12,390 research outputs found
Wireless Powered Dense Cellular Networks: How Many Small Cells Do We Need?
This paper focuses on wireless powered 5G dense cellular networks, where base
station (BS) delivers energy to user equipment (UE) via the microwave radiation
in sub-6 GHz or millimeter wave (mmWave) frequency, and UE uses the harvested
energy for uplink information transmission. By addressing the impacts of
employing different number of antennas and bandwidths at lower and higher
frequencies, we evaluate the amount of harvested energy and throughput in such
networks. Based on the derived results, we obtain the required small cell
density to achieve an expected level of harvested energy or throughput. Also,
we obtain that when the ratio of the number of sub-6 GHz BSs to that of the
mmWave BSs is lower than a given threshold, UE harvests more energy from a
mmWave BS than a sub-6 GHz BS. We find how many mmWave small cells are needed
to perform better than the sub-6 GHz small cells from the perspectives of
harvested energy and throughput. Our results reveal that the amount of
harvested energy from the mmWave tier can be comparable to the sub-6 GHz
counterpart in the dense scenarios. For the same tier scale, mmWave tier can
achieve higher throughput. Furthermore, the throughput gap between different
mmWave frequencies increases with the mmWave BS density.Comment: pages 1-14, accepted by IEEE Journal on Selected Areas in
Communication
Energy-aware caching and collaboration for green communication systems.
Social networks and mobile applications tend to enhance the need for high-quality content access. To meet the growing demand for data services in 5G cellular networks, it is important to develop effective content caching and distribution techniques, to reduce redundant data transmission and thereby improve network efficiency significantly. It is anticipated that energy harvesting and self-powered Small Base Stations' (SBS) are the rudimentary constituents of next-generation cellular networks. However, uncertainties in harvested energy are the primary reasons to opt for energy-efficient (EE) power control schemes to reduce SBS energy consumption and ensure the quality of services for users. Using edge collaborative caching, such EE design can also be achievable via the use of the content cache, decreasing the usage of capacity limited SBSs backhaul and reducing energy utilisation. Renewable energy (RE) harvesting technologies can be leveraged to manage the huge power demands of cellular networks. To reduce carbon footprint and improve energy efficiency, we tailored a more practical approach and propose green caching mechanisms for content distribution that utilise the content caching and renewable energy concept. Simulation results and analysis provide key insights that the proposed caching scheme brings a substantial improvement regarding content availability, cache storage capacity at the edge of cellular networks, enhances energy efficiency, and increases cache collaboration time up to 24%. Furthermore, self-powered base stations and energy harvesting are an ultimate part of next-generation wireless networks, particularly in terms of optimum economic sustainability and green energy in developing countries for the evolution of mobile networks
Joint Uplink and Downlink Coverage Analysis of Cellular-based RF-powered IoT Network
Ambient radio frequency (RF) energy harvesting has emerged as a promising
solution for powering small devices and sensors in massive Internet of Things
(IoT) ecosystem due to its ubiquity and cost efficiency. In this paper, we
study joint uplink and downlink coverage of cellular-based ambient RF energy
harvesting IoT where the cellular network is assumed to be the only source of
RF energy. We consider a time division-based approach for power and information
transmission where each time-slot is partitioned into three sub-slots: (i)
charging sub-slot during which the cellular base stations (BSs) act as RF
chargers for the IoT devices, which then use the energy harvested in this
sub-slot for information transmission and/or reception during the remaining two
sub-slots, (ii) downlink sub-slot during which the IoT device receives
information from the associated BS, and (iii) uplink sub-slot during which the
IoT device transmits information to the associated BS. For this setup, we
characterize the joint coverage probability, which is the joint probability of
the events that the typical device harvests sufficient energy in the given time
slot and is under both uplink and downlink signal-to-interference-plus-noise
ratio (SINR) coverage with respect to its associated BS. This metric
significantly generalizes the prior art on energy harvesting communications,
which usually focused on downlink or uplink coverage separately. The key
technical challenge is in handling the correlation between the amount of energy
harvested in the charging sub-slot and the information signal quality (SINR) in
the downlink and uplink sub-slots. Dominant BS-based approach is developed to
derive tight approximation for this joint coverage probability. Several system
design insights including comparison with regularly powered IoT network and
throughput-optimal slot partitioning are also provided
Robust Transmissions in Wireless Powered Multi-Relay Networks with Chance Interference Constraints
In this paper, we consider a wireless powered multi-relay network in which a
multi-antenna hybrid access point underlaying a cellular system transmits
information to distant receivers. Multiple relays capable of energy harvesting
are deployed in the network to assist the information transmission. The hybrid
access point can wirelessly supply energy to the relays, achieving multi-user
gains from signal and energy cooperation. We propose a joint optimization for
signal beamforming of the hybrid access point as well as wireless energy
harvesting and collaborative beamforming strategies of the relays. The
objective is to maximize network throughput subject to probabilistic
interference constraints at the cellular user equipment. We formulate the
throughput maximization with both the time-switching and power-splitting
schemes, which impose very different couplings between the operating parameters
for wireless power and information transfer. Although the optimization problems
are inherently non-convex, they share similar structural properties that can be
leveraged for efficient algorithm design. In particular, by exploiting
monotonicity in the throughput, we maximize it iteratively via customized
polyblock approximation with reduced complexity. The numerical results show
that the proposed algorithms can achieve close to optimal performance in terms
of the energy efficiency and throughput.Comment: 14 pages, 8 figure
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