2,111 research outputs found
On Green Energy Powered Cognitive Radio Networks
Green energy powered cognitive radio (CR) network is capable of liberating
the wireless access networks from spectral and energy constraints. The
limitation of the spectrum is alleviated by exploiting cognitive networking in
which wireless nodes sense and utilize the spare spectrum for data
communications, while dependence on the traditional unsustainable energy is
assuaged by adopting energy harvesting (EH) through which green energy can be
harnessed to power wireless networks. Green energy powered CR increases the
network availability and thus extends emerging network applications. Designing
green CR networks is challenging. It requires not only the optimization of
dynamic spectrum access but also the optimal utilization of green energy. This
paper surveys the energy efficient cognitive radio techniques and the
optimization of green energy powered wireless networks. Existing works on
energy aware spectrum sensing, management, and sharing are investigated in
detail. The state of the art of the energy efficient CR based wireless access
network is discussed in various aspects such as relay and cooperative radio and
small cells. Envisioning green energy as an important energy resource in the
future, network performance highly depends on the dynamics of the available
spectrum and green energy. As compared with the traditional energy source, the
arrival rate of green energy, which highly depends on the environment of the
energy harvesters, is rather random and intermittent. To optimize and adapt the
usage of green energy according to the opportunistic spectrum availability, we
discuss research challenges in designing cognitive radio networks which are
powered by energy harvesters
Green Cellular Networks: A Survey, Some Research Issues and Challenges
Energy efficiency in cellular networks is a growing concern for cellular
operators to not only maintain profitability, but also to reduce the overall
environment effects. This emerging trend of achieving energy efficiency in
cellular networks is motivating the standardization authorities and network
operators to continuously explore future technologies in order to bring
improvements in the entire network infrastructure. In this article, we present
a brief survey of methods to improve the power efficiency of cellular networks,
explore some research issues and challenges and suggest some techniques to
enable an energy efficient or "green" cellular network. Since base stations
consume a maximum portion of the total energy used in a cellular system, we
will first provide a comprehensive survey on techniques to obtain energy
savings in base stations. Next, we discuss how heterogeneous network deployment
based on micro, pico and femto-cells can be used to achieve this goal. Since
cognitive radio and cooperative relaying are undisputed future technologies in
this regard, we propose a research vision to make these technologies more
energy efficient. Lastly, we explore some broader perspectives in realizing a
"green" cellular network technologyComment: 16 pages, 5 figures, 2 table
Full-Duplex Non-Orthogonal Multiple Access for Modern Wireless Networks
Non-orthogonal multiple access (NOMA) is an interesting concept to provide
higher capacity for future wireless communications. In this article, we
consider the feasibility and benefits of combining full-duplex operation with
NOMA for modern communication systems. Specifically, we provide a comprehensive
overview on application of full-duplex NOMA in cellular networks, cooperative
and cognitive radio networks, and characterize gains possible due to
full-duplex operation. Accordingly, we discuss challenges, particularly the
self-interference and inter-user interference and provide potential solutions
to interference mitigation and quality-of-service provision based on
beamforming, power control, and link scheduling. We further discuss future
research challenges and interesting directions to pursue to bring full-duplex
NOMA into maturity and use in practice.Comment: Revised, IEEE Wireless Communication Magazin
Intelligent Wireless Communications Enabled by Cognitive Radio and Machine Learning
The ability to intelligently utilize resources to meet the need of growing
diversity in services and user behavior marks the future of wireless
communication systems. Intelligent wireless communications aims at enabling the
system to perceive and assess the available resources, to autonomously learn to
adapt to the perceived wireless environment, and to reconfigure its operating
mode to maximize the utility of the available resources. The perception
capability and reconfigurability are the essential features of cognitive radio
while modern machine learning techniques project great potential in system
adaptation. In this paper, we discuss the development of the cognitive radio
technology and machine learning techniques and emphasize their roles in
improving spectrum and energy utility of wireless communication systems. We
describe the state-of-the-art of relevant techniques, covering spectrum sensing
and access approaches and powerful machine learning algorithms that enable
spectrum- and energy-efficient communications in dynamic wireless environments.
We also present practical applications of these techniques and identify further
research challenges in cognitive radio and machine learning as applied to the
existing and future wireless communication systems
A Comprehensive Survey of Potential Game Approaches to Wireless Networks
Potential games form a class of non-cooperative games where unilateral
improvement dynamics are guaranteed to converge in many practical cases. The
potential game approach has been applied to a wide range of wireless network
problems, particularly to a variety of channel assignment problems. In this
paper, the properties of potential games are introduced, and games in wireless
networks that have been proven to be potential games are comprehensively
discussed.Comment: 44 pages, 6 figures, to appear in IEICE Transactions on
Communications, vol. E98-B, no. 9, Sept. 201
Directional Relays for Multi-Hop Cooperative Cognitive Radio Networks
In this paper, we investigate power allocation and beamforming in a relay assisted cognitive radio (CR) network. Our objective is to maximize the performance of the CR network while limiting interference in the direction of the primary users (PUs). In order to achieve these goals, we first consider joint power allocation and beamforming for cognitive nodes in direct links. Then, we propose an optimal power allocation strategy for relay nodes in indirect transmissions. Unlike the conventional cooperative relaying networks, the applied relays are equipped with directional antennas to further reduce the interference to PUs and meet the CR network requirements. The proposed approach employs genetic algorithm (GA) to solve the optimization problems. Numerical simulation results illustrate the quality of service (QoS) satisfaction in both primary and secondary networks. These results also show that notable improvements are achieved in the system performance if the conventional omni-directional relays are replaced with directional ones
Resource Allocation and Fairness in Wireless Powered Cooperative Cognitive Radio Networks
We integrate a wireless powered communication network with a cooperative
cognitive radio network, where multiple secondary users (SUs) powered
wirelessly by a hybrid access point (HAP) help a primary user relay the data.
As a reward for the cooperation, the secondary network gains the spectrum
access where SUs transmit to HAP using time division multiple access. To
maximize the sum-throughput of SUs, we present a secondary sum-throughput
optimal resource allocation (STORA) scheme. Under the constraint of meeting
target primary rate, the STORA scheme chooses the optimal set of relaying SUs
and jointly performs the time and energy allocation for SUs. Specifically, by
exploiting the structure of the optimal solution, we find the order in which
SUs are prioritized to relay primary data. Since the STORA scheme focuses on
the sum-throughput, it becomes inconsiderate towards individual SU throughput,
resulting in low fairness. To enhance fairness, we investigate three resource
allocation schemes, which are (i) equal time allocation, (ii) minimum
throughput maximization, and (iii) proportional time allocation. Simulation
results reveal the trade-off between sum-throughput and fairness. The minimum
throughput maximization scheme is the fairest one as each SU gets the same
throughput, but yields the least SU sum-throughput.Comment: Accepted in IEEE Transactions on Communication
Decentralized Fair Scheduling in Two-Hop Relay-Assisted Cognitive OFDMA Systems
In this paper, we consider a two-hop relay-assisted cognitive downlink OFDMA
system (named as secondary system) dynamically accessing a spectrum licensed to
a primary network, thereby improving the efficiency of spectrum usage. A
cluster-based relay-assisted architecture is proposed for the secondary system,
where relay stations are employed for minimizing the interference to the users
in the primary network and achieving fairness for cell-edge users. Based on
this architecture, an asymptotically optimal solution is derived for jointly
controlling data rates, transmission power, and subchannel allocation to
optimize the average weighted sum goodput where the proportional fair
scheduling (PFS) is included as a special case. This solution supports
decentralized implementation, requires small communication overhead, and is
robust against imperfect channel state information at the transmitter (CSIT)
and sensing measurement. The proposed solution achieves significant throughput
gains and better user-fairness compared with the existing designs. Finally, we
derived a simple and asymptotically optimal scheduling solution as well as the
associated closed-form performance under the proportional fair scheduling for a
large number of users. The system throughput is shown to be
, where is the
number of users in one cluster, is the number of subchannels and is
the active probability of primary users.Comment: 29 pages, 9 figures, IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL
PROCESSIN
Harvest the potential of massive MIMO with multi-layer techniques
Massive MIMO is envisioned as a promising technology for 5G wireless networks
due to its high potential to improve both spectral and energy efficiency.
Although the massive MIMO system is based on innovations in the physical layer,
the upper layer techniques also play important roles in harvesting the
performance gains of massive MIMO. In this article, we begin with an analysis
of the benefits and challenges of massive MIMO systems. We then investigate the
multi-layer techniques for incorporating massive MIMO in several important
network deployment scenarios. We conclude this article with a discussion of
open and potential problems for future research.Comment: IEEE Networ
Regulatory and Policy Implications of Emerging Technologies to Spectrum Management
This paper provides an overview of the policy implications of technological developments, and how these technologies can accommodate an increased level of market competition. It is based on the work carried out in the SPORT VIEWS (Spectrum Policies and Radio Technologies Viable In Emerging Wireless Societies) research project for the European Commission (FP6)spectrum, new radio technologies, UWB, SDR, cognitive radio, Telecommunications, regulation, Networks, Interconnection
- …