701 research outputs found
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
Spectral and Energy Efficiency in Cognitive Radio Systems with Unslotted Primary Users and Sensing Uncertainty
This paper studies energy efficiency (EE) and average throughput maximization
for cognitive radio systems in the presence of unslotted primary users. It is
assumed that primary user activity follows an ON-OFF alternating renewal
process. Secondary users first sense the channel possibly with errors in the
form of miss detections and false alarms, and then start the data transmission
only if no primary user activity is detected. The secondary user transmission
is subject to constraints on collision duration ratio, which is defined as the
ratio of average collision duration to transmission duration. In this setting,
the optimal power control policy which maximizes the EE of the secondary users
or maximizes the average throughput while satisfying a minimum required EE
under average/peak transmit power and average interference power constraints
are derived. Subsequently, low-complexity algorithms for jointly determining
the optimal power level and frame duration are proposed. The impact of
probabilities of detection and false alarm, transmit and interference power
constraints on the EE, average throughput of the secondary users, optimal
transmission power, and the collisions with primary user transmissions are
evaluated. In addition, some important properties of the collision duration
ratio are investigated. The tradeoff between the EE and average throughput
under imperfect sensing decisions and different primary user traffic are
further analyzed.Comment: This paper is accepted for publication in IEEE Transactions on
Communication
Sensing-Throughput Tradeoff for Interweave Cognitive Radio System: A Deployment-Centric Viewpoint
Secondary access to the licensed spectrum is viable only if interference is
avoided at the primary system. In this regard, different paradigms have been
conceptualized in the existing literature. Of these, Interweave Systems (ISs)
that employ spectrum sensing have been widely investigated. Baseline models
investigated in the literature characterize the performance of IS in terms of a
sensing-throughput tradeoff, however, this characterization assumes the
knowledge of the involved channels at the secondary transmitter, which is
unavailable in practice. Motivated by this fact, we establish a novel approach
that incorporates channel estimation in the system model, and consequently
investigate the impact of imperfect channel estimation on the performance of
the IS. More particularly, the variation induced in the detection probability
affects the detector's performance at the secondary transmitter, which may
result in severe interference at the primary users. In this view, we propose to
employ average and outage constraints on the detection probability, in order to
capture the performance of the IS. Our analysis reveals that with an
appropriate choice of the estimation time determined by the proposed model, the
degradation in performance of the IS can be effectively controlled, and
subsequently the achievable secondary throughput can be significantly enhanced.Comment: 13 pages, 10 figures, Accepted to be published in IEEE Transactions
on Wireless Communication
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