24,194 research outputs found
On the throughput of channel access algorithms with limited sensing
"December 1984."" NSF-ECS-8310698" " Contract ONR/N00014-84-K-0357"Pierre A. Humblet
Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks
Cognitive radio has been widely considered as one of the prominent solutions
to tackle the spectrum scarcity. While the majority of existing research has
focused on single-band cognitive radio, multiband cognitive radio represents
great promises towards implementing efficient cognitive networks compared to
single-based networks. Multiband cognitive radio networks (MB-CRNs) are
expected to significantly enhance the network's throughput and provide better
channel maintenance by reducing handoff frequency. Nevertheless, the wideband
front-end and the multiband spectrum access impose a number of challenges yet
to overcome. This paper provides an in-depth analysis on the recent
advancements in multiband spectrum sensing techniques, their limitations, and
possible future directions to improve them. We study cooperative communications
for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also
investigate several limits and tradeoffs of various design parameters for
MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that
differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE
Journal, Special Issue on Future Radio Spectrum Access, March 201
Maximizing System Throughput Using Cooperative Sensing in Multi-Channel Cognitive Radio Networks
In Cognitive Radio Networks (CRNs), unlicensed users are allowed to access
the licensed spectrum when it is not currently being used by primary users
(PUs). In this paper, we study the throughput maximization problem for a
multi-channel CRN where each SU can only sense a limited number of channels. We
show that this problem is strongly NP-hard, and propose an approximation
algorithm with a factor at least where is a system
parameter reflecting the sensing capability of SUs across channels and their
sensing budgets. This performance guarantee is achieved by exploiting a nice
structural property of the objective function and constructing a particular
matching. Our numerical results demonstrate the advantage of our algorithm
compared with both a random and a greedy sensing assignment algorithm
Throughput analysis for cognitive radio networks with multiple primary users and imperfect spectrum sensing
In cognitive radio networks, the licensed frequency bands of the primary users (PUs) are available to the secondary user (SU) provided that they do not cause significant interference to the PUs. In this study, the authors analysed the normalised throughput of the SU with multiple PUs coexisting under any frequency division multiple access communication protocol. The authors consider a cognitive radio transmission where the frame structure consists of sensing and data transmission slots. In order to achieve the maximum normalised throughput of the SU and control the interference level to the legal PUs, the optimal frame length of the SU is found via simulation. In this context, a new analytical formula has been expressed for the achievable normalised throughput of SU with multiple PUs under prefect and imperfect spectrum sensing scenarios. Moreover, the impact of imperfect sensing, variable frame length of SU and the variable PU traffic loads, on the normalised throughput has been critically investigated. It has been shown that the analytical and simulation results are in perfect agreement. The authors analytical results are much useful to determine how to select the frame duration length subject to the parameters of cognitive radio network, such as network traffic load, achievable sensing accuracy and number of coexisting PUs
Full-Duplex Cognitive Radio: A New Design Paradigm for Enhancing Spectrum Usage
With the rapid growth of demand for ever-increasing data rate, spectrum
resources have become more and more scarce. As a promising technique to
increase the efficiency of the spectrum utilization, cognitive radio (CR)
technique has the great potential to meet such a requirement by allowing
un-licensed users to coexist in licensed bands. In conventional CR systems, the
spectrum sensing is performed at the beginning of each time slot before the
data transmission. This unfortunately results in two major problems: 1)
transmission time reduction due to sensing, and 2) sensing accuracy impairment
due to data transmission. To tackle these problems, in this paper we present a
new design paradigm for future CR by exploring the full-duplex (FD) techniques
to achieve the simultaneous spectrum sensing and data transmission. With FD
radios equipped at the secondary users (SUs), SUs can simultaneously sense and
access the vacant spectrum, and thus, significantly improve sensing
performances and meanwhile increase data transmission efficiency. The aim of
this article is to transform the promising conceptual framework into the
practical wireless network design by addressing a diverse set of challenges
such as protocol design and theoretical analysis. Several application scenarios
with FD enabled CR are elaborated, and key open research directions and novel
algorithms in these systems are discussed
Throughput and Collision Analysis of Multi-Channel Multi-Stage Spectrum Sensing Algorithms
Multi-stage sensing is a novel concept that refers to a general class of
spectrum sensing algorithms that divide the sensing process into a number of
sequential stages. The number of sensing stages and the sensing technique per
stage can be used to optimize performance with respect to secondary user
throughput and the collision probability between primary and secondary users.
So far, the impact of multi-stage sensing on network throughput and collision
probability for a realistic network model is relatively unexplored. Therefore,
we present the first analytical framework which enables performance evaluation
of different multi-channel multi-stage spectrum sensing algorithms for
Opportunistic Spectrum Access networks. The contribution of our work lies in
studying the effect of the following parameters on performance: number of
sensing stages, physical layer sensing techniques and durations per each stage,
single and parallel channel sensing and access, number of available channels,
primary and secondary user traffic, buffering of incoming secondary user
traffic, as well as MAC layer sensing algorithms. Analyzed performance metrics
include the average secondary user throughput and the average collision
probability between primary and secondary users. Our results show that when the
probability of primary user mis-detection is constrained, the performance of
multi-stage sensing is, in most cases, superior to the single stage sensing
counterpart. Besides, prolonged channel observation at the first stage of
sensing decreases the collision probability considerably, while keeping the
throughput at an acceptable level. Finally, in realistic primary user traffic
scenarios, using two stages of sensing provides a good balance between
secondary users throughput and collision probability while meeting successful
detection constraints subjected by Opportunistic Spectrum Access communication
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