3,366 research outputs found
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
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
Secure Communications in NOMA System: Subcarrier Assignment and Power Allocation
Secure communication is a promising technology for wireless networks because
it ensures secure transmission of information. In this paper, we investigate
the joint subcarrier (SC) assignment and power allocation problem for
non-orthogonal multiple access (NOMA) amplify-and-forward two-way relay
wireless networks, in the presence of eavesdroppers. By exploiting cooperative
jamming (CJ) to enhance the security of the communication link, we aim to
maximize the achievable secrecy energy efficiency by jointly designing the SC
assignment, user pair scheduling and power allocation. Assuming the perfect
knowledge of the channel state information (CSI) at the relay station, we
propose a low-complexity subcarrier assignment scheme (SCAS-1), which is
equivalent to many-to-many matching games, and then SCAS-2 is formulated as a
secrecy energy efficiency maximization problem. The secure power allocation
problem is modeled as a convex geometric programming problem, and then solved
by interior point methods. Simulation results demonstrate that the
effectiveness of the proposed SSPA algorithms under scenarios of using and not
using CJ, respectively
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
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
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
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
A Survey on MIMO Transmission with Discrete Input Signals: Technical Challenges, Advances, and Future Trends
Multiple antennas have been exploited for spatial multiplexing and diversity
transmission in a wide range of communication applications. However, most of
the advances in the design of high speed wireless multiple-input multiple
output (MIMO) systems are based on information-theoretic principles that
demonstrate how to efficiently transmit signals conforming to Gaussian
distribution. Although the Gaussian signal is capacity-achieving, signals
conforming to discrete constellations are transmitted in practical
communication systems. As a result, this paper is motivated to provide a
comprehensive overview on MIMO transmission design with discrete input signals.
We first summarize the existing fundamental results for MIMO systems with
discrete input signals. Then, focusing on the basic point-to-point MIMO
systems, we examine transmission schemes based on three most important criteria
for communication systems: the mutual information driven designs, the mean
square error driven designs, and the diversity driven designs. Particularly, a
unified framework which designs low complexity transmission schemes applicable
to massive MIMO systems in upcoming 5G wireless networks is provided in the
first time. Moreover, adaptive transmission designs which switch among these
criteria based on the channel conditions to formulate the best transmission
strategy are discussed. Then, we provide a survey of the transmission designs
with discrete input signals for multiuser MIMO scenarios, including MIMO uplink
transmission, MIMO downlink transmission, MIMO interference channel, and MIMO
wiretap channel. Additionally, we discuss the transmission designs with
discrete input signals for other systems using MIMO technology. Finally,
technical challenges which remain unresolved at the time of writing are
summarized and the future trends of transmission designs with discrete input
signals are addressed.Comment: 110 pages, 512 references, submit to Proceedings of the IEE
Multi-Objective Resource Allocation for Secure Communication in Cognitive Radio Networks with Wireless Information and Power Transfer
In this paper, we study resource allocation for multiuser multiple-input
single-output secondary communication systems with multiple system design
objectives. We consider cognitive radio networks where the secondary receivers
are able to harvest energy from the radio frequency when they are idle. The
secondary system provides simultaneous wireless power and secure information
transfer to the secondary receivers. We propose a multi-objective optimization
framework for the design of a Pareto optimal resource allocation algorithm
based on the weighted Tchebycheff approach. In particular, the algorithm design
incorporates three important system objectives: total transmit power
minimization, energy harvesting efficiency maximization, and interference power
leakage-to-transmit power ratio minimization. The proposed framework takes into
account a quality of service requirement regarding communication secrecy in the
secondary system and the imperfection of the channel state information of
potential eavesdroppers (idle secondary receivers and primary receivers) at the
secondary transmitter. The adopted multi-objective optimization problem is
non-convex and is recast as a convex optimization problem via semidefinite
programming (SDP) relaxation. It is shown that the global optimal solution of
the original problem can be constructed by exploiting both the primal and the
dual optimal solutions of the SDP relaxed problem. Besides, two suboptimal
resource allocation schemes for the case when the solution of the dual problem
is unavailable for constructing the optimal solution are proposed. Numerical
results not only demonstrate the close-to-optimal performance of the proposed
suboptimal schemes, but also unveil an interesting trade-off between the
considered conflicting system design objectives.Comment: Accepted with minor revisions for publication as a regular paper in
the IEEE Transactions on Vehicular Technolog
Resource Allocation in Wireless Networks with RF Energy Harvesting and Transfer
Radio frequency (RF) energy harvesting and transfer techniques have recently
become alternative methods to power the next generation of wireless networks.
As this emerging technology enables proactive replenishment of wireless
devices, it is advantageous in supporting applications with quality-of-service
(QoS) requirement. This article focuses on the resource allocation issues in
wireless networks with RF energy harvesting capability, referred to as RF
energy harvesting networks (RF-EHNs). First, we present an overview of the
RF-EHNs, followed by a review of a variety of issues regarding resource
allocation. Then, we present a case study of designing in the receiver
operation policy, which is of paramount importance in the RF-EHNs. We focus on
QoS support and service differentiation, which have not been addressed by
previous literatures. Furthermore, we outline some open research directions.Comment: To appear in IEEE Networ
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