Cross‐layer perspective for channel assignment in cognitive radio networks: A survey

Gupta, Nitin; Dhurandher, Sanjay Kumar

doi:10.1002/dac.4261

Cited by 13 publications

(6 citation statements)

References 145 publications

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“…Assuming that the level of exactness is high, gadget activity will be ideal since the probability of erroneous spectrum task will be tiny and impacts between the PU and SUs will stay away. High energy financial plans will bring about precise sensing results however then again, contributing a lot to this undertaking probably won't be worth it on the off chance that meddling signs are irregular or are seen with extremely high power and are hence simple to identify [9]. Moreover, to accomplish the most elevated energy effectiveness, the sensing energy financial plan ought to be dimensioned representing the size of communicated bundles.…”

Section: International Journal Of Communication Network and Informati...mentioning

confidence: 99%

Energy Aware Channel Allocation with Spectrum Sensing in Pilot Contamination Analysis for Cognitive Radio Networks

Joshi¹,

Pandey²,

Aarju³

et al. 2022

Int. j. commun. netw. inf. secur.

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Cognitive radio (CR) is an innovative and contemporary technology that has been making an effort to overcome the problems of bandwidth reduction by rising the usage of mobile cellular bandwidth connections. The reallocation and distribution of channels is a fundamental characteristic of cellular mobile networks (CMN) to exploit the consumption of CMS. Meanwhile, throughput maximization might lead to higher power utilization, the spectrum sensing system must tackle the energy throughput tradeoff. The spectrum sensing time should be defined by the residual battery energy of secondary user (SU). In that context, energy effective algorithm for spectrum sensing should be developed for meeting the energy constraint of CRN. This study designs a new quantum particle swarm optimization-based energy aware spectrum sensing scheme (QPSO-EASSS) for CRNs. Here, the presented QPSO-EASSS technique dynamically estimates the sensing time depending upon the battery energy level of SUs and the transmission power can be computed based on the battery energy level and PU signal of the SUs. In addition, in this work, the QPSO-EASSS technique applies the QPSO algorithm for throughput maximization with energy constraints in the CRN. The detailed set of experimentations take place and reported the improvements of the QPSO-EASSS technique compared to existing models.

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Section: International Journal Of Communication Network and Informati...mentioning

confidence: 99%

Energy Aware Channel Allocation with Spectrum Sensing in Pilot Contamination Analysis for Cognitive Radio Networks

Joshi¹,

Pandey²,

Aarju³

et al. 2022

Int. j. commun. netw. inf. secur.

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“…The designs mentioned above rely on other layer parameters to yield routing and slot assignment information incorporated in control frames [25,26]. This increases the control overhead in the execution of route discovery, channel, and slot assignment.…”

Section: Related Workmentioning

confidence: 99%

A Novel Self-Forming Virtual Sub-Nets Based Cross-Layer MAC Protocol for Multihop Tactical Network

et al. 2021

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A tactical network mainly consists of software-defined radios (SDRs) integrated with programmable and reconfigurable features that provide the addition and customization of different waveforms for different scenarios, e.g., situational awareness, video, or voice transmission. The network, which is mission-critical, congested, and delay-sensitive, operates in infrastructure-less terrains with self-forming and self-healing capabilities. It demands reliability and the need to survive by seamlessly maintaining continuous network connectivity during mobility and link failures. SDR platforms transfer large amounts of data that must be processed with low latency transmissions. The state-of-the-art solutions lack the capability to provide high data throughput and incorporate overhead in route discovery and resource distribution that is not appropriate for resource-constrained mission-critical networks. A cross-layer design exploits existing resources to react to environment changes efficiently, enable reliability, and escalate network throughput. A solution that integrates SDR benefits and cross-layer optimization can perform all the mentioned operations efficiently. In tactical networks, SDR’s maximum usable bandwidth can be utilized by exploiting radios’ autonomous behavior. This paper presents a novel virtual sub-nets based cross-layer medium access control (VSCL-MAC) protocol for self-forming multihop tactical radio networks. It is a MAC-centric design with cross-layer optimization that enables dynamic routing and autonomous time-slot scheduling in a multichannel network environment among SDRs. The cross-layer coupling uses link-layer information from the hybrid of time division multiple access and frequency division multiple access (TDMA/FDMA) MAC to proactively enable distributed intelligent routing at the network layer. The virtual sub-nets based distributed algorithm exploits spectrum resources and provides call setup with persistently available k-hop route information and simultaneous collision-free transmission of voice and data. The experimental results over extensive simulations show significant performance improvements in terms of minimum control overhead, processing time in relay nodes, a substantial increase in network throughput, and lower data latency (up to 76.98%) compared to conventional time-slotted MAC protocols. The design is useful for mission-critical, time-sensitive networks and exploits multihop simultaneous communication in a distributed manner.

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“…Through the inception of several promising wireless devices, the exploitation of limited spectrum has risen in a significant manner in the recent few years. In [9], an in‐depth discussion of channel assignment mechanisms including different functionalities for CRNs is presented. At first, an overview was given to both CRNs and wireless networks.…”

Section: Related Workmentioning

confidence: 99%

Optimised Levenshtein centroid cross‐layer defence for multi‐hop cognitive radio networks

Ganesh

Kumar

Kumar³

2020

IET Communications

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Cognitive radio networks (CRN) make use of dynamic spectrum access to communicate opportunistically. Unlicensed users severely affect the spectrum sensing outcomes in CRN. Primary user emulation attack (PUEA) and spectrum sensing data falsification (SSDF) have become a paramount concern in CRNs. It is especially challenging when both masquerading (in the physical layer) and falsification (in the data link layer) occur by providing false spectrum reports. Existing methods to detect such attacks cannot be utilised in scenarios with multi-hop CRN. In this study, to mitigate attack against PUEA and SSDF, a method called optimised sensing and Levenshtein nearest centroid classification (OS-LNCC) for multi-hop CRN is presented. First, a network model for multi-hop CRN is designed. Next, a probable density optimal logical sensing model is designed to alleviate the problems related to falsification of spectrum reports. Here, the falsification of spectrum reports is overcome by exploiting dual factors, that is, probability for false alarm and probability for detection according to the departure rate of primary user (PU). With these dual factors, optimal logical sensing is made, therefore improving the throughput with minimum delay. Finally, each cognitive radio (CR) user evaluates its current sensing information to existing sensing classes through the Levenshtein distance function. Based on quantitative variables, the prediction function of each sensing class is measured using nearest centroid (NC) classifier and the sensing report is classified into either presence or absence of PU. These predictive classes are then integrated at the fusion centre so that robust mitigation against PUEA and SSDF is made. Computer simulation outputs show that OS-LNCC method performs better than the conventional methods using metrics such as sensing delay by 47%, percentage of error in prediction by 46% and throughput by 45%.

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Cross‐layer perspective for channel assignment in cognitive radio networks: A survey

Cited by 13 publications

References 145 publications

Energy Aware Channel Allocation with Spectrum Sensing in Pilot Contamination Analysis for Cognitive Radio Networks

Energy Aware Channel Allocation with Spectrum Sensing in Pilot Contamination Analysis for Cognitive Radio Networks

A Novel Self-Forming Virtual Sub-Nets Based Cross-Layer MAC Protocol for Multihop Tactical Network

Optimised Levenshtein centroid cross‐layer defence for multi‐hop cognitive radio networks

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