Number Of Secondary Users Research Articles

Green Cooperative Spectrum Sensing and Scheduling in Heterogeneous Cognitive Radio Networks

In this paper, we consider heterogeneous cognitive radio networks (CRNs) comprising primary channels (PCs) with heterogeneous characteristics and secondary users (SUs) with various sensing and reporting qualities for different PCs. We first define the opportunity as the achievable total data rate and its cost as the energy consumption caused from sensing , reporting , and channel switching operations and formulate a joint spectrum discovery and energy efficiency objective to minimize the energy spent per unit of data rate. Then, a mixed integer non-linear programming problem is formulated to determine: 1) the optimal subset of PCs to be scheduled for sensing; 2) the SU assignment set for each scheduled PC; and 3) sensing durations and detection thresholds of each SU on PCs it is assigned to sense. Thereafter, an equivalent convex framework is developed for specific instances of the above combinatorial problem. For comparison, optimal detection and sensing thresholds are also derived analytically under the homogeneity assumption. Based on these, a prioritized ordering heuristic is developed to order channels under the spectrum, energy, and spectrum-energy limited regimes. After that, a scheduling and assignment heuristic is proposed and is shown to perform very close to the exhaustive optimal solution. Finally, the behavior of the CRN is numerically analyzed under these regimes with respect to different numbers of SUs, PCs, and sensing qualities.

Application of Extra Sensing by Stochastic-Modeled Secondary Users Over a Medium-Traffic Network

Status changing of the primary user and the number of secondary users (SUs) are crucial issues for designing a reliable cognitive radio network. In this paper, a medium-traffic primary network is assumed when SUs are stochastically distributed over an area around a secondary base station. By using cooperative spectrum sensing over Rayleigh-faded sensing and imperfect reporting channels, we propose an extra sensing part within the transmission phase of the secondary network in which only some SUs (called sensing SUs) participate in sensing. Although the extra sensing may suffer from interference by transmitting SUs, we show that the total transmission throughput of the system can be improved significantly due to better quality of the detection. Moreover, we reveal that involving all SUs in the extra sensing part does not necessarily increase the total throughput of the system.

Cumulative Cooperative Spectrum Sensing Scheme to Defend Against Selfish Users

Background/Objectives: This paper considers combatting the jamming and selfish attacks in Cognitive Radio (CR) networks operating at the white (unused) and grey (underused) spaces in the RF spectrum. CR facilitates effective utilization of RF spectrum resources but still vulnerable to various network attacks. Methods/Statistical Analysis: This study considered the jamming and selfish type of attack detection and to defend against them because of its severity. An Intrusion Detection System (IDS) is formed to combat the against jamming and selfish type of attacks in CR. Findings: In this system cumulative-sum algorithm is used, which incorpates the control centre information over the channel. The cumulative-sum based algorithm shows improved performance in provisioning better packet delivery ratio, throughput and minimum energy and packet drop. Further, this algorithms works better for more number of Secondary Users (SU), and the Unlicensed Users. Applications/Improvements: This work can be enhanced further by simulating under various network attacks and in the presence of numerous SU.

DCCC-MAC: A Dynamic Common-Control-Channel-Based MAC Protocol for Cellular Cognitive Radio Networks

We propose a novel dynamic common-control-channel-based medium access control (DCCC-MAC) protocol for cellular (centralized) cognitive radio (CR) networks. Specifically, unlike the traditional dedicated-control-channel-based medium access control (MAC) protocols, the proposed MAC protocol eliminates the requirement of a dedicated channel for control information exchange. During a given transmission frame, the common control channel (CCC) is selected by a cooperating set of secondary users (SUs) by using a support-vector-machine (SVM)-based learning technique. In the DCCC-MAC protocol, the frame duration is divided into four main phases as follows: spectrum sensing, CCC selection, data transmission, and beaconing. The SUs that participate in the CCC selection process are allocated channels for data transmission during a frame interval using a scheduling process, whereas the other SUs have to contend to access the channels. We present an analytical approach to calculate the minimum required number of minislots in the transmission frame for a given number of SUs in the CCC selection process. The saturation throughput of the proposed MAC protocol is analyzed in closed form. To this end, the numerical and simulation results are presented to quantify the performance of the proposed DCCC-MAC protocol. We also compare the performance of the DCCC-MAC protocol with that of two other state-of-the-art CR MAC protocols that use CCCs.

A Proposed Sub-optimal Power Allocation using Simulated Annealing in Cognitive Radio Networks

Due to the rapid demand for wireless services and the increase in the wireless device count, there is a lack of available spectrum bands which constrain the further development of wireless communication .Therefore, Cognitive Radio (CR) has been adopted as a promising solution because of its ability to exploit the inefficiently used spectrum of licensed bands. Orthogonal Frequency Division Multiplexing (OFDM) become the enabling technique for CR due to its flexibility of allocating the available spectrum in dynamic environment. In this paper, a proposed distributed resource allocation framework based on Simulated Annealing (SA) algorithm for downlink OFDM-Based Cognitive Radio Network (CRN) will be applied. This algorithm gives less computational complexity for maximizing the total SUs transmission capacity. Moreover, the interference introduced from other Secondary Users (SUs) will be considered. For the sake of comparison, Lagrange dual method will be used. Simulation results showed that the proposed algorithm gives a better transmission capacity compared with Lagrange dual method. The parameters which are considered for comparison are maximum transmitted power, number of Primary Users (PUs) and number of SUs.

Cooperative Spectrum Sharing in Cognitive Radio Networks: A Centralized Contracted-Based Approach

In this paper, we study the relay-based communication schemes for cooperative spectrum sharing among multiple primary users (PUs) and multiple secondary users (SUs) with incomplete information. Inspired by contract theory, we model the network as a labor market. In this market, PUs and SUs are regarded as employer and employee respectively. Each PU proposes certain contracts to attract the SUs, the contract include relay power and spectrum access time, each SU maximize its utility by selecting the most suitable contract. But PUs and SUs have conflicting objectives in contract content. To tackle this problem, we put forward to a centralized maximizing expectation utility scheme, which convert the optimal contract design into an optimization problem. After that, a approximate method for solving the optimization problem is proposed. Simulation results show that the losses of PUs’ total utilities caused by incomplete information and approximate algorithm are relatively small, especially when the number of SUs is very large.

MIMO Cognitive Radio Spectrum Sharing Using Spatial Coding and User Scheduling for Fading Channels

Spectrum scarcity is one of the issue in wireless communication. Dynamic spectrum sharing is the solution for this problem in which the underutilized spectrums are utilized efficiently. Multiple Input Multiple Output (MIMO) based cognitive radio using spatial coding is used to dynamically share the spectrum which allows simultaneous usage of spectrum by more than one user. The drawback of spatial coding is the achievable capacity get reduced with the increased number of cognitive users which limits the number of users to share the spectrum. In order to maximize the number of secondary users sharing the spectrum of the primary user, this paper presents a cluster based multiple primary and secondary user’s MIMO spatial coding which provides higher capacity. The entire network is divided into number of cluster based on the location such that each cluster will be interference free from other. Each cluster is designed with one primary user and many secondary users and a User Scheduling algorithm called Cluster Based Max Signal Power User Scheduling (CBMSPUS) is proposed to select two best secondary users in each cluster. Since the performance of spatial coder depends on the channel matrix, this paper analyze the spatial pre-coder under Rayleigh, Rican and Nakagami fading channels with multiple users and evaluate the capacity of users under CBMSPUS scheduling algorithm. The results show that the Nakagami fading channel achieves high capacity than others. Primary user calculated capacity is 10.8bits/HZ /channel at low SNR region and 14.2 bits/HZ/channel at high SNR region. The secondary user archives maximum capacity of 9.8bits/HZ /channel at low SNR and 13 bits/HZ/channel at high SNR. The Proposed Scheduling method offers maximum of 15dB gain comparing FIFO scheduling algorithm.

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.

Advanced Energy Detector Based Cooperative Spectrum Sensing In Cognitive Networks

Cognitive radio is a befitting hopeful technology for future. Spectrum sensing is the most critical function of cognitive radio. Most of the spectrums sensing processes proposed earlier become impractical at lower signal to noise ratio conditions. Paper presents advanced cooperative spectrum sensing technique used in cognitive radio (CR) systems. By spectrum sensing it detects the presence of a primary user (PU) on a concerned spectrum. The accuracy of spectrum sensing depends on both sensing time and number of sensing nodes (secondary users) participating in the sensing process. We derive the optimal number of secondary users for cooperative spectrum sensing based on adaptive threshold energy detection to minimize spectrum detection error in conventional as well as improved energy detector.

Interference Alignment With Frequency-Clustering for Efficient Resource Allocation in Cognitive Radio Networks

In this paper, we investigate the resource management problem in orthogonal frequency division multiplexing (OFDM) based multiple-input multiple-output (MIMO) cognitive radio (CR) systems. We propose performing resource allocation based on interference alignment (IA) in order to improve the spectral efficiency of CR systems without affecting the quality of service of the primary system. IA plays a role in the proposed algorithm to enable the secondary users (SUs) to cooperate and share the available spectrum, which leads to a considerable increase in the spectral efficiency of CR systems. However, IA based spectrum sharing is restricted to a certain number of SUs per subcarrier in order to satisfy the IA feasibility conditions. Accordingly, the resource allocation problem is formulated as a mixed-integer optimization problem, which is considered an $\mathcal{NP}$ -hard problem. To reduce the computational complexity of the problem, a two-phases efficient sub-optimal algorithm is proposed. In the first phase, frequency-clustering is performed in order to satisfy the IA feasibility conditions, where each subcarrier is assigned to a feasible number of SUs. Whenever possible, frequency-clustering stage considers the fairness among the SUs. In the second stage, the available power is allocated among the subcarriers and SUs without violating the constraints that limit the maximum interference induced to the primary system. Simulation results show that IA with frequency-clustering achieves a significant sum rate increase compared to CR systems with orthogonal multiple access transmission techniques.

On a Cognitive Radio Network's Random Access Game With a Poisson Number of Secondary Users

In this letter a random access algorithm based on game theory for cognitive radio networks with random number of secondary users is investigated. The scenario examines a non-cooperative game in which all the players are unaware of the total number of devices participating (population uncertainty). We proposed a scheme where failed attempts to transmit (collisions) are penalized and, consequently, the optimum penalization in mixed strategies is calculated. Furthermore, an analytical approximation for the corresponding Pareto fronts which maximizes the throughput of individual secondary users is obtained. Finally, the impact that the presence of primary users have on the optimal access strategy is assessed.

Ergodic Sum-Rate Maximization for Fading Cognitive Multiple-Access Channels Without Successive Interference Cancelation

In this paper, the ergodic sum rate of a fading cognitive multiple-access channel (C-MAC) is studied, where a secondary network (SN) with multiple secondary users (SUs) transmitting to a secondary base station shares the spectrum band with a primary user (PU). An interference power constraint (IPC) is imposed on the SN to protect the PU. Under such a constraint and the individual transmit power constraint (TPC) imposed on each SU, we investigate the power allocation strategies to maximize the ergodic sum rate of a fading C-MAC without successive interference cancelation (SIC). In particular, this paper considers two types of constraints: 1) average TPC and average IPC and 2) peak TPC and peak IPC. For the first case, it is proved that the optimal power allocation is dynamic time-division multiple access (D-TDMA), which is exactly the same as the optimal power allocation to maximize the ergodic sum rate of the fading C-MAC with SIC under the same constraints. For the second case, it is proved that the optimal solution must be at the extreme points of the feasible region. It is shown that D-TDMA is optimal with high probability when the number of SUs is large. Moreover, we show that when the SUs can be sorted in a certain order, an algorithm with linear complexity can be used to find the optimal power allocation.

Multichannel CSMA Based MAC Scheme for Unsaturated Cognitive Radio Networks: Performance Study of the Opportunity and Contention Window

In cognitive radio networks, secondary users (SUs) opportunistically utilize the spectrum without harmful interruption to the primary users (PUs). In this article, the overlay medium access control (MAC) scheme is considered in which SU uses the spectrum portion which is not utilized by PU. The imperfect sensing is considered at SU network (SUN) to detect PU's transmission. In the SUN, carrier sense multiple access protocol with contention window (CW) is used to minimize the collisions between SUs and PUs. Multichannel decentralized MAC protocol is investigated to analyse the throughput and examine the impact of various arrival rates of PUs (opportunities) and SUs, number of SUs, number of channels, and CWs. Numerical results verify various events and demonstrate the performance of the proposed MAC protocol under imperfect sensing conditions.

Bayesian Hierarchical Mechanism Design for Cognitive Radio Networks

This paper considers a cognitive radio network where the licensed network, referred to as the primary user (PU) network, consists of a hierarchical structure in which multiple operators coexist in the same coverage area where each of the operators controls an exclusive set of frequency sub-bands. Unlicensed users, referred to as the secondary users (SUs), first send their requests to the operators, and can only access the sub-bands controlled by the operators that accept their requests. SUs are selfish and cannot exchange private information with each other. We model the dynamic spectrum access (DSA) problem of the SUs as a Bayesian game, referred to as the DSA game. We model the PU network as a forest where the roots represent the operators and the leaves represent the operators' sub-bands. We propose a novel forest matching market to model the interaction between the SUs and the PU network. In this market, a set of SUs can be first matched to a set of operators and the SUs matched to the same operator can then be matched to the corresponding sub-bands. We propose a distributed algorithm that results in a stable forest matching structure, which coincides with the optimal Bayesian Nash equilibrium of the DSA game. We prove that the Bayesian hierarchical mechanism associated with our proposed algorithm incentivizes truth-telling by SUs. Our algorithm does not require each SU to know the preference and conflict-solving rule of the PU network or the payoffs and actions of other SUs, and the complexity of each iteration in the worst case is given by O(L <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> K) where L is the number of operators, N is the maximum number of sub-bands of each operator, and K is the number of SUs.

Performance study of a CSMA based multiuser MAC protocol for cognitive radio networks: analysis of channel utilization and opportunity perspective

In the overlay medium access control (MAC) of cognitive radio networks, secondary user (SU) uses the spectrum portion which is assigned to primary user (PU), when PU is not using this spectrum at that time. In this article, a multiuser overlay MAC protocol is considered in which PUs and SUs are using time division multiple access and carrier sense multiple access (CSMA) MAC schemes, respectively. Firstly, new frame format and algorithm for the proposed MAC protocol are described, then the analytical modelling of this protocol is explained. In the SU network, Markov chain model along with the CSMA protocol is used for better utilization of the opportunity from the PU network (PUN). Channel utilization and probability of success are also derived and analyzed for this protocol with respect to idle time, collision (failure) time, various spectrum opportunities from PUN, number of SUs, and their fairness. This MAC scheme provides the optimal solution for channel utilization under a constraint on the probability of collisions. Numerical results are also provided to validate analysis of proposed MAC protocol and to investigate the performance behaviour of the optimal solution.

Exact Outage Performance Analysis of Multiuser Multi-relay Spectrum Sharing Cognitive Networks

In this paper, we investigate the outage per- formance of dual-hop multiuser multi-relay cognitive ra- dio networks under spectrum sharing constraints. Using an efficient relay-destination selection scheme, the exact and asymptotic closed-form expressions for the outage proba- bility are derived. From these expressions it is indicated that the achieved diversity order is only determined by the number of secondary user (SU) relays and destinations, and equals to M + N (where M and N are the number of desti- nation nodes and relay nodes, respectively). Further, we find that the coding gain of the SU network will be affected by the interference threshold ¯ I at the primary user (PU) receiver. Specifically, as the increases of the interference threshold, the coding gain of the considered network approaches to that of the multiuser multi-relay system in the non-cognitive net- work. Finally, our study is corroborated by representative numerical examples.

Joint Resource Allocation for Throughput Enhancement in Cognitive Radio Femtocell Networks

In cognitive radio femtocell network (CRFN), secondary users (SUs) cooperatively sense a spectrum band to decide the presence of primary network. However, this sensing overhead generally degrades the throughput performance. The prior work, to resolve this problem, proposed algorithms either to decrease the time spent in sensing or to decrease the number of SUs participating in sensing. In this paper, we propose a joint resource allocation (RA) strategy considering the time and energy consumed for spectrum sensing to maximize the throughput while satisfying the target detection performance in CRFN. Furthermore, to reduce the resources used in spectrum sensing additionally, we also adopt the right censored order statistics based cooperative spectrum sensing scheme, which produces the criterion for deciding the set of reporting SUs. By so jointly designing the time and energy for sensing, the proposed joint RA scheme provides the improvement of spectral efficiency. Through simulation results, it is shown that the proposed joint RA scheme exhibits the enhanced performance over the conventional ones in terms of total throughput of secondary networks.

Distributed Uplink Power Control for Multi-Cell Cognitive Radio Networks

We present a distributed power control algorithm to address the uplink interference management problem in cognitive radio networks where the underlaying secondary users (SUs) share the same licensed spectrum with the primary users (PUs) in multi-cell environments. Since the PUs have a higher priority of channel access compared to the SUs, minimal number of SUs should be gradually removed, subject to the constraint that all primary users are supported with their target signal-to-interference-plus-noise ratios (SINRs), which is assumed feasible. In our proposed algorithm, each primary user rigidly tracks its target-SINR by employing the conventional target-SINR tracking power control algorithm (TPC). Each transmitting SU employs the TPC as long as the total received power at the primary receiver is below a given threshold; otherwise, it decreases its transmit power in proportion to the ratio between the given threshold and the total received power at the primary receiver, which is referred to as the total received-power-temperature. We show that our proposed distributed power-update function has at least one fixed-point. We also show that our proposed algorithm not only improves the number of supported SUs but also guarantees that all primary users are supported with their (feasible) target-SINRs. Finally, we also propose an enhanced power control algorithm that achieves zero-outage for PUs and a better outage ratio for SUs. To this end, we provide a robust power control method that considers the uncertainties in channel gains.

On the Stability of Dynamic Spectrum Access Networks in the Presence of Heavy Tails

The heavy-tailed nature in dynamic spectrum access networks challenges the applicability of conventional network stability criterion. To counter this problem, a new stability criterion, namely moment stability, is introduced, which requires that all secondary users (SUs) with light-tailed traffic have bounded queueing delay with finite mean and variance. This stability criterion can prevent heavy-tailed traffic, e.g., video and Internet traffic, from degrading the QoS performance of light-tailed ones, e.g., email deliveries and audio/voice traffic. The critical conditions for the existence of a scheduling policy to achieve moment stability are derived. The network stability region yielded from these conditions is shown to be directly related to the primary and secondary user activities, the number of SUs, and the total number of primary user channels available to SUs. Moreover, it is shown that the maximum-weight- $\alpha$ scheduling algorithm, which makes the scheduling decision based on the queue lengths raised to the $\alpha$ -th power, is throughput optimal with respect to moment stability. It is proven that its throughput optimality holds independent of the stochastic properties of SU traffic including its marginal distribution (i.e., heavy-tailed or light-tailed distribution) and its time correlation structure (i.e., long range or short range dependence).

Spectrum Sharing in Cognitive Radio Work Using Goodput Mathematical Model for Perfect Sensing, Zero Interference and Imperfect Sensing, Non Zero Interference

In recent years, there has been increase in the demand for spectrum allocation as wireless communication witness rapid growth on a daily basis. Literatures have established that this spectrum is scarce and more than 70% of the available spectrum is not utilized optimally. This paper proposes a model called Goodput model by which the under-utilized spectrum can be shared effectively between primary users and the secondary users without causing harmful interference between the users and also find solution to the problem of increasing demand for spectrum allocation on an already scarce spectrum. Goodput is a mathematical modeling in which the total amount of primary and secondary data that is successfully delivered per unit time can be used as performance index. Compared to other models, the Goodput model with zero interference, perfect sensing and imperfect Sensing, non-zero interference is used to determine the secondary users that will be able to use unoccupied portion of radio frequency channel of primary users with different values of data probability of arrival. Result shows that, the point of intersection between np and N(1-p) is the optimum point of interference, where n,N,and p are number of secondary users, number of primary users, and Probability of data arrival rate respectively. Below the optimum point of interference (left side of the point), all the secondary users will transmit opportunistically without interference. However, above the optimum point of interference (right side of the point), there will be interference between any secondary users that attempt to transmit.