Blind channel selection strategies for distributed cognitive MAC

Rastegardoost, Nazanin; Jabbari, Bijan

doi:10.1109/pimrc.2016.7794808

Cited by 4 publications

(5 citation statements)

References 13 publications

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“…Morcel and others proposed a new algorithm that added proactive behavior for channel allocation at the medium access control layer [19]. Rastegardoost and Jabbari proposed an asymptotically optimal, fast-converging channel selection algorithm-referred to as a modified-myopic strategy-for a single-user scenario, based on the results of multiarmed bandits [20]. Saad and others presented a single channel, cognitive, medium access control protocol, for wireless industrial communication in highly dynamic, shared environments [21].…”

Section: Related Workmentioning

confidence: 99%

“…The delay coefficient, D prio , was 1, 2, and 3, for prio-1, prio-2, and prio-3 classes, respectively. Because there was no spectrum-sensing stage for licensed users, the equation for average delay, D l , was as shown in (20) below:…”

Section: Bayrakdarmentioning

confidence: 99%

“…The slot duration of the nonpersistent, slotted CSMA technique was 100 ms and data packet size was 58 bytes, while the acknowledgment packet size was 4 bytes. The data rate was 1000 kbps, while frequency was 3500 MHz, for both licensed and unlicensed nodes [20]. Licensed nodes were given permission to use spectrum primarily without interruption, while unlicensed nodes sensed the spectrum and tried to find idle frequency bands, using cognitive radio capabilities [24].…”

Section: Proposed Approachmentioning

confidence: 99%

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Exploiting cognitive wireless nodes for priority‐based data communication in terrestrial sensor networks

Bayrakdar

2019

ETRI Journal

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A priority-based data communication approach, developed by employing cognitive radio capacity for sensor nodes in a wireless terrestrial sensor network (TSN), has been proposed. Data sensed by a sensor node-an unlicensed user-were prioritized, taking sensed data importance into account. For data of equal priority, a first come first serve algorithm was used. Non-preemptive priority scheduling was adopted, in order not to interrupt any ongoing transmissions. Licensed users used a nonpersistent, slotted, carrier sense multiple access (CSMA) technique, while unlicensed sensor nodes used a nonpersistent CSMA technique for lossless data transmission, in an energy-restricted, TSN environment. Depending on the analytical model, the proposed wireless TSN environment was simulated using Riverbed software, and to analyze sensor network performance, delay, energy, and throughput parameters were examined. Evaluating the proposed approach showed that the average delay for sensed, high priority data was significantly reduced, indicating that maximum throughput had been achieved using wireless sensor nodes with cognitive radio capacity.

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Section: Related Workmentioning

confidence: 99%

Section: Bayrakdarmentioning

confidence: 99%

Section: Proposed Approachmentioning

confidence: 99%

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Exploiting cognitive wireless nodes for priority‐based data communication in terrestrial sensor networks

Bayrakdar

2019

ETRI Journal

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“…This might lead to contention across spectrum bands. The traditional technique for resolving such conflicts (when they arise) is to use contention resolution techniques, such as CSMA with exponential backoff [11,15], which unfortunately exhibits poor performance, in terms of both throughput and delay, when increasing the number of BSs [16]. A departure from this conventional CRN access technique, in which QPs are followed by TxOps, is the work presented in [17], called HOP-M, where a different methodology for sensing and accessing the spectrum was introduced.…”

Section: Introductionmentioning

confidence: 99%

“…Centralized policies for channel allocation can exhibit better performance compared to distributed policies, which are typically based on random selection executed by each cognitive BS without communicating with the rest of the network. Unfortunately, uncoordinated access to spectrum bands in distributed CRNs can result in excessive collisions, thus increasing delay and lowering throughput [15,16]. Centralized mechanisms can provide a much higher throughput and better levels of fairness (compared to distributed ones), due to the help of a central coordinator.…”

Section: Introductionmentioning

confidence: 99%

Sensing Device Management for History‐Based Spectrum Sharing in Cognitive Radio Networks

Hawa

Jubair

Al‐Zubi

et al. 2018

Wireless Communications and Mobile Computing

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A novel approach to managing a fully distributed cognitive radio network (CRN) is presented. This approach builds on the concept of history-based spectrum access, in which cognitive base stations (BSs) independently estimate the system load using history records and adaptively swap their occupied spectrum bands to ensure allocation fairness and high overall throughput. In addition, cognitive BSs monitor primary user (PU) behavior in order to avoid interfering with active PUs. In this work, we address two issues that afflict history-based access: the first is the high cost of the sensing devices needed at each cognitive BS to be able to independently draw conclusions about the status of the CRN and the second is the unreliability inherent in practical sensing hardware (such as energy detectors). Simulation results show that the proposed technique manages to solve the two abovementioned issues without any noticeable drop in performance and without sacrificing the distributed nature of the protocol.

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