Mobile Secondary Users Research Articles

Federated and Online Dynamic Spectrum Access for Mobile Secondary Users

Users in dynamic spectrum access (DSA) with federated reinforcement learning (FRL) autonomously access channels, avoiding centralized coordination and protecting users’ privacy. However, existing FRL-based DSA mechanisms are limited to ideal network states, i.e., assuming that channel states and users’ interference relationships are unchanged. Besides, users should upload intermediate results simultaneously for federated aggregation. The above conditions are impractical for mobile users since their network states and locations are unstable. Meanwhile, newly connected users have to train their models through local data with numerous computing resources since global models are unsuitable for them. We propose FRDSA, an FRL-based secure and lightweight channel selection mechanism in DSA for mobile users under dynamic network states. An independent channel selection environment with a virtual group strategy is presented to avoid interference between users under unstable channel states. Furthermore, an asynchronous parameter aggregation method in FRDSA dynamically adjusts the aggregation factors without users simultaneously uploading intermediate results. Simulations based on real trajectory data show that FRDSA significantly reduces approximately 60% interference between mobile users under unstable network states. Newly connected users can directly apply the well-trained global model to access channels autonomously instead of retraining a model, effectively reducing mobile users’ computing resource requirements.

On Sensing Performance of Multi-Antenna Mobile Cognitive Radio Conditioned on Primary User Activity Statistics

In limited space scenarios, the antennas in a multiantenna cognitive radio (CR) system are closely spaced and often experience correlation among them. In this paper, the sensing performance of arbitrarily correlated antennas over the Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> fading channel for the mobile CR user is analysed. In particular, the analytical expression for the average detection probability for a mobile CR user employing the selection combining with arbitrarily correlated triple diversity branches is derived as a special case. Moreover, to characterize the performance of an energy detector under mobility, the area under the curve of a receiver operating characteristic is analysed. Furthermore, as the sensing decisions can be utilized to improve the sensing performance, a comprehensive analysis of sensing performance of the mobile secondary user conditioned on the primary user (PU) activity statistics is carried out. We assume the PU traffic to be following the Discrete-Time Markov Chain (DTMC) model, and its <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$idle$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$busy$ </tex-math></inline-formula> periods to be following generalised Pareto distribution. The analytical framework is substantiated by Monte Carlo simulations. Results indicate that antenna correlation deteriorates detection performance. Moreover, the detection performance deteriorates further due to the mobility of CR users, especially in the deep fading channel scenarios. Furthermore, findings also suggest that under mobility, the sensing performance improves if the duty cycle of the PU channel is low. This work provides a realistic sensing framework for CR enabled vehicles.

Impact of Primary User Activity Statistics in Cognitive Vehicular Networks

Due to the scarcity of channel availability in IEEE 802.11p standard, applications related to infotainment and multimedia services are vulnerable to suffer from delays and connectivity. Cognitive radio (CR) has the potential to overcome the issue of spectrum scarcity. By making use of the CR technology, secondary users (SU) can access a radio frequency spectrum other than 802.11p through spectrum sensing. Majority of low complex existing algorithms are based on energy detection that are considering the static environment of SUs. In practice, the algorithms, which considers mobility are mainly focused on low vehicle speed. However, the combined effect of primary user (PU) activity statistics and SU mobility has not been tackled while evaluating the performance of opportunistic spectrum access. In particular, this work considers the joint impact of PU activity and vehicle mobility on spectrum sensing performance by considering single lane and double lane vehicular scenarios. We also evaluate the impact of traffic densities on sensing performance. The main contribution of this work is to show the impact of PU activity statistics on sensing performance by deriving analytical expressions for miss-detection probability. These expressions are used for analysis and simulation of cognitive radio enabled vehicular communications. From our observations, it is noted that the probability of vehicle connectivity is improved approximately by 50 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> for initial distance of SU when spectrum sensing is employed under PU activity.

Design and implementation of a novel two-phase spectrum handoff scheme for QoS aware mobile users in cognitive radio networks

Quality of Service (QoS) aware spectrum handoff operation is critical for Secondary Users (SUs) executing real-time applications like Voice over IP (VoIP) in Cognitive Radio Networks (CRNs). The problem is aggravated by the inclusion of occasionally mobile SUs where pre-selected target channels are often rendered insignificant during handoff under dynamic conditions. Conventional proactive and reactive schemes may underperform due to channel obsolescence issues and unacceptable handoff latency respectively while a combined approach is not yet explored under the constraints of practical applicability. In view of these challenges and enormous significance of VoIP based CRN in 5G networks, this paper proposes a practically feasible two-phase spectrum handoff methodology with I_Phase and S_Phase operating under alternate conditions. I_Phase deploys a three-level dropping decision scheme followed by a two-tier spectrum handoff policy and is motivated by an integrated approach spanning every CR operation. S_Phase incorporates user mobility and application-oriented aspects where channel drop is governed by a joint two-order Hidden Markov Model — custom Damerau–Levenshtein distance metric based policy and spectrum handoff is monitored by a novel non-cooperative TOPSIS method. These phases are assisted by two proposed prerequisite techniques namely ACT (Adaptive Call Transmission) involving CR timing parameters and VER (VoIP Early Resumption) dealing with early call resumption. Comparative analysis of QoS metrics including per-instance handoff latency, transmission duration per target channel, channel drop and call drop probabilities, etc. in analytical and simulation platforms record significant performance improvement. Novelty of this work further relies on design and execution of SU prototype with the proposed scheme in test-bed that successfully provides QoS guarantees during spectrum handoff.

Second order Kalman filtering channel estimation and machine learning methods for spectrum sensing in cognitive radio networks

We address the problem of spectrum sensing in decentralized cognitive radio networks using a parametric machine learning method. In particular, to mitigate sensing performance degradation due to the mobility of the secondary users (SUs) in the presence of scatterers, we propose and investigate a classifier that uses a pilot based second order Kalman filter tracker for estimating the slowly varying channel gain between the primary user (PU) transmitter and the mobile SUs. Using the energy measurements at SU terminals as feature vectors, the algorithm is initialized by a K-means clustering algorithm with two centroids corresponding to the active and inactive status of PU transmitter. Under mobility, the centroid corresponding to the active PU status is adapted according to the estimates of the channels given by the Kalman filter and an adaptive K-means clustering technique is used to make classification decisions on the PU activity. Furthermore, to address the possibility that the SU receiver might experience location dependent co-channel interference, we have proposed a quadratic polynomial regression algorithm for estimating the noise plus interference power in the presence of mobility which can be used for adapting the centroid corresponding to inactive PU status. Simulation results demonstrate the efficacy of the proposed algorithm.

Analysis of spectrum handoff schemes for cognitive radio networks considering secondary user mobility

Analysis of spectrum handoff schemes for cognitive radio networks considering secondary user mobility

Analysis of spectrum handoff schemes for cognitive radio networks considering secondary user mobility

Cognitive radio has been proposed as an intelligent wireless communication system towards the usage of dynamic spectrum access in next generation networks, where the primary users (PU) and secondary users (SU) can share the spectrum, while causing minimum interference to each other. Spectrum mobility is the main element for the effective execution of cognitive radio networks. Spectrum mobility can be achieved by means of spectrum handoff (SHO). Initially, SUs continuously sense the channels to identify an idle channel. Error in sensing channel is possible. A detection theory is put forth to analyse the spectrum-sensing errors with the receiver operating characteristic (ROC) considering false alarm probability, missed detection and detection probability. Also, we meticulously investigate and analyse the probability of spectrum handoff (PSHO) with lognormal-3 and Hyper-Erlang distribution models considering SU call duration and residual time of spectrum holes availability designed for tele-traffic analysis.

Secrecy outage probability of inter‐vehicular cognitive radio networks

SummaryHerein, we consider an underlay cognitive radio network (CRN) where mobile secondary user wishes to transmit a confidential information to the secondary destination in the presence of an illegitimate eavesdropper which is trying to steal the classified message signal. The proposed scenario can be viable for a secondary safety task force working with a primary regiment, which wishes to transmit the confidential information to the commander while an eavesdropper is trying to intercept the classified information. In the analysis, two novel power allocation methods are considered by assuming perfect and limited feedback channels of the primary network, and for both methods, exact and asymptotic expressions of secrecy outage probability (SOP) are derived for N*Nakagami‐m fading channels which are used to model fading channels such as mobile‐to‐mobile/vehicle‐to‐vehicle communication systems where the nodes are moving into a rich scattering environment. We further verified our analytic results through Monte‐Carlo simulations. It is shown from the numerical results that the cascading degree of the channels has a worsening effect on the secrecy outage performance of the CRN systems.

A novel cloud based self-adaptive cognitive radio network architecture

The constraints of battery, data processing and memory in mobile Secondary User (SU) in a Cognitive Radio Network (CRN) make it essential to move the spectrum sensing functionality from the SUs to the network. The cloud performing the role of the earlier defined “Spectrum Agent” or “Spectrum Monitoring Device” has a scope of taking up the computational tasks of spectrum sensing and path selection. The paper presents a novel cloud based self-adaptive network architecture for a multi-hop cognitive radio system including its communication protocol. A new method of optimal multi-hop relay selection based on Critical Path Method (CPM) is also introduced for execution in the cloud having network connectivity information. The proposed network architecture and relay selection scheme is analyzed and the performance tested with respect to the reported methods to show its strength in terms of end-to-end delay and reliability. A closed-form expression of outage probability of failed transmission for a generic multi-hop network is also analytically derived and used for testing the reliability of the proposed architecture. The results are encouraging to extend the use of CRN in dynamic environment of large deployment areas.

Perfromance Analysis of aTree Routing Protocol for Cognitive Radio Network Under Impact of Different Primary User Activity Patterns.

The mistakes in the spectrum management have drive to a problem of the scarcity of spectrum,which can be solved through the use of Cognitive Radio (CR) technology. The main concept of CRtechnology allows unauthorized users (secondary users (SUs))for using the spectrum resources forcommunication without harm authorized users (primary users (PUs)).The traditional wireless networks,the nodes are connected based on a centralized infrastructure. But in Cognitive Radio Ad Hoc Network(CRAHN) Networks, mobile SUs nodes are connected to each other without a central infrastructure.Routing in CRAHNs is an important and necessary process in CRAHNs. It faces many and variouschallenges. These challenges include PUs intervention, frequently dynamic topology, energyconsumption problems, unavailable channels, and fragile connections between nodes. The our probasedrouting protocol called A tree routing protocol for cognitive radio network (C-TRP) has utilized the treerouting algorithm with a spectrum management module in one routing decision module. In this paper,weevalute a performance of the tree routing protocol (C-TRP) under the influence of the different PUsactivity patterns with help of three performance metrics :hop count, the number of CR nodes and numberof available channels. The performance evaluation is evaluted using NS-2 simulator. Simulation resultsconfirm that C-TRP outperforms “spectrum-tree based on demand routing protocol for multi-hopcognitive radio networks”(STOD-RP), and Cognitive Tree-based Routing(CTBR) in terms of packetdelivery ratio and causes less harmful interference to PR nodes, and also less end-to-end delay in allprimary radio nodes activity patterns.

Cognitive MIMO-RF/FSO Cooperative Relay Communication With Mobile Nodes and Imperfect Channel State Information

This paper analyzes the performance of an underlay cognitive radio based decode-and-forward mixed multiple-input multiple-output radio frequency/free space optical cooperative relay system with multiple mobile secondary and primary user nodes. The effect of imperfect channel state information (CSI) arising due to channel estimation error is also considered at the secondary user transmitters (SU-TXs) and relay on the power control and symbol detection processes respectively. A unique aspect of this paper is that both fixed and proportional interference power constraints are employed to limit the interference at the primary user receivers. Analytical results are derived to characterize the exact and asymptotic outage and bit error probabilities of the above system under practical conditions of node mobility and imperfect CSI, together with impairments of the optical channel, such as path loss, atmospheric turbulence, and pointing errors, for orthogonal space-time block coded transmission between each SU-TX and relay. Finally, simulation results are presented to yield various interesting insights into the system performance such as the benefits of a midamble versus preamble for channel estimation.

Impact of secondary user mobility on spectrum handoff under generalized residual time distributions in cognitive radio networks

Cognitive Radio is an emerging technology to accommodate the growing demand for wireless technology via dynamic spectrum access to enhance spectrum efficiency. Spectrum handoff is an important component of Cognitive Radio technology for practical implementation of radio frequency access strategy and better utilization of spectrum in both primary and secondary networks. The probability of spectrum handoff and expected number of spectrum handoffs are key parameters in performance analysis and design of the cognitive radio network. This work presents an analytical model to evaluate the impact of secondary users’ mobility on intra-cell spectrum handoff considering primary users’ activity model in a cognitive radio network. A standard form of intra-cell spectrum handoff probability and expected number of intra-cell spectrum handoffs are derived for complete call duration of a non-stationary secondary user. The probability and expected number of intra-cell spectrum handoffs of a post inter-cell handoff call are also derived for generalized residual time distributions of call holding time and spectrum holes. A detailed analysis of these performance measuring metrics is presented under the impact of departure rate and cell crossing rate of secondary users. The accuracy of the derived analytical result is validated by Monte-Carlo simulation of the model.

Anti-Shadowing Resource Allocation for General Mobile Cognitive Radio Networks

Resource allocation (RA) for mobile secondary users is considered one of the most important techniques for designing the next-generation cognitive radio network (CRN). In this paper, effective capacity (EC) is proposed to improve the RA performance for an underlay-based mobile CRN. By optimizing EC, an efficient resource allocation scheme is developed. First, we consider a moving secondary system, where the channel state information can be predicted by location-awareness techniques. According to the prediction result, we set protecting parameters for both the secondary and the primary performance targets to minimize the prediction error introduced by the decorrelated shadowing. Second, the computed sum average EC of the cognitive system is maximized. To solve the optimization RA problem, a low-complexity stepwise algorithm is proposed based on four procedures aimed at access, initialization, subchannel, and power. Moreover, the speeds of the primary users are taken into account, and a general system model is built. The corresponding resource allocation solutions can be induced easily through extending the originally proposed solution. Finally, simulation results are provided to confirm the EC-based algorithm. The proposed approach can not only improve the total secondary capacity but also achieve higher energy efficiency and spectrum efficiency for the mobile secondary system.

Optimal Guard Distance for Maximizing Spatial-Temporal Spectrum Access Opportunity in Mobile CRNs

Cognitive radios have demonstrated its ability in improving spectrum efficiency. Along with the popularity of mobile broadband devices in future mobile communications, research for cognitive radios with mobility will be paid more and more attentions. In a mobile cognitive radio network, we derived the analytical expression for the dynamic spectrum access opportunity of secondary users in spatial and temporal dimensions. Through maximizing the spatial-temporal opportunity, we obtained the closed-form solution of the optimal guard distance, which is a key part of primary protection region against the mobile secondary users’ interference. Numerical results verified the accuracy and correctness of our theoretical analysis, and indicated that using our solution the secondary user has more spatial-temporal opportunity than the existing research result.

Performance of improved energy detector with cognitive radio mobility and imperfect channel state information

A cooperative cognitive radio (CR) network with multiple secondary users (or CRs) is considered. Each CR consists of an arbitrary M number of antennas. For spectrum sensing, at each CR, an improved energy detector with selection combining mechanism is assumed. Moreover, the impact of secondary user mobility on the performance of spectrum sensing is analysed. Specifically, the expression for received signal at destination is derived considering the imperfect channel state information in Rayleigh fading environment. The authors derive the expression for probability of false alarm and miss detection using arbitrary power p-based improved energy detector and analyse the error performance of the system. The area under receiver operating characteristics curve is also obtained. Simulation results are provided to verify the analysis presented in this study.

Cluster-CMSS: A Cluster-Based Coordinated Spectrum Sensing in Geographically Dispersed Mobile Cognitive Radio Networks

A coordinated multiband spectrum sensing (CMSS) policy for mobile and geographically dispersed cognitive radio networks (CRNs), referred to as cluster-CMSS, is proposed. The goal is to detect the spectrum holes and to assign each secondary user (SU) a sensing channel with the maximum probability of being empty. In geographically dispersed CRNs, channel availability varies over the space, and this makes the sensing outcomes and sensing assignments location dependent. However, if the SUs are not equipped with location-finding technologies, fusing the sensing outcomes to find the optimal spectrum sensing assignments for the next sensing time becomes challenging for the base station (BS). To tackle this problem, we introduce a metric solely based on the sensing outcomes of SUs. Using this metric, along with a low-complexity clustering algorithm, enables the BS to efficiently divide the network into clusters. Further, we present an adaptive learning algorithm, to learn the dynamic behavior of channel occupancy in the primary network. The proposed learning algorithm considers SUs mobility model to determine the optimal learning window. To determine the sensing assignments, the BS performs a graph-theory-based coordinated multiband spectrum sensing within each cluster. Specifically, a weighted bipartite matching is employed. We have shown that cluster-CMSS significantly increases the spectrum opportunity discovery ratio for SUs at the cost of a slight increase in the energy consumption associated with spectrum sensing.

Reputation-based cooperative spectrum sensing algorithm for mobile cognitive radio networks

Identifying malicious users accurately in cognitive radio networks (CRNs) is the guarantee for excellent detection performance. However, existing algorithms fail to take the mobility of secondary users into consideration. If applied directly in mobile CRNs, those conventional algorithms would overly punish reliable users at extremely bad or good locations, leading to an obvious decrease in detection performance. To overcome this problem, we divide the whole area of interest into several cells to consider the location diversity of the network. Each user's reputation score is updated after each sensing slot and is used for identifying whether it is malicious or not. If so, it would be removed away. And then our algorithm assigns users in cells with better channel conditions, i.e. larger signal-to-noise ratios (SNRs), with larger weighting coefficients, without requiring the prior information of SNR. Detailed analysis about the validity of our algorithm is presented. The simulation results show that in a CRN with 60 mobile secondary users, among which, 18 are malicious, our solution has an improvement of detection probability by 0.97-dB and 3.57-dB when false alarm probability is 0.1, compared with a conventional trust-value-based algorithm and a trusted collaborative spectrum sensing for mobile CRNs, respectively.

Detection performance analysis of spectrum sensing in cognitive radio networks with mobile secondary users

The majority of existing papers about spectrum sensing have the assumption that secondary users (SUs) are stationary. However, mobility is an essential feature of mobile communications networks. In this paper, the detection performance of spectrum sensing by mobile SUs was analyzed. Three performance metrics, i.e., detection probability, miss detection probability and false alarm probability, were thoroughly investigated. In our analysis, a critical variable was the real-time received primary user signal power by a mobile SU. Its probability distribution and mathematical expectation were analytically derived. Moreover, the three performance metrics in single-node spectrum sensing and multi-node collaborative spectrum sensing systems were also derived. Extensive simulations were performed. The results are consistent with the theoretical analysis. And it is concluded that SU mobility has a significant impact on the detection probability and the miss detection probability, but not on the false alarm probability.

Spatial-Temporal Spectrum Access Analysis for Multi-Channel Mobile Cognitive Radio Networks

Cognitive radios have demonstrated its ability in improving spectrum efficiency by accessing licensed spectrum bands opportunistically. Along with the popularity of mobile broadband devices in future mobile communications, research for cognitive radios with mobility will be paid more and more attentions. In this paper, a multi-channel cognitive radio network with mobile secondary users is investigated. Based on the reality that the primary licensed channels have different available states on spatial and temporal dimensions for secondary users, we analyze the spatial-temporal spectrum utilization rate and derive the network throughput of secondary users combined with successful probability of wireless transmission. Finally, through maximizing the throughput we obtain the optimal spectrum access strategy. Numerical results show the effect of the system parameters on the proposed strategy and verify our proposed strategy outperforms other strategies such as equiprobable, inverse proportional and random access strategies.

A Topology Control and Routing Method in MCRNs Based on Power Consumption and Link Stability

In this paper, we study topology control and routing issues in mobile cognitive radio networks and propose local cognitive topology control algorithm (LCTCA) to provide the optimal network topology for routing. LCTCA combines link availability with link power consumption to form a multiobjective metric of network topology and routing optimization. The link availability prediction is aware of the interference from secondary users to primary users, the spectrum utilization of primary users, the mobility of secondary users and primary users. Based on the link availability and the power consumption, LCTCA captures the dynamic changes of the topology and constructs a reliable topology under the conditions of network connectivity, which is aimed at selecting the optimal network path and mitigating frequently rerouting. We further analyze the effect of power consumption and link stability on cognitive radio network path selection. Simulation investigation is also provided to verify the theoretical analysis. It shows that the link power consumption and the link stability are both important when selecting the network path.