10 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
Analysis Framework for Opportunistic Spectrum OFDMA and its Application to the IEEE 802.22 Standard
We present an analytical model that enables throughput evaluation of
Opportunistic Spectrum Orthogonal Frequency Division Multiple Access (OS-OFDMA)
networks. The core feature of the model, based on a discrete time Markov chain,
is the consideration of different channel and subchannel allocation strategies
under different Primary and Secondary user types, traffic and priority levels.
The analytical model also assesses the impact of different spectrum sensing
strategies on the throughput of OS-OFDMA network. The analysis applies to the
IEEE 802.22 standard, to evaluate the impact of two-stage spectrum sensing
strategy and varying temporal activity of wireless microphones on the IEEE
802.22 throughput. Our study suggests that OS-OFDMA with subchannel notching
and channel bonding could provide almost ten times higher throughput compared
with the design without those options, when the activity and density of
wireless microphones is very high. Furthermore, we confirm that OS-OFDMA
implementation without subchannel notching, used in the IEEE 802.22, is able to
support real-time and non-real-time quality of service classes, provided that
wireless microphones temporal activity is moderate (with approximately one
wireless microphone per 3,000 inhabitants with light urban population density
and short duty cycles). Finally, two-stage spectrum sensing option improves
OS-OFDMA throughput, provided that the length of spectrum sensing at every
stage is optimized using our model
When Channel Bonding is Beneficial for Opportunistic Spectrum Access Networks
Transmission over multiple frequency bands combined into one logical channel
speeds up data transfer for wireless networks. On the other hand, the
allocation of multiple channels to a single user decreases the probability of
finding a free logical channel for new connections, which may result in a
network-wide throughput loss. While this relationship has been studied
experimentally, especially in the WLAN configuration, little is known on how to
analytically model such phenomena. With the advent of Opportunistic Spectrum
Access (OSA) networks, it is even more important to understand the
circumstances in which it is beneficial to bond channels occupied by primary
users with dynamic duty cycle patterns. In this paper we propose an analytical
framework which allows the investigation of the average channel throughput at
the medium access control layer for OSA networks with channel bonding enabled.
We show that channel bonding is generally beneficial, though the extent of the
benefits depend on the features of the OSA network, including OSA network size
and the total number of channels available for bonding. In addition, we show
that performance benefits can be realized by adaptively changing the number of
bonded channels depending on network conditions. Finally, we evaluate channel
bonding considering physical layer constraints, i.e. throughput reduction
compared to the theoretical throughput of a single virtual channel due to a
transmission power limit for any bonding size.Comment: accepted to IEEE Transactions on Wireless Communication
A Cognitive radio approach for usage of virtual unlicensed spectrum
Abstract — While essentially all of the frequency spectrum is allocated to different applications, observations provide evidence that usage of the spectrum is actually quite limited, particularly in bands above 3 GHz. In this paper we present a Cognitive Radio approach for usage of Virtual Unlicensed Spectrum (CORVUS), a vision of a Cognitive Radio (CR) based approach that uses allocated spectrum in a opportunistic manner to create “virtual unlicensed bands ” i.e. bands that are shared with the primary (often licensed) users on a non-interfering basis. Dynamic spectrum management techniques are used to adapt to immediate local spectrum availability. We define the system requirements for this approach, as well as the general architecture and basic physical and link layer functions of CORVUS. I