In this paper, we propose a secondary user (SU) resource assignment algorithm for a multi-hop (MH) cognitive radio network to improve the end-to-end throughput. In the MH networks used for spectrum sharing, each SU needs to improve the throughput by taking the primary user (PU) protection into account. For overcoming this problem, we estimate the PU acceptable received power, which is determined by the acknowledgment packet (ACK) power from the PU receiver at each SU. With this estimation, we propose an SU optimal transmit power control algorithm to not only maximize the end-to-end throughput of the SU MH flow but also maintain the considered PU acceptable interference power. In this study, a distributed joint allocation algorithm has been used to solve the optimization problem and to effectively allocate the power of each SU.

This paper derives the optimal learning time for the learning-assisted rendezvous channel. One problem with the dynamic spectrum access system of cognitive radio is access channel mismatch between two wireless terminals. In the learning-assisted rendezvous channel, before exchanging packets for link connection, the rate of channel occupancy by the other system is estimated within the learning time; it is referred to as the channel occupancy rate (COR). High speed packet exchange is made possible by selecting a low COR channel. However, the optimal learning time and the impact of COR estimation errors have not been clarified yet. This paper analyzes the time to rendezvous channel (TTR), where TTR is the time needed to complete the rendezvous with a certain probability. The results indicate that the learning time and TTR have a concave relationship which means that the optimal learning time can be determined.

In this paper, resource-efficient multiple description coding (MDC) multicast is investigated in cognitive radio networks with the consideration of imperfect spectrum sensing and imperfect channel feedback. Our objective is to maximize the system goodput, which is defined as the total successfully received data rate of all multicast users, while guaranteeing the maximum transmit power budget and the maximum average received interference constraint. Owing to the uncertainty of the spectrum state and the non-closed-form expression of the objective function, it is difficult to solve the problem directly. To circumvent this problem, a pretreatment is performed, in which we first estimate the real spectrum state of primary users and then propose a Gaussian approximation for the probability density functions of transmission channel gains to simplify the computation of the objective function. Thereafter, a two-stage resource allocation algorithm is presented to accomplish the subcarrier assignment, the optimal transmit channel gain to interference plus noise ratio (T-CINR) setting, and the transmit power allocation separately. Simulation results show that the proposed scheme is able to offset more than 80% of the performance loss caused by imperfect channel feedback when the feedback error is not high, while keeping the average interference on primary users below the prescribed threshold.

Most recent work on cooperative spectrum sensing using cognitive radios has focused on issues involving the sensing channels and seemed to ignore those involving the reporting channels. Furthermore, no research has treated the effect of correlated composite Rayleigh-lognormal fading, also known as Suzuki fading, in cognitive radio. This paper proposes a technique for reuse of shadowed CRs, discarded during the sensing phase, as amplified-and-forward (AF) diversity relays for other surviving CRs to mitigate the effects of such fading in reporting channels. A thorough analysis of and a closed-form expression for the outage probability of the resulting cooperative AF diversity network in correlated composite Rayleigh-lognormal fading channels are presented in this paper. In particular, an efficient solution to the “PDF of sum-of-powers” of correlated Suzuki-distributed random variables using moment generating function (MGF) is proposed.

Cognitive radio ad hoc networks can be used to solve the problems of limited available spectrum and inefficient spectrum usage by adaptively changing their transmission parameters. Routing protocol design has a significant impact on the network performance. However, an efficient protocol that takes account of primary user flows and the long-term channel assignment issue in route selection is still missing. In this paper, we propose AODV-cog, a cognitive routing protocol for CSMA/CA ad hoc networks based on AODV. AODV-cog chooses a route by considering the effect on the primary users, available channel bandwidth and link reliability. AODV-cog also takes account of future channel utilization which is an important but underexplored issue. AODV-cog switches channels for secondary user flows when network congestion occurs. We use theoretical analysis and computer simulations to show the advantage of AODV-cog over existing alternatives.

Cognitive radio has been developed recently as a promising solution to tackle the spectrum related issues such as spectrum scarcity and spectrum underutilization. Cognitive spectrum assignment is necessary for allocating spectrum bands to secondary users in order to avoid conflicts among secondary users and maximize the total network performance under a given set of conditions. In most spectrum assignment schemes, throughput is considered as the main criterion for spectrum selection or spectrum assignment. In this paper, we propose a distortion-aware channel allocation scheme for multiple secondary users who compete for primary channels to transmit multimedia data. In the proposed scheme, idle spectrum bands are assigned to the multimedia secondary users that attain the highest video distortion reduction. The scheme is expected to mitigate the selfish behaviors of users in competing channels. The performance effectiveness of our proposed channel allocation scheme is demonstrated through simulation by comparing with a benchmark of two reference spectrum assignment schemes.

Underlay cognitive radio (CR) permits unlicensed secondary users (SUs) to transmit their own data over the licensed spectrum unless the interference from the SUs on the licensed primary user (PU) exceeds an acceptable level. This paper proposes two generalized interference alignment (IA)-based distributed optimization designs for multiple secondary transceivers in the underlay CR case with channel uncertainty under assumption that the actual channel error norm is below a certain bound. One of the designs is an extension to an existing method and the other one is a new design. In these methods, the precoding and power allocation matrices for each SU are either independently or jointly optimized for imperfect channel knowledge to maximize the secondary rates and to hold the secondary interference on the primary receiver under an acceptable limit that is determined by the primary receiver. Numerical results prove the ability of the proposed methods to support significant secondary rates provided that the PU is protected from extra interference from SUs, even in presence of channel uncertainty.

In this paper, we propose distributed medium access control (MAC) protocols based on an adaptive sensing period adjustment scheme for low-cost multiple secondary users in interweave-type cognitive radio (CR) networks. The proposed MAC protocols adjust the sensing period of each secondary user based on both primary sensing and secondary data channels in distributed manner. Then, the secondary user with the shortest sensing period accesses the medium using request-to-send (RTS) and clear-to-send (CTS) message exchange. Three components affect the length of each user's sensing period: sensing channel quality from the primary system, data channel quality to the secondary receiver, and collision probability among multiple secondary transmitters. We propose two sensing period adjustment (SPA) schemes to efficiently improve achievable rate considering the three components, which are logarithmic SPA (LSPA) and exponential SPA (ESPA). We evaluate the performance of the proposed schemes in terms of the achievable rate and other factors affecting it, such as collision probability, false alarm probability, and average sensing period.

The outage capacity of the fading cognitive multicast channel (CMC) is investigated in this paper. Assume that the instantaneous channel state information (CSI) of the interference link between the cognitive base station (CBS) and the primary user (PU) is available at the CBS, we derive the outage capacity in Rayleigh fading environments under the interference power and the transmit power constraints. Under the condition that the interference power limit is sufficiently larger or smaller than the transmit power limit, the asymptotic outage capacity is obtained in closed-form. Assume that only the channel distribution information (CDI) of the interference link is available at the CBS, the outage capacity under the interference outage and the transmit power constraints is derived in closed-form. The theoretical results are confirmed by simulations. It is shown that the outage capacity is not degraded due to partial knowledge of the interference link when the interference power limit is sufficiently larger than the transmit power limit. It is also shown that the capacity gain due to increasing the number of the secondary users (SUs) is negligible if the number of the SUs is already large. Additionally, the case of CDI with estimation error is also investigated. Interestingly, we show that the estimation error of CDI may be a positive factor for improving the outage capacity of the CMC.

Due to the high speed mobile environment, the aeronautical Cognitive Radio (CR) communications base on the channel with the time-variant stochastic non-continuous spectrum. The traditional fading channel models, such as Rayleigh, Rice, Nakagami-m and multipath channel models, can not describe the whole property of the channels of CR communications. In this letter, the statistical channel modeling scheme for aeronautical CR communications is proposed with a M/M/s(1) queuing model, which properly describes the random spectrum occupation of the primary users, i.e. aircrafts in aeronautical communications. The proposed channel model can be easily utilized in the channel simulation to testify the validity and efficiency of the aeronautical CR communications.

With the increase of the number of wireless sensing or metering devices, the collection of sensing data using wireless communication becomes an important part of a smart grid system. Cognitive radio technology can be used to facilitate the deployment of smart grid systems. In this paper, we propose a data collection and dissemination framework for cognitive radio smart grid systems to fully utilize wireless resources while maintaining a reliably connected and efficient topology for each channel. In the proposed framework, each sensor node selects a channel considering the primary user (PU) channel utilization and network connectivity. In this way, the data collection and dissemination can be performed with a high reliability and short delay while avoiding a harmful effect on primary users. We use computer simulations to evaluate the proposed framework.

In this paper we present a cognitive architecture inspired on the biological functioning of the motor system in humans. To test the model, we built a robotic hand with a Lego Mindstorms™ kit. Then, through communication between the architecture and the robotic hand, the latter was able to perform the movement of the fingers, which therefore allowed it to perform grasping of some objects. In order to obtain these results, the architecture performed a conversion of the activation of motor neuron pools into specific degrees of servo motor movement. In this case, servo motors acted as muscles, and degrees of movement as exerted muscle force. Finally, this architecture will be integrated with high-order cognitive functions towards getting automatic motor commands generation, through planning and decision making mechanisms.

This paper investigates power allocation and outage performance for the MIMO full duplex relaying (MFDR) based on orthogonal space-time block Codes (OSTBC) in cognitive radio systems. OSTBC transmission is used as a simple way to obtain multi-antenna diversity gain. Cognitive MFDR systems offer the advantage not only of increasing spectral efficiency by spectrum sharing but also of extending the coverage through the use of relays. In cognitive MFDR systems, the primary user experiences interference from the secondary source and relay simultaneously due to the full duplexing. What is therefore needed is a way to optimize the transmission powers at the secondary source and relay. Therefore, we propose an optimal power allocation (OPA) scheme based on minimizing the outage probability in cognitive MFDR systems. We then analyze the outage probability of the secondary user in the noise-limited and interference-limited environments under Nakagami-m fading channels. Simulation results show that the proposed schemes achieve performance improvement in terms of outage probability.

Cognitive radio is one of the most promising wireless technologies and has been recognized as a new way to improve the spectral efficiency of wireless networks. In a cognitive radio network, secondary users exchange control information for network coordination such as transmitter-receiver handshakes, for sharing spectrum sensing results, for neighbor discovery, to maintain connectivity, and so on. Spectrum utilization and resource optimizations thus rely on information exchange among secondary users. Normally, secondary users exchange the control information via a predefined channel, called a common control channel (CCC). Most of the medium access control (MAC) protocols for cognitive radio networks were designed by assuming the existence of a CCC, and further assuming that it was available for every secondary user. However, the main drawback of using a static CCC is it is susceptible to primary user activities since the channel can be occupied by primary users at any time. In this paper, we propose a MAC protocol for cognitive radio networks with dynamic control channel assignment, called DYN-MAC. In DYN-MAC, a control channel is dynamically assigned based on spectrum availability. Thus, it can tolerate primary user activities. DYN-MAC also supports collision free network-wide broadcasting and addresses other major problems such as primary/secondary user hidden terminal problems.

This paper studies an underlay-based cognitive two-way relay network which consists of a primary network (PN) and a secondary network (SN). Two secondary users (SUs) exchange information with the aid of multiple single-antenna amplify-and-forward relays while a primary transmitter communicates with a primary receiver in the same spectrum. Unlike the existing contributions, the transmit powers of the SUs and the distributed beamforming weights of the relays are jointly optimized to minimize the sum interference power from the SN to the PN under the quality-of-service (QoS) constraints of the SUs determined by their output signal-to-interference-plus-noise ratio (SINR) and the transmit power constraints of the SUs and relays. This approach leads to a non-convex optimization problem which is computationally intractable in general. We first investigate two necessary conditions that optimal solutions should satisfy. Then, the non-convex minimization problem is solved analytically based on the obtained conditions for single-relay scenarios. For multi-relay scenarios, an iterative numerical algorithm is proposed to find suboptimal solutions with low computational complexity. It is shown that starting with an arbitrarily initial feasible point, the limit point of the solution sequence derived from the iterative algorithm satisfies the two necessary conditions. To apply this algorithm, two approaches are developed to find an initial feasible point. Finally, simulation results show that on average, the proposed low-complexity solution considerably outperforms the scheme without source power control and performs close to the optimal solution obtained by a grid search technique which has prohibitively high computational complexity.

This paper proposes a new spectrum sharing scheme which uses one-sided collaboration. In the proposed system, the transmitter of the secondary system relays the primary signal and overlays its own data on the retransmitted primary signal. The results of the theoretical analysis show that the proposed scheme with regenerative relay allows the secondary system to communicate at the same speed as the primary system that disregards the presence of the secondary system.

In this letter, the k-out-of-n rule for cooperative sensing is considered. For a given n, we derive the optimal value of k that minimizes the total sensing error probability subject to the sensing accuracy, considering both the effective of sensing errors and the primary activities. According to the optimal k, we analyze the performance and compare with other schemes, which illustrate the effectiveness of the proposed scheme.

We propose a cooperative compressed spectrum sensing scheme for correlated signals in wideband cognitive radio networks. In order to design a reconstruction algorithm which accurately recover the wideband signals from the compressed samples in low SNR (Signal-to-Noise Ratio) environments, we consider the multiple measurement vector model exploiting a sequence of input signals and propose a cooperative sparse Bayesian learning algorithm which models the temporal correlation of the input signals. Simulation results show that the proposed scheme outperforms existing compressed sensing algorithms for low SNRs.

Dynamic spectrum access is the key approach in cognitive wireless regional area networks, and it is adopted by secondary users to access the licensed radio spectrum opportunistically. In order to realize real-time secondary spectrum usage, a dynamic spectrum access model based on stochastic differential games is proposed to realize dynamic spectrum allocation; a Nash equilibrium solution to the model is given and analyzed in this paper. From an overall perspective, the relationships between available spectrum percentage and the spectrum access rate are studied. Changes in the available spectrum percentage of the cognitive wireless regional area networks involve a deterministic component and a stochastic component which depends upon an r-dimensional Wiener process. The Wiener process represents an accumulation of random influences over the interval, and it reflects stochastic and time-varying properties of the available spectrum percentage. Simulation results show that the dynamic spectrum access model is efficient, and it reflects the time-varying radio frequency environment. Differential games are useful tools for the spectrum access and management in the time-varying radio environment.

Cognitive radio (CR) systems aim for more efficient spectrum utilization by having so called secondary users (SUs) transmit on a frequency band reserved for licensed primary users (PUs). The secondary transmissions are allowed provided that no harmful interference will be caused to the PUs. SU terminals with multiple antennas can employ transmit power control with transmit precoding in order to control the interference levels. In most of the existing works, perfect channel state information (CSI) is assumed to be available for the SUs. However, in practical systems where perfect CSI is not available, the SUs are not able to guarantee that the interference constraints are sufficiently satisfied. In this paper, we investigate the problem of spectrum sharing for multiantenna CR systems using estimated CSI. Due to the random nature of the estimation error, we set a probabilistic interference constraint and, in order to satisfy it, provide a density function for the interference power. In addition, we present a power control framework for the SU to meet the probabilistic interference constraint.