Cognitive Radio Transmission Research Articles

Elastic bandwidth allocation scheme with softened peak interference power constraint for the dynamic cognitive radio systems

The popularity of diverse wireless communication systems has led to increased strains on the unlicensed spectrum. However, investigations have shown that vast portions of the licensed spectrum remain underutilized across frequency, space and time. To improve the utilization of the existing radio spectrum, cognitive radio (CR) allows a secondary system to access the licensed spectrum as long as the primary system's operation is not compromised. Two main CR transmission modes, spectrum overlay and underlay have been proposed. In the spectrum overlay mode, challenges in quality-of-service (QoS) provisioning arise due to the necessity for secondary users to vacate the channels when a primary user appears. In the underlay model, interference caused to the primary system has to be carefully managed resulting in a constraint of the secondary system's transmit power, which causes difficulty in QoS provisioning. In this paper, we propose an elastic bandwidth allocation scheme to make concurrent use of both spectrum overlay and underlay transmission modes. Different from existing hybrid transmission strategy, our scheme employ a novel softened peak interference power constraint to improve the performance of the secondary system while still granting the superior protection to the primary system transmissions. This allows the proposed scheme to achieve a superior transmission capacity in the CR network while avoiding the weaknesses of the both spectrum overlay and spectrum underlay transmission modes.

Multimedia Transmission Over Cognitive Radio Channels Under Sensing Uncertainty

This paper studies the performance of hierarchical modulation-based multimedia transmission in cognitive radio (CR) systems with imperfect channel sensing results under constraints on both transmit and interference power levels. Unequal error protection (UEP) of data transmission using hierarchical quadrature amplitude modulation (HQAM) is considered in which high priority (HP) data is protected more than low priority (LP) data. In this setting, closed-form bit error rate (BER) expressions for HP data and LP data are derived in Nakagami-$m$ fading channels in the presence of sensing errors. Subsequently, the optimal power control that minimizes weighted sum of average BERs of HP bits and LP bits or its upper bound subject to peak/average transmit power and average interference power constraints is derived and a low-complexity power control algorithm is proposed. Power levels are determined in three different scenarios, depending on the availability of perfect channel side information (CSI) of the transmission and interference links, statistical CSI of both links, or perfect CSI of the transmission link and imperfect CSI of the interference link. The impact of imperfect channel sensing decisions on the error rate performance of cognitive transmissions is also evaluated. In addition, tradeoffs between the number of retransmissions, the severity of fading, and peak signal-to-noise ratio (PSNR) quality are analyzed numerically. Moreover, performance comparisons of multimedia transmission with conventional quadrature amplitude modulation (QAM) and HQAM, and the proposed power control strategies are carried out in terms of the received data quality and number of retransmissions.

Effective capacity of cognitive radio systems in asymmetric fading channels

As known that the effective capacity theory offers a methodology for exploring the performance limits in delay constrained wireless networks, this article considered a spectrum sharing cognitive radio (CR) system in which CR users may access the spectrum allocated to primary users (PUs). Particularly, the channel between the CR transmitter (CR-T) and the primary receiver and the channel between the CR-T and the CR receiver (CR-R) may undergo different fading types and arbitrary link power gains. This is referred to as asymmetric fading. The authors investigated the capacity gains achievable under a given delay quality-of-service (QoS) constraint in asymmetric fading channels. The closed-form expression for the effective capacity under an average received interference power constraint is obtained. The main results indicate that the effective capacity is sensitive to the fading types and link power gains. The fading parameters of the interference channel play a vital role in effective capacity for the looser delay constraints. However, the fading parameters of the CR channel play a decisive role in effective capacity for the more stringent delay constraints. Also, the impact of multiple PUs on the capacity gains under delay constraints has also been explored.

Optimal soft combination for multiple antenna energy detection under primary user emulation attacks

One of common threats imposed to the cognitive radio (CR) network is primary user emulation attack (PUEA), where some malicious users try to mimic the primary signal and deceive secondary users to prevent them from accessing the vacant frequency. Here, we propose a cooperative spectrum sensing scheme based on energy detection for CR networks in the presence of multiple smart PUEAs with spectrum sensing capability. In particular, we assume that the CR receiver has a number of L antennas and the CR transmitter sends combined information to the fusion center using beamforming with a single antenna. Soft combination of the observed energies from different CR users is investigated. By employing the Neyman–Pearson criterion, an optimal soft combination scheme is designed to maximize the cognitive signal-to-interference-plus-noise ratio (CSINR) for a given false alarm probability. Comparative simulation results validate the superiority of our proposed method in terms of detection accuracy compared to conventional methods.

Optimization of Cooperative Spectrum Sensing with Parallel Frame Structure

In cognitive radio (CR) networks, cooperative spectrum sensing (CSS) can greatly improve the sensing performance. In this paper, we propose a parallel frame structure for CSS in which spectrum sensing and data transmission are conducted concurrently over two different parts of the primary user (PU) spectrum band. We focus on the optimal fusion schemes of the proposed parallel CSS to minimize the CR user transmission delay and the average sensing error probability under the conditions of sufficient protection to PUs and required bandwidth for potential CR user data transmission. Some algorithms are proposed to calculate the optimal solutions. Computer simulations show that the delay performance is greatly improved by using the optimal fusion scheme I, and optimal fusion scheme II will further decrease the average sensing error probability compared to that using fixed thresholds in the fusion center.

Power and Contention Control Scheme: As a Good Candidate for Interference Modeling in Cognitive Radio Network

Due to the ever growing need for spectrum, the cognitive radio (CR) has been proposed to improve the radio spectrum utilization. In this scenario, the secondary users (SU) are permitted to share spectrum with the licensed primary users (SU) with a strict condition that they do not cause harmful interference to the cognitive network. In this work, we have proposed an interference model for cognitive radio network that utilizes power or contention control interference management schemes. We derived the probability density function (PDF) with the power control scheme, where the power of transmission of the CR transmitter is guided by the power control law and also with contention control scheme that has a fixed transmission power for all CR transmitter controlled by a contention control protocol. This protocol makes a decision on which CR transmitter can transmit at any point in time. In this work, we have shown that power and contention control schemes are good candidates for interference modeling in cognitive radio system. The impact of the unknown location of the primary receiver on the resulting interference generated by the CR transmitters was investigated and the results shows that the challenges of the hidden primary receivers lead to higher CR-primary interference in respect to higher mean and variance. Finally, the presented results show power control and the contention control scheme are good candidates in reducing the interference generated by the cognitive radio network.

Priority queueing models for cognitive radio networks with traffic differentiation

In this paper, we present a new queueing model providing the accurate average system time for packets transmitted over a cognitive radio (CR) link for multiple traffic classes with the preemptive and non-preemptive priority service disciplines. The analysis considers general packet service time, general distributions for the channel availability periods and service interruption periods, and a service-resume transmission. We further introduce and analyze two novel priority service disciplines for opportunistic spectrum access (OSA) networks which take advantage of interruptions to preempt low priority traffic at a low cost. Analytical results, in addition to simulation results to validate their accuracy, are also provided and used to illustrate the impact of different OSA network parameters on the average system time. We particularly show that, for the same average CR transmission link availability, the packet system time significantly increases in a semi-static network with long operating and interruption periods compared to an OSA network with fast alternating operating and interruption periods. We also present results indicating that, due to the presence of interruptions, priority queueing service disciplines provide a greater differentiated service in OSA networks than in traditional networks. The analytical tools presented in this paper are general and can be used to analyze the traffic metrics of most OSA networks carrying multiple classes of traffic with priority queueing service differentiation.

인지무선네트워크에서 적응적 채널예측에 기반한 핸드오프기법

Spectrum handoff is the process of exchanging progressing data transmission from the current channel to another idle channel. The essential goal of spectrum handoff in CR(Cognitive Radio) networks is to perform consistent data transmission while sustaining performance of ongoing transmission of secondary users. This handoff procedure can cause additional latency that eventually affects on the performance of CR transmission. Channel prediction method is expected to avoid the disruption to primary users and to reduce the handoff latency. In this paper, adaptive channel prediction is proposed to cope with time-varying channel and an adaptive channel prediction based proactive handoff procedure is designed to enhance data transmission performance.

Performance Analysis of Uplink Cognitive Radio Transmission based on Overloaded MC-DS-CDMA

This paper reports a cognitive radio network architecture based on overloaded multicarrier direct sequence code division multiple access (O-MC-DS-CDMA). The O-MC-DSCDMA technique combines CDMA with a multicarrier modulation technique to overcome the channel fading effects. In this technique, secondary users are enabled to share the available bandwidth with the existing primary users. Two sets of orthogonal Gold codes are used to support the primary and secondary users simultaneously. The orthogonality between the spreading codes is lost due to the non-zero cross correlation between the codes and the timing synchronization error in the uplink transmission, which causes interference between primary and secondary users. This paper proposes two modified hybrid parallel/successive interference cancellation techniques for primary and secondary user base station receivers with multiple antennas to suppress the interference among users. Interference among the same group of users is cancelled by parallel interference cancellation and the interference among groups is cancelled using successive interference cancellation. The simulation results confirmed that the proposed modified interference cancellation techniques show better BER performance over conventional interference cancellation techniques.

An Objection-Based Collaborative Spectrum Sensing for Cognitive Radio Networks

Cognitive radio transmission relies on awareness of the instantaneous spectrum utilization. Such awareness can be gained by the spectrum sensing process. To this end, collaborative spectrum sensing (CSS) is preferred as it yields more reliable results than individual sensing. However, CSS requires collaboration among all the cognitive users (CUs), which leads to a high energy consumption. This letter provides a new energy-efficient CSS scheme. The proposed scheme implies that only a CU will broadcast its local decision among the whole network. All the other CUs that have a different local decision will object to the fusion center, whereas the CUs that agree with the announced decision will stay silent. Accordingly, the fusion center will be informed of all the local decisions of the CUs and will make a global decision. An analytical study on how to select the broadcasting CU such that energy efficiency is maximized is provided. Simulation and analytic results explore the energy efficiency gain compared to the literature.

Improving spectrum access using a beam‐forming relay scheme for cognitive radio transmissions

Cognitive radio (CR) systems allow unlicensed secondary users to transmit on the licensed frequency bands without degrading the transmissions of licensed primary users. Combining CR with other emerging techniques such as multi-antenna relaying may bring many benefits for the secondary transmissions. In this study, the authors propose and investigate a new relay-based cooperation scheme for a CR network to improve the secondary access to the licensed spectrum band without causing additional interference to the simultaneous primary transmission. The proposed scheme considers one multi-antenna relay node that can assist either the primary or the secondary transmission using beam-forming (BF). In the proposed new scheme, the BF weights are designed in the presence of imperfect channel state information (CSI). Simulation results show that the secondary's channel capacity is significantly improved and outperforms conventional transmission schemes. The results also reveal the impact of imperfect CSI on the primary outage performance and the efficiency of the proposed solution for minimising the interference due to imperfect CSI.

Energy-Efficient Power Allocation Using Probabilistic Interference Model for OFDM-Based Green Cognitive Radio Networks

We study the energy-efficient power allocation techniques for OFDM-based cognitive radio (CR) networks, where a CR transmitter is communicating with CR receivers on a channel borrowed from licensed primary users (PUs). Due to non-orthogonality of the transmitted signals in the adjacent bands, both the PU and the cognitive secondary user (SU) cause mutual-interference. We assume that the statistical channel state information between the cognitive transmitter and the primary receiver is known. The secondary transmitter maintains a specified statistical mutual-interference limits for all the PUs communicating in the adjacent channels. Our goal is to allocate subcarrier power for the SU so that the energy efficiency metric is optimized as well as the mutual-interference on all the active PU bands are below specified bounds. We show that the green power loading problem is a fractional programming problem. We use Charnes-Cooper transformation technique to obtain an equivalent concave optimization problem for what the solution can be readily obtained. We also propose iterative Dinkelbach method using parametric objective function for the fractional program. Numerical results are given to show the effect of different interference parameters, rate and power thresholds, and number of PUs.

Simultaneous Sensing and Transmission in Cognitive Radio

In cognitive radio, spectrum sensing is used to find the white spectrum or protect the primary user from interference caused by the secondary user (SU). There are two conventional spectrum sensing approaches: quiet and active. However, these conventional approaches have several problems. In quiet sensing, the quiet period degrades the SU capacity. With active sensing, the SU capacity is also degraded by the need for additional resource consumption and the mismatch in feedback information. In order to mitigate these problems, the structure of simultaneous PU sensing and data transmission is introduced. This structure is equipped with antenna isolation and self-interference cancellation in which the communication and the sensing radios are already assumed to be significantly isolated. This approach is designed so that the SU transmitter can sense PU signals and transmit data signals at the same time by dividing its spatial resources. Expanding on this work, we propose a concept of which adaptively uses spatial resource according to the surrounding environments. To effectively use TranSensing, we propose a two-stage algorithm (TSA). Finally, the impact of residual interference on TranSensing is investigated. Simulation results show that TranSensing with TSA enhances the SU capacity over the conventional quiet or active sensing.

A Multiple-Ring Model for Cognitive Radio Aggregate Interference

This paper proposes a new, flexible, multiple ring model for the aggregate interference analysis of a Poisson field of cognitive radio transmitters distributed over an annular region. For Rayleigh fading or composite Rayleigh fading and Gamma shadowing environments, the moment generating function of the aggregate interference and the exact and asymptotic analysis of the outage are derived for the model. Typically, the model is most accurate for larger guard distances and lower path loss exponents. However, its parameters can be tuned such that a required accuracy is obtained for a trade-off in complexity.

A New Signal Structure for Active Sensing in Cognitive Radio Systems

This paper presents a new signal structure for spectrum sensing under active cognitive radio (CR) transmission (i.e., active sensing). Specifically, the known pilots used for the base station of primary users (PU) are duplicated and reallocated in the CR transmission signal properly so that there is no overlap between the reallocated pilot subcarriers and the original subcarriers. Given the CR signal structure, the signal received by a spectrum sensor of the CR system becomes correlated on the subcarriers when PU reoccupation occurs during the data-transmission periods, which makes it easy to detect PU activities by computing the spectral correlation function of the received signal. Both theoretical analyses and simulation results are given to demonstrate the effectiveness of the proposed active-sensing approach. The proposed method attains a detection probability of 0.99 and a false-alarm probability of 0.01 within 170 orthogonal frequency-division multiplexing symbols under a signal-to-noise ratio of -25dB and a signal-to-interference ratio of -20dB. The performance would be degraded under practical conditions, but is acceptable in most cases if the carrier frequency offset is less than 0.3. Compared with traditional cyclostationary feature detection, the proposed approach requires only about half the sensing time to achieve the same sensing accuracy, at about a 3% loss of throughput.

Error Rate Analysis of Cognitive Radio Transmissions with Imperfect Channel Sensing

This paper studies the symbol error rate performance of cognitive radio transmissions in the presence of imperfect sensing decisions. Two different transmission schemes, namely sensing-based spectrum sharing (SSS) and opportunistic spectrum access (OSA), are considered. In both schemes, secondary users first perform channel sensing, albeit with possible errors. In SSS, depending on the sensing decisions, they adapt the transmission power level and coexist with primary users in the channel. On the other hand, in OSA, secondary users are allowed to transmit only when the primary user activity is not detected. Initially, for both transmission schemes, general formulations for the optimal decision rule and error probabilities are provided for arbitrary modulation schemes under the assumptions that the receiver is equipped with the sensing decision and perfect knowledge of the channel fading, and the primary user's received faded signals at the secondary receiver has a Gaussian mixture distribution. Subsequently, the general approach is specialized to rectangular quadrature amplitude modulation (QAM). More specifically, the optimal decision rule is characterized for rectangular QAM, and closed-form expressions for the average symbol error probability attained with the optimal detector are derived under both transmit power and interference constraints. The effects of imperfect channel sensing decisions, interference from the primary user and its Gaussian mixture model, and the transmit power and interference constraints on the error rate performance of cognitive transmissions are analyzed.

Power allocation in OFDM cognitive radio relay networks with outdated channel state information

SummaryIn this paper, we study power allocation in OFDM cognitive radio (CR) relay networks. The objective of power allocation is to maximize the instantaneous capacity of the CR network. It is assumed that the available channel state information between the secondary and primary users is an outdated but correlated version of the actual instantaneous channel state information. Optimal power allocation schemes are developed for both decode‐and‐forward and amplify‐and‐forward relay assisted CR transmission, assuming that the primary users are subject to average interference constraints and the CR transmitters are subject to maximum transmit power constraint. In addition, suboptimal power allocation schemes with reduced complexity are also proposed. Performance of the proposed schemes is compared with uniform power allocation and numerical results confirm that the proposed power allocation schemes achieve significant capacity improvement in comparison to uniform power loading. Furthermore, the proposed suboptimal power allocation schemes can be used as less complex alternatives for optimal power allocation with some capacity degradation. Copyright © 2014 John Wiley & Sons, Ltd.

Generalized Area Spectral Efficiency: An Effective Performance Metric for Green Wireless Communications

Area spectral efficiency (ASE) was introduced as a metric to quantify the spectral utilization efficiency of cellular systems. Unlike other performance metrics, ASE takes into account the spatial property of cellular systems. In this paper, we generalize the concept of ASE to study arbitrary wireless transmissions. Specifically, we introduce the notion of affected area to characterize the spatial property of arbitrary wireless transmissions. Based on the definition of affected area, we define the performance metric, generalized area spectral efficiency (GASE), to quantify the spatial spectral utilization efficiency as well as the greenness of wireless transmissions. After illustrating its evaluation for point-to-point transmission, we analyze the GASE performance of several different transmission scenarios, including dual-hop relay transmission, three-node cooperative relay transmission and underlay cognitive radio transmission. We derive closed-form expressions for the GASE metric of each transmission scenario under Rayleigh fading environment whenever possible. Through mathematical analysis and numerical examples, we show that the GASE metric provides a new perspective on the design and optimization of wireless transmissions, especially on the transmitting power selection. We also show that introducing relay nodes can greatly improve the spatial utilization efficiency of wireless systems. We illustrate that the GASE metric can help optimize the deployment of underlay cognitive radio systems.

Cognitive ultra wideband radio spectrum sensing window length optimization algorithm

A critical objective of cognitive radio (CR) system is to enhance the spectrum efficiency, and one of the key factors that can determine the spectrum efficiency is the system spectrum sensing performance with respect to sensing window length. For non-coherent detection-based sensing technique, the length of the sensing window required to meet the detection criteria is inversely proportional to the detected signal-to-noise ratio (SNR) of the primary users (PUs). This fact may result in an inadequate use of the white or gray space for the conventional CR system whose transmission and sensing window length are both fixed because a high detected PUs SNR can lead to an excessive long fixed sensing window which occupies the potential CR transmission opportunities while a low received PUs SNR can result in an insufficient sensing window length which degrades the CR detection criteria. In this paper, to improve the spectrum efficiency compared with the fixed sensing/transmission window length-based CR system, we propose an adaptive spectrum sensing window length optimization algorithm. We design the algorithm based on the ultra wideband (UWB) system which is an ideal candidate for the implementation of the CR technology. Based on the analysis of the CR-UWB’s spectrum sensing technique in terms of the factors such as spectrum efficiency, spectrum sensing length, PUs SNR, detection criteria etc., we formulate the optimization problem into a convex problem, which enables the proposed algorithm to find the optimal trade-off with low computational complexity between the sensing window length and the desired detection probabilities for the CR-UWB system. Compared with the conventional fixed length spectrum sensing techniques, the proposed algorithm is verified to be able to adapt the length of the CR-UWB’s transmission window according to the PUs SNR to optimize the use of the available spectrum while guaranteeing the PUs from being interfered.

Distributed Beamforming with Nodes Selection for Cognitive Radio Networks

In order to collaboratively forward the Cognitive Radio (CR) signal to the Distant CR (DCR) users, we have introduced the Distributed Beamforming (DB) technique CR networks. However we face a practical difficulty of the extreme narrow main beam in the pattern generated by the DB method, when applying it to CR networks. To solve this problem, we propose a novel Nodes Selection (NS) method based on studies of the differences in beam width of a broadside array and an end-fire array. The proposed NS method selects those CR nodes, which are able to form a full size end-fire array and a reduced size broadside array. It chooses CR nodes located in the “belt” area along the direction of the DCR user. Simulation results of the average beampattern of our NS method show that the main beams are successfully directed towards the DCR users and are enlarged for practical applications in CR networks. What is more, for a CR network with a large physical size, our NS method can widen the main beam while maintaining sufficiently low sidelobe levels for CR transmission.