202 research outputs found
Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks
Conventional cellular wireless networks were designed with the purpose of
providing high throughput for the user and high capacity for the service
provider, without any provisions of energy efficiency. As a result, these
networks have an enormous Carbon footprint. In this paper, we describe the
sources of the inefficiencies in such networks. First we present results of the
studies on how much Carbon footprint such networks generate. We also discuss
how much more mobile traffic is expected to increase so that this Carbon
footprint will even increase tremendously more. We then discuss specific
sources of inefficiency and potential sources of improvement at the physical
layer as well as at higher layers of the communication protocol hierarchy. In
particular, considering that most of the energy inefficiency in cellular
wireless networks is at the base stations, we discuss multi-tier networks and
point to the potential of exploiting mobility patterns in order to use base
station energy judiciously. We then investigate potential methods to reduce
this inefficiency and quantify their individual contributions. By a
consideration of the combination of all potential gains, we conclude that an
improvement in energy consumption in cellular wireless networks by two orders
of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843
Toward 6G TK Extreme Connectivity: Architecture, Key Technologies and Experiments
Sixth-generation (6G) networks are evolving towards new features and
order-of-magnitude enhancement of systematic performance metrics compared to
the current 5G. In particular, the 6G networks are expected to achieve extreme
connectivity performance with Tbps-scale data rate, Kbps/Hz-scale spectral
efficiency, and s-scale latency. To this end, an original three-layer 6G
network architecture is designed to realise uniform full-spectrum cell-free
radio access and provide task-centric agile proximate support for diverse
applications. The designed architecture is featured by super edge node (SEN)
which integrates connectivity, computing, AI, data, etc. On this basis, a
technological framework of pervasive multi-level (PML) AI is established in the
centralised unit to enable task-centric near-real-time resource allocation and
network automation. We then introduce a radio access network (RAN) architecture
of full spectrum uniform cell-free networks, which is among the most attractive
RAN candidates for 6G TK extreme connectivity. A few most promising key
technologies, i.e., cell-free massive MIMO, photonics-assisted Terahertz
wireless access and spatiotemporal two-dimensional channel coding are further
discussed. A testbed is implemented and extensive trials are conducted to
evaluate innovative technologies and methodologies. The proposed 6G network
architecture and technological framework demonstrate exciting potentials for
full-service and full-scenario applications.Comment: 15 pages, 12 figure
QoE Driven Multimedia Service Schemes in Wireless Networks Resource Allocation: Evolution from Optimization, Game Theory, to Economics
In order to deal with the Quality of Experience (QoE) improvement issue in the wireless networks services. In this dissertation we first investigated the Device to Device (D2D) relaying approach in the conventional Base Station (BS) to User Equipment (UE) two entities multimedia service system. In this part, the Multiple Input Multiple Output (MIMO) technology will be implemented in the D2D communication. Furthermore, factors such as the multimedia content distribution (i.e., Quad-tree fractal image compression method), the power allocation strategy, and modulation size are jointly considered to improve the QoE performance and energy efficiency. In addition, the emerging Non-Orthogonal Multiple Access (NOMA) transmission method is becoming very popular and being considered as one of the most potential technologies for the next generation of wireless networks. For the purpose of improving the QoE of UE in the wireless multimedia service, the power allocation method and the corresponding limitations are studied in detail in the wireless system where the traditional Orthogonal Multiple Access (OMA) technology and the promising NOMA technology are compared. At last, facing the real business model in the wireless network services, where the Content Provider (CP), Wireless Carrier (WC), and UE are included, we extend on work from the conventional BS-UE two entities research model to the CP-WC-UE three entities model. More specifically, a generalized best response Smart Media Pricing (SMP) method is studied in this dissertation. In our work, the CP and WC are treated as the service provider alliance. The SMP approach and the game theory are utilized to determine the data length of UE and the data price rate determined by the CP-WC union. It is worth pointing out that the concavity of utility function is no longer necessary for seeking the game equilibrium under the proposed best response game solution. Numerical simulation results also validate the system performance improvement of our proposed transmission schemes
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
Sparse Signal Processing Concepts for Efficient 5G System Design
As it becomes increasingly apparent that 4G will not be able to meet the
emerging demands of future mobile communication systems, the question what
could make up a 5G system, what are the crucial challenges and what are the key
drivers is part of intensive, ongoing discussions. Partly due to the advent of
compressive sensing, methods that can optimally exploit sparsity in signals
have received tremendous attention in recent years. In this paper we will
describe a variety of scenarios in which signal sparsity arises naturally in 5G
wireless systems. Signal sparsity and the associated rich collection of tools
and algorithms will thus be a viable source for innovation in 5G wireless
system design. We will discribe applications of this sparse signal processing
paradigm in MIMO random access, cloud radio access networks, compressive
channel-source network coding, and embedded security. We will also emphasize
important open problem that may arise in 5G system design, for which sparsity
will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces
Predictor Antenna Systems: Exploiting Channel State Information for Vehicle Communications
Vehicle communication is one of the most important use cases in the fifth
generation of wireless networks (5G). The growing demand for quality of service
(QoS) characterized by performance metrics, such as spectrum efficiency, peak
data rate, and outage probability, is mainly limited by inaccurate
prediction/estimation of channel state information (CSI) of the rapidly
changing environment around moving vehicles. One way to increase the prediction
horizon of CSI in order to improve the QoS is deploying predictor antennas
(PAs). A PA system consists of two sets of antennas typically mounted on the
roof of a vehicle, where the PAs positioned at the front of the vehicle are
used to predict the CSI observed by the receive antennas (RAs) that are aligned
behind the PAs. In realistic PA systems, however, the actual benefit is
affected by a variety of factors, including spatial mismatch, antenna
utilization, temporal correlation of scattering environment, and CSI estimation
error. This thesis investigates different resource allocation schemes for the
PA systems under practical constraints.Comment: Licentiate thesis, Chalmers University of Technolog
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