operating over Generalized Fading Channels
Device-to-device (D2D) communications are now considered as an integral part
of future 5G networks which will enable direct communication between user
equipment (UE) without unnecessary routing via the network infrastructure. This
architecture will result in higher throughputs than conventional cellular
networks, but with the increased potential for co-channel interference induced
by randomly located cellular and D2D UEs. The physical channels which
constitute D2D communications can be expected to be complex in nature,
experiencing both line-of-sight (LOS) and non-LOS (NLOS) conditions across
closely located D2D pairs. As well as this, given the diverse range of
operating environments, they may also be subject to clustering of the scattered
multipath contribution, i.e., propagation characteristics which are quite
dissimilar to conventional Rayeligh fading environments. To address these
challenges, we consider two recently proposed generalized fading models, namely
and , to characterize the fading behavior in D2D
communications. Together, these models encompass many of the most widely
encountered and utilized fading models in the literature such as Rayleigh, Rice
(Nakagami-), Nakagami-, Hoyt (Nakagami-) and One-Sided Gaussian. Using
stochastic geometry we evaluate the rate and bit error probability of D2D
networks under generalized fading conditions. Based on the analytical results,
we present new insights into the trade-offs between the reliability, rate, and
mode selection under realistic operating conditions. Our results suggest that
D2D mode achieves higher rates over cellular link at the expense of a higher
bit error probability. Through numerical evaluations, we also investigate the
performance gains of D2D networks and demonstrate their superiority over
traditional cellular networks.Comment: Submitted to IEEE Transactions on Wireless Communication
Cache-enabled Heterogeneous Cellular Networks: Comparison and Tradeoffs
Caching popular contents at base stations (BSs) is a promising way to unleash
the potential of cellular heterogeneous networks (HetNets), where backhaul has
become a bottleneck. In this paper, we compare a cache-enabled HetNet where a
tier of multi-antenna macro BSs is overlaid by a tier of helper nodes having
caches but no backhaul with a conventional HetNet where the macro BSs tier is
overlaid by a tier of pico BSs with limited-capacity backhaul. We resort
stochastic geometry theory to derive the area spectral efficiencies (ASEs) of
these two kinds of HetNets and obtain the closed-form expressions under a
special case. We use numerical results to show that the helper density is only
1/4 of the pico BS density to achieve the same target ASE, and the helper
density can be further reduced by increasing cache capacity. With given total
cache capacity within an area, there exists an optimal helper node density that
maximizes the ASE.Comment: Accepted by IEEE International Conference on Communications (ICC)
2016. This version includes detailed proofs of the proposition
Energy Efficiency and Sum Rate when Massive MIMO meets Device-to-Device Communication
This paper considers a scenario of short-range communication, known as
device-to-device (D2D) communication, where D2D users reuse the downlink
resources of a cellular network to transmit directly to their corresponding
receivers. In addition, multiple antennas at the base station (BS) are used in
order to simultaneously support multiple cellular users using multiuser or
massive MIMO. The network model considers a fixed number of cellular users and
that D2D users are distributed according to a homogeneous Poisson point process
(PPP). Two metrics are studied, namely, average sum rate (ASR) and energy
efficiency (EE). We derive tractable expressions and study the tradeoffs
between the ASR and EE as functions of the number of BS antennas and density of
D2D users for a given coverage area.Comment: 6 pages, 7 figures, to be presented at the IEEE International
Conference on Communications (ICC) Workshop on Device-to-Device Communication
for Cellular and Wireless Networks, London, UK, June 201
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