1,130 research outputs found
Optimal Random Access and Random Spectrum Sensing for an Energy Harvesting Cognitive Radio with and without Primary Feedback Leveraging
We consider a secondary user (SU) with energy harvesting capability. We
design access schemes for the SU which incorporate random spectrum sensing and
random access, and which make use of the primary automatic repeat request (ARQ)
feedback. We study two problem-formulations. In the first problem-formulation,
we characterize the stability region of the proposed schemes. The sensing and
access probabilities are obtained such that the secondary throughput is
maximized under the constraints that both the primary and secondary queues are
stable. Whereas in the second problem-formulation, the sensing and access
probabilities are obtained such that the secondary throughput is maximized
under the stability of the primary queue and that the primary queueing delay is
kept lower than a specified value needed to guarantee a certain quality of
service (QoS) for the primary user (PU). We consider spectrum sensing errors
and assume multipacket reception (MPR) capabilities. Numerical results show the
enhanced performance of our proposed systems.Comment: ACCEPTED in EAI Endorsed Transactions on Cognitive Communications.
arXiv admin note: substantial text overlap with arXiv:1208.565
Optimal Random Access and Random Spectrum Sensing for an Energy Harvesting Cognitive Radio
We consider a secondary user with energy harvesting capability. We design
access schemes for the secondary user which incorporate random spectrum sensing
and random access, and which make use of the primary automatic repeat request
(ARQ) feedback. The sensing and access probabilities are obtained such that the
secondary throughput is maximized under the constraints that both the primary
and secondary queues are stable and that the primary queueing delay is kept
lower than a specified value needed to guarantee a certain quality of service
(QoS) for the primary user. We consider spectrum sensing errors and assume
multipacket reception (MPR) capabilities. Numerical results are presented to
show the enhanced performance of our proposed system over a random access
system, and to demonstrate the benefit of leveraging the primary feedback.Comment: in WiMob 201
Interference-Based Optimal Power-Efficient Access Scheme for Cognitive Radio Networks
In this paper, we propose a new optimization-based access strategy of
multipacket reception (MPR) channel for multiple secondary users (SUs)
accessing the primary user (PU) spectrum opportunistically. We devise an
analytical model that realizes the multipacket access strategy of SUs that
maximizes the throughput of individual backlogged SUs subject to queue
stability of the PU. All the network receiving nodes have MPR capability. We
aim at maximizing the throughput of the individual SUs such that the PU's queue
is maintained stable. Moreover, we are interested in providing an
energy-efficient cognitive scheme. Therefore, we include energy constraints on
the PU and SU average transmitted energy to the optimization problem. Each SU
accesses the medium with certain probability that depends on the PU's activity,
i.e., active or inactive. The numerical results show the advantage in terms of
SU throughput of the proposed scheme over the conventional access scheme, where
the SUs access the channel randomly with fixed power when the PU is sensed to
be idle
EC-CENTRIC: An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design
The radio transceiver of an IoT device is often where most of the energy is consumed. For this reason, most research so far has focused on low power circuit and energy efficient physical layer designs, with the goal of reducing the average energy per information bit required for communication. While these efforts are valuable per se, their actual effectiveness can be partially neutralized by ill-designed network, processing and resource management solutions, which can become a primary factor of performance degradation, in terms of throughput, responsiveness and energy efficiency. The objective of this paper is to describe an energy-centric and context-aware optimization framework that accounts for the energy impact of the fundamental functionalities of an IoT system and that proceeds along three main technical thrusts: 1) balancing signal-dependent processing techniques (compression and feature extraction) and communication tasks; 2) jointly designing channel access and routing protocols to maximize the network lifetime; 3) providing self-adaptability to different operating conditions through the adoption of suitable learning architectures and of flexible/reconfigurable algorithms and protocols. After discussing this framework, we present some preliminary results that validate the effectiveness of our proposed line of action, and show how the use of adaptive signal processing and channel access techniques allows an IoT network to dynamically tune lifetime for signal distortion, according to the requirements dictated by the application
Resource Allocation Challenges and Strategies for RF-Energy Harvesting Networks Supporting QoS
This paper specifically addresses the resource allocation challenges encountered in wireless sensor networks that incorporate RF energy harvesting capabilities, commonly referred to as RF-energy harvesting networks (RF-EHNs). RF energy harvesting and transmission techniques bring substantial advantages for applications requiring Quality of Service (QoS) support, as they enable proactive replenishment of wireless devices. We commence by providing an overview of RF-EHNs, followed by an in-depth examination of the resource allocation challenges associated with this technology. In addition, we present a case study that focuses on the design of an efficient operating strategy for RF-EHN receivers. Our investigation highlights the critical aspects of service differentiation and QoS support, which have received limited attention in previous research. Besides, we explore previously unexplored areas within these domains
Cognition-inspired 5G cellular networks: a review and the road ahead
Despite the evolution of cellular networks, spectrum scarcity and the lack of intelligent and autonomous capabilities remain a cause for concern. These problems have resulted in low network capacity, high signaling overhead, inefficient data forwarding, and low scalability, which are expected to persist as the stumbling blocks to deploy, support and scale next-generation applications, including smart city and virtual reality. Fifth-generation (5G) cellular networking, along with its salient operational characteristics - including the cognitive and cooperative capabilities, network virtualization, and traffic offload - can address these limitations to cater to future scenarios characterized by highly heterogeneous, ultra-dense, and highly variable environments. Cognitive radio (CR) and cognition cycle (CC) are key enabling technologies for 5G. CR enables nodes to explore and use underutilized licensed channels; while CC has been embedded in CR nodes to learn new knowledge and adapt to network dynamics. CR and CC have brought advantages to a cognition-inspired 5G cellular network, including addressing the spectrum scarcity problem, promoting interoperation among heterogeneous entities, and providing intelligence and autonomous capabilities to support 5G core operations, such as smart beamforming. In this paper, we present the attributes of 5G and existing state of the art focusing on how CR and CC have been adopted in 5G to provide spectral efficiency, energy efficiency, improved quality of service and experience, and cost efficiency. This main contribution of this paper is to complement recent work by focusing on the networking aspect of CR and CC applied to 5G due to the urgent need to investigate, as well as to further enhance, CR and CC as core mechanisms to support 5G. This paper is aspired to establish a foundation and to spark new research interest in this topic. Open research opportunities and platform implementation are also presented to stimulate new research initiatives in this exciting area
Energy Harvesting Wireless Communications: A Review of Recent Advances
This article summarizes recent contributions in the broad area of energy
harvesting wireless communications. In particular, we provide the current state
of the art for wireless networks composed of energy harvesting nodes, starting
from the information-theoretic performance limits to transmission scheduling
policies and resource allocation, medium access and networking issues. The
emerging related area of energy transfer for self-sustaining energy harvesting
wireless networks is considered in detail covering both energy cooperation
aspects and simultaneous energy and information transfer. Various potential
models with energy harvesting nodes at different network scales are reviewed as
well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications
(Special Issue: Wireless Communications Powered by Energy Harvesting and
Wireless Energy Transfer
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