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Joint spatial-temporal spectrum sensing for cognitive radio networks
- IEEE TVT
, 2010
"... Abstract—In a wireless system with opportunistic spectrum sharing, secondary users equipped with cognitive radios attempt to access radio spectrum that is not being used by the primary licensed users. On a given frequency channel, a secondary user can perform spectrum sensing to determine spatial or ..."
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Cited by 12 (5 self)
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Abstract—In a wireless system with opportunistic spectrum sharing, secondary users equipped with cognitive radios attempt to access radio spectrum that is not being used by the primary licensed users. On a given frequency channel, a secondary user can perform spectrum sensing to determine spatial or temporal opportunities for spectrum reuse. Whereas most prior works address either spatial or temporal sensing in isolation, we propose a joint spatial-temporal spectrum sensing scheme, which exploits information from spatial sensing to improve the performance of temporal sensing. Our simulation results show that the proposed joint spatial-temporal approach significantly outperforms existing temporal sensing schemes. Index Terms—Dynamic spectrum access, cognitive radio, hypothesis testing, spectrum sensing I.
1Spectrum Sensing Using a Hidden Bivariate Markov Model
"... Abstract—A new statistical model, in the form of a hidden bivariate Markov chain observed through a Gaussian channel, is developed and applied to spectrum sensing for cognitive radio. We focus on temporal spectrum sensing in a single narrowband channel in which a primary transmitter is either in an ..."
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Cited by 4 (1 self)
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Abstract—A new statistical model, in the form of a hidden bivariate Markov chain observed through a Gaussian channel, is developed and applied to spectrum sensing for cognitive radio. We focus on temporal spectrum sensing in a single narrowband channel in which a primary transmitter is either in an idle or an active state. The main advantage of the proposed model, compared to a standard hidden Markov model (HMM) is that it allows a phase-type dwell time distribution for the process in each state. This distribution significantly generalizes the geometric dwell time distribution of a standard HMM. Measurements taken from real data confirm that the geometric dwell time distribution characteristic of the HMM is not adequate for this application. The Baum algorithm is used to estimate the parameter of the proposed model and a forward recursion is applied to online estimation and prediction of the state of the cognitive radio channel. The performance of the proposed model and spectrum sensing approach are demonstrated using numerical results derived from real spectrum measurement data.
1Interference Model for Spectrum Sensing with Power Control
"... Abstract—This paper analyzes the aggregate interference in a cognitive radio network. We consider a model in which the secondary transmitters are geographically distributed according to a Poisson point process in a wireless environment subject to shadowing noise and path loss. The secondary transmit ..."
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Cited by 1 (0 self)
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Abstract—This paper analyzes the aggregate interference in a cognitive radio network. We consider a model in which the secondary transmitters are geographically distributed according to a Poisson point process in a wireless environment subject to shadowing noise and path loss. The secondary transmitters may transmit simultaneously and consequently incur an aggregate interference level on the primary system. We derive the mo-ment generating function and the expectation of the aggregate interference for this model using properties of the Poisson point process. Based on the interference analysis, a scheme is proposed to estimate the maximum transmission power for each of the active secondary transmitters so as to satisfy a constraint on the aggregate interference. Our numerical results show a significant gain in the achievable capacity for the secondary system relative to an earlier scheme in which only a single secondary transmitter was permitted to transmit at any given time.1
Aspects and Approaches of Spectrum Sensing Techniques in Cognitive Radio Network: A Survey Ashima Rout
"... Abstract: The changeover of communication applications from the domain of voice-only to multimedia type has necessitated an increase in the data rates. This exploits the concept of opportunistic usage of limited available spectrum dynamically. Thus, the problem of spectral congestion is overcome by ..."
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Abstract: The changeover of communication applications from the domain of voice-only to multimedia type has necessitated an increase in the data rates. This exploits the concept of opportunistic usage of limited available spectrum dynamically. Thus, the problem of spectral congestion is overcome by further increase in its efficiency. However, present scenario of wireless vicinity strives to focus upon enhanced speed with increasing data rates and decrease in the overheads like cost per bit. To recapitulate this objective and refrain from the sporadic usage of spectrum bands, a challenging paradigm known as Cognitive Radio has been emerged towards resolving the bottleneck in spectrum utility. Different spectrum sensing methodologies are adapted as regards to spectrum detection mechanism and type of spectrum sharing methods in a variety of networking environment like homogeneous & heterogeneous. Current generation wireless network involved with varied range of high definition audio as well as video applications with QoS is greatly heterogeneous. Spectrum sensing comprises of studying the radio spectrum with its explanations in order to accomplish the knowledge of the licensed-transmission in the shared spectrum group. Thus, Spectrum sensing is a significant assignment in CR system that is very much essential in the IEEE 802.22 standard. We have analyzed the effects and impact of various spectrum sensing techniques in a wide range of wireless domain. The heterogeneity of a wireless link could be
1Joint Spatial-Temporal Spectrum Sensing for Cognitive Radio Networks
"... Abstract—In a wireless system with opportunistic spectrum sharing, secondary users equipped with cognitive radios attempt to access radio spectrum that is not being used by the primary licensed users. On a given frequency channel, a secondary user can perform spectrum sensing to determine spatial or ..."
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Abstract—In a wireless system with opportunistic spectrum sharing, secondary users equipped with cognitive radios attempt to access radio spectrum that is not being used by the primary licensed users. On a given frequency channel, a secondary user can perform spectrum sensing to determine spatial or temporal opportunities for spectrum reuse. Whereas most prior works address either spatial or temporal sensing in isolation, we propose a joint spatial-temporal spectrum sensing scheme, which exploits information from spatial sensing to improve the performance of temporal sensing. We quantify the performance benefit of the joint spatial-temporal scheme over pure spatial sensing and pure temporal sensing based on counting rule and linear quadratic detectors. Finally, we analyze a multi-level quantization feedback scheme that can improve the performance of temporal sensing based on counting rule detectors. Index Terms—Dynamic spectrum access, cognitive radio, hy-pothesis testing, spectrum sensing I.
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"... In traditional wireless systems, spectrum or frequency is allocated to licensed users over a geographic area. Within these constraints, spectrum is considered a scarce resource due to static spectrum allocation. Recent empirical studies of radio spectrum usage have shown that licensed spectrum is ty ..."
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In traditional wireless systems, spectrum or frequency is allocated to licensed users over a geographic area. Within these constraints, spectrum is considered a scarce resource due to static spectrum allocation. Recent empirical studies of radio spectrum usage have shown that licensed spectrum is typically highly underutilized (Broderson et al., 2004;
(CORN)2: Correlation-Based Cooperative Spectrum Sensing in Cognitive Radio Networks
"... Abstract—In this paper, (CORN)2, a correlation-based, optimal sensing scheduling algorithm is developed for cognitive radio networks to minimize energy consumption. A sensing quality metric is defined as a measure of the correctness of spectral availability information. The optimal scheduling algori ..."
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Abstract—In this paper, (CORN)2, a correlation-based, optimal sensing scheduling algorithm is developed for cognitive radio networks to minimize energy consumption. A sensing quality metric is defined as a measure of the correctness of spectral availability information. The optimal scheduling algorithm is shown to minimize the cost of sensing (e.g., energy consumption, sensing duration) while meeting the sensing quality requirements. To this end, (CORN)2 utilizes a novel sensing deficiency virtual queue concept and exploits the correlation between spectrum measurements of a particular secondary user and its collabo-rating neighbors. The proposed algorithm is further proved to achieve a distributed and optimal solution under certain, easily satisfied assumptions. In addition to the theoretically proved performance guarantees, the proposed algorithm is also evaluated through simulations. I.
Performance Analysis of Unreliable Sensing for an Opportunistic Spectrum Sharing System
"... Abstract: Opportunistic spectrum sharing (OSS) is a promising technique to improve spectrum utilization using cognitive radios. Unreliable spectrum sensing by cognitive radios is inevitable in the OSS system. In this paper, we analyze the types of unreliable sensing and their impact on the system pe ..."
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Abstract: Opportunistic spectrum sharing (OSS) is a promising technique to improve spectrum utilization using cognitive radios. Unreliable spectrum sensing by cognitive radios is inevitable in the OSS system. In this paper, we analyze the types of unreliable sensing and their impact on the system performance. The secondary users equipped with cognitive radios sense channels that are unused by the primary users and utilize the idle channels. An ongoing secondary user also detects when a primary user accesses its channel and then either moves to another idle channel or moves to a buffer if no idle channel is available. Unreliable spectrum sensing is modeled by false alarm and misdetection events for both initiating and ongoing secondary users. We solve the steady-state probability vector of the system and derive a set of performance metrics of interest. Numerical results are presented to highlight the analysis. The proposed modeling method can be used to evaluate the performance of future opportunistic spectrum sharing networks.
