This letter proposes a novel decision fusion algorithm for cooperative spectrum sensing in cognitive radio sensor networks where a reinforcement learning algorithm is utilized at the fusion center to estimate the sensing performance of local spectrum sensing nodes. The estimates are then used to determine the weights of local decisions for the final decision making process that is based on the Chair-Vashney optimal decision fusion rule. Simulation results show that the sensing accuracy of the proposed scheme is comparable to that of the Chair-Vashney optimal decision fusion based scheme even though it does not require any knowledge of prior probabilities and local sensing performance of spectrum sensing nodes.

This paper discusses the possibility of deploying a short-range cognitive radio (secondary communication system) within the service area of a primary system. Although the secondary system interferes with the primary system, there are certain locations in the service area of the primary system where the cognitive radio can reuse the frequency of the primary system without causing harmful interference to it and being disturbed by the primary system. These locations are referred to as having a spatial opportunity for communications in the secondary system, since it can reuse the frequency of the primary system. Simulation results indicate that the antenna gain, beamwidth, and propagation path loss greatly affect the spatial opportunity of frequency reuse for the secondary users. The results show that spatial spectrum reuse can be significantly increased when the primary system users are equipped with directional antennas. An important component in this study is the heterogeneous path loss model, i.e., the path loss model within the primary system is different from the model used to calculate the interference between the primary and the secondary systems. Our results show that the propagation models corresponding to the actual antenna heights in the primary/secondary system can largely impact the possibilities for spectrum reuse by the cognitive radios.

Multiple antenna is introduced into spectrum sensing in cognitive radios recently. However, conventional multiple antenna spectrum sensing schemes exploited only space diversity. In this paper, we propose a new multiple antenna sensing scheme based on space and time diversity (MASS-BSTD). First, the primary user signal to be sensed is over-sampled at each antenna, and signal samples collected at the same time instant from different antennas are stacked into a column vector. Second, each column vector is utilized to estimate space correlation matrix that exploits space diversity, and two consecutive column vectors are utilized to estimate time correlation matrix that exploits time diversity. Third, the estimated space correlation matrix and time correlation matrix are combined and analyzed using eigenvalue decomposition to reduce information redundancy of signals from multiple antennas. Lastly, the derived eigenvalues are utilized to construct the test statistic and sense the presence of the primary user signal. Since the proposed MASS-BSTD exploits both space diversity and time diversity, it achieves performance gain over the counterparts that only exploit space diversity. Furthermore, the proposed MASS-BSTD requires no prior information on the primary user, the channel between primary user transmitter and secondary user receiver, and is robust to noise uncertainty. Theoretical analysis and simulation results show that the proposed MASS-BSTD can sense the presence of primary user signal reliably.

Utilizing available channels to improve the network performance is one of the most important targets for the cognitive MAC protocol design. Using antenna technologies is an efficient way to reach this target. Therefore, in this paper, we propose a novel cognitive MAC protocol, called Polarization-based Long-range Communication Directional MAC Protocol (PLRC-DMAC), for Cognitive Ad Hoc Networks (CAHNs). The proposed protocol uses directional antennas to acquire better spatial reuse and establish long-range communication links, which can support more nodes to access the same channel simultaneously. Moreover, the PLRC-DMAC also uses polarization diversity to allow nodes in the CAHN to share the same channel with Primary Users (PUs). Furthermore, we also propose a Long-range Orientation (LRO) algorithm to orient the long-range nodes. Simulation results show that the LRO algorithm can accurately orient the long-range nodes, and the PLRC-DMAC can significantly increase the network throughput as well as reduce the end-to-end delay.

The performance of spectrum sensing in cognitive radio can be improved by employing multiple antennas. In this letter, the effect of antenna correlation on the performance improvement by deploying multiple antennas in the sensing node of the secondary system is investigated. It is proved mathematically that in the regime of low SNR, with antenna correlation, the secondary sensing node can achieve almost the same performance improvement as that without correlation. Simulation results verify the conclusions.

Mobile operators need to migrate from 2G to 3G networks in a cost-effective manner. Cognitive radio systems are currently being investigated as a promising solution to achieve spectrum efficiency by allowing coexistence of unlicensed (secondary) networks and licensed (primary) networks. However, conventional mechanisms to operate these systems incur additional complexity and fail to maximize network performance. In this paper, we propose a pilot sensing and frequency selection method with low complexity for OFDMA-based cognitive radio systems. Subject to the interference constraints imposed by the primary network, capacity maximization problems involving both up-link and down-link connections are considered for overall network performance improvement. The throughput and outage probability of the proposed method are evaluated by simulations. Our proposed method shows outstanding performance if the channel varies frequently in the primary network and the frequency reuse factor of the primary network is high.

The sensing scheme based on the generalized likelihood ratio test (GLRT) technique has attracted a lot of research interest in the field of cognitive radios (CR). Although its potential advantages in detecting correlated primary signal have been illustrated in prior work, no theoretical analysis of the positive effects of the correlation has appeared in the literature. In this letter, we derive the theoretical false-alarm and detection probabilities of GLRT detector. The theoretical analysis shows that, in the low signal-to-noise ratio (SNR) region, the detector's performance can be improved by exploiting the high correlations between the primary signal samples. The conclusions of the analysis are verified by numerical simulation results.

Wireless regional area network (WRAN) is intended to offer the fixed wireless access services using cognitive radio technology in the TV white space. Therefore, WRAN shall minimize the transmission power so that harmful interference is not imposed on the licensed users operating in the TV bands. In this paper, we propose a processing block that offers improvements in the SNR and diversity gain using the block to algebraically process two constellation symbols. Thus, the transmission power can be reduced by an amount equal to the gains. The simulation result shows that the proposed scheme has a better bit error performance than the transmission scheme defined in the IEEE 802.22 draft standard.

It is known that a heterodyne multimode receiver implemented with a single RF (Radio Frequency) receiver suffers from image-band interference due to imbalance, i.e. the phase error and the gain imbalance of the RF Hilbert transformer. The blind image band interference canceler with deterministic imbalance estimation that has been proposed mitigates the image-band interference. This performance of the image-band interference canceler is analyzed theoretically in this paper. As a result, it is revealed that estimation accuracy of the deterministic imbalance estimation is improved slightly as the imbalance becomes greater. In addition, it is also shown that the deterministic estimation achieves better performance as the power of image-band interference increases. The performance is confirmed by computer simulation.

The traditional spectrum auctions require a central auctioneer. Then, the secondary users (SUs) can bid for spectrum in multiple auction or sealed auction way. In this paper, we address the problem of distributed spectrum sharing in the cognitive networks where multiple owners sell their spare bands to multiple SUs. Each SU equips multi-interface/multi-radio, so that SU can buy spare bands from multiple owners. On the other hand, each owner can sell its spare bands to serval SUs. There are two questions to be addressed for such an environment: the first one is how to select bands/the owners for each SU; the second one is how to decide the competitive prices for the multiple owners and multiple SUs. To this end, we propose a two-side multi-band market game theoretic framework to jointly consider the benefits of all SUs and owners. The equilibrium concept in such games is named core. The outcomes in the core of the game cannot be improved upon by any subset of players. These outcomes correspond exactly to the price-lists that competitively balance the benefits of all SUs and owners. We show that the core in our model is always non-empty. When the measurement of price takes discrete value, the core of the game is defined as discrete core. The Dynamic Multi-band Sharing algorithm (DMS) is proposed to converge to the discrete core of the game. With small enough measurement unit of price, the algorithm can achieve the optimal performance compared with centralized one in terms of the system utility.

We consider the problem of transmit power and bit rate allocation for OFDM based cognitive radio systems. An efficient allocation algorithm which mainly consists of two steps is proposed to maximize the sum rate of secondary users. In the first step of the algorithm, original nonlinear problem is converted to a convex problem which is solved by dual methods, and in the second step the final resource allocation results is obtained via iterative power rescale operation. Numerical results show the effectiveness of the proposed algorithm.

This paper proposes a concept for a new technical field called wireless distributed network (WDN) as a strategic technical field to enable flexible networking and radio resource management (RRM) to cope with dynamic variation of spatially distributed traffic demands. As the core technical subject areas for the WDN, this paper identifies distributed networking for flexible network creation, cooperative transmission and reception for flexible link creation, and dynamic spectrum access for flexible radio resource management, and explains their technical features and challenges for constructing the WDN. This paper also discusses some already being studied application fields as well as potential future directions of the WDN applications.

A Gaussian MIMO broadcast channel (GMBC) models the MIMO transmission of Gaussian signals from a transmitter to one or more receivers. Its capacity region and different precoding schemes for it have been well investigated, especially for the case wherein there are only transmit power constraints. In this paper, a special case of GMBC is investigated, wherein receive power constraints are also included. By imposing receive power constraints, the model, called protected GMBC (PGMBC), can be applied to certain scenarios in spatial spectrum sharing, secretive communications, mesh networks and base station cooperation. The sum capacity, capacity region, and application examples for the PGMBC are discussed in this paper. Sub-optimum precoding algorithms are also proposed for the PGMBC, where standard user precoding techniques are performed over a BC with a modified channel, which we refer to as the "protection-implied BC." In the protection-implied BC, the receiver protection constraints have been implied in the channel, which means that by satisfying the transmit power constraints on the protection implied channel, receiver protection constraints are guaranteed to be met. Any standard single-user or multi-user MIMO precoding scheme may then be performed on the protection-implied channel. When SINR-matching duality-based precoding is applied on the protection-implied channel, sum-capacity under full protection constraints (zero receive power), and near-sum-capacity under partial protection constraints (limited non-zero receive power) are achieved, and were verified by simulations.

In a spectrum sharing system, lower-priority users are allowed to spatially reuse the spectrum allocated to higher-priority users as long as they do not disrupt communications of the latter. Therefore, to improve spectrum utilization, an important requirement for the former users is to manage the interference and ensure that the latter users can maintain reliable communications. In the present paper, a game theoretic framework of joint channel selection and power allocation for spectrum sharing in distributed cognitive radio networks is proposed. First, a utility function that captures the cooperative behavior to manage the interference and the satisfaction level to improve the throughput of the lower-priority users is defined. Next, based on the defined utility function, the proposed framework can be formulated as a potential game; thus, it is guaranteed to converge to a Nash equilibrium when the best response dynamic is performed. Simulation results show the convergence of the proposed potential game and reveal that performance improvements in terms of network throughput of the lower-priority users and outage probability of the higher-priority users can be achieved by the introduction of an adaptive coefficient adjustment scheme in the proposed utility function at the expense of the convergence to the Nash equilibrium.

The spectrum handoff problem for cognitive radio systems is considered in this paper. The secondary users (SUs) can only opportunistically access the spectrum holes, i.e. the frequency channels unoccupied by the primary users (PUs). As long as a PU appears, SUs have to vacate the channel to avoid interference to PUs and switch to another available channel. In this paper, a prediction-based spectrum handoff scheme is proposed to reduce the negative effect (both the interference to PUs and the service block of SUs) during the switching time. In the proposed scheme, a hidden Markov model is used to predict the occupancy of a frequency channel. By estimating the state of the model in the next time instant, we can predict whether the frequency channel will be occupied by PUs or not. As a cross-layer design, the spectrum sensing performance parameters false alarm probability and missing detection probability are taken into account to enhance accuracy of the channel occupancy prediction. The proposed scheme will react on the spectrum sensing algorithm parameters while the spectrum handoff performance is significantly affected by them. The interference to the PUs could be reduced obviously by adapting the proposed spectrum handoff scheme, associated with a potential increase of switch delay of SUs. It will also be helpful for SUs to save broadband scan time and prefer an appropriate objective channel so as to avoid service block. Numerical results demonstrate the above performance improvement by using this prediction-based scheme.

A channel-hopping medium access control (MAC) protocol is proposed for cognitive operation of the 802.16d Mesh networks. The proposal mainly includes a channel-hopping algorithm of channel accessing for control messages transmission and reception, an algorithm of bandwidth allocation in cognitive operation, a cognition-enhanced frame structure, a method of spectrum sensing results reporting, and a method of incumbent detection. Compared to other studies, the channel-hopping algorithm for control messages transmission and reception requires no extra common control channels and operation of mesh clusters, thus it is more cost-effective and simpler in operation. Analysis shows that with this algorithm a Mesh node with any available channels has fair opportunities to receive beacon and network configuration information. Numerical results show that, compared to the mesh cluster method, the proposed channel-hopping algorithm has gain, e.g., as high as 3 times, in getting the data scheduling control messages received by one-hop neighbors, thus it has advantages in minimizing bandwidth allocation collisions. The algorithm of bandwidth allocation details the three-way handshake framework for bandwidth application and grant that is defined in 802.16d Mesh standard, and it enables dynamical resource allocations in cognitive operations. The feasibility of the channel-hopping MAC protocol is confirmed by simulations. And simulation results show that with the parameters set, a normalized aggregate saturation throughput of about 70% is achievable.

From the viewpoint of service availability, which is an important evaluation factor in communication quality, we analytically study the performance improvement of heterogeneous radio networks that cooperatively select one system from among multiple communication systems. It is supposed herein that the heterogeneous network selects one system with the larger throughput or with the smaller time delay. To this end, we firstly derive analytical methods using the probability density function of the performance characteristics of the communication systems consisting of the heterogeneous radio network. The analytical method described here is comparatively general and enables the handling of cases where complete cooperation can and cannot be achieved in the heterogeneous network. As for the performance characteristics, we conduct an experiment using the wireless LAN to establish the probability distribution models of the throughput and time delay in the communication system. Using the analytical method and the experimental model obtained, we calculate the performance improvement by cooperative operation in the heterogeneous network. The equational expression to obtain the theoretical performance improvement limit is also investigated through the analytical equations.

In a periodic spectrum sensing framework where each frame consists of a sensing block and a data transmitting block, increasing sensing duration decreases the probabilities of both missed opportunity and interference with primary users, but increasing sensing duration also decreases the energy efficiency and the transmitting efficiency of the cognitive network. Therefore, the sensing duration to use is a trade-off between sensing performance and system efficiencies. The relationships between sensing duration and state transition probability are analyzed firstly, when the licensed channel stays in the idle and busy states respectively. Then a state transition probability based sensing duration optimization algorithm is proposed, which can dynamically optimize the sensing duration of each frame in the current idle/busy state by predicting each frame's state transition probability at the beginning of the current state. Analysis and simulation results reveal that the time-varying optimal sensing duration increases as the state transition probability increases and compared to the existing method, the proposed algorithm can use as little sensing duration in each frame as possible to satisfy the sensing performance constraints so as to maximize the energy and transmitting efficiencies of the cognitive networks.

Selections of radio access networks by terminals are currently not coordinated and utilizations of the radio resources are not balanced. As a result, radio resources on some radio systems are occupied even though others can afford. In this paper, in order to provide a framework to resolve this issue, Cognitive Wireless Router (CWR) system is proposed for distributed management and independent reconfiguration of heterogeneous wireless networks. The proposed system selects appropriate operational frequency bands and radio systems to connect to the Internet in corporation between the CWRs and a server and therefore can provide optimized wireless Internet access easily even in environments without wired networks. The developed prototype system reconfigures the radio devices to connect to the Internet in 27 seconds at most. It is revealed that this reconfiguration time can be shortened to less than 100 ms by elaborating its procedure. It is also clarified that network data speed required at the server to deal with 10,000 CWRs is only 4.1 Mbps.

Spectrum sensing is a fundamental function for cognitive radio network to protect transmission of primary system. Cooperative spectrum sensing, which can help increasing sensing performance, is regarded as one of the most promising methods in realizing a reliable cognitive network. In such cooperation system, however the communication resources such as sensing time delay, control channel bandwidth and consumption energy for reporting the cognitive radio node's sensing results to the fusion center may become extremely huge when the number of cognitive users is large. In this paper, we propose an ordered sequential cooperative spectrum sensing scheme in which the local sensing data will be sent according to its reliability order to the fusion center. In proposed scheme, the sequential fusion process is sequentially conducted based on Dempster Shafer theory of evidence's combination of the reported sensing results. Above all, the proposed scheme is highly feasible due to the proposed two ordered sequential reporting methods. From simulation results, it is shown that the proposed technique not only keeps the same sensing performance of non-sequential fusion scheme but also extremely reduces the reporting resource requirements.