2,567 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
Content Placement in Cache-Enabled Sub-6 GHz and Millimeter-Wave Multi-antenna Dense Small Cell Networks
This paper studies the performance of cache-enabled dense small cell networks
consisting of multi-antenna sub-6 GHz and millimeter-wave base stations.
Different from the existing works which only consider a single antenna at each
base station, the optimal content placement is unknown when the base stations
have multiple antennas. We first derive the successful content delivery
probability by accounting for the key channel features at sub-6 GHz and mmWave
frequencies. The maximization of the successful content delivery probability is
a challenging problem. To tackle it, we first propose a constrained
cross-entropy algorithm which achieves the near-optimal solution with moderate
complexity. We then develop another simple yet effective heuristic
probabilistic content placement scheme, termed two-stair algorithm, which
strikes a balance between caching the most popular contents and achieving
content diversity. Numerical results demonstrate the superior performance of
the constrained cross-entropy method and that the two-stair algorithm yields
significantly better performance than only caching the most popular contents.
The comparisons between the sub-6 GHz and mmWave systems reveal an interesting
tradeoff between caching capacity and density for the mmWave system to achieve
similar performance as the sub-6 GHz system.Comment: 14 pages; Accepted to appear in IEEE Transactions on Wireless
Communication
Partially Blind Handovers for mmWave New Radio Aided by Sub-6 GHz LTE Signaling
For a base station that supports cellular communications in sub-6 GHz LTE and
millimeter (mmWave) bands, we propose a supervised machine learning algorithm
to improve the success rate in the handover between the two radio frequencies
using sub-6 GHz and mmWave prior channel measurements within a temporal window.
The main contributions of our paper are to 1) introduce partially blind
handovers, 2) employ machine learning to perform handover success predictions
from sub-6 GHz to mmWave frequencies, and 3) show that this machine learning
based algorithm combined with partially blind handovers can improve the
handover success rate in a realistic network setup of colocated cells.
Simulation results show improvement in handover success rates for our proposed
algorithm compared to standard handover algorithms.Comment: (c) 2018 IEEE. Personal use of this material is permitted. Permission
from IEEE must be obtained for all other uses, in any current or future
media, including reprinting/republishing this material for advertising or
promotional purposes, creating new collective works, for resale or
redistribution to servers or lists, or reuse of any copyrighted component of
this work in other work
Maximising system throughput in wireless powered sub-6 GHz and millimetre-wave 5G heterogeneous networks
Millimetre wave (mm-Wave) bands and sub-6 GHz are key technologies in solving the spectrum critical situation in the fifth generation (5G) wireless networks in achieving high throughput with low transmission power. This paper studies the performance of dense small cells that involve a millimetre wave (mm-Wave) band and sub-6 GHz that operate in high frequency to support massive multiple-input-multiple-output systems (MIMO). In this paper, we analyse the propagation path loss and wireless powered transfer for a 5G wireless cellular system from both macro cells and femtocells in the sub-6 GHz (µWave) and mm-Wave tiers. This paper also analyses the tier heterogeneous in downlink for both mm-Wave and sub-6 GHz. It further proposes a novel distributed power to mitigate the inter-beam interference directors and achieve high throughput under game theory-based power constraints across the sub-6 GHz and mm-Wave interfaces. From the simulation results, the proposed distributed powers in femtocell suppresses inter-beam interference by minimising path loss to active users (UEs) and provides substantial power saving by controlling the distributed power algorithm to achieve high throughput
Performance Analysis and Optimization of Cache-Enabled Small Cell Networks
This paper studies the performance of cache-enabled dense small cell networks consisting of multi- antenna sub-6 GHz and millimeter-wave base stations. We first derive the successful content delivery probability by accounting for the key channel features at sub-6 GHz and mmWave frequencies. In general, the optimal content placement is unknown when the base stations have multiple antennas. Then we propose a simple yet effective probabilistic content placement scheme to maximize the successful content delivery probability, which could balance caching both the most popular contents and achieving content diversity. Numerical results demonstrate that our proposed content placement scheme yields significantly better performance than only caching the most popular contents. The comparisons between the sub-6 GHz and millimeter-wave systems reveal an interesting tradeoff between caching capacity and base station density for the millimeter-wave system to achieve similar performance as the sub-6 GHz system
Content Placement in Cache-Enabled Sub-6 GHz and Millimeter-Wave Multi-Antenna Dense Small Cell Networks
This paper studies the performance of cacheenabled dense small cell networks consisting of multi-antenna
sub-6 GHz and millimeter-wave (mm-wave) base stations. Different from the existing works which only consider a single antenna at each base station, the optimal content placement is unknown when the base stations have multiple antennas. We first derive the successful content delivery probability by accounting for the key channel features at sub-6 GHz and mm-wave frequencies. The maximization of the successful content delivery probability is a challenging problem. To tackle it, we first propose a constrained
cross-entropy algorithm which achieves the near-optimal solution with moderate complexity. We then develop another simple yet effective heuristic probabilistic content placement scheme, termed two-stair algorithm, which strikes a balance between caching the most popular contents and achieving content diversity. Numerical results demonstrate the superior performance of the constrained cross-entropy method and that the two-stair algorithm yields significantly better performance than only caching the most popular contents. The comparisons between the sub-6 GHz and
mm-wave systems reveal an interesting tradeoff between caching capacity and density for the mm-wave system to achieve similar performance as the sub-6 GHz system
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