Number Of Secondary Users Research Articles

Turning foes to allies in cognitive radio networks

We study a class of problems in Cognitive Radio Networks where multiple half-duplex unlicensed (secondary) users can eavesdrop and jam the communications of licensed (primary) users unless granted access to communicate over the same spectrum band. The problem is to characterize the optimal rule for the primary system that grants spectrum access to selected secondary users and the optimal resource allocation for the secondary users. We model the problem as a Stackelberg game with the primary system as the leader. The equilibrium analysis shows that it is not always optimal to grant access to the strongest eavesdroppers. In addition, it is shown that transmitting secondary users can limit the eavesdropping capabilities of other secondary users, possibly leading to improved primary secure transmission data rate. Thus, interestingly, the outcome reveals a recruiting process that turns selected eavesdroppers into helping jammers under certain conditions. Finally, we propose a low complexity algorithm to select a subset of secondary users for transmission and evaluate the performance of the primary system when different number of secondary users are granted access through simulations.

Design and Analysis of Distributed Hopping-Based Channel Access in Multi-Channel Cognitive Radio Systems with Delay Constraints

To support delay-sensitive traffic in multi-channel cognitive radio systems, designing a channel access scheme faces two major challenges, namely, the long waiting time due to continuous channel occupancy of primary users (PUs) and the performance degradation due to transmission collisions among secondary users (SUs). To address both issues, we propose a two-phase channel access scheme, which consists of a distributed channel negotiation phase and a hopping-based channel access phase for each SU. Specifically, in its first phase, an SU attempts to negotiate a specific initial slot/channel differing from the ones chosen by other SUs. Then, in its second phase, the SU chooses a channel in each time slot in a hopping-based manner to transmit data, where the hopping starts from its initial channel and follows a common hopping sequence. Virtual channels are introduced to accommodate the situation when the number of SUs is larger than that of actual channels. The average maximal waiting time due to the channel negotiation phase is derived, and the effective capacity of the service process for each SU in the channel access phase is analyzed. Numerical results show that the proposed scheme can support a higher traffic load under the statistical delay constraint, as compared with fixed or random channel access schemes.

A Generalized Markovian Based Framework for Dynamic Spectrum Access in Cognitive Radios

Radio spectrum is a precious resource and characterized by fixed allocation policy. However, a large portion of the allocated radio spectrum is underutilized. Conversely, the rapid development of ubiquitous wireless technologies increases the demand for radio spectrum. Cognitive Radio (CR) methodologies have been introduced as a promising approach in detecting the white spaces, allowing the unlicensed users to use the licensed spectrum thus realizing Dynamic Spectrum Access (DSA) in an effective manner. This paper proposes a generalized framework for DSA between the licensed (primary) and unlicensed (secondary) users based on Continuous Time Markov Chain (CTMC) model. We present a spectrum access scheme in the presence of sensing errors based on CTMC which aims to attain optimum spectrum access probabilities for the secondary users. The primary user occupancy is identified by spectrum sensing algorithms and the sensing errors are captured in the form of false alarm and mis-detection. Simulation results show the effectiveness of the proposed spectrum access scheme in terms of the throughput attained by the secondary users, throughput optimization using optimum access probabilities, probability of interference with increasing number of secondary users. The efficacy of the algorithm is analyzed for both imperfect spectrum sensing and perfect spectrum sensing.

The asymptotic throughput and connectivity of cognitive radio networks with directional transmission

Throughput scaling laws for two coexisting ad hoc networks with m primary users (PUs) and n secondary users (SUs) randomly distributed in an unit area have been widely studied. Early work showed that the secondary network performs as well as stand-alone networks, namely, the per-node throughput of the secondary networks is $\Theta (1/\sqrt {n \log n})$. In this paper, we show that by exploiting directional spectrum opportunities in secondary network, the throughput of secondary network can be improved. If the beamwidth of secondary transmitter (TX)'s main lobe is $\delta = o(1/ \log n)$, SUs can achieve a per-node throughput of $\Theta (1/\sqrt {n \log n})$ for directional transmission and omni reception (DTOR), which is $\Theta (\log n)$ times higher than the throughput without directional transmission. On the contrary, if $\delta = \omega (1/ \log n)$, the throughput gain of SUs is 2π/δ for DTOR compared with the throughput without directional antennas. Similarly, we have derived the throughput for other cases of directional transmission. The connectivity is another critical metric to evaluate the performance of random ad hoc networks. The relation between the number of SUs n and the number of PUs m is assumed to be n = mβ. We show that with the HDP-VDP routing scheme, which is widely employed in the analysis of throughput scaling laws of ad hoc networks, the connectivity of a single SU can be guaranteed when β > 1, and the connectivity of a single secondary path can be guaranteed when β > 2. While circumventing routing can improve the connectivity of cognitive radio ad hoc network, we verify that the connectivity of a single SU as well as a single secondary path can be guaranteed when β > 1. Thus, to achieve the connectivity of secondary networks, the density of SUs should be (asymptotically) bigger than that of PUs.

Cognitive beamhopping for spectral coexistence of multibeam satellites

SUMMARYHerein, the spectral coexistence scenario of two multibeam satellites over a common coverage area is studied where a primary satellite produces larger beams while a secondary satellite has smaller beams. A novel cognitive beamhopping satellite system is proposed assuming that the secondary gateway is aware of the primary's beamhopping pattern. The performance of the proposed system is evaluated and compared with that of conventional multibeam and beamhopping systems in terms of throughput. It is shown that the proposed system significantly enhances the spectral efficiency (SE) in comparison to other systems. Furthermore, a power control technique is applied on the secondary transmission in order to adhere to the primary's interference constraint. It is noted that the total SE increases with the number of secondary users in the full frequency reuse approach. Moreover, the exclusion zone (EZ) principle is applied to exploit the regions in which the secondary system can operate without causing harmful interference to the primary system. It is shown that the EZ radius of 8.5 dB is sufficient to protect the primary system perfectly with a significant gain in SE. Finally, it is shown that power control and the EZ methods are suitable for lower and higher values of secondary aggregated interference, respectively. Copyright © 2014 John Wiley & Sons, Ltd.

Connectivity-based Performance Evaluation for Mobile Cognitive Radio Network

In this paper, we propose a model of mobile cognitive radio network after fully considering the analysis method of network connectivity based on random way-point (RWP) mobility scheme. The closed-form solution of connectivity probability has been derived to evaluate the network performance in this model. And it shows that the network connectivity is related to the size of mobile cognitive radio network, the number of secondary users, the transmission range of secondary users and primary users, the interference range of secondary users and primary users, the number of primary users and the activity factor of primary users. Simulation results are good agreement with numerical results, which verifies our theoretical analysis is correct and reasonable.

Handoff Delay-Based Call Admission Control in Cognitive Radio Networks

In this paper, we investigate how to achieve call admission control (CAC) for guaranteeing call dropping probability QoS which is caused by handoff timeout in cognitive radio (CR) networks. When primary user (PU) appears, spectrum handoff should be initiated to maintain secondary user (SU)'s link. We propose a novel virtual queuing (VQ) scheme to schedule spectrum handoff requests sent by multiple SUs. Unlike the conventional first-come-first-served (FCFS) scheduling, resuming transmission in the original channel has higher priority than switching to another channel. It costs less because it avoids the cost of signaling frequent spectrum switches. We characterize the handoff delay on the effect of PU's behavior and the number of SUs in CR networks. And user capacity under certain QoS requirement is derived as a guideline for CAC. The analytical results show that call dropping performance can be greatly improved by CAC when a large amount of SUs arrives fast as well as the VQ scheme is verified to reduce handoff cost compared to existing methods.

A Hybrid Combination Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks

We propose a novel hybrid combination scheme in cooperative spectrum sensing (CSS), which utilizes the diversity of reporting channels to achieve better throughput performance. Secondary users (SUs) with good reporting channel quality transmit quantized local observation statistics to fusion center (FC), while others report their local decisions. FC makes the final decision by carrying out hybrid combination. We derive the closed-form expressions of throughput and detection performance as a function of the number of SUs which report local observation statistics. The simulation and numerical results show that the hybrid combination scheme can achieve better throughput performance than hard combination scheme and soft combination scheme.

Asymptotic capacity analysis in multipoint-to-point cognitive radio networks with an arbitrary peak power

In this paper, we investigate the capacity of a multipoint-to-point cognitive radio network. In existing works, the asymptotic capacity is only obtained in the high peak power region at secondary transmitter (ST) or obtained without considering the interference from primary transmitter (PT) for easy analysis. Here, we analyze the asymptotic capacity by considering an arbitrary peak power at the ST and the interference from the PT based on extreme value theory. Simulation results show that our approximated capacity is well-matched to the exact capacity. Furthermore, the scaling law of our capacity is found to be double logarithm of the number of secondary users.

Optimal power allocation for green cognitive radio: fractional programming approach

In this study, the problem of determining the power allocation that maximises the energy efficiency of cognitive radio network is investigated as a constrained fractional programming problem. The energy-efficient fractional objective is defined in terms of bits per Joule per Hertz. The proposed constrained fractional programming problem is a non-linear non-convex optimisation problem. The authors first transform the energy-efficient maximisation problem into a parametric optimisation problem and then propose an iterative power allocation algorithm that guarantees e-optimal solution. A proof of convergence is also given for the e-optimal algorithm. The proposed e-optimal algorithm provide a practical solution for power allocation in energy-efficient cognitive radio networks. In simulation results, the effect of different system parameters (interference threshold level, number of primary users and number of secondary users) on the performance of the proposed algorithms are investigated.

Interference alignment and cancellation based concurrent transmission and scheduling scheme for multiuser CR-MIMO system

In this paper, an Interference Alignment and Cancellation (IAC) based transmission and scheduling scheme is proposed for an infrastructured Cognitive Radio (CR) Multiple-Input Multiple-Output (MIMO) system with multiple secondary users. With the cooperation of Primary Base Station (PBS) and Secondary Base Station (SBS), a signal processing procedure is designed to guarantee the priority of the primary transmission. As a reward for offering help to the PBS, the SBS is granted communication opportunity. The transmission difference of various spatial channels is exploited in Secondary User (SU) scheduling. With the proposed scheme, interference-free concurrent transmission of both PBS and SBS is implemented. Spatial channel resources can be effectively utilised compared with a traditional Interference Alignment (IA) based strategy. Simulation results show that the achievable data for primary transmission is enhanced by cooperative signal processing at the SBS. With respect to the SBS, its data rate grows with an increasing number of SUs by exploiting the multiuser diversity gain.

Energy-Efficient Multichannel Cooperative Sensing Scheduling With Heterogeneous Channel Conditions for Cognitive Radio Networks

Spectrum sensing is an important aspect of cognitive radio networks (CRNs). Secondary users (SUs) should periodically sense the channels to ensure primary-user (PU) protection. Sensing with cooperation among several SUs is more robust and less error prone. However, cooperation also increases the energy spent for sensing. Considering the periodic nature of sensing, even a small amount of savings in each sensing period leads to considerable improvement in the long run. In this paper, we consider the problem of energy-efficient (EE) spectrum sensing scheduling with satisfactory PU protection. Our model exploits the diversity of SUs in their received signal-to-noise ratio (SNR) of the primary signal to determine the sensing duration for each user/channel pair for higher energy efficiency. We model the given problem as an optimization problem with two different objectives. The first objective is to minimize the energy consumption, and the second objective is to minimize the spectrum sensing duration to maximize the remaining time for data transmission. We solve both problems using the outer linearization method. In addition, we present two suboptimal but efficient heuristic methods. We provide an extensive performance analysis of our proposed methods under various numbers of SUs, average channel SNR, and channel sampling frequency. Our analysis reveals that all proposals with an energy minimization perspective provide significant energy savings compared with a pure transmission-time maximization (TXT) technique.

Randomized Masking in Cognitive Radio Networks

A decentralized network of one Primary User (PU) and several Secondary Users (SU) is studied. PU is licensed to exploit the resources, while the party of SUs intend to share the resources with PU. Each SU must guarantee to not disturb the performance of PU beyond a certain level, while maintaining a satisfactory quality of service for itself. It is proposed that each secondary transmitter adopts a Randomized Masking (RM) strategy with full average transmission power where it remains silent or transmits a symbol in its codeword independently from transmission slot to transmission slot. We consider a setup where the primary transmitter is unaware of channel coefficients, code-books of secondary users and the number of secondary users. SUs are anonymous to each other, i.e, they are unaware of each others' code-books, however, each SU is smart in the sense that it is aware of the code-book of PU, channel coefficients and the number of active SUs. Invoking the concept of e-outage capacity, we define the (e,ν)-admissible region as the set of masking probabilities for each SU such that the probability of outage for PU is maintained under a threshold \varepsilon in a case where PU sets its transmission rate at a fraction ν of its e-outage capacity as if there were no SUs in the network. The masking probability of SUs is designed through maximizing the average (with respect to channel coefficients) achievable rate per SU over the (e,ν)-admissible region. In our analysis, the primary receiver treats interference as noise, however, each secondary receiver has the option to decode and cancel the interference caused by PU, while treating the signals of other SUs as noise. In another approach, referred to as Continuous Transmission with Power Control (CTPC), each SU transmits continuously (no masking is applied), however, it adjusts its transmission power in order to yield the largest value for average achievable rate per SU. The schemes RM and CTPC are compared for different values of transmission power for each SU and PU and distance between different users. It is observed that neither of RM or CTPC always outperforms the other in various scenarios in terms of the underlying system parameters. A combination of RM and CTPC referred to as Randomized Masking with Power Control (RMPC) is also investigated where each SU controls both its probability of masking and average transmission power. It is demonstrated through simulations that RMPC can outperform both RM and CTPC.

A Spectrum Switching Delay-Aware Scheduling Algorithm for Centralized Cognitive Radio Networks

We formulate a scheduling problem that takes into account different hardware delays experienced by the secondary users (SUs) in a centralized cognitive radio network (CRN) while switching to different frequency bands. We propose a polynomial-time suboptimal algorithm to address our formulated scheduling problem. We evaluate the impact of varying switching delay, number of frequencies, and number of SUs. Our simulation results indicate that our proposed algorithm is robust to changes in the hardware spectrum switching delay and its performance is very close to its upper bound. We also compare our proposed method with the corresponding constant switching delay-based algorithm and demonstrate that our suggestion of taking into account the different hardware delays while switching to different frequency bands is essential for scheduling in CRNs.

Joint optimisation algorithm of cooperative spectrum sensing with cooperative overhead and sub‐band transmission power for wideband cognitive radio network

AbstractCognitive radio (CR) allows a secondary user (SU) to utilise the spectrum allocated to the primary user (PU) on the premise of detecting the absence of PU by spectrum sensing. The SU often adopts cooperative spectrum sensing to cope with the hidden terminal problem if the PU is shadowed or in serious multi‐path fading; however, the cooperative overhead may decrease the throughput of the SU. In this paper, we consider a wideband CR network that can reuse multiple idle sub‐bands after cooperative spectrum sensing and then analyse the total throughput of the SU over all the sub‐bands. A multi‐variable nonconvex optimisation problem of cooperative spectrum sensing with cooperative overhead and sub‐band transmission power is proposed, which maximises the total throughput of the SU subject to the constraints of the false‐alarm probability, the detection probability, the cooperative overhead and the maximal total power of the SU. For obtaining the optimal solution, we divide the optimisation problem into two sub‐optimisation problems: one for optimising the cooperative spectrum sensing including the sensing time and the number of SUs and the other one for optimising the sub‐band transmission power. We have proven the convex optimisation of the two sub‐optimisation problems and proposed a joint optimisation algorithm of the sensing time, the number of SUs and the sub‐band transmission power. The simulation results show that the proposed joint optimisation algorithm can achieve the largest throughput with the false‐alarm probability and the detection probability within their limits. Copyright © 2013 John Wiley & Sons, Ltd.

Scaling Laws of Cognitive Ad Hoc Networks over General Primary Network Models

We study the capacity scaling laws for the cognitive network that consists of the primary hybrid network (PhN) and secondary ad hoc network (SaN). PhN is further comprised of an ad hoc network and a base station-based (BS-based) network. SaN and PhN are overlapping in the same deployment region, operate on the same spectrum, but are independent with each other in terms of communication requirements. The primary users (PUs), i.e., the ad hoc nodes in PhN, have the priority to access the spectrum. The secondary users (SUs), i.e., the ad hoc nodes in SaN, are equipped with cognitive radios, and have the functionalities to sense the idle spectrum and obtain the necessary information of primary nodes in PhN. We assume that PhN adopts one out of three classical types of strategies, i.e., pure ad hoc strategy, BS-based strategy, and hybrid strategy. We aim to directly derive multicast capacity for SaN to unify the unicast and broadcast capacities under two basic principles: 1) The throughput for PhN cannot be undermined in order sense due to the presence of SaN. 2) The protocol adopted by PhN does not alter in the interest of SaN, anyway. Depending on which type of strategy is adopted in PhN, we design the optimal-throughput strategy for SaN. We show that there exists a threshold of the density of SUs according to the density of PUs beyond which it can be proven that: 1) when PhN adopts the pure ad hoc strategy or hybrid strategy, SaN can achieve the multicast capacity of the same order as it is stand-alone; 2) when PhN adopts the BS-based strategy, SaN can asymptotically achieve the multicast capacity of the same order as if PhN were absent, if some specific conditions in terms of relations among the numbers of SUs, PUs, the destinations of each multicast session in SaN, and BSs in PhN hold.

On the Decision Threshold of Eigenvalue Ratio Detector Based on Moments of Joint and Marginal Distributions of Extreme Eigenvalues

Eigenvalue Ratio (ER) detector based on the two extreme eigenvalues of the received signal covariance matrix is currently one of the most effective solution for spectrum sensing. However, the analytical results of such scheme often depend on asymptotic assumptions since the distribution of the ratio of two extreme eigenvalues is exceptionally complex to compute. In this paper, a non-asymptotic spectrum sensing approach for ER detector is introduced to approximate the marginal and joint distributions of the two extreme eigenvalues. The two extreme eigenvalues are considered as dependent Gaussian random variables such that their joint probability density function (PDF) is approximated by a bivariate Gaussian distribution function for any number of cooperating secondary users and received samples. The PDF approximation approach is based on the moment matching method where we calculate the exact analytical moments of joint and marginal distributions of the two extreme eigenvalues. The decision threshold is calculated by exploiting the statistical mean and the variance of each of the two extreme eigenvalues and the correlation coefficient between them. The performance analysis of our newly proposed approximation approach is compared with the already published asymptotic Tracy-Widom approximation approach. It has been shown that our results are in perfect agreement with the simulation results for any number of secondary users and received samples.

Performance Analysis of Hybrid MAC Protocol for Cognitive Radio Networks

The rapid growth in demand for broadband wireless services coupled with the recent developmental work on wireless communications technology and the static allocation of the spectrum have led to the artificial scarcity of the radio spectrum. The traditional command and control model (Static allocation) of spectrum allocation policy allows for severe spectrum underutilization. Spectrum allocated to TV operators can potentially be shared by wireless data services, either when the primary service is switched off or by exploiting spatial reuse opportunities. This paper describes a hybrid access scheme based on CSMA/CA and TDMA MAC protocols for use in the TV bands. The approach allows secondary users (SU) to operate in the presence of the primary users (PU) and the OPNET simulation and modelling software has been used to model the performance of the scheme. An analysis of the results shows that, the proposed schemes protect the primary user from harmful Interference from the secondary user. In terms of delay, it was found that packet arrival rates, data rates and the number of secondary users have significant effects on delay.

Analysis on Communication Performance for Secondary Users Classified in Cognitive Radio Networks

Cognitive Radio Networks is an effective technology and a hot research direction which can solve the problem of deficient resource and revolutionize utilization. In order to enhance the communication efficiency, secondary users are classified by some strategy. We exploit the queuing theory model to research on the communication performance of secondary users, considering primary user as the first grade user and secondary users as other grades users. The research results indicate that the users which have lower priority level are more sensitive than those have higher priority level when primary user appears. Under Primary User Emulation Attack (PUEA), if the number of secondary users reaches 300, the waiting time would larger than 15 minutes. And if the appearance rate of PUEA reaches 4, the break-out rate would be 80%, which is much harmful for CRN.

Resource allocation for heterogeneous services in multiuser cognitive radio networks

SUMMARYThis paper considers a downlink cognitive radio network consisting of one cognitive base station and multiple secondary users (SUs) that shares spectrum with a primary network. Unlike most of previous studies that focus on the SUs that carry only one type of service, in this paper, the SUs that carry heterogeneous services are considered. Specifically, the SUs are classified by service types, that is, the SUs that carry nonreal‐time services and the SUs that carry real‐time services. The QoS of the nonreal‐time SUs is guaranteed by the minimum mean rate constraint, whereas the QoS of the real‐time SUs is guaranteed by the minimum instantaneous rate constraint. Under this setup, a joint subchannel, rate, and power allocation scheme based on dual optimization method is proposed to minimize the mean transmit power consumption of the cognitive base station. The complexity of the proposed scheme is linear in the number of subchannels and the number of SUs. Extensive simulation results are provided to validate the proposed resource allocation scheme. Copyright © 2012 John Wiley & Sons, Ltd.