On Spectrum Sharing and Dynamic Spectrum Allocation: MAC Layer Spectrum Sensing in Cognitive Radio Networks

Hamid, Mohamed; Mohammed, Abbas; Yang, Zhe

doi:10.1109/cmc.2010.342

Cited by 22 publications

(14 citation statements)

References 7 publications

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“…The CTMC model has widely been used in the study of various DSA/CR techniques such as MAC protocols for spectrum sharing [213,214], MAC-layer sensing schemes [215][216][217] and adaptive spectrum sensing solutions [218] as well as to analyze the sensing-throughput trade-off [219,220] and the performance of DSA/CR sensor networks [221].…”

Section: Previous Work Based On Continuous-time Markov Chainsmentioning

confidence: 99%

“…The continuous-time counterpart of the DTMC model is the well-known Continuous-Time Markov Chain (CTMC) model, where the state holding times are modeled as exponentially distributed random variables. As mentioned in Chapter 7, the CTMC model has widely been used in the literature to study various aspects of DSA/CR networks [213][214][215][216][217][218][219][220][221]. However, some works based on empirical measurements [222][223][224][225][226] have demonstrated that the lengths of busy and idle periods in real systems are not exponentially distributed, meaning that the CTMC model is unrealistic.…”

Section: Introductionmentioning

confidence: 99%

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Spectrum Usage Models for the Analysis, Design and Simulation of Cognitive Radio Networks

López-Benítez

Casadevall

2012

Lecture Notes in Electrical Engineering

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ADVERTIMENT. La consulta d'aquesta tesi queda condicionada a l'acceptació de les següents condicions d'ús: La difusió d'aquesta tesi per mitjà del servei TDX (www.tesisenxarxa.net) ha estat autoritzada pels titulars dels drets de propietat intel·lectual únicament per a usos privats emmarcats en activitats d'investigació i docència. No s'autoritza la seva reproducció amb finalitats de lucre ni la seva difusió i posada a disposició des d'un lloc aliè al servei TDX. No s'autoritza la presentació del seu contingut en una finestra o marc aliè a TDX (framing). Aquesta reserva de drets afecta tant al resum de presentació de la tesi com als seus continguts. En la utilització o cita de parts de la tesi és obligat indicar el nom de la persona autora.ADVERTENCIA. La consulta de esta tesis queda condicionada a la aceptación de las siguientes condiciones de uso: La difusión de esta tesis por medio del servicio TDR (www.tesisenred.net) ha sido autorizada por los titulares de los derechos de propiedad intelectual únicamente para usos privados enmarcados en actividades de investigación y docencia. No se autoriza su reproducción con finalidades de lucro ni su difusión y puesta a disposición desde un sitio ajeno al servicio TDR. No se autoriza la presentación de su contenido en una ventana o marco ajeno a TDR (framing). Esta reserva de derechos afecta tanto al resumen de presentación de la tesis como a sus contenidos. En la utilización o cita de partes de la tesis es obligado indicar el nombre de la persona autora. WARNING.On having consulted this thesis you're accepting the following use conditions: Spreading this thesis by the TDX (www.tesisenxarxa.net) service has been authorized by the titular of the intellectual property rights only for private uses placed in investigation and teaching activities. Reproduction with lucrative aims is not authorized neither its spreading and availability from a site foreign to the TDX service. Introducing its content in a window or frame foreign to the TDX service is not authorized (framing). This rights affect to the presentation summary of the thesis as well as to its contents. In the using or citation of parts of the thesis it's obliged to indicate the name of the author Essentially, all models are wrong, but some are useful.George E. P. BoxTo my beloved family for their unconditional love and support.A mi querida familia por su cariño y apoyo incondicionales. 0 ABSTRACTThe owned spectrum allocation policy, in use since the early days of modern radio communications, has been proven to effectively control interference among radio communication systems and simplify the design of hardware for use at a known and fixed range of frequencies. However, the overwhelming proliferation of new operators, innovative services and wireless technologies during the last years has resulted, under this static regulatory regime, in the depletion of all spectrum bands with commercially attractive radio propagation characteristics. The vast majority of spectrum regarded as usable has already been allocated, thus...

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Section: Previous Work Based On Continuous-time Markov Chainsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spectrum Usage Models for the Analysis, Design and Simulation of Cognitive Radio Networks

López-Benítez

Casadevall

2012

Lecture Notes in Electrical Engineering

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“…Thus, the proposed algorithms cannot be practical in a real‐world environment. There are also some recent studies about channel handover strategies (CHSs) aiming at reducing the frequency of handover using proactive schemes . In these studies, the authors assumed that SUs have global spectrum knowledge and were tracking all PU activities in all of the channels.…”

Section: Introductionmentioning

confidence: 99%

An efficient and adaptive channel handover procedure for cognitive radio networks

Kahraman

Buzluca

2013

Wirel. Commun. Mob. Comput.

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In designing cognitive radio systems, one of the most critical issues is handling the channel handover process (CHP). The CHP consists of spectrum sensing, spectrum decision, negotiation on the common control channel, and adjustment of frequency and modulation settings, and such, it can be a time-consuming process. Consequently, initiating the CHP after each detected user activity (UA) can decrease the aggregate spectrum utilization. To alleviate this problem, we introduce a novel handover strategy to find the optimal trade-off between the durations of the CHP and UAs. With the use this model, secondary users (SUs) track only local information on their current data channel to make the decision to initiate the CHP or to wait for the termination of the ongoing UA. The system adapts to the dynamic conditions of the data channels and reduces the frequency of handovers to increase throughput and decrease access delay. We give analytical utilization bounds for SUs and also compare the performance of our model to those of other channel handover strategies by using extensive simulations. Our results for channels with heterogeneous loads and dynamic environments show that this model can clearly decrease the frequency of handover and consequently increase the aggregate SU utilization.

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“…A great advantage of the exponential distribution is the traceability in finding analytical solutions for optimization problems. Therefore, exponential distribution has been intensively used to model cellular channel occupancy, see [4] as an example. Nevertheless, many research findings concluded poor similarity between exponential distribution and empirical data [6].…”

Section: Introductionmentioning

confidence: 99%

“…Among the statistics used for traffic evaluation in cellular systems is the channel occupancy which is defined as the time that a user occupies a channel in a cell while it is located in the serving area of that cell [3]. The channel usage for a cellular system is modelled as a two states Markov chain process [4]. The first state is the busy state when the channel is being assigned for a user whereas the second state is the idle state when the channel is idle.…”

Section: Introductionmentioning

confidence: 99%

Empirical Statistical Model for LTE Downlink Channel Occupancy

Hamid

Björsell

Slimane

2017

Wireless Pers Commun

Self Cite

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This paper develops an empirical statistical channel occupancy model for downlink long-term evolution (LTE) cellular systems. The model is based on statistical distributions mixtures for the holding times of the channels. Moreover, statistical distribution of the time when the channels are free is also considered. The data is obtained through an extensive measurement campaign performed in Stockholm, Sweden. Two types of mixtures are considered, namely, exponential and log-normal distributions to fit the measurement findings. The log-likelihood of both mixtures is used as a quantitative measure of the goodness of fit. Moreover, finding the optimal number of linearly combined distributions using the Akaike information criterion is investigated. The results show that good fitting can be obtained by using either exponential or log-normal distributions mixture. Even though, the fitting is done for a representative case with a tempo-spatial consideration, the model is yet applicable in general for LTE and other cellular systems in a wider sense.

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On Spectrum Sharing and Dynamic Spectrum Allocation: MAC Layer Spectrum Sensing in Cognitive Radio Networks

Cited by 22 publications

References 7 publications

Spectrum Usage Models for the Analysis, Design and Simulation of Cognitive Radio Networks

Spectrum Usage Models for the Analysis, Design and Simulation of Cognitive Radio Networks

An efficient and adaptive channel handover procedure for cognitive radio networks

Empirical Statistical Model for LTE Downlink Channel Occupancy

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