Underlay Cognitive Radio Research Articles

SSO Based Energy Efficient Power Allocation with Optimal Power Constraints for Underlay Cognitive Radio Networks

ABSTRACT The most desired scheme in wireless communication (WC) technology is a cognitive radio network (CRN), which enhanced spectral efficiency. The main challenging problem for CRN is the power allocation (PA) scheme since it requires deliberating the quality of service (QoS) parameters for secondary users (SUs) through sustaining the power inference (PI) to Primary users (PUs) under the threshold of Interference Temperature (IT). The spectral insufficiency issues and interferences among the users possess a challenging task in CRN technology. To solve this issue, this paper statements shark smell optimisation (SSO) PA complications with optimal power constraints to diminishes the interference power and maximise capacity by permitting a large number of secondary users in CRN technology. In addition to that, multi-objective optimisation problems have been considered and targeted to maximise the minimum signal to noise ratio (SNR), network throughput utility and energy efficiency (EE). The proposed method is executed in MATLAB software, and the simulation results evaluate that the proposed strategy maintain ethical balance when compared to other existing approaches also it contributes to spectral scarcity issues resourcefully.

Optimal precoders and power splitting factors in multiuser multiple‐input multiple‐output cognitive decode‐and‐forward relay systems with wireless energy harvesting

SummaryThis paper considers an underlay cognitive radio (CR) wireless network with the assistance of a two‐hop decode‐and‐forward (DF) relay node. Different from the conventional CR relay networks, in this paper, the relay node using power‐splitting (PS) techniques harvests wireless energy transmitted from the secondary base station (SBS) and, then, uses its harvested energy to forward the received signals to multiple secondary receive users (SRUs). Due to the highly mutual dependence of the transmission strategies at nodes on the system performance, the optimal design of signal processing at transceivers to efficiently handle the interference and energy constraints is crucial. This paper studies the jointly optimal design of the precoders, PS factors to maximize the minimum user rate under the transmit power, harvested energy, and interference power constraints. Owing to the nonlinearly and mutually coupled design matrix variables in both objective function and constraints, the joint design of the precoders and PS factors for the concerned problem is mathematically challenging. To tackle these difficulties, we devise the appropriate surrogate functions to recast the nonconvex optimization problem into the convex one. By using the minorization–maximization framework, an efficient iterative algorithm with provable convergence is developed by solving the convex optimization problem in each iteration. Numerical results are provided to evaluate the achievable user rate performance of the considered system and investigate the effects of the interference power thresholds at the primary receive users and the number of antennas at the SBS and the relay on the minimum achievable user rate.

Secure Cognitive Radio Communication via Intelligent Reflecting Surface

In this paper, an intelligent reflecting surface (IRS) assisted spectrum sharing underlay cognitive radio (CR) wiretap channel (WTC) is studied, and we aim at enhancing the secrecy rate of secondary user in this channel subject to total power constraint at secondary transmitter (ST), interference power constraint (IPC) at primary receiver (PR) as well as unit modulus constraint at IRS. Due to extra IPC and eavesdropper (Eve) are considered, all the existing solutions for enhancing secrecy rate of IRS-assisted non-CR WTC as well as enhancing transmission rate in IRS-assisted CR channel without eavesdropper fail in this work. Therefore, we propose new numerical solutions to optimize the secrecy rate of this channel under full primary, secondary users’ channel state information (CSI) and three different cases of Eve’s CSI: full CSI, imperfect CSI with bounded estimation error, and no CSI. To solve the difficult non-convex optimization problem, an efficient alternating optimization (AO) algorithm is proposed to jointly optimize the beamformer at ST and phase shift coefficients at IRS. In particular, when optimizing the phase shift coefficients during each iteration of AO, a Dinkelbach based solution in combination with successive approximation and penalty based solution is proposed under full CSI and a penalty convex-concave procedure solution is proposed under imperfect Eve’s CSI. For no Eve’s CSI case, artificial noise (AN) aided approach is adopted to help enhancing the secrecy rate. Simulation results show that our proposed solutions for the IRS-assisted design greatly enhance the secrecy performance compared with the existing numerical solutions with and without IRS under full and imperfect Eve’s CSI. And positive secrecy rate can be achieved by our proposed AN aided approach given most channel realizations under no Eve’s CSI case so that secure communication also can be guaranteed. All of the proposed AO algorithms are guaranteed to monotonic convergence.

Twelfth mode on-demand band notch UWB antenna for underlay cognitive radio

A wide-slot ultra-wideband (UWB) antenna with on-demand band rejection characteristics that can serve underlay cognitive radio is presented in this paper. This antenna is designed to work in twelve operation modes; one to cover the whole UWB while each of the rest modes excludes one or more of the ranges that are allocated for Worldwide Interoperability for Microwave Access (WiMax), C-band, wireless local area network (WLAN), X-band and International Telecommunication Union (ITU) in a single, dual, triple, quad or penta band rejection state. A spiral shape slot in the patch and three slots mainly based on half-circular structures in the ground plane are the means to create the desired frequency notches. A positive-intrinsic-negative (PIN) diode across each of these slots is used to enable/disable band(s) rejection process. Configuration of the proposed antenna to the desired mode of operation is decided by the state of its four PIN diodes. This work is simulated by computer simulation technology (CST) v.10. It’s S11, voltage-standing-wave-ratio (VSWR) and realized gain results when combined with antenna's 25x25x0.8 mm3 compact size and the large number of modes and states, all ensure its capability to eliminate or reduce the interference within the targeted bands and hence being suitable for the applications of underlay cognitive radio.

Performance Analysis of Underlay Cognitive Radio System with Self-Sustainable Relay and Statistical CSI

The relentlessly increasing number of small-sized devices with limited powering and computational capabilities requires the adoption of new approaches to spectrum access. In this paper, we analyze an underlay cooperative cognitive wireless system based on available statistical channel state information (CSI) that is applicable to the cognitive system with limited computational resources due to its low complexity. We considered the scenario where the primary and the cognitive network coexist in the same spectrum band, under the constraints of interference threshold and maximal tolerable outage permitted by the primary user. The communication in the secondary decode-and-forward (DF) relaying system is established via a self-sustainable relay, which harvests energy from both cognitive and primary transmitters. The closed-form expressions for the outage probability of the cognitive network are derived, which are valid for both time-switching relaying (TSR) and power-splitting relaying (PSR) protocols. We analyze the influence of both cognitive and primary systems as well as the impact of channel parameters on the cognitive system outage performance. The derived analytical results are corroborated by an independent simulation method.

Performance Analysis of NOMA-Based Underlay Cognitive Radio Networks With Partial Relay Selection

This paper investigates outage and throughput performance of non-orthogonal multiple access (NOMA) based underlay cognitive radio (i.e., CR-NOMA) network under partial relay selection (PRS) scheme. Here NOMA is used in the secondary network, where K half duplex, decode-and-forward (DF) relays are available for assisting the secondary base station (SBS) to deliver information to the secondary users (SUs). We derive analytical expressions for the outage probabilities experienced by the SUs under imperfect successive interference cancellation (i-SIC) conditions. The interference threshold constraint of the primary receiver and the maximum transmit power constraint of the secondary nodes are considered for the analysis. To provide more insights on the outage performance, we obtain expressions for the asymptotic outage probabilities of the SUs in the high transmit power region. Next, we derive analytical expressions for the optimal power allocation (OPA) factors at the SBS and at the selected relay that independently maximize the delay limited throughput of the secondary network in CR-NOMA system. We also determine the jointly optimal power allocation factors that maximize the throughput. We use numerical and simulation investigations to establish that the outage probabilities of the SUs reduce significantly while the throughput improves under the considered PRS scheme, compared to random relay selection and fixed relaying strategies. Further, it is established that the proposed OPA factors can significantly reduce the outage probabilities experienced by the SUs and improve the system throughput compared to equal/random power allocation schemes.

Rate Maximization of Wireless-Powered Cognitive Massive MIMO Systems

In order to combat the challenges of scarce spectrum bandwidth and energy supply in the Internet-of-Things networks, this article investigates a wireless-powered massive multiple-input-multiple-output (MIMO) underlay cognitive radio (CR) system, where the secondary user (SU) harvests the energy from the primary network through a time-switching (TS) strategy. Moreover, the detection technique of maximum-ratio combining (MRC) is applied at base stations (BSs) due to its low complexity. Thereon, the achievable rate of the secondary network is thoroughly analyzed by accounting for spatial correlations at both users and BSs, which significantly differentiates the analysis from the prior literature. With the analytical results, the impacts of the number of antennas and the spatial correlations are quantified. In particular, the negative impact of the spatial correlation on the achievable rate is theoretically proved based on the majorization theory. Furthermore, the TS factor and/or power allocation coefficients are optimally designed based on the statistical channel state information (CSI) only to maximize the achievable rate while ensuring the maximum endurable interference constraint. It is found that the optimal power allocation matrix is a variant of water-filling solution with two water levels associated with sum power constraint and sum weighted power constraint, respectively. The weighting matrix is aligned with the transmit spatial correlation in the SU. The joint design of TS factor and power allocation coefficients is also shown to reach a superior performance over the algorithms-based solely on TS factor or power allocation coefficients optimizations. Finally, the analytical results are validated by conducting simulations.

On the Performance of Secure Underlay Cognitive Radio Networks With Energy Harvesting and Dual-Antenna Selection

In this letter, we consider a secure underlay cognitive radio network consisting of a secondary source-destination pair and a primary transmitter-receiver pair in the presence of a primary passive eavesdropper. Herein, a secondary multi-antenna full-duplex destination node acts as a jammer to the primary eavesdropper in an effort to improve the physical layer security of the primary network. In return for this favor, the energy constrained secondary source gets access to the primary network to transmit its own information so long as the interference to the latter is below a certain level. In light of the aforementioned, we evaluate the system performance in terms of the outage probability for the secondary network, the secrecy outage probability, and the probability of non-zero secrecy capacity for the primary network. Numerical results are provided to verify the correctness of the proposed analytical framework.

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

HCR-WSN: Hybrid MIMO cognitive radio system for wireless sensor network

Multi Input Multi Output (MIMO) based Cognitive Radio (CR) provisions an efficient utilization of the scarce electromagnetic spectrum. Traditional CR includes Interweave and Underlay techniques. We propose a Hybrid MIMO CR system for Wireless Sensor Network, HCR-WSN, that utilizes both underlay and interweave CR techniques and provides higher spectral efficiency. The wireless sensor network consisting of CR nodes achieves higher throughput using the proposed framework.HCR-WSN improves the spectral efficiency gain of an Uplink Hybrid Cognitive Radio MIMO system in wireless sensor network (WSN), by implementing Narrowband and Wideband (Multiple Carrier Direct Sequence Code Division Multiple Access, i.e., MC-DS-CDMA) technology adhering to the Interference Threshold limit. The WSN is consisting of nodes acting as primary users (PU) and CR secondary users (SU). The proposed Hybrid CR system ensures efficient spectral utilization under circumstances resulting in near zero throughput for SU. In the presence of PU, CR-SU transmits in either Narrowband or MC-DS-CDMA based on the proposed transmission selection algorithm. In the absence of PU, SU uses Interweave technique thereby allowing other competing SUs to transmit in Interference Alignment underlay mode in a multi-user scenario. The achievable throughput is enhanced using the proposed technique in a multi-user hybrid MIMO cognitive radio wireless sensor network.

Secrecy Capacity Analysis of an Underlay Cognitive Radio Network in the Presence of Co-channel and Primary Network Interference

Secrecy Capacity Analysis of an Underlay Cognitive Radio Network in the Presence of Co-channel and Primary Network Interference

Energy Efficient Power Allocation with Antenna Selection for Interference Alignment based MIMO-OFDM Cognitive Radio Networks

Energy efficient communications in cognitive radio (CR) networks has been of great interest. In order to address the power consumption problem and to maximise the energy efficiency (EE) in MIMO-OFDM underlay CR systems, power allocation (PA) and antenna selection (AS) algorithms are proposed. Interference alignment, which helps in mitigating the interference at primary and secondary receivers, is considered for setting-up the underlay CR scenario. The AS transmit is employed for the secondary users (SUs) on a per-subcarrier basis to improve their QoS. Further, to improve the QoS of both primary user (PU) and SUs, the AS is followed by energy efficient PA. Due to the fractional nature of EE, the EE maximisation problem is transformed into an equivalent parametric optimisation problem based on Dinkelbach method. Simulation results confirm that the proposed EE aware algorithms can improve the EE performance of both PU and SUs than the SE aware algorithms.

Energy efficient power allocation with antenna selection for interference alignment-based MIMO-OFDM cognitive radio networks

Energy efficient communications in cognitive radio (CR) networks has been of great interest. In order to address the power consumption problem and to maximise the energy efficiency (EE) in MIMO-OFDM underlay CR systems, power allocation (PA) and antenna selection (AS) algorithms are proposed. Interference alignment, which helps in mitigating the interference at primary and secondary receivers, is considered for setting-up the underlay CR scenario. The AS transmit is employed for the secondary users (SUs) on a per-subcarrier basis to improve their QoS. Further, to improve the QoS of both primary user (PU) and SUs, the AS is followed by energy efficient PA. Due to the fractional nature of EE, the EE maximisation problem is transformed into an equivalent parametric optimisation problem based on Dinkelbach method. Simulation results confirm that the proposed EE aware algorithms can improve the EE performance of both PU and SUs than the SE aware algorithms.

Outage Minimization of Energy Harvesting-Based Relay-Assisted Random Underlay Cognitive Radio Networks With Interference Cancellation

This paper incorporates interference cancellation in the outage analysis of a wireless energy harvesting cognitive relay network. Based on an interference threshold, primary receivers are assumed to be able to cancel a fraction of the strongest interferers in the primary network which often dominates the total interference. To achieve this, the coefficient of cancellation is adapted into the analysis to reduce the level of interference. The rationale is to improve the successful transmission probability of the primary network by cancelling interference at its receivers. Interestingly, this reduces the overhead incurred by the secondary network to guarantee the primary outage constraint. In this work, the optimal relay selection range is derived and deployed to minimize the secondary outage probability. Analytical results show that this approach can be used to significantly reduce the secondary outage probability which in turn improves the network performance. However, this is at the cost of reducing the energy harvesting success probability of the relays within the secondary network.

Optimization and Transmit Power Control Based on Deep Learning with Inaccurate Channel Information in Underlay Cognitive Radio Network

In cognitive radio network(CRN), power control often faces the complicated iterations and large calculations, resulting in poor real time performance of the system. In this paper, a deep learning-based power control is proposed for CRNs, where the secondary users (SUs) can share the same channel of primary users (PUs) without causing excessive interference to the communication of PU. In the novel scheme, the DNN model is used to treat the input and output of the power control algorithm as unknown non-linear mappings and fit them, which determines the proportion of transmit power allocated to each SU, considering the interference caused to the PU. With this scheme, the maximization of the SUs sum-rate can be achieved. Furthermore, due to some errors in the practical samples of channel information, an auto-encoder is used to compress the channel coefficient through an encoder and reconstruct them through a decoder before DNN training. The simulations results show that the power control method using a combination of auto-encoding and DNN can improve the real-time performance of the system. And the sum-rate of SU is improved while the interference caused to the PU can be regulated even with the inaccurate channel information.

Energy efficient transmission in underlay CR-NOMA networks enabled by reinforcement learning

In order to improve the energy efficiency (EE) in the underlay cognitive radio (CR)networks, a power allocation strategy based on an actor-critic reinforcement learning is proposed, where a cluster of cognitive users (CUs) can simultaneously access to the same primary spectrum band under the interference constraints of the primary user (PU), by employing the non-orthogonal multiple access (NOMA) technique. In the proposed scheme, the optimization of the power allocation is formulated as a non-convex optimization problem. Additionally, the power allocation for different CUs is based on the actor-critic reinforcement learning model, in which the weighted data rate is set as the reward function, and the generated action strategy (i.e. the power allocation) is iteratively criticized and updated. Both the CU's spectral efficiency and the PU's interference constrains are considered in the training of the actor-critic reinforcement learning. Furthermore, the first order Taylor approximation as well as other manipulations are adopted to solve the power allocation optimization problem for the sake of considering the conventional channel conditions. According to the simulation results, we find that our scheme could achieve a higher spectral efficiency for the CUs compared to a benchmark scheme without learning process as well as the existing Q-learning based method, while the resultant interference affecting the PU transmission can be maintained at a given tolerated limit.

Interference resilient stochastic prediction based dynamic resource allocation model for cognitive MANETs

Background/Objectives: Being dynamic in nature, Mobile Ad-hoc Network (MANET) requires robust resource allocation strategy that can ensure both optimal transmission reliability and resource efficiency to meet Quality of Service (QoS) demands. The objective of this research is to address interference resilience requirement in MANETs which is must due to greedy nature of nodes especially when accessing resource or bandwidth and develop a highly robust stochastic prediction based resource allocation strategy. Methods: The proposed Interference Resilient Stochastic Prediction based Dynamic Resource Allocation model for Cognitive MANET (ISP-DRACM) intends to enable optimal resource allocation under interweave and underlay network setup with instantaneous as well as average interference conditions. It employs a joint power management and resource allocation strategy where it intends to maximize the weighted sum-rate of the secondary users under certain defined conditions like average power and stochastic interference level. Findings/Novelty: Inculcating resource allocation problem as controlled Markov Decision Process using Hidden Markov Model (HMM) and Lagrange relaxation, our proposed model achieves better resource allocation under limited noise or interference condition and hence achieves both costeffectiveness as well as QoS provision. This method has exhibited satisfactory performance towards spectrum allocation to the secondary users without imposing any significant interference for both interweave as well as underlay Cognitive Radio setup. Keywords: Cognitive mobile ad-hoc network; stochastic prediction; interference resilience; channel state information; dynamic resource allocation; underlay and overlay cognitive MANET

Secrecy analysis of multiple‐input multiple‐output underlay cognitive radio networks with energy harvesting

AbstractThe cognitive radio (CR) technique is an encouraging approach to deal with spectrum scarcity in wireless networks. However, this technique raises the issues of secrecy and privacy in the CR network. In this work, a multiple‐input multiple‐output underlay CR network is considered, which consists of a primary network, a secondary network, and an eavesdropper. All the primary, secondary as well aseavesdropper's nodes are assumed to have multiple antennas with radio frequency energy harvesters to enhance their spectral and energy efficiency properties. The eavesdropper node manipulates it's simultaneous wireless information and power transfer architecture in a pursuit to intercept the secure communication between the cognitive transmitter and the cognitive receiver. This technique and considered network are combined with the traditional selection combining (SC) and maximal ratio combining (MRC) scheme and the results are compared. The Monte Carlo simulation is done for the validation of results. The main aim is to drive the closed‐form analytical expression for exact and asymptotic secrecy outage probability. The present results show that the SC scheme at eavesdropper provides better secrecy in comparison to the MRC technique and also the number of antennas affects the secrecy of the system. Moreover, the impact of power splitter is considered and also the optimal value of power splitter is derived to maximize information decoding.

Outage Analysis of Energy-Harvesting-Based Relay-Assisted Random Underlay Cognitive Radio Networks With Multihop Primary Transmissions

This article exploits the recent advances in wireless energy harvesting to develop a framework for the outage probability of energy harvesting underlay cognitive radio networks. In this model, N-hop primary users are equipped with constant energy source while secondary users (SUs) harvest energy from the transmissions of primary devices. The transmit power of secondary users is regulated to ensure that it does not violate the target end-to-end outage probability constraint of the N-hop primary network. Potential relays that have harvested sufficient energy are eligible to relay data for other SUs within the network. Using this model, we reveal the impacts of the number of primary hops on the relay selection region and harvested energy. An expression for the total outage probability that encapsulates the impact of N primary hops is also derived. Moreover, the effects of other relevant parameters on the outage probability are shown in detail.

Performance Analysis of Overlay Cognitive NOMA Systems With Imperfect Successive Interference Cancellation

Non-orthogonal multiple access (NOMA) and cognitive radio (CR) are envisioned as promising solutions to achieve high spectral efficiency for future wireless networks. This work investigates the outage performance of an overlay cognitive NOMA system with imperfect successive interference cancellation (SIC). The outage probability of primary user and secondary user are derived in closed forms. To obtain further insights, asymptotic expressions of outage probability and system throughput are evaluated when the transmit signal-to-noise ratio approaches infinity. An optimal power allocation coefficient is provided to maximize the system throughput. Moreover, the overlay cognitive NOMA system is compared with the underlay CR system and the overlay cognitive orthogonal multiple access (OMA) system in terms of outage probability. Finally, the performance analysis is validated by simulations. The simulation results demonstrate that the outage performance and system throughput of overlay cognitive NOMA system are superior to those of overlay cognitive OMA system and underlay CR system when the imperfect SIC satisfies certain conditions.