Multi-hop Cognitive Radio Networks Research Articles

Secure transmission performance analysis of multi-hop cognitive relay radio networks with energy harvesting and artificial noise aided

Secure transmission performance analysis of multi-hop cognitive relay radio networks with energy harvesting and artificial noise aided

Tree-based Multicast Routing and Channel Assignment for Enhanced Throughout in Emerging Cognitive Radio Networks

In future multi-hop wireless networks like 5G and B5G, efficient large-scale video sharing and data dissemination are expected to rely heavily on multicast routing and Cognitive Radio (CR) technology. While multicast routing is efficient when the network always has access to the spectrum, the dynamic nature of Primary User (PU) activities, heterogeneous spectrum across the CR Network (CRN), and PU access priority make it challenging to implement efficient multicast routing protocols in CRNs. This paper proposes a hierarchical multicast routing mechanism for multi-hop CRNs that exploits the Shortest Path Tree (SPT) and Minimum Spanning Tree (MST) concepts. The proposed multicast routing mechanism consists of tree construction and channel assignment algorithms. The tree-construction algorithm models the network topology as a multicast tree rooted at the CR source and spanning all the CR nodes. Based on the constructed tree, the channel assignment algorithm employs the Probability Of Success (POS) metric to assign channels to the various layers defined by the constructed SPT or MST, ensuring that the most reliable channel is used for the multi-hop multicast transmissions. Simulation experiments are conducted to evaluate the mechanism’s effectiveness, revealing significant improvements in throughput and Packet Delivery Rate (PDR) compared to state-of-the-art protocols under different network conditions. The simulations also show that the SPT-based mechanism outperforms the MST-based mechanism in terms of throughput but has a higher tree construction complexity.

An Energy Balance-Oriented Clustering Routing Protocol for Cognitive Radio Sensor Networks

Uneven clustering is an effective solution to solve the energy hole problem in multihop cognitive radio sensor networks (CRSNs). However, current literature leaves control overhead and multihop intercluster routing out of consideration and adopts constant weight coefficients for cluster radius calculation instead of reasonably setting their values according to specific network configurations. To solve the above problems, a distributed energy balance-oriented uneven clustering routing protocol (EBUCRP) is proposed in this article. First, by fully considering the energy consumption of control information exchange and data transmission, EBUCRP theoretically derives the optimal cluster radius of each unit within which distributed clusters are formed. Second, communication capability-based selection criteria are defined from joint energy and spectral efficiency perspectives to help select high-quality cluster heads and next-hop relays. In this case, the monitoring information can be transferred to the sink through efficient intracluster data aggregation and intercluster multihop forwarding. Third, EBUCRP strictly restricts the energy consumption of control information exchange during network operation. Simulation results show that EBUCRP gains obvious advantages over competing protocols in enhancing the lifetime and supervision capability of both single-hop and multihop CRSNs.

A weighted energy consumption minimization-based multi-hop uneven clustering routing protocol for cognitive radio sensor networks

Aiming at solving the effective data delivery and energy hole problem in multi-hop cognitive radio sensor networks (CRSNs), a weighted energy consumption minimization-based uneven clustering (ECMUC) routing protocol is proposed in this paper. For the first time, the impact of control overhead on the network performance is taken into consideration, to be specific, the energy consumption of control overhead is integrated with that of data communication to model the network energy consumption. Through effective transformation and theoretical analysis, cluster radius of each ring is derived by minimizing the network energy consumption and balancing the residual energy among nodes in different rings. Distributed cluster heads (CHs) selection and cluster formation are carried out within this range to control the cluster size and the corresponding energy cost. Expected times for being CHs metric is defined to measure nodes’ energy and spectral potential and help select powerful CHs. Simulation results show that ECMUC protocol is superior to most clustering protocols designed for CRSNs in terms of network surveillance capability and network lifetime, and it is also demonstrated that taking control overhead into consideration is beneficial for improving the network performance.

Optimization-based spectrum sensing in crn for effective utilization of available channel

Cognitive radio networks (CRN) are subjected to the challenge of demand in available resources, limited fair resource allocation between users in the heterogeneous CRN. The availability of minimal resources affects the channel allocation between Primary Users (PUs) and Secondary Users (SUs). In heterogeneous CRNs, efficient resources are available to SUs with fair resource allocation in a multi-hop environment. This paper proposed an efficient resource allocation in multi-hop CRN through Monte-Carlo Normal Form (MCNF). The proposed MCNF is involved in the optimization of the available resources through the estimation of the objective function. With Monte-Carlo estimation, MCNF computes the optimal resource availability within the CRN. Based on the Normal Form game theory resource availability of the network is computed and allocated between the users. The performance of the proposed MCNF is computed in terms of throughput, PDR, and running time. The proposed MCNF is comparatively examined with conventional game theory and the Monte-Carlo technique. The simulation analysis of the proposed MCNF expressed that running time is reduced with increased Packet delivery rate (PDR) and throughput.

Full-duplex routing with low-complexity sequential-decision for throughput enhancement in dynamic access networks

Integrating the Full-Duplex (FD) communication technology in multi-hop Cognitive Radio Networks (CRNs) can significantly enhance routing decisions such that overall network performance is improved. Unfortunately, when employing the FD technology in multi-hop routing, the channel assignment becomes very challenging due to the possible simultaneous transmissions/reception. Hence, careful low-complexity channel assignment over the various hops along a path is needed to avoid hop-to-hop interference and enhance network performance. In this paper, we propose a low-complexity sequential-decision routing protocol, referred to as Sequential FD (SFD)-aware protocol. The SFD protocol identifies a set of possible routes between any source–destination communicating pair. For each discovered route, SFD successively assigns channels for each hop along the router such that the maximum route capacity is achieved. Then, SFD selects the routes with the highest capacity. Unlike most of existing FD-CRN channel assignment/routing protocols, which require optimization procedures with NP-hard time complexity with the number of channels and hops, the time-complexity of the proposed SFD protocol is polynomial. Compared to the optimal FD-aware routing (obtained using the brute-force search method) and maximum per-hop rate FD-unaware routing protocols, the simulation results confirm the effectiveness of our proposed protocol and its superiority over the existing FD-unaware baseline routing protocol in terms of the end-to-end network throughput. The results also confirm that the SFD protocol provides solutions within 5% of the optimal ones.

Performance of a multihop cognitive radio network with diversity under imperfect CSI

ABSTRACT This paper analyses the outage performance of a multihop relay-based cognitive radio network under imperfect channel state information. A backoff power control scheme is applied to ensure both the quality of service (QoS) and interference constraints of the primary network. To reduce the interference at the primary network, we have proposed a new multihop transmission method where a relay node forwards the signal to the next relay node only when the signal is decoded successfully and QoS of the primary network is satisfied. Unlike the conventional relay transmission scheme, in our system model, a relay node receives signals not only from the previous node but also from the previous-to-previous node. The selection combining (SC) and maximum ratio combining (MRC) diversity schemes are applied to enhance the outage performance of the secondary network. The Monte Carlo simulation is adopted to validate the analysis. It is observed from the simulation results that the outage probability of the secondary network and interference probability of the primary network are impacted by the correlation coefficient between real and estimated channels, the number of hops and the backoff power coefficient.

Cross Layer QoS Aware Scheduling based on Loss-Based Proportional Fairness with Multihop CRN

As huge users are involved, there is a difficulty in spectrum allocation and scheduling in Cognitive Radio Networks (CRNs). Collision increases when there is no allocation of spectrum and these results in huge drop rate and network performance degradation. To solve these problems and allocate appropriate spectrum, a novel method is introduced termed as Quality of Service (QoS) Improvement Proper Scheduling (QIPS). The major contribution of the work is to design a new cross layer QoS Aware Scheduling based on Loss-based Proportional Fairness with Multihop (QoSAS-LBPFM). In Medium Access Control (MAC) multi-channel network environment mobile nodes practice concurrent broadcast between several channels. Acquiring the advantage of introduced cross layer design, the real-time channel conditions offered by Cognitive Radio (CR) function allows adaptive sub channel choice for every broadcast. To optimize the resources of network, the LBPFM adaptively plans the radio resources for allocating to diverse services without lessening the quality of service. Results obtained from simulation proved that QoSAS-LBPFM provides enhanced QoS guaranteed performance against other existing QIPS algorithm.

Effective cooperative spectrum sensing using deep recurrent reinforced learning‐based Q‐routing in multihop cognitive radio networks

SummaryCognitive radio network (CRN) is a promising technology that mitigates the scarcity of spectrum. The main challenge faced in the opportunistic CRN is the spectrum sensing (SS). The traditional methods of SS use detectors to find the available bands, which appear to provide unreliable performance in the case of actual environment where noise is predominant. Literature has proved that employing an artificial intelligence (AI) model for routing overcomes the lack of network knowledge and lack of human intervention and helps to learn robust patterns. Reinforced learning (RL) is a dynamically learning process that selects the actions based on continuous feedback received from the dynamic environment to maximize the reward. Deep reinforcement learning (DRL) models have proven to be successful at learning control policies image inputs. However, they struggle with learning policies that require longer term information. Recurrent neural network (RNN) architectures have been used in tasks dealing with longer term dependencies between data points. Motivated by the performance of AI models, these architectures are investigated in this work to overcome the difficulties arising from learning policies with long‐term dependencies. Thus, a deep recurrent reinforced learning‐based Q‐routing (DRRL‐based Q‐routing) is developed. The proposed study suggests a multihop CRN operated in an interweave mode. This algorithm finds optimal routing path between the secondary user transmitter (SUT) and the secondary user destination (SUD), optimal SS duration, and individual secondary user (SU) power requirements for SS and data transmission process while minimizing the end‐to‐end outage under the constraints of energy causality, SS reliability, interference threshold, and individual link throughput.

Genetic algorithm optimized fuzzy decision system for efficient data transmission with deafness avoidance in multihop cognitive radio networks

Genetic algorithm optimized fuzzy decision system for efficient data transmission with deafness avoidance in multihop cognitive radio networks

Effective peer-to-peer routing in heterogeneous half-duplex and full-duplex multi-hop cognitive radio networks

Effective peer-to-peer routing in heterogeneous half-duplex and full-duplex multi-hop cognitive radio networks

Energy harvesting with adaptive transmit power for multi-antenna multihop cognitive radio networks

This paper optimizes the throughput of cooperative cognitive radio networks (CRN). There are multiple branches and multiple hops. Transmission is performed on the branch with the highest signal to interference plus noise ratio (SINR). Secondary source and relays have multiple receiving antennas to harvest energy from radio frequency (RF) signal received from primary transmitter PT. These secondary nodes have multiple transmitting antennas and transmission is performed from the best antenna. Also, secondary source and relays adapt their power to generate interference at Primary Receiver PR less than a given threshold I. We optimize harvesting duration to enhance the throughput in the secondary network.

Link‐delay and spectrum‐availability aware routing in cognitive sensor networks

This study designs and presents routing protocols multi-channel, multi-hop cognitive radio sensor network (CRSN), which are based on spectrum sensing, spectrum-availability analysis and per-hop delay analysis. In order to cope with the spectrum dynamics in the CRSNs, a framework is proposed to estimate the remaining duration of spectrum availability which is based on the expected idle length of channels, sensing period and communication history on the channel. Such methodology allows cognitive users to mitigate communication interruptions caused by arrivals of primary users, thus to improve the transmission performance over each hop. In particular, in combination with the per-hop delay analysis, the routing paths from sources to the sink can be established such as they provide the shortest delay opportunistically or shorter delay but reliable communication along the selected paths. Extensive simulation results show that the proposed routing algorithms potentially improve the network performances in terms of throughput, delay and energy consumption.

Quantifying the Impact of Time-Sharing on Route Capacity in Cognitive Radio Networks With Full-Duplex Capability

Recent advances in full-duplex (FD) communications along with the introduction of the concept of device-to-device communications have challenged the applicability of traditional routing and scheduling schemes in multi-hop cognitive radio networks (CRNs). In this letter, we derived a close-form expression to quantify the impact of time-sharing of a given channel assignment along a given path on network performance. Based on the derived expression, we mathematically model the channel-assignment problem that minimizes the number of time-shared hops along a given path as a binary-quadratic optimization problem (BQP). Then, we transfer the BQP into a binary linear programming problem (BLP), which is sub-optimally solvable using a polynomial-time sequential fixing method. Simulation results indicate that routing with assignment that minimizes the needed number of time-shared transmissions along a path can provide significant improvement in network throughput.

Adaptive Bitrate Video Transmission Over Cognitive Radio Networks Using Cross Layer Routing Approach

Due to the recent developments in the wireless mesh and ad-hoc networks, multi-hop cognitive radio networks (MCRNs) have attained the significant attention towards providing the reliable multimedia communications. However, in reliable multimedia communications each multimedia application observed a very stringent quality-of-service (QoS) requirements. Moreover, in MCRNs, channel allocated to the multimedia secondary users (MSUs) can be re-occupied by the primary users (PUs) at any time which causes the end-to-end path discontinuity that severely affect the performance of the MCRNs. Therefore, under the dynamic channel availability, selecting an end-to-end path that is not only stable but also fulfills the QoS requirements of the real time and multimedia (RM) applications is a challenging task and still an open research problem. Hence, in this paper, we propose a cross-layer routing scheme that supports adaptive bit-rate multimedia (ABM) transmissions over MCRNs. Moreover, our path selection is based on the QoS-aware end-to-end path delay, and PU-activity aware end-to-end path stability metrices. Furthermore, to avoid the PU interference, continuity in transmission, efficient channel utilization, and supporting error resilience over time varying wireless channels our selected end-to-end path is periodically updated. Simulation study shows that the proposed scheme is more robust and suitable for supporting ABM over MCRNs.

On performance of multihop energy harvesting CRN in the presence of co-channel interferers

ABSTRACT In this paper, the performance of a multihop cognitive radio network is investigated in the presence of co-channel interference (CCI) which affects the primary receiver and secondary receiver nodes. A deterministic expression for the maximum allowable transmit power of the secondary nodes is derived based on the tolerable outage probability of the primary network. The system considers radio frequency energy harvesting at the secondary source and intermediate secondary nodes from the primary user transmitter as well as from the various CCIs present around the nodes. We analyse secondary outage probability and derive a closed-form analytical expression for secondary outage probability. We present the impact of PU-TX transmit power and efficiency of harvester circuit on the secondary outage probability. The optimum number of intermediate relays is indicated for several number of CCIs which minimises outage probability of secondary network.

Performance off cluster‐based multi‐hop underlay networks with energy harvesting nodes

In this paper, the authors consider an underlay multi-hop cognitive radio network with energy harvesting secondary nodes, where there is a cluster of secondary decode-and-forward relays in each hop. The secondary nodes have no separate energy source available with them, but wake up from idle mode to harvest energy from the primary signal with the time-switching protocol, and use it for transmitting/relaying using the peak interference constraint. In each cluster, a relay with maximum transmit power is selected except in the last one. In the last cluster, a relay which has a maximum signal-to-noise ratio (SNR) at the secondary destination is selected. Though the suggested scheme has low implementation complexity and requires very little channel estimation, its performance is close to that of a scheme in which the link with the best SNR is chosen in each hop (which requires a lot of channel estimation). Analytical expressions are derived for the end-to-end outage probability and throughput assuming Rayleigh faded channels. They show that it is important to optimise the time-switching parameter (fraction of time devoted to energy harvesting) and the number of hops. Simulations confirm the accuracy of the derived expressions.

Outage Analysis in Cognitive Radio Networks With Energy Harvesting and Q-Routing

The present work explores mitigation in end-to-end outage probability in an energy harvesting (EH) enabled cognitive radio networks (CRNs) through reinforcement learning (RL) based multi-hop Q-routing. The operation of CRN follows a frame structure that includes cooperative spectrum sensing (CSS), based on the decision of which, secondary transmit nodes either do EH from the primary user (PU) signal or make an opportunistic data transmission. In either operation, both PU reappearance and disappearance probabilities are considered in mathematical analysis. An optimization problem is formulated that minimizes the outage probability in the CRN under the constraints of primary user interference protection, individual secondary link throughput, and energy causality in EH. The closed-form expressions are derived to find the optimal values of sensing duration, secondary power allocation fraction on SS and data transmission. The present multi-hop CRN studies RL-based Q-routing in different network topologies and analyzes the worst-case runtime complexities. It is observed that the tree structure based network reduces the complexity of Q-routing over the other topologies and provides a significant gain on the outage. The present work improves the CRN outage performance by 11.01% and 39.89% over the existing techniques.

MCSAAR: Multi-Coefficient Spectrum Aware Based Shortest Anypath Routing in Multi-hop CRNs

Wireless communication technology has grown tremendously with an advancement of better communication quality. It depends on the available spectrum bands but due to increased demand, the spectrum scarcity has become a challenging issue. Recently dynamic spectrum management is proposed as a recommended solution by Federal Communication Commission (FCC) which can enhance the spectrum management. To overcome the identified problem, we look at Cognitive Capacity Harvesting network and develop a multi-hop cognitive radio network routing protocol. The proposed routing protocol Multi-Coefficient Spectrum Aware based shortest Anypath Routing in Multi-hop CRNs (MCSAAR) is designed based on the link quality, energy consumption and trust values for identifying the next-hop. The proposed approach performance is compared against existing anypath routing schemes. The obtained simulation result ensures better efficiency in terms of packet delivery ratio and end-to-end delay.

On Platform to Enable the Cognitive Radio Over 5G Networks

With the increase in the number of communication devices, the requirement for higher bandwidth is essential. To achieve this goal, research and industrial communities have both suggested that future wireless systems will take advantage of the numerous emerging technologies. Utilization of Cognitive Radio (CR) for the next-generation Fifth Generation (5G) communication technology is the major advancement for getting a higher bandwidth in a cellular communication network. In this paper, we present a comprehensive study of CR from the perspectives of spectrum allocation schemes, impact and role of MAC layer in spectrum sensing and sharing, CR application in multi-hop wireless networks, and challenges associated with channel selection and packet routing in multi-hop heterogeneous CR networks. This paper also presents the analysis, in literature, of a range of intelligent routing protocols that are considered viable for packets routing in CR networks. The need to address the issue of spectrum depletion and the apparent underutilization of available scarce spectrum resources in existing wireless networks is the primary motivation behind this study. Considering the fact that CR technology can potentially maximize the utilization of bulk of the unused communication spectrum bands for the future 5G of wireless network and beyond.