Cooperative Cognitive Radio Research Articles

Cooperative Cognitive Radio Networks: New Approach for Detection Accuracy Analysis Under Impaired Channels

The quality of the reporting channel and the relaying mechanism play a significant role in cooperative spectrum sensing (CSS). However, these factors are frequently overlooked when it comes to discussing the performance of CSS in cognitive radio (CR) networks. In this work we investigate the performance of a relay-based CSS approach proposed for CR applications. Specifically, we analyze the detection accuracy of a CR network considering channel impairments, amplify-and-forward relying protocol, and a selection combining scheme. First, a closed form expression for the average false alarm probability is derived. Then, the probability density function (PDF) of the end-to-end signal-to-noise ratio (SNR) is obtained and a closed-form expression for the average detection probability at high SNR applications is derived. The sensing and the reporting channels are assumed to be subjected to independent and identically distributed Rayleigh fading. The PDF approach is used in our analysis. This approach is not easily tractable as it involves higher orders of Bessel functions. However, an approximated polynomial representation of a first-order modified Bessel function of the second kind makes this task possible. The results obtained validate the derived closed form expressions and show the importance of considering reporting channel statistics and relaying mechanism for accurate performance analysis of the CSS in CR networks.

Fair and Efficient Spectrum Splitting for Unlicensed Secondary Users in Cooperative Cognitive Radio Networks

In cooperative cognitive radio networks (CCRNs), a licensed primary-user (PU) is allowed to leverage several unlicensed secondary-users (SUs) to relay its traffic. In this paper, a staged dynamic spectrum allocation (DSA) scheme is proposed for CCRNs. In the first stage, the network is uncongested. A simple pricing based DSA scheme is proposed for the PUs to lease their idled frequency bands to the SUs. And, hence, the initial quality of service (QoS) demands (in terms of the minimum rate requirements) of the PUs and the SUs are both satisfied through direct transmission on the allocated frequency bands. In the second stage, the network reaches the full-loaded situation. Therefore, a cooperative relaying based DSA scheme is proposed to stimulate the PUs to split more extra frequency bands to fulfill the increased QoS demands of the SUs, on condition that the QoS of the PUs are well maintained. By applying the cooperative bargaining game theory in the proposed cooperative relaying based DSA, on the one hand, the SUs can get fairness rate-rewards from the PUs according to the level of contribution that they can make to compensate the PUs for the rate-losses. Hence, the increased QoS demands of the SUs can be accommodated in short term. On the other hand, the PUs could retain the SUs successfully to obtain the long-term revenue, on condition that their QoS constraints are still satisfied. Finally, the analysis results of the proposed bargaining game theoretic DSA scheme (in the second stage) are testified through computer simulations.

A novel cooperative spectrum sensing scheme based on virtual soft information fusion

In cognitive radio (CR), the performance of hard information fusion (HIF) strategy for cooperative sensing will deteriorate when cooperative CR user are not uniformly reliable. To deal with this problem, this paper proposed a novel virtual soft information fusion (VSIF) strategy which uses expectation for primary users (PU) presence probability to replace the local sensing decision of each user in the information fusion. Compared with the HIF-based scheme, VSIF-based sensing scheme keeps the advantages of low data transmission in HIF-based scheme, and modifies the way of information fusion at the fusion center to achieve better performance when the user sensing reliability is non-uniform. Simulation shows VSIF strategy has significant superiority on the missing detection probability over HIF in the scenarios of non-uniform user reliability.

Optimization algorithm of periodical cooperative spectrum sensing in cognitive radio

SUMMARYTo decrease the interference to the primary user (PU) and improve the detected performance of cognitive radio (CR), a single‐band sensing scheme wherein the CR periodically senses the PU by cooperative spectrum sensing is proposed in this paper. In this scheme, CR first senses and then transmits during each period, and after the presence of the PU is detected, CR has to vacate to search another idle channel. The joint optimization algorithm based on the double optimization is proposed to optimize the periodical cooperative spectrum sensing scheme. The maximal throughput and minimal search time can be respectively obtained through the joint optimization of the local sensing time and the number of the cooperative CRs. We also extend this scheme to the periodical wideband cooperative spectrum sensing, and the joint optimization algorithm of the numbers of the sensing time slots and cooperative CRs is also proposed to obtain the maximal throughput of CR. The simulation shows that the proposed algorithm has lower computational quantity, and compared with the previous algorithms, when SNR = 5 dB, the throughput and search time of the proposed algorithm can respectively improve 0.3 kB and decrease 0.4 s. The simulation also indicates that the wideband cooperative spectrum sensing can achieve higher throughput than the single‐band cooperative spectrum sensing. Copyright © 2012 John Wiley & Sons, Ltd.

Optimal Throughput of Secondary Users over Two Primary Channels in Cooperative Cognitive Radio Networks

In this paper, we investigated the throughput of a cognitive radio network where two primary frequency channels (PCs) are sensed and opportunistically accessed by N secondary users. The sharing sensing member (SSM) protocol is introduced to sense both PCs simultaneously. According to the SSM protocol, N SUs (Secondary User) are divided into two groups, which allows for the simultaneous sensing of two PCs. With a frame structure, after determining whether the PCs are idle or active during a sensing slot, the SUs may use the remaining time to transmit their own data. The throughput of the network is formulated as a convex optimization problem. We then evaluated an iterative algorithm to allocate the optimal sensing time, fusion rule and the number of members in each group. The computer simulation and numerical results show that the proposed optimal allocation improves the throughput of the SU under a misdetection constraint to protect the PCs. If not, its initial date of receipt shall be nullified.

Connectivity of Multiple Cooperative Cognitive Radio Ad Hoc Networks

In cognitive radio networks, the signal reception quality of a secondary user degrades due to the interference from multiple heterogeneous primary networks, and also the transmission activity of a secondary user is constrained by its interference to the primary networks. It is difficult to ensure the connectivity of the secondary network. However, since there may exist multiple heterogeneous secondary networks with different radio access technologies, such secondary networks may be treated as one secondary network via proper cooperation, to improve connectivity. In this paper, we investigate the connectivity of such a cooperative secondary network from a percolation-based perspective, in which each secondary network's user may have other secondary networks' users acting as relays. The connectivity of this cooperative secondary network is characterized in terms of percolation threshold, from which the benefit of cooperation is justified. For example, while a noncooperative secondary network does not percolate, percolation may occur in the cooperative secondary network; or when a noncooperative secondary network percolates, less power would be required to sustain the same level of connectivity in the cooperative secondary network.

Power saving for cooperative spectrum sharing-based cognitive radios under primary user short-term rate protection

In cooperative spectrum sharing-based cognitive radio systems, the secondary user (SU) acts as a cooperator of the primary user (PU) to assist the PU's transmission and is allowed to simultaneously transmit at the same spectrum only if it is not harmful to the primary transmission. Here the authors studies a power minimising problem of the SU with real-time services for this system under constraints on the SU's quality-of-service requirement and guaranteeing the PU's instantaneous rate unchanged if the SU allocates part of its power for its own transmissions. Superposition coding (SC) is further employed by the SU to eliminate the interference caused by the PU. The problem is formulated as an optimisation problem. Owing to its high complexity, this problem is then converted into a single variable optimisation problem, and a greedy-based power minimisation method with low complexity is thus proposed. Numerical comparison shows that the proposed method can lead to reductions in the secondary transmission power of about 30 and 14% against for the non-SC one and the equal bit allocation-based one, respectively.

A Price-Based Spectrum Management Scheme with Stackelberg Game in Cooperative Cognitive Radio Networks

A Price-Based Spectrum Management Scheme with Stackelberg Game in Cooperative Cognitive Radio Networks

Throughput Maximization Based on Joint Channel and Sensing Time Assignment for the Cooperative Cognitive Radio Network

Throughput Maximization Based on Joint Channel and Sensing Time Assignment for the Cooperative Cognitive Radio Network

Weighted Sum Rate Maximization in OFDM Based Cooperative Cognitive Radios: A Joint Optimization Approach

Improving utilization of the radio spectrum is the main goal of Cognitive Radio Networks (CRN). Recent studies made use of cooperative relay technology in cognitive networks, to increase transmission diversity gain. In this paper we consider an OFDM based cooperative cognitive network with a pair of Source-Destination nodes as the primary user (PU), and a pair of Source-Destination nodes—which is assisted with a relay—as the secondary (cognitive) user (SU). Both primary and secondary users share a same spectrum. In a two hop transmission, the source transmits in the first hop, and the half-duplex relay decodes the message, re-encodes and forwards it to the destination in the second hop on a different subcarrier. The cognitive network obeys an underlay paradigm where the SU is allowed to transmit simultaneously with PU, while its power is limited such that the interference caused for PU does not exceed a defined temperature. Under this constraint, a joint subcarrier pairing and power allocation is proposed for SU to maximize its weighted sum rate. The problem is transformed to a convex optimization problem and solved in the dual domain. Then an algorithm to achieve feasible solutions is used based on the optimization results. Through extensive simulations, we compare the spectrum utilization of the proposed approach with the existing ones, and show that interestingly the proposed method improves the weighted sum rate of SU.

Optimizing Cooperative Cognitive Radio Networks with Opportunistic Access

Optimal resource allocation for cooperative cognitive radio networks with opportunistic access to the licensed spectrum is studied. Resource allocation is based on minimizing the symbol error rate at the receiver. Both the cases of all-participate relaying and selective relaying are considered. The objective function is derived and the constraints are detailed for both scenarios. It is then shown that the objective functions and the constraints are nonlinear and nonconvex functions of the parameters of interest, that is, source and relay powers, symbol time, and sensing time. Therefore, it is difficult to obtain closed-form solutions for the optimal resource allocation. The optimization problem is then solved using numerical techniques. Numerical results show that the all-participate system provides better performance than its selection counterpart, at the cost of greater resources.

Throughput analysis of cooperative spectrum sensing in Rayleigh-faded cognitive radio systems

In a cognitive radio (CR) network, cooperative spectrum sensing is a viable sensing technique to enhance spectral utilisation efficiency of secondary users (SUs) while ensuring the quality of service (QoS) of primary users (PUs). Intuitively, the more SUs are involved in sensing, the more sensing accuracy the CR can achieve, whereas the more sensing overhead the SUs consume, the less throughput the CR network can achieve. In this study, the authors investigate overhead-throughput trade-off over Rayleigh-fading channels in a cooperative CR network that consists of a number of the SUs employing energy detectors and a single decision fusion centre. Considering the trade-off, the authors prove that there is an optimal set of the sensing length and the number of SUs that maximise the throughput of an SU network. They further extend their analysis to a two-stage cooperative sensing mechanism where the second-stage fine sensing is triggered whenever any SU reports the presence of a PU after the first-stage detection. Numerical results showed that compared with the single-stage sensing, the two-stage sensing scheme achieves higher throughput via a reduction of the false alarm probability.

A Low Complexity High Resolution Cooperative Spectrum-Sensing Scheme for Cognitive Radios

Conventional distributed cognitive radio (CR) communication aims to increase the sensing accuracy and reduce the detection time by allowing the CR users to operate in the same frequency band in a cooperative fashion and by forming efficient decision making. In this paper, we propose a spectrum-sensing scheme which provides accurate detection at low complexity, by assigning different sensing tasks to the CRs. If the number of cooperative CRs is N, our method offers an effective sensing resolution of N times higher than that of the conventional method. An inherently low complex progressive decimation filter bank, which provides variable sensing resolutions by software reconfiguration, is employed at each CR. The design example shows that the hardware complexity of our sensing scheme is 41.3% less than that of the conventional spectrum sensor. It is also shown that the proposed system can support multiple communication standards.

A Resource Allocation Scheme for Cooperative Multiuser OFDM-Based Cognitive Radio Systems

This paper presents a joint subcarrier and power allocation algorithm for cooperative multiuser orthogonal frequency division multiplexing (MU-OFDM) cognitive radio (CR) systems. By simplifying a three-node relay network to a two node network with the equivalent channel gain, we formulate the resource allocation problem for a cooperative MU-OFDM CR system in a similar form to that for a non-cooperative MU OFDM CR system. With this problem formulation, a rule is derived for performing subcarrier assignment operations under a given power distribution, where the sum capacity optimization is alternated between the subcarrier and power to form a joint subcarrier and power allocation algorithm. To simplify the high complexity optimal power allocation algorithm (i.e., the iterative partitioned water-filling algorithm) for the joint scheme, we further develop a simple method for updating the water level when each subcarrier is assigned. Simulation results show that, with or without cooperative transmission, using the proposed method to update the water level achieves a system capacity close to that of the joint subcarrier and power allocation algorithm with the optimal power distribution. In addition, if the relay node is at the midpoint between the source and destination, the system capacity can reach its maximum value.

Cross-layer Resource Scheduling in OFDM-based Cooperative Cognitive Radio Networks

协同通信与认知无线电是未来移动通信的重要技术。针对基于OFDM的无线协同认知网络中的资源分配问题，该文提出了一种有效的跨层资源调度方案。该调度方案在考虑对主用户所受干扰功率进行控制的前提下，以最大化认知用户超帧中总的传输速率为目标，在调度帧中对各传输帧两阶段的子载波进行最佳配对，并为配对子载波分配最优的发送功率。通过分步求解的方法，该调度方案形成的优化问题得到有效解决。仿真结果表明该资源调度方案使得认知用户传输速率有显著提升，方案的可行性与有效性得到了验证。

QoS Provisioning for Heterogeneous Services in Cooperative Cognitive Radio Networks

In this paper, we propose a spectrum allocation framework that jointly considers the Quality-of-Service (QoS) provisioning for heterogeneous secondary Real-Time (RT) and Non-Real Time (NRT) users, the spectrum sensing, spectrum access decision, channel allocation, and call admission control in distributed cooperative Cognitive Radio Networks (CRNs). Giving priority to the RT users with QoS requirements in terms of the dropping and blocking probabilities, a number of the identified available channels are allocated to the optimum number of the RT users that can be admitted into the network, while the remaining identified available channels are allocated adaptively to the optimum number of the NRT users considering the spectrum sensing and utilization indispensability. Extensive analytical and simulation results are provided to demonstrate the effectiveness of the proposed QoS-based spectrum resource allocation framework.

Robust detection analysis of linear cooperative spectrum sensing for cognitive radio networks

Robust detection is employed in this work to cope with uncertainties on the channel gains and the noise power levels in a cognitive radio system based on linear cooperative spectrum sensing. The minimum number of samples required to achieve given false-alarm and missed-detection probabilities is derived as a function of the system parameter uncertainty levels and the nominal SNRs. A lower bound to the received symbol energy required to achieve reliable system operation is derived. This lower bound extends the concept of SNR wall to the case of a cooperative CR system with multiple secondary users. Then, a symmetric CR system scenario is investigated analytically and by numerical simulations. Simple asymptotic results are obtained in this case to relate the minimum number of samples required and the system parameters.

Coalitional Game Theoretic Approach for Secondary Spectrum Access in Cooperative Cognitive Radio Networks

In this paper, we exploit a novel setting for Cognitive Radio (CR) networks to enable multiple operators to involve secondary users (SUs) as cooperative relays for their primary users. In return, SUs get an opportunity to access spare channels for their own data transmission. Initially, we assume that the CR network supports payment transfer. Then, we formulate the system as a transferable utility coalitional game. We show that there is an operating point that maximizes the sum utility over all operators and SUs while providing each player a share such that no subset of operators and SUs has an incentive to break away from the grand coalition. Such operating points exist when the solution set of the game, the core, is nonempty. Subsequently, we examine an interesting scenario where there is no payment mechanism in the network. This scenario can be investigated by using a nontransferable utility coalitional game model. We show that there exists a joint action to make the core nonempty. A general method with exponential computational complexity to get such a joint action is discussed. Then, we relate the core of this game to a competitive equilibrium of an exchange economy setting under special situations. As a result, several available efficient centralized or distributed algorithms in economics can be employed to compute a member in the core. In a nutshell, this paper constitutes the design of new coalition based dynamics that could be used in future CR networks.

Cooperative Spectrum Sensing for Cognitive Radios Using Kriged Kalman Filtering

A cooperative cognitive radio (CR) sensing problem is considered, where a number of CRs collaboratively detect the presence of primary users (PUs) by exploiting the novel notion of channel gain (CG) maps. The CG maps capture the propagation medium per frequency from any point in space and time to each CR user. They are updated in real-time using Kriged Kalman filtering (KKF), a tool with well-appreciated merits in geostatistics. In addition, the CG maps enable tracking the transmit-power and location of an unknown number of PUs, via a sparse regression technique. The latter exploits the sparsity inherent to the PU activities in a geographical area, using an <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ℓ</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -norm regularized, sparsity-promoting weighted least-squares formulation. The resulting sparsity-cognizant tracker is developed in both centralized and distributed formats, to reduce computational complexity and memory requirements of a batch alternative. Numerical tests demonstrate considerable performance gains achieved by the proposed algorithms .

A Low-Interference Relay Selection for Decode-and-Forward Cooperative Network in Underlay Cognitive Radio

In the underlay decode-and-forward (DaF) cooperative cognitive radio (CR) network, an optimal relay can be selected by the conventional max-min selection on the condition of not violating the interference temperature (IT) constraint. However, the max-min selection may cause some extra amount of interference to the primary system (PS) such that the so-called transfer ratio (TR) may be lower. Note that TR is newly defined as the ratio of the secondary system's (SS's) capacity gain to the PS's capacity loss due to the activities of SS. In order to improve the TR value, we are motivated by the pricing function in game theory to propose a novel low-interference relay selection by taking the impacts of the interference from SS to PS into consideration. Using the low-interference selection, however, it will not always allow the optimal relay to be picked. To clarify this phenomenon, the still optimal probability is defined as the probability of selecting the optimal relay by the proposed scheme. In addition, the impacts of the low-interference selection on the SS's capacity and outage probability are also analyzed. The simulation results prove that compared with the max-min selection, the proposed scheme can achieve higher TR values as well as the total capacity which also indicates that a higher spectrum efficiency can be achieved. It is believed that the results of this paper can provide an alternative viewpoint of evaluating the spectrum efficiency and inspire more interesting and important research topics in the future.