34,356 research outputs found
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
Joint Resource Partitioning and Offloading in Heterogeneous Cellular Networks
In heterogeneous cellular networks (HCNs), it is desirable to offload mobile
users to small cells, which are typically significantly less congested than the
macrocells. To achieve sufficient load balancing, the offloaded users often
have much lower SINR than they would on the macrocell. This SINR degradation
can be partially alleviated through interference avoidance, for example time or
frequency resource partitioning, whereby the macrocell turns off in some
fraction of such resources. Naturally, the optimal offloading strategy is
tightly coupled with resource partitioning; the optimal amount of which in turn
depends on how many users have been offloaded. In this paper, we propose a
general and tractable framework for modeling and analyzing joint resource
partitioning and offloading in a two-tier cellular network. With it, we are
able to derive the downlink rate distribution over the entire network, and an
optimal strategy for joint resource partitioning and offloading. We show that
load balancing, by itself, is insufficient, and resource partitioning is
required in conjunction with offloading to improve the rate of cell edge users
in co-channel heterogeneous networks
A Comprehensive Analysis of 5G Heterogeneous Cellular Systems operating over - Shadowed Fading Channels
Emerging cellular technologies such as those proposed for use in 5G
communications will accommodate a wide range of usage scenarios with diverse
link requirements. This will include the necessity to operate over a versatile
set of wireless channels ranging from indoor to outdoor, from line-of-sight
(LOS) to non-LOS, and from circularly symmetric scattering to environments
which promote the clustering of scattered multipath waves. Unfortunately, many
of the conventional fading models adopted in the literature to develop network
models lack the flexibility to account for such disparate signal propagation
mechanisms. To bridge the gap between theory and practical channels, we
consider - shadowed fading, which contains as special cases, the
majority of the linear fading models proposed in the open literature, including
Rayleigh, Rician, Nakagami-m, Nakagami-q, One-sided Gaussian, -,
-, and Rician shadowed to name but a few. In particular, we apply an
orthogonal expansion to represent the - shadowed fading
distribution as a simplified series expression. Then using the series
expressions with stochastic geometry, we propose an analytic framework to
evaluate the average of an arbitrary function of the SINR over -
shadowed fading channels. Using the proposed method, we evaluate the spectral
efficiency, moments of the SINR, bit error probability and outage probability
of a -tier HetNet with classes of BSs, differing in terms of the
transmit power, BS density, shadowing characteristics and small-scale fading.
Building upon these results, we provide important new insights into the network
performance of these emerging wireless applications while considering a diverse
range of fading conditions and link qualities
- …