Cognitive Radio Ad Hoc Networks Research Articles

Cooperative Sensing Assisted Cross layer QoS Assured Routing in Cognitive Radio Adhoc Networks: Ensuring Security and Privacy

Cooperative Sensing Assisted Cross layer QoS Assured Routing in Cognitive Radio Adhoc Networks: Ensuring Security and Privacy

Optimizing Multichannel Path Scheduling in Cognitive Radio Ad Hoc Networks using Differential Evolution

One important area of study in cognitive radio ad hoc networks is multi-channel path scheduling. Cognitive radio networks have trouble communicating and using the spectrum effectively because of weather and dispersion. Optimizing multichannel path scheduling enhances network performance and reliability in a cognitive radio ad hoc net. The Optimizing Multichannel Path Scheduling (OMPS) model methodically tackles various scheduling problems. For the OMPS model, this domain is new. It effectively resolves multichannel path scheduling. The computer method used in the study is called Differential Evolution. During optimization, several factors are carefully considered, including Channel Fade Margin, Cross-Correlation and Coherence Time, Spectral Efficiency, Interference Level, Power Consumption, Retransmission Rate, Access Probability, and Propagation Delay. To increase the scheduling efficiency of the DE algorithm, many steps are meticulously planned: initialization, mutation, crossover, fitness evaluation, selection for iteration evolution, and termination. Latency, Packet Delivery Ratio (PDR), Spectrum Utilization, Interference Level, Energy Efficiency, and Established Path Success Rate are all assessed by the OMPS model. These indicators assess the effectiveness and dependability of the network. OMPS performs better in crucial simulations than the existing model. The demonstration demonstrates decreased latency for real-time applications, greater packet delivery ratios (PDRs), improved spectrum efficiency, channel interference, energy efficiency, and connection formation odds, as well as increased throughput that enhances network resource utilization. To do this, a variety of multichannel path scheduling situations are simulated.

Centralized multicasting AODV routing protocol optimized for intermittent cognitive radio ad hoc networks

The advancement of wireless technology is affected by Spectrum scarcity and the overcrowding of free spectrum. Cognitive Radio Ad Hoc Networks (CRAHNs) have emerged as a possible solution to both the scarcity and overcrowding challenges of the spectrum. The CRAHNs ensure that the Secondary Users (SUs) do co-exist with Primary Users (PUs) in a non-interfering manner. The SUs access the licensed spectrum opportunistically when they are idle. CRAHNs have many use cases which include intermittent networks here referred to as intermittent CRAHNs (ICRAHNs). For example, the Military (MCRAHNs). MCRAHN is complex and characterized by a dynamic topology which is subject to frequent partitioning and route breakages due to attacks and destruction in combat. This study optimizes the routing protocols for intermittent networks such as the MCRAHNs. ICRAHN routing is a challenge due to the network’s intermittent attribute, which is subject to destruction in the case of MCRAHN which is characterized by frequent link breakages. To better understand the routing in this network scenario, this paper presents two analytic models for the AODV and MAODV protocols based on queuing theory. The analytic models simulate unicast and multicast AODV in terms of factors such as queuing delay, throughput, and network scalability. Numerical analysis shows that MAODV outperforms AODV. Furthermore, the suggested routing protocols' performance was tested using network simulations utilizing the following metrics: throughput, Routing Path delay, Node Relay delay, and Spectrum Mobility delay. The simulation findings suggest that the MAODV protocol outperforms the AODV protocol.

Spectrum Sensing and SINR Estimation in IEEE 802.11s Cognitive Radio Ad Hoc Networks with Heterogeneous Interference

Spectrum Sensing and SINR Estimation in IEEE 802.11s Cognitive Radio Ad Hoc Networks with Heterogeneous Interference

BSMACRN: Design of an Efficient Blockchain-Based Security Model for Improving Attack-Resilience of Cognitive Radio Ad-hoc Networks

BSMACRN: Design of an Efficient Blockchain-Based Security Model for Improving Attack-Resilience of Cognitive Radio Ad-hoc Networks

Spectrum-Aware Transitive On-Demand Routing Protocol for Military Cognitive Radio Ad Hoc Networks

The advancement of wireless technology is increasing the demand for scarce spectrum. Cognitive radio ad hoc networks (CRAHNs) were proposed as a solution to spectrum scarcity which is also deployed in combat. However, military cognitive radio ad-hoc networks (MCRAHNs) are subject to destruction and frequent link breakages. The challenge with MCRAHNs routing is the timing-out of packets. This paper proposes the spectrum-aware transitive multi-cast on-demand distance vector (SAT-MAODV), optimised for throughput and delay. The relay nodes are selected based on zonal data and mobility. This is achieved through handshaking and sharing of location data. The nodes are expected to store location data of nodes encountered, which is used in routing and in determining the movement of the node. The mobility of military nodes is organised and structured, which simplifies routing. The SAT-MAODV was evaluated in network simulator 2 and the results show that the scheme is effective. UsingSAT-MAODV instead of xWCETT reduced routing path and node relay delay by at least 65% and 13% respectively, and increased achievable throughput by 31%. It also improved the delivery ratio by 9% while reducing latency by 27% in comparison with MARSA.

Spectrum Sensing based Trust Aware Routing for Cognitive Radio Ad hoc Networks (CRAHNs)

Spectrum Sensing based Trust Aware Routing for Cognitive Radio Ad hoc Networks (CRAHNs)

Primary user supported routing protocol for cognitive radio ad hoc networks in search of higher throughput

SummaryA routing protocol for cognitive radio ad hoc networks (CRAHNs), namely, primary user supported routing (PSR) is demonstrated in this research. Unlike existing routing protocols for CRAHN, where routing of cognitive users (CUs) is accomplished within CUs, in this proposed protocol, some of the primary users (PUs) support CUs to communicate, by forwarding CU packets. This service provided by PU is of voluntary nature. However, such assistance shall be provided by the PUs, only when they are idle, thereby, preserving the principles of cognitive radio networks (CRNs), which indicates that the operation of PU should not be disturbed by the CU activities. The proposed work is compared with cognitive ad hoc on‐demand distance vector (CAODV) protocol. The performance parameters considered are routing overhead, rate of loss of packets, and e2e packet delay. PSR outperforms CAODV in all these performance parameters. There has been on average 26.25% improvement in routing overhead, 34.12% decrease in loss, and 27.01% improvement in e2e delivery in the proposed PSR.

Optimized MAC Protocol Using Fuzzy-Based Framework for Cognitive Radio AdHoc Networks

Cognitive radio networks (CRNs) have been widely used in various applications for effective radio spectrum utilization in recent years. It is essential to fend off the growing demand for this finite natural resource for next-generation communications. In CRNs, detecting the activity of the primary user requires opportunistic spectrum sensing for efficient usage of the available radio spectrum, which is a limited and exquisite resource. Thus, CRNs are the key component in solving the spectrum scarcity issue in the presence of primary user bands through secondary users. Cognitive radio AdHoc networks (CRAHNs) are a unique kind of CRNs where infrastructures less cognitive radio (CR) nodes are furnished. In CRAHN, the CR-MAC protocol works slightly differently from the traditional wireless network MAC protocols. Particularly, the proposed method includes a high traffic scenario under contention-based IEEE 802.11 DCF MAC protocol. Accordingly, it can be observed that both, throughput and delay, increase as the CW size and packet length of the 802.11 (DCF) MAC protocol for CRAHN varies. Therefore, this paper proposed a fuzzy-based optimization framework for the 802.11 (DCF) MAC protocol in CRAHNs. Furthermore, it optimized throughput and delay by training a database of input parameters, contention window, and packet length for the Mamdani and Sugeno fuzzy inference system (FIS) models of the 802.11 (DCF) protocol simultaneously. The experimental result of the proposed framework for CRAHN with FIS shows that altering the contention window increases throughput by 25% and reduces the delay by 38% compared to the IEEE802.11 (DCF) protocol for CRAHNs without FIS. Moreover, it is also revealed that the throughput is increased by and 7% and the delay is reduced by 40% to 50% due to altering the packet length.

Effect of Noise Uncertainty during Spectrum Sensing for Cognitive Radio Ad-hoc Networks

Effect of Noise Uncertainty during Spectrum Sensing for Cognitive Radio Ad-hoc Networks

ENHANCED HYBRID COGNITIVE RADIO AD HOC NETWORKS (CRAHNs) FOR MOBILE NETWORK

In sensor networks, a very crucial aspect of the maintenance of the communications of secure data is the data, which is the most difficult of all tasks. The sensor network consists of hierarchical elements like the Base Station (BS), the Cluster Head (CH) and the Sensor Nodes (SNs), and this will have three different keys, which are the public and private, the cluster and the master keys. Through the opportunistic use of the currently available wireless spectrum, cognitive radio (CR) technology is intended to address the issues in wireless networks brought on by the limited amount of range accessible and the inefficient use of spectrum. With the inherent capabilities of cognitive radio, CR networks will offer the most advanced spectrum-aware communication paradigm in wireless communications. However, the significant spectral fluctuation and various quality-of-service (QoS) requirements faced by CR networks provide unique difficulties. The distributed multihop design, the dynamic network topology, and the time- and location-varying spectrum availability are essential differentiating elements in cognitive radio ad hoc networks (CRAHNs).

Energy Aware Multipath Routing Protocol for Cognitive Radio Ad Hoc Networks

Cognitive radio networks (CRNs) emerged as a paradigm to solve the problem of limited spectrum availability and the spectrum underutilization in wireless networks by opportunistically exploiting portions of the spectrum temporarily vacated by licensed primary users (PUs). Routing in CRNs is a challenging problem due to the PU activities and mobility. On the other hand, energy aware routing is very important in energy-constraint CRNs. In addition, it is crucial that CR users efficiently exchange data with each other before the appearance of PUs. To design a robust routing scheme for mobile CR ad hoc networks (CRANs), the constraints on residual energy of each CR user, reliability, and the protection of PUs must additionally be taken into account. Moreover, multipath routing has great potential for improving the end-to-end performance of ad hoc networks. Considering all these evidences, in this paper, we propose an energy aware on-demand multipath routing (EOMR) protocol for mobile CRANs to ensure the robustness and to improve the throughput. The proposed routing scheme involves energy efficient multipath route selection and spectrum allocation jointly. The simulation results show that our approach improves the overall performance of the network.

Performance Analysis of Typical Routing Protocols for Cognitive Radio Ad Hoc Networks

Cognitive Radio Ad Hoc Networks (CRAHNs) have powerful growth potential, a solution to solve the scarce spectrum resources problem. Due characteristics can change configuration parameters during transmission, thereby opening up the possibility to use the dynamic spectrum. This leads to the complexity of the design of routing protocols. In this paper, we present the routing protocol is proposed to apply for Cognitive Radio Ad hoc Networks. After explaining the principle of operation, we analyze and evaluate the performance of the protocol on NS2. Simulation results show that the protocol End-to-End with throughput and latency is best improved. Finally, we discuss the limitations of recently routing protocols and propose some further research directions.

A Survey of Game Theoretical Approach in Cognitive Radio Network and 5G-6G Communications

The development of telecommunications, especially wireless communication, requires data transmission at high speed and wide bandwidth to support 5G-6G communication services. For this reason, it is necessary to have a network with adaptive capabilities in managing and improving performance parameters independently through an intelligent radio network system or better known as Cognitive Radio Network (CRN). The use of CRN in several implementations such as Cognitive Radio Ad Hoc Network (CRAHN), Cognitive Radio Vehicular Ad Hoc Networks (CR-VANET), Intelligent CRN and even 6G-CRN has also been widely used. Another method that is also used to optimize system performance independently is through the Game Theory (GT) approach. Game theory can be implemented on CRN as well as on 5G-6G communications. The use of GT in the CRN system provides improvements in terms of increasing system performance such as reducing interference and bit error rate (BER), increasing throughput and Signal to Interference plus Noise Ratio (SINR), power efficiency, increasing utility and resource capacity and being able to achieve convergence or reach the Nash equilibrium state more rapidly. Meanwhile, the use of GT in 5G-6G communication and other technologies are related to the power control, resource allocation, spectrum sharing, channel estimation, channel selection and Quality of Service (QoS) or Quality of Experience (QoE). In general, the use of GT can help to improve the overall performance of a system.

Hybrid strategy for reliable packet transfer and packet loss reduction in cognitive radio Ad-Hoc Network

Hybrid strategy for reliable packet transfer and packet loss reduction in cognitive radio Ad-Hoc Network

Intelligent Fish Swarm Inspired Protocol (IFSIP) For Dynamic Ideal Routing in Cognitive Radio Ad-Hoc Networks

Intelligent Fish Swarm Inspired Protocol (IFSIP) For Dynamic Ideal Routing in Cognitive Radio Ad-Hoc Networks

Active Rendezvous Broadcast Algorithm Based on Channel Weight in Cognitive Radio Ad Hoc Networks

Active Rendezvous Broadcast Algorithm Based on Channel Weight in Cognitive Radio Ad Hoc Networks

CCH: a clique based asymmetric rendezvous scheme for cognitive radio ad-hoc networks

Rendezvous (RDV) in cognitive radio ad-hoc networks (CRAHNs) is one of the key ways for a pair of unknown cognitive radio users to initiate communications. CRAHN is a multi-channel environment where channel status changes over time depending on primary users’ (PUs) activities. Thus, achieving RDV in CRAHNs cannot be guaranteed on a predetermined common control channel (CCC). However, CCC results channel saturation, extreme transmission overhead of control information, and a point of vulnerability. To address this problem, channel hopping (CH) protocols have proposed for enabling RDV. This research presents a CH protocol based on clique system, called clique based channel hopping (CCH) for the purpose of RDV establishment. The proposed CCH is a role based blind RDV CH system where sender and receiver generates CH sequence based on h-clique and v-clique respectively. The CCH employs channel-ranking information for allocating more slots to high-rank channels than low-rank ones. The system dynamically updates the CH sequence by replacing channels from both the licensed and unlicensed bands to protect intermittent PUs. The CCH protocol satisfies the following requirements: (1) guaranteed RDV; (2) no synchronisation; and (3) symmetric and asymmetric channel model. Simulation results show that the proposed CCH scheme outperforms similar CH schemes in terms of average time-to-rendezvous and the degree of overlap in both symmetric and asymmetric channel scenario.

A Model to Improve the Effectiveness and Energy Consumption to Address the Routing Problem for Cognitive Radio Ad Hoc Networks by Utilizing an Optimized Cuckoo Search Algorithm

A cognitive radio ad hoc network (CRAHN) is a mobile network that can communicate without any form of centralized infrastructure. The nodes can learn about the environment and make routing decisions. Furthermore, distributed computing, spectrum mobility, and the Internet of Things have created large data sets, which require more spectrum for data transmission. Unfortunately, the spectrum is a scarce resource that underutilized by licensed users, while unlicensed users are overcrowding the free spectrum. The CRAHNs technology has emerged as a promising solution to the underutilization of the spectrum. The focus of this study is to improve the effectiveness and energy consumption of routing in order to address the routing problem of CRAHNs through the implementation of the optimized cuckoo search algorithm. In CRAHNs, the node and spectrum mobility cause some frequent link breakages within the network, which degrades the performance of the routing protocols. This requires a routing solution to this routing problem. The proposed scheme was implemented in NS2 installed in Linux operating system, with a cognitive radio cognitive network (CRCN) patch. From the experimental results, we observed that the proposed OCS-AODV scheme outperformed CS-DSDV and ACO-AODV schemes. It obtained at least 3.87% packet delivery ratio and 2.56% and lower packets lost. The scheme enabled the mobile nodes to adjust accordingly to minimize energy consumption. If not busy, they switch to an idle state to save battery power.

Joint resource allocation and routing optimization for spectrum aggregation based CRAHNs

As an integration of spectrum aggregation (SA) and cognitive radio Ad Hoc networks (CRAHNs), SA-enabled CRAHNs are capable of utilizing non-continuous spectrum components and is promising in improving the network performance. However, existing research on CRAHNs mainly assuming of an ideal spectrum sensing while ignoring the false alarm probability, resulting in an inaccurate capacity characterization. Hence, in this paper, we propose a more accurate capacity characterization while the detection and false alarm probability are considered. Moreover, we propose the joint optimization model for SA-enabled CRAHNs constrained by QoS requirements of primary users and network resource allocation. We propose the prim-dual method to decompose this problem into two sub-problems: a physical (PHY) layer sub-problem on CC assignment and power allocation, and a network layer sub-problem on route selection. Besides, these two sub-problems are coupled on the link capacity constraint. For sub-problem at PHY layer, we propose the genetic algorithm to obtain the optimal CC assignment and successive convex approximation method to the find the optimal power allocation. For sub-problem at network layer, we propose to apply the standard convex method to find the optimal solution. The numerical simulations demonstrate that network throughput can be improved by increasing the number of CCs. The obtained network throughput outperforms algorithms that without power control, spectrum aggregation or route optimization.