2,680 research outputs found
A New Look at Physical Layer Security, Caching, and Wireless Energy Harvesting for Heterogeneous Ultra-dense Networks
Heterogeneous ultra-dense networks enable ultra-high data rates and ultra-low
latency through the use of dense sub-6 GHz and millimeter wave (mmWave) small
cells with different antenna configurations. Existing work has widely studied
spectral and energy efficiency in such networks and shown that high spectral
and energy efficiency can be achieved. This article investigates the benefits
of heterogeneous ultra-dense network architecture from the perspectives of
three promising technologies, i.e., physical layer security, caching, and
wireless energy harvesting, and provides enthusiastic outlook towards
application of these technologies in heterogeneous ultra-dense networks. Based
on the rationale of each technology, opportunities and challenges are
identified to advance the research in this emerging network.Comment: Accepted to appear in IEEE Communications Magazin
Edge Cache-assisted Secure Low-Latency Millimeter Wave Transmission
In this paper, we consider an edge cache-assisted millimeter wave cloud radio
access network (C-RAN). Each remote radio head (RRH) in the C-RAN has a local
cache, which can pre-fetch and store the files requested by the actuators.
Multiple RRHs form a cluster to cooperatively serve the actuators, which
acquire their required files either from the local caches or from the central
processor via multicast fronthaul links. For such a scenario, we formulate a
beamforming design problem to minimize the secure transmission delay under
transmit power constraint of each RRH. Due to the difficulty of directly
solving the formulated problem, we divide it into two independent ones:
{\textit{i)}} minimizing the fronthaul transmission delay by jointly optimizing
the transmit and receive beamforming; {\textit{ii)}} minimizing the maximum
access transmission delay by jointly designing cooperative beamforming among
RRHs. An alternatively iterative algorithm is proposed to solve the first
optimization problem. For the latter, we first design the analog beamforming
based on the channel state information of the actuators. Then, with the aid of
successive convex approximation and -procedure techniques, a semidefinite
program (SDP) is formulated, and an iterative algorithm is proposed through SDP
relaxation. Finally, simulation results are provided to verify the performance
of the proposed schemes.Comment: IEEE_IoT, Accep
Wireless Communications in the Era of Big Data
The rapidly growing wave of wireless data service is pushing against the
boundary of our communication network's processing power. The pervasive and
exponentially increasing data traffic present imminent challenges to all the
aspects of the wireless system design, such as spectrum efficiency, computing
capabilities and fronthaul/backhaul link capacity. In this article, we discuss
the challenges and opportunities in the design of scalable wireless systems to
embrace such a "bigdata" era. On one hand, we review the state-of-the-art
networking architectures and signal processing techniques adaptable for
managing the bigdata traffic in wireless networks. On the other hand, instead
of viewing mobile bigdata as a unwanted burden, we introduce methods to
capitalize from the vast data traffic, for building a bigdata-aware wireless
network with better wireless service quality and new mobile applications. We
highlight several promising future research directions for wireless
communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications
Magazin
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