Cooperative Cognitive Radio Networks Research Articles

Secrecy outage probability analysis of energy‐aware relay selection for energy‐harvesting cooperative systems

The secrecy outage performance for a cooperative cognitive radio energy-harvesting network is analyzed. The cognitive network is composed of an energy-constrained cognitive source (CS), multiple energy-constrained cognitive relays (CRs) and a cognitive destination (CD) as well as an eavesdropper (E) coexists with a primary network consisting of a primary transmitter (PT) and a primary receiver (PR). The CS and CRs are equipped with energy harvesters for collecting energy from the radio frequency signal from PT and their transmit powers are limited by the interference threshold at PR. To prevent confidential information leaking to E, an optimal relay selection (ORS) scheme and a suboptimal relay selection (SRS) scheme are proposed. In ORS scheme, the whole channels state information (CSI) of wireless links is available to CRs while SRS only needs to know the CSI of main channels from CRs to CD. Moreover, the closed-form expressions of secrecy outage probabilities for both ORS and SRS schemes are derived. For the purpose of comparison, the classical round-robin relay selection (RRRS) is also analyzed in terms of secrecy outage probability. Furthermore, the numerical results show that ORS achieves the best performance and RRRS performs the worst in terms of secrecy outage probability.

A decision model for selecting best reliable relay queue for cooperative relaying in cooperative cognitive radio networks: the extent analysis based fuzzy AHP solution

Nowadays, the selection of relay in cooperation-based communication is a very demanding topic in research. The choice of the relay majorly depends on various criteria; hence, multiple criteria decision-making techniques are required to find out the best relay as relay-based transmission performs better than without relay transmission. Existing research has not considered the transmission failure of the relay node. In this paper, the authors also suggested a relay queue instead of a single BEST relay, which increases the network's efficiency for preventing unsuccessful transmission and guarantees relay-based connectivity without fail. In this paper, the authors have discussed different AHP based multiple criteria decision-making techniques to select reliable relay nodes as AHP based techniques require low latency time in decision making. Again, in this paper, authors have selected relays using extent analysis based fuzzy AHP technique over other AHP techniques as this technique not only registers the ambiguity and fuzziness of the judgment creators but also provides better time complexity than other fuzzy AHP methods. An algorithm, numerical examples, and simulation study are all carried out in this correspondence to find the best relays.

Clustering in Cooperative Cognitive Radio Networks Based on Mobility Aware Hybridized Algorithm for Optimization

Clustering in Cooperative Cognitive Radio Networks Based on Mobility Aware Hybridized Algorithm for Optimization

Sum-Rate Maximization of Wireless Powered Primary Users for Cooperative CRNs: NOMA or TDMA at Cognitive Users?

Recently, wireless powered cooperative cognitive radio networks (CRNs), which combine the technologies of radio frequency (RF) energy harvesting and CR, have drawn great attention. In such networks, energy cooperation between the cognitive users (CUs) and the wireless powered primary users (PUs) can be performed, where the CUs can charge the PUs wirelessly in exchange for the spectrum access. Specifically, energy cooperation and information transmission is executed in two phases, where the CUs transmit their data signals and the PUs harvest energy from these signals in the first phase, and the PUs transmit their data using the harvested energy in the second phase. In particular, we consider two multiple access schemes for the CUs, namely non-orthogonal multiple access (NOMA) and time-division multiple access (TDMA). For both NOMA and TDMA, the PU sum-rate maximization problems under the minimum CU sum-rate constraint are first simplified by exploring particular problem structure, then are transformed to convex problems, and finally are solved optimally. The PU sum-rates of the two schemes are compared theoretically as well as numerically. It is revealed that the circuit power consumption at the CUs, the required minimum CU sum-rate, and the PU energy harvesting sensitivity and saturation thresholds play key roles in the PU performance comparison of the two schemes.

BER Performance Analysis of Energy Harvesting Underlay Cooperative Cognitive Radio Network With Randomly Located Primary Users and Secondary Relays

In this work, we investigate the error probability of an energy harvesting co-operative cognitive radio network (CRN) in the presence of Poisson field of primary users (PU). We consider the scenario where, after harvesting energy from primary transmitters (PTs), a secondary transmitter (ST) would transmit its symbol towards secondary destination (SD) through a suitable secondary relay from a group of randomly scattered idle nodes within a circular region. Several relay selection criteria have been considered for relay node selection. Performance of a secondary transceiver has been analysed in terms of probability of error. Relationships among the bit error ratio (BER) performance of an ST and several other network entities such as density of PUs, transmit power of PTs and required transmit power of ST have also been investigated through detailed analysis. Numerical results are provided to assess the precision of derived analytical expressions.

Intercept Probability Analysis of Cooperative Cognitive Networks Using Fountain Codes and Cooperative Jamming

This paper evaluates intercept probability (IP) of a cooperative cognitive radio network. Using Fountain codes, a secondary source continuously generates encoded packets, and sends them to secondary destination and relay nodes that attempt to receive a sufficient number of the encoded packets for recovering the source data. If the relay can sufficiently collect the packets before the destination, it replaces the source to transmit the encoded packets to the destination. Also in the secondary network, a passive eavesdropper attempts to illegally receive the packets sent by the source and relay nodes, and if it can accumulate enough encoded packets, the source data is intercepted. To enhance secrecy performance, in terms of IP, a cooperative jammer is used to transmit noises on the eavesdropper. We also propose a simple transmit power allocation method for the secondary transmitters such as source, relay and jammer so that outage performance of a primary network is not harmful. We derive an exact closed-form expression of IP over Rayleigh fading channel, and verify it by performing Monte-Carlo simulations.

A New Hardware-Efficient Spectrum-Sensor VLSI Architecture for Data-Fusion-Based Cooperative Cognitive-Radio Network

This article presents a hardware-friendly algorithm and architecture for cooperative spectrum sensing (CSS) in the data-fusion-based cognitive-radio (CR) network. The proposed VLSI-algorithm is based on the iterative power method and deflation technique that alleviate the computational complexity of conventional CSS algorithm with minimal performance degradation. In this work, a new hardware-efficient VLSI architecture of cooperative spectrum sensor (CSR) for the data-fusion center is presented, which supports up to six secondary users in the cooperative CR network. Its performance analysis under fading channel environment has been carried out where it delivers 0.8 detection probability ( $P_{d}$ ) at −8 dB of channel SNR with a false alarm rate of 0.1. It shows the minimum performance degradation of 0.057 dB at $P_{d} = 0.88$ compared to the conventional algorithm. The suggested CSR architecture has been application-specific integrated circuit (ASIC)-synthesized and postlayout simulated in UMC 90 nm-CMOS process. Thus, it occupies 2.4 mm2 of the core area, consumes 36 mW of total power, and delivers a low sensing time of $60.41~\mu \text{s}$ while operating at a maximum clock frequency of 87.7 MHz. Comparison with the reported works indicates that the proposed design requires 40.3% lesser area, and it is 41% hardware efficient than the conventional implementation. Eventually, this design has been field-programmable gate array (FPGA) prototyped, and its functionality is verified in the real-world test environment.

Spectral efficiency enhancement of green metric cognitive radio network using novel channel design and intellectual African buffalo optimization

In an advance world, the field of information technology is full of contemporary wireless approaches as because of this the spectral efficiency and spectral sensing technology brings a broad interest in the Cooperative Cognitive Radio Network (CCRN). Besides, the Green metric CCRN spectral sharing is one of the efficient modern approaches compared with other traditional wireless technologies. Nevertheless, the distribution of spectral between the cooperative cognitive customers has dramatic challenges due to the collaboration between the licensed and unlicensed customers. Therefore, the motivation of this research work is to show the better performance of green metric CCRN using novel techniques. Here, a novel Markov Gaussian Wideband Distribution (MGWD) and Dynamic First-Rate Relay Protocol is developed for communication. Moreover, a novel Intellectual African Buffalo Optimization (IABO) is proposed to estimate the finest spectral sensing and false alarm detection. The implementation of this work is done on the MATLAB platform. Sequentially, the performance of green metric CCRN is estimated in terms of the communication ratio, spectral efficiency, outage probability, and throughput. Moreover, the simulation outcomes show that the developed method in CCRN attain higher throughput and diminished power consumption in terms of both Primary User (PU) and Secondary User (SU) successful transmission of probability compared with the other conventional strategies.

Game-based approach of fair resource allocation in wireless powered cooperative cognitive radio networks

A resource allocation approach is proposed for wireless powered cooperative cognitive radio network (WP-CCRN) in this paper, where multiple secondary users (SUs) capture both the wireless energy and the authorized spectrum from primary user (PU) to communicate with a secondary access point (SAP). In return, SUs serve as relay nodes to help the primary transmitter (PT) forwarding data to the primary receiver (PR). For the sake of the stable cooperation between PU and SUs, we present a game-based fair resource allocation algorithm (GFRAA) that takes into account the utilities of both sides. The Stackelberg game is applied for solving the resource allocation problem between PU and SUs, where PU acts as a leader while SUs are followers. To solve the non-convex optimization problem in the primary network, a new variable namely allocated energy is introduced to transform the primal problem into a convex problem. Meanwhile, the relationship among SUs is modeled as a Supermodular game. Since SUs are rational and selfish, a fairness evaluation mechanism is designed to adjust the fairness among SUs. Simulation results unveil the trade-off between the fairness of SUs, the throughput of PU, and the sum-throughput of SUs. The superiority of the GFRAA has been validated by comparing with the other two algorithms.

Chaotic Compressive Spectrum Sensing Based on Chebyshev Map for Cognitive Radio Networks

Recently, the chaotic compressive sensing paradigm has been widely used in many areas, due to its ability to reduce data acquisition time with high security. For cognitive radio networks (CRNs), this mechanism aims at detecting the spectrum holes based on few measurements taken from the original sparse signal. To ensure a high performance of the acquisition and recovery process, the choice of a suitable sensing matrix and the appropriate recovery algorithm should be done carefully. In this paper, a new chaotic compressive spectrum sensing (CSS) solution is proposed for cooperative CRNs based on the Chebyshev sensing matrix and the Bayesian recovery via Laplace prior. The chaotic sensing matrix is used first to acquire and compress the high-dimensional signal, which can be an interesting topic to be published in symmetry journal, especially in the data-compression subsection. Moreover, this type of matrix provides reliable and secure spectrum detection as opposed to random sensing matrix, since any small change in the initial parameters generates a different sensing matrix. For the recovery process, unlike the convex and greedy algorithms, Bayesian models are fast, require less measurement, and deal with uncertainty. Numerical simulations prove that the proposed combination is highly efficient, since the Bayesian algorithm with the Chebyshev sensing matrix provides superior performances, with compressive measurements. Technically, this number can be reduced to 20% of the length and still provides a substantial performance.

Overview of Cognitive Radio Networks

Cognitive radio (CR) allows the best use of dynamic access to spectrum and wide spectrum diversity to mitigate spectrum depletion issues and fulfil huge wireless networking requirements. This paper also illustrates, discusses, and focuses on some essential applications, a proactive spectrum sharing strategy using full-duplex (FD) in the cooperative Cognitive Radio Networks (CRN).

Combining Power Allocation and Superposition Coding for an Underlay Two-way Decode-and-forward Scheme

Combining Power Allocation and Superposition Coding for an Underlay Two-way Decode-and-forward Scheme

Secrecy Performance for Underlay Cooperative Cognitive Radio Network with Energy Harvesting and Transmit Antenna Selection Using MIMO Over Nakagami-m Fading Channels.

Secrecy Performance for Underlay Cooperative Cognitive Radio Network with Energy Harvesting and Transmit Antenna Selection Using MIMO Over Nakagami-m Fading Channels.

Outage Analysis in Underlay OFDMA Based Cooperative Cognitive Radio Networks

Background: Efficient resource allocation in Cooperative Cognitive Radio Network (CCRN) is necessary in order to meet the challenges in future wireless networks. With proper resource allocation, the Quality of Service (QoS) comprising of outage probability and data rate are evaluated in this paper and sufficiently improved with proper subcarrier allocation. Objective: Another important parameter is Signal to Interference Ratio (SIR) which should be above a threshold called minimum protection ratio to maintain the required QoS. Results: The network considered is Orthogonal Frequency Division Multiple Access (OFDMA) based Hybrid Cooperative Cognitive Radio Network (HCCRN) in downlink in which licensed as well as unlicensed resources are used by cognitive user depending on it’s availability keeping the interference constraint in limit. The number of subcarriers required is different for every user depending upon its distance from the base station to satisfy the requirement of data rate which depends on the experienced SIR. To avoid outage of users at the boundary of a cell, it is necessary to allocate more number of subcarriers. Conclusion: It is observed that for a given user position and outage probability, as the number of subcarrier allocation in a subchannel increases high data rates can be achieved. This analysis can be useful in allocation of subcarriers to users depending upon their position.

Compressive spectrum sensing using two-stage scheme for cognitive radio networks

The modern applications of communications that use wideband signals suffer the lacking since the resources of this kind of signals are limited especially for fifth generation (5G). The Compressive Spectrum Sensing (COMPSS) techniques address such issues to reuse the detected signals in the networks and applications of 5G. However, the raw techniques of COMPSS have low compression ratio and high computational complexity rather than high level of noise variance. In this paper, a hybrid COMPSS scheme has been developed for both non-cooperative and cooperative cognitive radio networks. The proposed scheme compiles on discrete wavelet transform – single resolution (DWT-SR) cascaded with discrete cosine transform (DCT). The first is constructed according to the pyramid algorithm to achieve 50% while the second performed 30% compression ratios. The simulation and analytic results reveal the significant detection performance of the proposed technique is better than that of the raw COMPSS techniques.

Performance analysis of centralized dynamic spectrum access via channel reservation mechanism in cognitive radio networks

The two main goals in wireless networks are to provide channel allocation opportunities for incoming services and to assure the accomplishment of ongoing services. In this paper, a channel reservation scheme in cooperative cognitive radio networks (CRNs) based on dynamic spectrum access (DSA) is proposed. In this scheme, a centralized cognitive manager (CCM) provides the dynamic coordination access for primary users (PUs) and secondary users (SUs) through partitioning the spectrum into non-reserved channels (N-CRN) and reserved channels (R-CRN). N-CRN can be exploited by licensed PUs and unlicensed SUs, while R-CRN is dedicated for active SUs until the successful completion of their service. If a SU session in N-CRN is interrupted by the sudden arrival of PU, then a spectrum handover occurs to R-CRN to resume its session. The reserved channel number R is deduced upon the reduction of both forced termination and blocking probabilities for SUs while satisfying PUs’ traffic demands. Also, overall system cost and SU cost functions are investigated. Simulation results show significant reduction in blocking and forced termination probabilities and improvement in utility function and service completion rate of SUs while meeting PU’s quality of service (QoS) aims. For example, when the arrival traffic rates per channel λp=0.5, and for R=1,R=2 and R=3, the values of specific SU forced termination probabilities Pft are 0.1597, 0.116, 0.0799 respectively compared to 0.2106 for the case of no channel reservation. Furthermore, blocking probability and service completion rate of PU are evaluated to demonstrate the effect of channel reservation variation on the system performance.

On spectrally-efficient device-to-device communication with wireless information and power transfer

In this paper, the model of cooperative cognitive radio network is used to explore the two-way communications between a pair of unlicensed users by sharing the spectrum of any existing pair of licensed users. The licensed users of the spectrum are considered as primary users (PUs) and the unlicensed users of the spectrum are considered as secondary users (SUs). SUs are able to access the PUs spectrum by serving the relaying action between PU-to-PU communications. SUs are enabled by harvesting the energy from radio frequency signal following the principle of power splitting (PS) scheme of simultaneous wireless information and power transfer protocol. The closed form outage expressions of both PU and SU systems are derived. Analytical results validated through the simulations results. The results are also compared with existing work on two-way SU communications in presence of two-way PU communications. Based on the comparison, it is found that about $${\sim 191\%}$$ and $${\sim 656\%}$$ performance gains are possible to achieve by using proposed PS protocol in terms of spectrum efficiency and energy efficiency, respectively as compared to similar system using time switching protocol.

Enhanced physical layer security for cognitive radio systems through joint spectrum access and power allocation

Physical layer (PHY) security is an important issue in wireless communication systems. In this study, the authors investigate the interactions between the PHY security performance and the spectrum access technique in a cooperative cognitive radio (CR) network. In the classical spectrum access, if the measured energy on a given subchannel is less than a threshold, the subband is dedicated for CR transmission. Here, they consider a probabilistic spectrum access (PSA), which assigns to each primary subchannel a probability which is determined according to the measured energy on that subchannel. In addition, both spectrum access and CR power allocation are performed simultaneously. They formulate the general outage probability and some important PHY security performance metrics, such as average secrecy rate, secrecy outage probability, and probability of positive secrecy rate in terms of the spectrum access and optimal power allocation functions. The authors' numerical analysis indicates that the PSA method achieves a superior PHY security and outage performance compared to the classical threshold-based spectrum sensing and power allocation method.

Outage Analysis of Relay-Assisted NOMA in Cooperative Cognitive Radio Networks with SWIPT

In this paper, we investigate a relay-assisted cooperative spectrum sharing for the considered non-orthogonal multiple access (NOMA) scheme in cognitive radio networks, where the relay node assists the base station (BS) to transmit the superimposed composite signal to two receivers by utilizing an amplified-and-forward (AF) technique with simultaneous wireless information and power transfer (SWIPT). The exact expressions for outage probabilities of two receivers are derived in closed forms. Moreover, a joint optimization of power allocation and the proportion of information splitting for energy harvesting is proposed in terms of energy efficiency (EE) maximization under required data reliability. Simulation results validate the analytical results since the analytical results match well with simulation results and demonstrate the performance advantages of the proposed scheme over other schemes and direct transmission.

From Cognitive to Intelligent Secondary Cooperative Networks for the Future Internet: Design, Advances, and Challenges

Cognitive Radio (CR) technology was first introduced to solve the problem of radio spectrum under-utilization. A cognitive radio network consists of smart radio devices that have the ability to sense radio environment variables and take actions accordingly. To realize their full potential and to become fully cognitive, the CR nodes need to be equipped with learning and reasoning capabilities. Machine learning has been one of the enabling vehicles for intelligent CR networks. Inspired by the cognition cycle of a CR node, over the past years there has been an ever growing interest in using machine learning techniques to enhance the performance of CR networks. In this article, an overview of the various learning techniques currently used in the literature of CR networks is given. We focus on feature classification and clustering algorithms, and their application in cooperative CR networks. We outline the steps to establishing a learning-based cooperative secondary network, highlighting factors that impact detection performance. Additionally, current state-of-the-art learning-based applications in Cognitive Internet of Things (CIoT) are presented. Finally, the key challenges and future directions of intelligent cognitive networks are discussed.