Cross layer optimization for outage minimizing routing in cognitive radio ad hoc networks with primary users’ outage protection

Basak, Surajit; Acharya, Tamaghna

doi:10.1016/j.jnca.2017.09.004

Cited by 7 publications

(4 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Energy Consumption [6] problem was studied under the constraint of probabilistic interference to primary receivers and proposed a centralized solution for optimal spectrum assignment cum route selection. But the proposed method didn't meet the optimum level of energy consumption.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance Modeling of Bio-Inspired Routing Protocols in Cognitive Radio Ad Hoc Network to Reduce End-to-End Delay

Jaganathan¹,

Vadivel²

2019

IJIES

View full text Add to dashboard Cite

The rapid advancement of Cognitive Radio Ad Hoc Network (CRAHN) has created a demand for effectively utilizing the spectrum without affecting the environment. End-to-end delay in CRAHN affects the performance in numerous ways. The major task of routing protocols is to transfer the data to the destination in a shorter duration by utilizing low energy. Congestion in the network leads a way to end-to-end delay and exhaustive energy consumption, but optimization can be used to control it. This research work aims to propose a bio-inspired routing protocol inspired from characteristics from wolves to reduce the overall end-to-end delay which results in reducing the consumption of energy and extends the lifetime of the network. This research work utilizes M/G/1 queueing model to avoid network congestion, where the requests from nodes are markovian and service times regarding the requests have general distribution time. With benchmark performance metrics NS2 simulations are carried out to check the performance of the proposed protocols. Results conclude that the proposed protocol significantly outperforms than other protocols with better packet delivery ratio, reduced end-to-end latency and energy consumption.CRAHNs are autonomous networks enabled with CR technology, where it does not need the support of base stations or any other infrastructure based support [3]. Devices used in CRAHN are based on the battery that they hold. The present technologies used in the battery will make it work for a long period of time with the tolerable energy, even when it is charged for a shorter duration. One of the very important issues of CRAHN is the conservation of energy because the batteries hold the limited capacity of energy. The nodes of CRAHN get dead when the battery life gets complete. The two things that determine the duration of nodes are conservation of energy and battery life.There exist two kinds of users in CRAHN, which are Primary User (PU) and Secondary User (SU). PU's are authorized to access the network at an associate degree level because they hold the license. Normally these users are given the maximum preference to use the spectrum and are liable to assured quality-of-service (QoS). SU's are authorized to access the network but not in an associate degree level as like the PU. Preferences are not given much to these users and QoS are also not maintained as like PU. Primitive concept of CR network is to move out the SU (which don't have any license) from the network when PU (which has a license) is spotted [3]. The opportunity of using the CRAHN is unstable for the SU with time and location, due to the importance is given to PU. In this manner, routing of data packets in CRAHNs requires cooperation between its module and functionality of spectrum management for continuous aware of the physical environment to make more accurate decisions [4,5]. Exhaustive usage of spectrum by PU will give way for routing problem in CRAHNs. For this reason, it's always necessary to design a routing protocol that will effectively alloca...

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Performance Modeling of Bio-Inspired Routing Protocols in Cognitive Radio Ad Hoc Network to Reduce End-to-End Delay

Jaganathan¹,

Vadivel²

2019

IJIES

View full text Add to dashboard Cite

show abstract

“…In Table 2, the principal aspects considered in two main categories (i.e., PU's activities and to PU's protections) are concluded together, to present and to classify the existing works and methods towards PU's design. [15], [27], [32]- [33] Transmission Power [3], [22], [26], [34] PU interference [28], [29], [34] PU's protections Detection Constraint [35]- [39] Collision Avoidance [32], [40]- [41] Traffic Load [42]- [44] QoS Provisioning [18], [45]- [47] [10], [35]- [37], [48] mainly apply a lower bound of detection probability to guarantee the accuracy of detection, and consider other targets (e.g. EE, throughput, PU's spectrum utilization, etc.)…”

Section: Performance Metrics Pu Protection and Sinr Targetsmentioning

confidence: 99%

“…The environment of spectrum sharing between these two layers of users is becoming a comprehensive target. For example, according to [31], [47], [73], [99]- [100], [101], novel schemes propose the operations on the upper layer to solve the multiple-PUs-multiple-SUs spectrum sensing issue which is more complicated than single-PU case.…”

Section: Current Challenge and Future Workmentioning

confidence: 99%

A Survey of EE Optimization Methods for Primary and Secondary Users in Cognitive Radio Networks

Tian¹,

Esseghir²,

Khoukhi³

2019

NPA

View full text Add to dashboard Cite

A large scale of spectrum sensing techniques are proposed to improve the use of spectrum resources. However, the EE (energy efficiency) should be guaranteed for both primary and secondary users, especially under various detection performance constraints. In this regard, the linking between activities of PU (primary user) and dynamic access behaviors of SUs (secondary users) should be considered in an integrated way. This survey has compared different existing scenarios and frameworks on EE optimizations. The principal objective is to enhance the system throughput and to coordinate on the physical layer of both PU and SUs, in order to enable a high-quality spectrum detection and a more efficient spectrum access. In the technical part, several optimization methods are introduced under PU’s constraints, and different methods based on game theory are applied to suitable cooperative sensing scenarios for SUs’ optimal access. Finally, the complexity of algorithms is compared, to further reduce the execution time and deploy real-time adaptation for users with lower delay.

show abstract

“…In Basak and Acharya, the authors study the routing issue by considering the probabilistic interference to primary receivers. This is formulated as a joint transmit power control, spectrum assignment, and routing problem in CRAHNs.…”

Section: Related Workmentioning

confidence: 99%

Joint load balanced stable routing and communication segment assignment in mobile cognitive radio ad‐hoc networks

Amiri-Doomari

Mirjalily

Abouei

2018

Int J Communication

View full text Add to dashboard Cite

Summary The fundamental issues in mobile cognitive radio ad‐hoc networks are the selection of the optimal stable paths between nodes and proper assignment of the frequency channels/time slots (communication segments) to the links. In this paper, a joint load balanced stable routing and communication segment assignment algorithm is proposed that considers jointly the mobility prediction, mitigating the co‐channel interference and energy consumption. The novelty of the proposed algorithm lies in the increasing of the path stability, which benefits from the maximum link lifetime parameter and introduced weighting function to keep routes away from the PU's region. This avoids the negative impacts on the PUs' operations and decreases the conflict of the cognitive nodes. In the proposed algorithm, the concept of load balancing is considered that yields in the balancing energy consumption in the network, improving the network performance and distributing traffic loads on all available channels. The effectiveness of the proposed algorithm is verified by evaluating the aggregate interference energy, average end‐to‐end delay, goodput, and the energy usage per packet under 6 scenarios. The results show that the performance of the proposed algorithm is significantly better than the recently proposed joint stable routing and channel assignment protocol.

show abstract

Cross layer optimization for outage minimizing routing in cognitive radio ad hoc networks with primary users’ outage protection

Cited by 7 publications

References 38 publications

Performance Modeling of Bio-Inspired Routing Protocols in Cognitive Radio Ad Hoc Network to Reduce End-to-End Delay

Performance Modeling of Bio-Inspired Routing Protocols in Cognitive Radio Ad Hoc Network to Reduce End-to-End Delay

A Survey of EE Optimization Methods for Primary and Secondary Users in Cognitive Radio Networks

Joint load balanced stable routing and communication segment assignment in mobile cognitive radio ad‐hoc networks

Contact Info

Product

Resources

About