In this study, we propose a cooperative sensing with distributed pre-detection for gathering sensing information on shared primary system. We have proposed a system that gathers multiple sensing information by using the orthogonal narrowband signal; the system is called the orthogonal frequency-based sensing information gathering (OF-SIG) method. By using this method, sensing information from multiple secondary nodes can be gathered from the surrounding secondary nodes simultaneously by using the orthogonal narrowband signals. The advantage of this method is that the interference from each node is small because a narrowband tone signal is transmitted from each node. Therefore, if appropriate power and transmission control are applied at the surrounding nodes, the sensing information can be gathered in the same spectrum as the primary system. To avoid interference with the primary receiver, we propose a cooperative sensing with distributed pre-detection for gathering sensing information in each node by limiting sensing node power. In the proposed method, the number of sensing information transmitting nodes depends on the pre-detection ability of the individual sensing at each node. Then the secondary node can increase the transmit power by improving the sensing detection ability, and the secondary node can gather the sensing information from the surrounding secondary nodes which are located more far by redesign the transmit power of the secondary nodes. Here, we design the secondary transmit power based on OF-SIG while considering the aggregated interference from multiple sensing nodes and individual sensing ability. Finally we confirm the performance of the cooperative sensing of the proposed method through computer simulation.

In this paper, a Spectrum-Aware Routing (SAR) protocol for cognitive radio ad hoc networks, (CRAHN), is proposed which is robust to primary user activity and node failures. The protocol allows nodes to collect spectrum information during a spectrum management interval followed by a transmission period. Cognitive users discover routes by joint channel and next hop selection (synchronization) in the transmission intervals. A restricted geographical routing approach is adopted to avoid performance degradation specially due to routing overhead. We also add spectrum mobility capabilities to routes in our proposed method to provide robustness to primary user activity. SAR protocol performance is investigated through simulations of different scenarios and is compared with the most similar work, CAODV protocol. The results indicate that SAR can achieve significant reduction in control overhead as well as improved throughput.

In this letter, we focus on detecting a random primary user (PU) network for cognitive radio systems in a cooperative manner by using maximum likelihood (ML) detection. Different from traditional PU network models, the random PU network model in this letter considers the randomness in the PU network topology, and so is better suited for describing the infrastructure-less PU network such as an ad hoc network. Since the joint pdf required for the ML detection is hard to obtain in a closed form, we derive approximate ones from the Gaussian approximation. The performance of the proposed algorithm is comparable to the optimal one.

This paper investigates the use of cooperative spectrum sensing (CSS) to detect primary user (PU) signals during spectrum sharing between the PU and the secondary user (SU). In particular, we employ a variant of CSS (which achieves space diversity), called weighted gain combining CSS (W-CSS), which has the potential to achieve increased diversity gain and enhance detection performance. In a typical W-CSS system, the SU needs to obtain the PU signal power information in order to set the proper weight value. However, as it is hard for the SU to ascertain whether the PU is present or absent, this is difficult to obtain. To address this problem, a PU signal power estimation algorithm is introduced. In addition, we also analyze the statistics of the estimator and derive the detection probability of the W-CSS when the PU signal power estimation algorithm is applied. The analysis and related simulation results reveal that the detection probability of the proposed W-CSS under time-variant Rayleigh fading asymptotically approaches the detection probability in an additive white Gaussian noise channel as the number of antennas is increased. This also follows results from our Monte Carlo simulations, showing that multiple antenna elements could suppress the effect of Rayleigh fading. In short, the accuracy of the estimation algorithm is affected by channel variation (especially in the case of fast Rayleigh fading). Hence, to address this problem, we employ multiple antenna elements with a square-law combining energy detector in the W-CSS.

In this letter we propose a practical sensing-based opportunistic spectrum sharing scheme for cognitive radio (CR) downlink MIMO systems. Multi-antennas are exploited at the secondary transmitter to opportunistically access the primary spectrum and effectively achieve a balance between secondary throughput maximization and mitigation of interference probably caused to primary radio link. We first introduce a brief secondary frame structure, in which a sensing phase is exploited to estimate the effective interference channel. According to the sensing result and taking the interference caused by the primary link into account, we propose an enhanced signal-to-leakage-and-noise ratio (SLNR)-based precoding scheme for the secondary transmitter. Compared to conventional schemes where perfect knowledge of the channels over which the CR transmitter interferes with the primary receiver (PR) is assumed, our proposed scheme shows its superiority and simulation results validate this.

A price-based spectrum investment and pricing scheme in cooperative cognitive radio networks is presented to use wireless resource more efficiently in technical and economic aspects. We analyze the impact of cooperative communications and the relationship between spectrum hole cost and leasing cost in the optimal decision of SAP.

In this paper, the resource allocation problem for proportional fairness in hybrid Cognitive Radio (CR) systems is studied. In OFDMA-based CR systems, traditional resource allocation algorithms can not guarantee proportional rates among CR users (CRU) in each OFDM symbol because the number of available subchannels might be smaller than that of CRUs in some OFDM symbols. To deal with this time-varying nature of available spectrum resource, a hybrid CR scheme in which CRUs are allowed to use subchannels in both spectrum holes and primary users (PU) bands is adopted and a resource allocation algorithm is proposed to guarantee proportional rates among CRUs with no undue interference to PUs.

A sensing efficiency optimization scheme based on two-stage spectrum sensing that maximizes the achievable throughput of the secondary network and minimizes the average sensing time is proposed in this paper. A selection method for the threshold is proposed and proved to ensure optimal sensing performance. An effective iterative algorithm is presented to solve the constructed efficiency optimization problem.

In this letter, we address the performance analysis of underlay selective decode-and-forward (DF) relay networks in Rayleigh fading channels with non-necessarily identical fading parameters. In particular, a novel result on the outage probability of the considered system is presented. Monte Carlo simulations are performed to verify the correctness of our exact closed-form expression. Our proposed analysis can be adopted for various underlay spectrum sharing applications of cognitive DF relay networks.

In this paper, a hybrid overlay/underlay cognitive radio system is modeled as an M/M/1 queue where the rate of arrival and the service capacity are subject to Poisson alternations. Each packet as a customer arriving at the queue makes a decision to join the queue or not. Upon arrival, the individual decision of each packet is optimized based on his observation about the queue length and the state of system. It is shown that the individually optimal strategy for joining the queue is characterized by a threshold of queue length. Thus, the individual optimal threshold of queue length is analyzed in detail in this work.

This paper proposed three channel aggregation schemes for cognitive radio networks, a constant channel aggregation scheme, a probability distribution-based variable channel aggregation scheme, and a residual channel-based variable channel aggregation scheme. A cognitive radio network can have a wide bandwidth if unused channels in the primary networks are aggregated. Channel aggregation schemes involve either constant channel aggregation or variable channel aggregation. In this paper, a Markov chain is used to develop an analytical model of channel aggregation schemes; and the performance of the model is evaluated in terms of the average sojourn time, the average throughput, the forced termination probability, and the blocking probability. Simulation results show that channel aggregation schemes can reduce the average sojourn time of cognitive users by increasing the channel occupation rate of unused channels in a primary network.

Underlay cognitive systems allow secondary users (SUs) to access the licensed band allocated to primary users (PUs) for better spectrum utilization with the power constraint imposed on SUs such that their operation does not harm the normal communication of PUs. This constraint, which limits the coverage range of SUs, can be offset by relaying techniques that take advantage of shorter range communication for lower path loss. Symbol error rate (SER) analysis of underlay cognitive relay systems over fading channel has not been reported in the literature. This paper fills this gap. The derived SER expressions are validated by simulations and show that underlay cognitive relay systems suffer a high error floor for any modulation level.

An adaptive rate controller (ARC) based on an adaptive neural fuzzy inference system (ANFIS) is designed to autonomously adjust the data rate of a mobile heterogeneous network to adapt to the changing traffic load and the user speed for multimedia call services. The effect of user speed on the handoff rate is considered. Through simulations, it has been demonstrated that the ANFIS-ARC is able to maintain new call blocking probability and handoff failure probability of the mobile heterogeneous network below a prescribed low level over different user speeds and new call origination rates while optimizing the average throughput. It has also been shown that the mobile cognitive wireless network with the proposed CS-ANFIS-ARC protocol can support more traffic load than neural fuzzy call-admission and rate controller (NFCRC) protocol.

Cognitive radio is an emerging technology to further improve the efficiency of spectrum use. Due to the nature of the technology, it has many facets, including its enabling technologies, its implementation issues and its regulatory implications. In ITU-R (International Telecommunications Union – Radiocommunication sector), cognitive radio systems are currently being studied so that ITU-R can have a clear picture on this new technology and its potential regulatory implications, from a viewpoint of global spectrum management. This paper introduces the recent results of the ITU-R studies on cognitive radio on both regulatory and technical aspects. This paper represents a personal opinion of the author, but not an official view of the ITU-R.

It is important to optimize aggregation schemes for heterogeneous wireless networks for maximizing communication throughput utilizing any available radio access networks. In the heterogeneous networks, differences of the quality of service (QoS), such as throughput, delay and packet loss rate, of the networks makes difficult to maximize the aggregation throughput. In this paper, we firstly analyze influences of such differences in QoS to the aggregation throughput, and show that it is possible to improve the throughput by adjusting the parameters of an aggregation system. Since manual parameter optimization is difficult and takes much time, we propose an autonomous parameter tuning scheme using a machine learning algorithm for the heterogeneous wireless network aggregation. We implement the proposed scheme on a heterogeneous cognitive radio network system. The results on our experimental network with network emulators show that the proposed scheme can improve the aggregation throughput better than the conventional schemes. We also evaluate the performance using public wireless network services, such as HSDPA, WiMAX and W-CDMA, and verify that the proposed scheme can improve the aggregation throughput by iterating the learning cycle even for the public wireless networks. Our experimental results show that the proposed scheme achieves twice better aggregation throughput than the conventional schemes.

An important and widely considered signal identification technique for cognitive radios is cyclostationarity-based feature detection because this method does not require time and frequency synchronization and prior information except for information concerning cyclic autocorrelation features of target signals. This paper presents the development and experimental evaluation of cyclostationarity-based signal identification equipment. A spatial channel emulator is used in conjunction with the equipment that provides an environment to evaluate realistic spectrum sharing scenarios. The results reveal the effectiveness of the cyclostationarity-based signal identification methodology in realistic spectrum sharing scenarios, especially in terms of the capability to identify weak signals.

of late, many researchers have been interested in sparse representation of signals and its applications such as Compressive Sensing in Cognitive Radio (CR) networks as a way of overcoming the issue of limited bandwidth. Compressive sensing based wideband spectrum sensing is a novel approach in cognitive radio systems. Also in these systems, using spatial-frequency opportunistic reuse is emerged interestingly by constructing and deploying spatial-frequency Power Spectral Density (PSD) maps. Since the CR sensors are distributed in the region of support, the sensed PSD by each sensor should be transmitted to a master node (base-station) in order to construct the PSD maps in space and frequency domains. When the number of sensors is large, this data transmission which is required for construction of PSD map can be challenging. In this paper, in order to transmit the CR sensors' data to the master node, the compressive sensing based scheme is used. Therefore, the measurements are sampled in a lower sampling rate than of the Nyquist rate. By using the proposed method, an acceptable PSD map for cognitive radio purposes can be achieved by only 30% of full data transmission. Also, simulation results show the robustness of the proposed method against the channel variations in comparison with classical methods. Different solution schemes such as Basis Pursuit, Lasso, Lars and Orthogonal Matching Pursuit are used and the quality performance of them is evaluated by several simulation results over a Rician channel with respect to several different compression and Signal to Noise Ratios. It is also illustrated that the performance of Basis Pursuit and Lasso methods outperform the other compression methods particularly in higher compression rates.

We propose a new cognitive radio network architecture using the IP multimedia subsystem (IMS) functionality. We implement the cognitive radio network entities standardized in IEEE 1900.4 on the IMS that exchanges RAN and terminal context information between the networks and the terminals to make optimum and immediate reconfiguration decisions. In our proposed architecture, RAN context information is obtained from cellular networks which are directly connected to the IMS. The presence management functions of the IMS are applied to exchange those information in a “push” manner, which enables immediate notification of changes in wireless environment. We evaluate the performance of the proposed context information exchange method, by comparing with the cases that adequate and immediate RAN context information is not available. The evaluation results show that the proposed framework gives 10–30% superior performance than the conventional cognitive radio networks.

In this paper, we study the problem of distributed spectrum allocation under a vertical spectrum sharing scenario in a cognitive radio network. The secondary users share the spectrum licensed to the primary user by observing the activity statistics of the primary users, and regulate their transmission strategy in order to abide by the spectrum sharing etiquette. When the primary user is inactive in a subset of the available frequency bands, from the perspective of the secondary users the problem reduces to a distributed horizontal spectrum sharing. For a specific class of networks, the latter problem is addressed by the recently proposed GADIA algorithm [1]. In this paper, we present analytical and numerical results on the performance of the GADIA algorithm in conjunction with the above-mentioned vertical spectrum sharing scenario. These results reveal near-optimal performance guarantees for the overall vertical spectrum sharing scenario.

In this paper, performance analysis of a cognitive radio network is conducted. In the network, there is imperfect sensing and the wireless channel is a Gilbert-Elliott channel. The focus is on the network's capacity in serving traffic with delay constraints. Specifically, the maximum traffic arrival rates of both primary users and secondary users, which the network can support with guaranteed delay bounds, are investigated. The analysis is based on stochastic network calculus. A general relationship between delay bounds, traffic patterns and important characteristics such as spectrum sensing errors and channel fading of the cognitive radio network is derived. This relationship lays a foundation for finding the capacity under different traffic scenarios. Two specific traffic types are exemplified, namely periodic traffic and Poisson traffic. Analytical results are presented in comparison with simulation results. The comparison shows a good match between them, validating the analysis.