7,739 research outputs found
Full-Duplex Cooperative Cognitive Radio Networks with Wireless Energy Harvesting
This paper proposes and analyzes a new full-duplex (FD) cooperative cognitive
radio network with wireless energy harvesting (EH). We consider that the
secondary receiver is equipped with a FD radio and acts as a FD hybrid access
point (HAP), which aims to collect information from its associated EH secondary
transmitter (ST) and relay the signals. The ST is assumed to be equipped with
an EH unit and a rechargeable battery such that it can harvest and accumulate
energy from radio frequency (RF) signals transmitted by the primary transmitter
(PT) and the HAP. We develop a novel cooperative spectrum sharing (CSS)
protocol for the considered system. In the proposed protocol, thanks to its FD
capability, the HAP can receive the PT's signals and transmit energy-bearing
signals to charge the ST simultaneously, or forward the PT's signals and
receive the ST's signals at the same time. We derive analytical expressions for
the achievable throughput of both primary and secondary links by characterizing
the dynamic charging/discharging behaviors of the ST battery as a finite-state
Markov chain. We present numerical results to validate our theoretical analysis
and demonstrate the merits of the proposed protocol over its non-cooperative
counterpart.Comment: 6 pages, 3 figures, conferenc
RF-Powered Cognitive Radio Networks: Technical Challenges and Limitations
The increasing demand for spectral and energy efficient communication
networks has spurred a great interest in energy harvesting (EH) cognitive radio
networks (CRNs). Such a revolutionary technology represents a paradigm shift in
the development of wireless networks, as it can simultaneously enable the
efficient use of the available spectrum and the exploitation of radio frequency
(RF) energy in order to reduce the reliance on traditional energy sources. This
is mainly triggered by the recent advancements in microelectronics that puts
forward RF energy harvesting as a plausible technique in the near future. On
the other hand, it is suggested that the operation of a network relying on
harvested energy needs to be redesigned to allow the network to reliably
function in the long term. To this end, the aim of this survey paper is to
provide a comprehensive overview of the recent development and the challenges
regarding the operation of CRNs powered by RF energy. In addition, the
potential open issues that might be considered for the future research are also
discussed in this paper.Comment: 8 pages, 2 figures, 1 table, Accepted in IEEE Communications Magazin
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
Optimal Cooperative Cognitive Relaying and Spectrum Access for an Energy Harvesting Cognitive Radio: Reinforcement Learning Approach
In this paper, we consider a cognitive setting under the context of
cooperative communications, where the cognitive radio (CR) user is assumed to
be a self-organized relay for the network. The CR user and the PU are assumed
to be energy harvesters. The CR user cooperatively relays some of the
undelivered packets of the primary user (PU). Specifically, the CR user stores
a fraction of the undelivered primary packets in a relaying queue (buffer). It
manages the flow of the undelivered primary packets to its relaying queue using
the appropriate actions over time slots. Moreover, it has the decision of
choosing the used queue for channel accessing at idle time slots (slots where
the PU's queue is empty). It is assumed that one data packet transmission
dissipates one energy packet. The optimal policy changes according to the
primary and CR users arrival rates to the data and energy queues as well as the
channels connectivity. The CR user saves energy for the PU by taking the
responsibility of relaying the undelivered primary packets. It optimally
organizes its own energy packets to maximize its payoff as time progresses
Sensing Throughput Optimization in Fading Cognitive Multiple Access Channels With Energy Harvesting Secondary Transmitters
The paper investigates the problem of maximizing expected sum throughput in a
fading multiple access cognitive radio network when secondary user (SU)
transmitters have energy harvesting capability, and perform cooperative
spectrum sensing. We formulate the problem as maximization of sum-capacity of
the cognitive multiple access network over a finite time horizon subject to a
time averaged interference constraint at the primary user (PU) and almost sure
energy causality constraints at the SUs. The problem is a mixed integer
non-linear program with respect to two decision variables namely spectrum
access decision and spectrum sensing decision, and the continuous variables
sensing time and transmission power. In general, this problem is known to be NP
hard. For optimization over these two decision variables, we use an exhaustive
search policy when the length of the time horizon is small, and a heuristic
policy for longer horizons. For given values of the decision variables, the
problem simplifies into a joint optimization on SU \textit{transmission power}
and \textit{sensing time}, which is non-convex in nature. We solve the
resulting optimization problem as an alternating convex optimization problem
for both non-causal and causal channel state information and harvested energy
information patterns at the SU base station (SBS) or fusion center (FC). We
present an analytic solution for the non-causal scenario with infinite battery
capacity for a general finite horizon problem.We formulate the problem with
causal information and finite battery capacity as a stochastic control problem
and solve it using the technique of dynamic programming. Numerical results are
presented to illustrate the performance of the various algorithms
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