Large Number Of Secondary Users Research Articles

UAV-Assisted Cooperative & Cognitive NOMA: Deployment, Clustering, and Resource Allocation

Cooperative and cognitive non-orthogonal multiple access (CCR-NOMA) has been recognized as a promising technique to overcome issues of spectrum scarcity and support massive connectivity envisioned in next-generation wireless networks. In this paper, we investigate the deployment of an unmanned aerial vehicle (UAV) as a relay that fairly serves a large number of secondary users in a hot-spot region. The UAV deployment algorithm must jointly account for user clustering, channel assignment, and resource allocation sub-problems. We propose a solution methodology that obtains user clustering and channel assignment based on the optimal resource allocations for a given UAV location. To this end, we derive closed-form optimal power and time allocations and show it delivers optimal max-min fair throughput by consuming less energy and time than geometric programming. Based on optimal resource allocation, the optimal coverage probability is also provided in closed-form, which takes channel estimation errors, hardware impairments, and primary network interference into account. The optimal coverage probabilities are used by the proposed max-min fair user clustering and channel assignment approaches. The results show that the proposed method achieves 100% accuracy in more than five orders of magnitude less time than the optimal benchmark.

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.

Exploiting Underlay Spectrum Sharing in Cell-Free Massive MIMO Systems

We investigate the coexistence of underlay spectrum sharing in cell-free massive multiple-input multiple-output (MIMO) systems. A primary system with geographically distributed primary access points (P-APs) serves a multitude of primary users (PUs), while a secondary system serves a large number of secondary users (SUs) in the same primary/licensed spectrum by exploiting the underlay spectrum sharing. To mitigate the secondary co-channel interference inflected at PUs, stringent secondary transmit power constraints are defined for the secondary access points (S-APs). A generalized pilots sharing scheme is used to locally estimate the uplink channels at P-APs/S-APs, and thereby, conjugate precoders are adopted to serve PUs/SUs in the same time-frequency resource element. Moreover, the effect of a user-centric AP clustering scheme is investigated by assigning a suitable set of APs to a particular user. The impact of estimated downlink (DL) channels at PUs/SUs via DL pilots beamformed by P-APs/S-APs is investigated. The achievable primary/secondary rates at PUs/SUs are derived for the statistical DL and estimated DL CSI cases. User-fairness for PUs/SUs is achieved by designing efficient transmit power control policies based on a multi-objective optimization problem formulation of joint underlay spectrum sharing and max-min criteria. The proposed orthogonal multiple-access based analytical framework is also extended to facilitate non-orthogonal multiple-access. Our analysis and numerical results manifest that the primary/secondary performance of underlay spectrum sharing can be boosted by virtue of the average reduction of transmit powers/path-losses, uniform coverage/service, and macro-diversity gains, which are inherent to distributed transmissions/receptions of cell-free massive MIMO.

Clustering formation in cognitive radio networks using machine learning

The goal of spectrum sensing is to elevate the detection performance of secondary users (SUs) in a cognitive radio network (CRN). In cooperative spectrum sensing, all secondary users (SUs) of the network deliver their sensing measurement to the fusion center (FC) for the final decision regarding the activity of primary user (PU). The collaboration among large number of SUs might create overhead for the FC. To improve the performance of cooperative spectrum sensing, a novel method is proposed, which segregates the network into clusters. We have used artificial intelligence to make the clusters. The formation of clusters is made based on machine learning affinity propagation algorithm. Using proposed method, SUs share local messages with their neighbors until a highest class of cluster heads are chosen and a corresponding clustering configuration is made. The messages are evaluated depend on measures of similarity between the SUs, which are selected based on the objective of the clustering process. The sensing message of delimited number of SUs is shared with their cluster heads, which is ultimately shared with the FC for final decision. The proposed approach obtains the highest energy and performance efficiency in comparison with conventional clustering schemes.

Asymptotic Performance Analysis of Generalized User Selection for Interference-Limited Multiuser Secondary Networks

We analyze the asymptotic performance of a generalized multiuser diversity scheme for an interference-limited secondary multiuser network of underlay cognitive radio systems. Assuming a large number of secondary users and that the noise at each secondary user's receiver is negligible compared to the interference from the primary transmitter, the secondary transmitter transmits information to the $k$-th best secondary user, namely, the one with the $k$-th highest signal-to-interference ratio (SIR). We use extreme value theory to show that the $k$-th highest SIR converges uniformly in distribution to an inverse gamma random variable for a fixed $k$ and large number of secondary users. We use this result to derive asymptotic expressions for the average throughput, effective throughput, average bit error rate and outage probability of the $k$-th best secondary user under continuous power adaptation at the secondary transmitter, which ensures satisfaction of the instantaneous interference constraint at the primary receiver caused by the secondary transmitter. Numerical simulations show that our derived asymptotic expressions are accurate for different values of system parameters.

A New Energy Efficiency/Spectrum Efficiency Model for Cooperative Cognitive Radio Network

In this paper we study the resources access problem in cognitive radio networks, especially we are interested in the large number of secondary users (SUs). We establish a model based on channel access process when the PU (Primary User) is active, respecting the level of interference authorized by the operator. We study a system of cooperation between the SUs and the PUs to increase the performance of the system. SUs pass through an negotiation phase with the PUs for the acquisition of the underutilized channels with exceeded interference caused to the PU. The PU will support additional interference Δ but will benefit from the cooperation of SUs to relay its data. We model this cooperation as coalitional game.The utility function depends on two main parameters which are: transmission power and noise level. A distributed coalition formation algorithm is also proposed, which can be used by SUs to decide whether to join or leave a coalition. Such a decision is based on whether it can increase the maximal coalition utility value. We consider also the trade off between energy efficiency and the target throughput in the proposed cooperative relay network. The objective of this work is to validate the expected enhancement of the overall throughput of the network and also the energy efficiency while increasing the opportunity for SUs to access the licensed spectrum owned by PUs.

Multi-Objective Clustering Optimization for Multi-Channel Cooperative Spectrum Sensing in Heterogeneous Green CRNs

In this paper, we address energy efficient (EE) cooperative spectrum sensing policies for large scale heterogeneous cognitive radio networks(CRNs) which consist of multiple primary channels and large number of secondary users (SUs) with heterogeneous sensing and reporting channel qualities. We approach this issue from macro and micro perspectives. Macro perspective groups SUs into clusters with the objectives: 1) total energy consumption minimization; 2) total throughput maximization; and 3) inter-cluster energy and throughput fairness. We adopt and demonstrate how to solve these using the non-dominated sorting genetic algorithm-II. The micro perspective, on the other hand, operates as a sub-procedure on cluster formations decided by the macro perspective. For the micro perspectives, we first propose a procedure to select the cluster head (CH) which yields: 1) the best CH which gives the minimum total multi-hop error rate and 2) the optimal routing paths from SUs to the CH. Exploiting Poisson-Binomial distribution, a novel and generalized ${K}$ -out-of- ${N}$ voting rule is developed for heterogeneous CRNs to allow SUs to have different local detection performances. Then, a convex optimization framework is established to minimize the intra-cluster energy cost by jointly obtaining the optimal sensing durations and thresholds of feature detectors for the proposed voting rule. Likewise, instead of a common fixed sample size test, we developed a weighted sample size test for quantized soft decision fusion to obtain a more EE regime under heterogeneity. We have shown that the combination of proposed CH selection and cooperation schemes gives a superior performance in terms of energy efficiency and robustness against reporting error wall.

Multiuser-diversity-based interference alignment in cognitive radio networks

As a promising interference management technique, interference alignment (IA) has been applied to cognitive radio (CR) networks. However, the received signal-to-interference-plus-noise ratio (SINR) may decrease dramatically under some channel conditions in IA-based CR networks, and this will reduce the quality of service (QoS) of primary users (PUs). In this paper, we study the problem of SINR decrease and propose a multiuser-diversity-based IA scheme to make it more practical to be applied to CR networks. Since the number of secondary users (SUs) is changing dynamically in practical CR networks, we present two schemes targeted at two different scenarios. In the first scenario with a large number of SUs, the IA network cannot accommodate all the PUs and SUs simultaneously with perfect elimination of interferences. The corresponding scheme is to select those SUs, which can maximally improve the QoS of PUs, to access to the spectrum by forming an IA network with the PUs. Thus the performance of PUs can be significantly improved. To further ensure the interest of SUs, the scheme is revised and a tradeoff is made between the PUs and SUs. In the second scenario with a smaller number of SUs, the IA network can accommodate all the users simultaneously without mutual interference. User selection and antenna selection strategies are adaptively employed to guarantee the performance of PUs. Furthermore, fairness among SUs is also investigated. Simulation results are presented to show the effectiveness of the proposed schemes for CR networks.

A preload cooperative sensing scheme with low overhead in cognitive radio networks

AbstractIn cognitive radio networks (CRNs), users can collaborate to improve the accuracy of spectrum sensing, but a large number of secondary users reporting their local sensing results may create significant overhead. In this paper, we propose a new pre‐sensing scheme, called preload cooperative sensing (PCS), which not only attains the given sensing accuracy for CRNs but also reduces the whole sensing time T. In order to reduce the sensing overhead in CRNs, the proposed scheme adopts two key technologies: selective reporting technology and pre‐sensing sequential detection technology. Selective reporting technology implies that only those users, which detect the presence of primary users, need to report the results, while pre‐sensing sequential detection technology is an asynchronous parallel scheme, which sets a threshold to determine the presence of primary users. Considering the preload sensing slots, we derive a formula to express the overall miss detection probability, and at a given Quality of Service (QoS) value, the sensing overheads of PCS are analyzed over Rayleigh fading channel. Also, we consider the overhead minimization problems in PCS. Simulation results show the superiority and efficiency of the PCS scheme. Copyright © 2015 John Wiley & Sons, Ltd.

On the feasibility of indoor broadband secondary access to 960–1215 MHz aeronautical spectrum

ABSTRACTIn this paper, we analyse the feasibility of indoor broadband service provisioning using secondary spectrum access to the 960–1215 MHz band, primarily allocated to the distance measuring equipment (DME) system for aeronautical navigation. We propose a practical secondary sharing scheme customised to the characteristics of the DME. Because the primary system performs a safety‐of‐life functionality, protection from harmful interference becomes extremely critical. The proposed scheme controls aggregate interference by imposing an individual interference threshold on the secondary users. We examine the feasibility of large scale secondary access in terms of the transmission probability of the secondary users that keeps the probability of harmful interference below a given limit. Uncertainties in the estimation of propagation loss and DME location affect the feasibility of the secondary access. Numerical results show that a large number of secondary users are able to operate in adjacent DME channels without harming the primary system even with limited accuracy on the estimation of the propagation loss. Copyright © 2013 John Wiley & Sons, Ltd.

Outage analysis in presence of correlated interferers in a cognitive radio – CDMA network

In this paper, the outage performance of a primary user (PU) is evaluated analytically in presence of a large number of secondary users (SUs) in an underlay spectrum sharing architecture. We consider cognitive users in ad hoc mode using the spectrum licensed for a cellular CDMA network. We develop an analytical framework for evaluation of downlink interference in our proposed cognitive radio CDMA (CR-CDMA) networking model. A closed form expression for the probability of outage for a PU assuming correlation amongst interferences caused by co-channel BSs and SUs has been derived. We study the impact of SUs and several other parameters (of channel and network) on the outage probability for a PU. Analytical results are validated with simulation results.