Access In Cognitive Radio Networks Research Articles

Throughput Maximization of CSMA in Cognitive Radio Networks with Cooperative Spectrum Sensing

This study aims the throughput maximization of carrier sense multiple access (CSMA) in random access cognitive radio networks (CRNs) by using cooperative spectrum sensing. In the cooperative spectrum sensing, multiple cognitive radio (CR) users individually monitor the spectrum for the primary users (PUs)' activities and send their local decisions to the CR access point. Upon receiving the individual decisions, the CR access point gives the final decision about the PU's presence at the spectrum and sends it to all CR users in the network. At decision stage, CR access point utilizes the k-out-of-N decision fusion rule with optimal k value in order to obtain maximum CRN throughput. In this paper, we model a CRN utilizing CSMA medium access control scheme and focus on analyzing the throughput performance of it. Throughput performances of our CRN model which separately utilizes AND, OR, MAJORITY fusion rules and k-out-of-N decision fusion rule with the optimum k value are obtained and compared under the same network level probability of detection constraint. The throughput results obtained show that our CRN model utilizing k-out-of-N decision fusion rule with the optimum k value achieves higher throughput performance than AND, OR and MAJORITY fusion rules when they all have the same CRN load.

An Overlapping Coalitional Game for Cooperative Spectrum Sensing and Access in Cognitive Radio Networks

Cognitive radio networks (CRNs) provide an effective solution to address the increasing demand for spectrum resources. The cooperation among secondary users (SUs) improves the sensing performance and spectrum efficiency. In this paper, we study the traffic-demand-based cooperation strategy of SUs in multichannel CRNs, in which each SU makes its own cooperative sensing decision according to its traffic demand. When an SU has high traffic demand, it can choose to sense multiple channels in the sensing period and obtain more chances to use spectrum resources. If an SU has no data to transmit, it can choose not to perform spectrum sensing. We formulate this problem as a nontransferable utility (NTU) overlapping coalitional game. In this game, each SU implements a cooperation strategy according to its expected payoff, which takes into account the expected throughput and energy efficiency. We propose two different algorithms, namely, an overlapping coalition formation (OCF) algorithm and a sequential coalition formation (SCF) algorithm, to obtain a coalition structure. The OCF algorithm guarantees that the coalition structure is stable, whereas the SCF algorithm has lower computational complexity and less information exchange among SUs. Moreover, when being assigned a certain channel, SU implements an adaptive transmission power control scheme to further improve its energy efficiency. Simulation results show that our proposed algorithms achieve a higher aggregate throughput than the disjoint coalition formation algorithm from the literature, where each SU can join only one coalition.

GLRT-Based Spectrum Sensing for MIMO SC-FDMA Cognitive Radio Systems in the Presence of Synchronization Impairments

This letter proposes a generalized likelihood ratio test (GLRT)-based spectrum sensing scheme for multiple-input multiple-output (MIMO) single carrier frequency division multiple access (SC-FDMA) cognitive radio networks considering the effect of synchronization impairments such as carrier frequency offset, sampling frequency offset, and symbol timing error. The MIMO SC-FDMA cognitive radio system is initially developed in the presence of synchronization impairments. Subsequently, the finite record GLRT is derived for the above scenario considering the channel response as well as the various synchronization parameters and noise variance to be unknown. Closed-form expressions are derived for the probabilities of false alarm and detection to characterize the finite sample and asymptotic performance of the GLRT. Additionally, a computational complexity analysis is presented for the proposed test. Simulation results demonstrate the performance of the proposed GLRT-based detector in comparison with existing detectors in literature such as the matched filter detector, maximum eigenvalue detector, and the conventional energy detector while simultaneously validating the analytical performance expressions.

An overview of medium access control strategies for opportunistic spectrum access in cognitive radio networks

Cognitive radio (CR) is a promising wireless technology that provides efficient spectral usage. Medium Access Control (MAC) has an important role in several cognitive radio functions such as sensing, spectrum mobility, resource allocation and spectrum sharing. We focus on the opportunistic spectrum access (OSA) functionality of the CR network MAC layer by which the secondary users (SUs) access licensed spectrum in space and time with no harmful interference to primary users (PUs), without prior information on spectral usage. To achieve this, the unlicensed users should have the ability to adaptively and dynamically seek and exploit opportunities in licensed spectrum in time, polarization and frequency domains. There have been several OSA MAC schemes proposed for CR networks. This article presents a detailed review of such state-of-the-art schemes. First the differences between the conventional MAC protocols and OSA based MAC protocols are discussed. Existing OSA MAC protocols are classified according to their key attributes and their performances. Finally, future research directions are discussed.

Joint versus separate spectrum sensing and resource allocation in OFDMA‐based cognitive radio networks

In this study, the authors investigate the resource allocation issue for sensing-based orthogonal frequency-division multiple access (OFDMA) cognitive radio networks. They consider a network consisting multiple secondary users (SUs) and a secondary base station (BS) implementing a two-phase protocol. In the first phase, cooperative spectrum sensing is carried out to detect the vacant subchannels. In the second phase, SUs transmit data in the uplink to the BS by using OFDMA. They optimise the sensing parameters, transmit power and subchannel assignments jointly to minimise the total energy consumption with the constraints on SUs’ quality of service and detection probability of the primary user. This is a mixed binary integer programming problem which is NP (non-deterministic polynomial-time)-hard and generally intractable. They represent the problem as a bilevel problem and propose two efficient algorithms to solve the slave and master subproblems. They also study the separate optimisation, in which the sensing parameters of SUs are set regardless of the allocated resources. They investigate the energy savings of joint versus separate optimisation using numerical experiments. The results show that the joint optimisation method can introduce up to 16% of energy saving in zero sensing signal-to-noise ratio with the same total transmission bandwidth of 2.5 MHz.

Achievable Throughput Analysis of Opportunistic Spectrum Access in Cognitive Radio Networks With Energy Harvesting

In this paper, we consider a cognitive radio (CR) network that consists of multiple secondary users (SUs), each of which is equipped with an energy harvesting capability. We consider the opportunistic use of the idle spectrum, unused by primary users (PUs), through a mechanism of two-step opportunistic spectrum access for the SUs, consisting of random channel sensing followed by random channel access. Unlike the majority of previous studies, which have considered CR networks with energy harvesting under a single user setting, the goal of this paper is to investigate the joint impact of sensing probability, access probability, and energy queue capacity on the maximum achievable throughput in a multiuser CR network incorporating energy harvesting. For two extreme cases, those where the energy queue capacity is either infinite or extremely small, we show that the maximum achievable throughput is not affected by the channel access probability if the channel sensing probability is chosen appropriately and the optimal sensing probability is derived as a function of network parameters such as the energy arrival rate, channel availability probability, and number of contending SUs.

On Using Spectrum History to Manage Opportunistic Access in Cognitive Radio Networks

Cognitive radio networks (CRNs) open up the underutilized parts of the licensed spectrum for secondary reuse, so long as this secondary access does not cause harmful interference to the licensed users. Being able to run CRNs in a completely decentralized manner, as opposed to centralized operation, can be quite advantageous, because it avoids the complexity and single point-of-failure issues that arise from the presence of a central controller, and also eliminates the difficult step of establishing and maintaining a common control channel, which can suffer from saturation and malicious attacks. To that end, we propose in this paper a novel decentralized spectrum allocation technique for CRNs that not only provides great performance in terms of high throughput, excellent fairness, and minimal interference between cognitive users but also provides very stable network operation, in which cognitive users do not have to switch their operating frequency quite regularly. This is achieved by systematically observing the history of the spectrum usage to determine the proper channel assignment in the CRN. Our proposed technique is intuitive, is completely decentralized, and allows for quick reaction to changes in the CRN, such as when the primary users licensed to use the spectrum are suddenly activated.

GLRT Based Spectrum Sensing for MIMO SC-FDMA Cognitive Radio Networks

This work presents generalized likelihood ratio test (GLRT) based spectrum sensing schemes for multiple-input multiple-output (MIMO) single carrier frequency division multiple access (SC-FDMA) cognitive radio networks. The finite record GLRT is initially derived for the MIMO SC-FDMA cognitive radio scenario. Subsequently, the GLRT is extended to a scenario with unknown noise variance. Closed form expressions are derived for the probabilities of false alarm and detection to characterize the performance of the GLRT for finite sample as well as asymptotic scenarios. Further, the computational complexity of the proposed GLRT-based detectors is analyzed. Simulation results are presented to illustrate the spectrum sensing performance of the proposed tests in comparison with existing detectors in literature such as the conventional energy detector, maximum eigenvalue-based detector and also to verify the analytical expressions derived for the detection performance.

Joint Optimal Spectrum Sensing and Power Allocation in CDMA-Based Cognitive Radio Networks

In this paper, we investigate the power allocation issue for cooperative-sensing-based code-division multiple access (CDMA) cognitive radio (CR) networks. We consider a network consisting of multiple secondary users (SUs) and a secondary base station (BS) implementing a two-phase protocol. In the first phase, censor-based cooperative spectrum sensing is carried out to detect the PU's presence. When the channel is estimated to be free, SUs transmit data in the uplink to the BS in the second phase by using CDMA. We optimize the sensing parameters and transmit power of SUs jointly to minimize the total energy consumption with the constraints on SUs' quality of service (QoS) and detection probability of the PU. This is a nonconvex problem, which we represent as a monotonic optimization problem and solve by means of monotonic programming. Furthermore, we study the separate optimization problem in which sensing parameters and transmit power are optimized to minimize the energy consumption of the first phase and the second phase disjointly. Numerical results show that the proposed joint optimization method saves energy consumption significantly in lower signal-to-noise ratios (SNRs). It can introduce as high as 3.9 and 8.7 dB joule energy saving per time slot in zero-sensing SNR under the same data rate constraints of 0.5 and 1 bit/s/Hz, respectively.

A Trust Game Model and Algorithm for Cooperative Spectrum Sensing in Cognitive Radio Networks

The existence of malicious secondary users will bring damage to the performance of cooperative spectrum sensing and spectrum access in cognitive radio networks, so effectively curbing malicious behavior of secondary users become the key to success for cooperative spectrum sensing mechanism. Inspired by economics of repeated game theory, a trust game model and algorithm of distributed cooperative spectrum sensing oriented to malicious secondary users named FRTrust is proposed. In FRTrust, the reputation status is used to describe the performance of a secondary user in cooperative spectrum sensing process. It encourages secondary users to choose positive and honest behavior strategies for greater and long term benefits. Simultaneously, a ‘differentiation’ punishment mechanism is presented to respond malicious behaviors of secondary users. By this way, the ‘first offender’ secondary users and the ‘recidivist' secondary users can be distinguished effectively. If a secondary user departs from the normal times in its life period, it will be punished superimposed. Simulation results show that the FRTrust algorithm can encourage secondary users to participate in spectrum sensing in a cooperative attitude, improve the transaction success ratio of cooperative spectrum sensing, and guarantee the fairness and spectrum access performance for cognitive radio networks.

Three Regions for Space–Time Spectrum Sensing and Access in Cognitive Radio Networks

In this paper, spectrum holes in space–time dimensions are exploited to improve the spectrum utilization of cognitive radio networks (CRNs). To achieve this goal, we design the architecture of three regions, which are separately known as the black region, the gray region, and the white region. Temporal spectrum holes exist in the gray region, where secondary users (SUs) can opportunistically access the licensed spectrum with interweave spectrum sharing. In the white region, SUs can exploit spatial spectrum opportunities and transmit at any time by taking advantage of their long distances from the primary users (PUs), without causing severe interference to PUs. Moreover, the existence condition of the transition zone between the gray region and the white region is theoretically analyzed, where power control should be implemented in SUs. Closed-form bounds of three regions are obtained, which can be used in space–time spectrum sensing and access in CRNs. Finally, we provide numerical results to evaluate the relations among the key parameters in the three regions.

Impact of Channel Switching in Energy Constrained Cognitive Radio Networks

In this letter, we investigate the energy efficiency of multichannel spectrum access in cognitive radio networks. We consider two channel access schemes. In one case, a secondary user (SU) is assigned multiple channels and the channels are switched whenever a primary user (PU) returns. In the other, the SU operates on a single channel without switching to other channels. We develop an analytic framework on achievable channel utilization and energy consumption performance of the SU. From the results, we examine the trade-off between SU channel utilization and energy consumption, and identify the PU traffic conditions where one scheme outperforms the other.

Myopic policy for opportunistic access in cognitive radio networks by exploiting primary user feedbacks

The authors consider a cognitive radio network overlaying on top of a legacy primary network in which a secondary user is allowed to access primary channel by overhearing feedback signals over the primary channels. Each channel is assumed to be a two state Makovian process. Aiming at maximising the expected accumulated discounted network throughput, the considered sequential decision-making problem can be cast into a restless multi-armed bandit (RMAB) problem which is well-known to be PSPACE-hard, and thus a natural alternative approach is to seek a simple myopic policy. This study presents a theoretical study on the optimality of the proposed myopic policy for the special RMAB problem by considering four different cases: negatively correlated homogeneous channels, heterogeneous channels, positively correlated heterogeneous channels and negatively correlated heterogeneous channels. More specifically, the authors establish the closed-form conditions to guarantee the optimality of the myopic policy for the four cases, respectively, which, combined with the case of positively correlated homogeneous channels, constitute a complete paradigm for the optimality of the myopic policy.

To Stay or To Switch: Multiuser Multi-Channel Dynamic Access

In this paper we study opportunistic spectrum access (OSA) policies in a multiuser multi-channel random access cognitive radio network, where users perform channel probing and switching in order to obtain better channel condition or higher instantaneous transmission quality. Prior studies in this area include those on channel probing and switching policies for a single user to exploit spectral diversity, and those on probing and access policies for multiple users over a single channel to exploit temporal and multiuser diversity. By contrast, in this study we consider the collective switching of multiple users over multiple channels. This inevitably necessitates explicit modeling of the effect of collision. Furthermore, we consider finite arrivals, whereby users are not assumed to always have data to send and the demand for channel follows a certain arrival process. Under such a scenario, the users' ability to opportunistically exploit temporal diversity (the temporal variation in channel quality over a single channel) and spectral diversity (quality variation across multiple channels at a given time) is greatly affected by the level of congestion in the system. We investigate the associated decision process in this case, and show that the optimal policy is given by a nested stopping rule which may be viewed as a type of generalization to results found in existing literature in this area. We analytically and numerically evaluate the extent to which congestion affects potential gains from opportunistic dynamic channel switching.

Proactive channel access in cognitive radio networks using statistical radio environment maps

Inclusion of statistical knowledge of the primary user (PU) channel usage had shown to be beneficial in dynamic spectrum access. Motivated by this fact, this paper investigated the importance of collecting and using statistics on neighboring secondary users (SUs) in selecting channels in addition to the knowledge of PU channel usage. The paper assumed that PU traffic characteristics of the channels are included in the radio environment map in the form of probabilistic suffix trees, which is a sequence predictor based on Markov property. In the proposed method, an intelligent sequence hopping-based common control channel and a carrier sense multiple access (CSMA)/collision avoidance (CA)-based medium access control (MAC) protocol were introduced. As shown in the paper, selecting channels using statistics of both the neighboring SUs and PUs reduced the number of packet collisions compared to a scheme which only uses PU statistics. Furthermore, the simulation results showed that the scheme proposed had better throughput performance with respect to both the random channel selection scheme and the scheme which only uses PU statistics while having less training complexity.

Analysis of opportunistic spectrum access in cognitive radio networks using hidden Markov model with state prediction

We propose a study using hidden Markov model (HMM) with state prediction for opportunistic spectrum access (OSA) in cognitive radio (CR) networks. The primary channels are assumed to be operating in a TDMA manner with synchronous time slots of equal length and alternating between idle and busy states. The secondary users (SUs) may use them when they are idle by channel sensing. In contrast to the traditional scheme relying only on channel sensing for exploring spectrum opportunities, the proposed prediction scheme takes advantage of state prediction, channel sensing, and acknowledgments (ACKs) from the receiver in an attempt to maximize the utility. In the prediction scheme, there are three distinct actions: direct skip, sensing then conditional access, and direct access. We impose some constraints on the system parameters and derive thresholds by which we can specify the optimal action. We then conduct simulations to compare the performance of the prediction scheme to that of the traditional scheme. Results show that the former is superior to the latter. We believe the proposed prediction scheme is suitable for the OSA system using spectrum sensing.

A Cooperative Transmission Scheme for Improving the Secondary Access in Cognitive Radio Networks

In this paper, we examine the problem of secondary access blocking in cognitive radio networks when secondary trans- missions cause unacceptably high interference to primary trans- missions. In general, the access of secondary users (SUs) to a licensed spectrum band is only allowed when this access does not alter the performance of primary users that can be defined by the primary QoS requirement. In this paper, we propose a cooperative scheme that allows SUs to increase their access to the spectrum band and access the spectrum even when the primary QoS is not satisfied. Using relay selection and a proper power allocation method, we show that the secondary outage performance can be significantly improved, whereas the primary outage performance is either not altered or slightly improved. Moreover, closed-form expressions of the primary and secondary outage probabilities are derived, and the achieved diversity order is calculated. Finally, analytical and simulation results illustrate the primary outage performance and secondary outage performance of the proposed scheme and show its advantages compared with conventional schemes.

Entropy‐based opportunistic spectrum access for cognitive radio networks

AbstractThis paper proposes an opportunistic spectrum decision scheme based on the weighted residual entropy concept for cognitive radio networks. The proposed scheme maximum entropy channel access selects appropriate spectrum opportunities based on the usefulness of the idle‐channel remaining lifetime estimated through the weighted residual entropy function for the unoccupied channels. The performance of the proposed spectrum decision scheme is evaluated using a wealth of efficiency metrics, namely channel utilisation, channel collision, spectrum handoff rate and collision probability in perfect and imperfect spectrum sensing environments. The probabilities of primary signal detection and false detection are taken into the proposed spectrum hole selection technique. Despite the increasing probability of false detection, simulation results show that this central spectrum decision scheme greatly improves spectrum utilisation when the stated performance metrics were compared with those of known spectrum decision schemes such as random channel access, first‐opportunity channel access and maximum remaining lifetime. Copyright © 2014 John Wiley & Sons, Ltd.

A Multiagent Based Scheme for Unlicensed Spectrum Access in CR Networks

In recent wireless network domains static spectrum access is a major concern. Generally, this access leads to spectrum scarcity problem by creating empty holes or white spaces. However, the scarcity is temporary and can be alleviated if spectrum access is performed dynamically and efficiently. One important step towards dynamic spectrum access is the development of cognitive radio (CR) technology, which senses nearby spectrum portions (or bands) and tries to use them either opportunistically or by negotiating with the neighboring users. Nonetheless, dynamic spectrum access raises several challenges which need to be addressed in detail. These challenges include efficient allocation of spectrum for users in order to maximize spectrum utilization and to avoid user level conflicts both under licensed and unlicensed bands. In this paper, considering the relative rarity of solutions for unlicensed spectrum access and their inadequacy, we propose a scheme, where the CR devices (equipped with agents) interact with their neighbors to form several coalitions over the unlicensed bands. These types of coalitions can provide a less-conflicted access as the agents mutually agree for spectrum sharing and they allow other CR users to enter in their vicinity of acquired spectrum via bilateral message exchanges. Further, we present continuous time Markov chains to model the spectrum access process in continuous time and derive important performance metric as the blocking probability for without and with queuing systems. Amongst others, the important comparisons we made between analytical and simulation results in terms of blocking probability verify that our proposed model is correct. In essence, our proposed solution aims to increase dynamic spectrum usage by enabling cooperation between the users.

An Effective Spectrum Sensing Method Based on Correlation Coefficient and Energy Detection

Spectrum sensing is the key functionality for dynamic spectrum access in cognitive radio networks. Energy detection is one of the most popular spectrum sensing methods due to its low complexity and easy implementation. However, performance of the energy detector is susceptible to uncertainty in noise power. To overcome this problem, this paper proposes an effective spectrum sensing method based on correlation coefficient. The proposed method utilizes a single receiving antenna with a delay device to acquire the original received signal and the delayed signal. Then the correlation coefficient of the two signals is computed and the result is used as the test statistic. Theoretical analysis shows that the decision threshold is unrelated to noise power, thus the proposed approach can effectively overcome the influence of noise power uncertainty. Simulation results testify the effectiveness of the proposed method even in low signal-to-noise (SNR) conditions.