This paper presents the design and proof-of-concept validation of a novel network-assisted spectrum coordination (NASCOR) service for improved radio coexistence in future shared spectrum bands. The basic idea is to create an overlay network service for dissemination of spectrum usage information between otherwise independent radio devices and systems, enabling them to implement decentralized spectrum coexistence policies that reduce interference and improve spectrum packing efficiency. The proposed method is applicable to unlicensed band and shared spectrum systems in general (including femtocells), but is particularly relevant to emerging TV white spaces and cognitive radio systems which are still in need of scalable and accurate solutions for both primary-to-secondary and secondary-to-secondary coordination. Key challenges in enabling a network layer spectrum coordination service are discussed along with the description of our system architecture and a detailed case-study for a specific example of spectrum coordination: client-AP association optimization in dense networks. Performance gains are evaluated through large-scale simulations with multiple overlapping networks, each consisting of 15-35 access points and 50-250 clients in a 0.5×0.5 sq.km. urban setting. Results show an average of 150% improvement in random deployments and upto 7× improvements in clustered deployments for the least-performing client throughputs with modest reductions in the mean client throughputs.

Spectrum sensing is one of the methods to identify available white spaces for secondary usage which was specified by the regulators. However, signal quality to be sensed can plunge to a very low signal-to-noise-ratio due to signal propagation and hence readings from individual sensors will be unreliable. Distributed sensing by the cooperation of multiple sensors is one way to cope with this problem because the diversity gain due to the combining effect of data captured at different position will assist in detecting signals that might otherwise not be detected by a single sensor. In effect, the probability of detection can be improved. We have implemented a distributed sensing system to evaluate the performance of different cooperative sensing algorithms. In this paper we describe our implementation and measurement experience which include the system design, specification of the system, measurement method, the issues and solutions. This paper also confirms the performance enhancement offered by distributed sensing algorithms, and describes several ideas for further enhancement of the sensing quality.

Cooperative spectrum sensing is an effective approach that utilizes spatial diversity gain to improve detection performance. Most studies assume that the background noise is exactly known. However, this is not realistic because of noise uncertainty which will significantly degrade the performance. A novel weighted hard combination algorithm with two thresholds is proposed by dividing the whole range of the local test statistic into three regions called the presence, uncertainty and absence regions, instead of the conventional two regions. The final decision is made by weighted combination at the common receiver. The key innovation is the full utilization of the information contained in the uncertainty region. It is worth pointing out that the weight coefficient and the local target false alarm probability, which determines the two thresholds, are also optimized to minimize the total error rate. Numerical results show this algorithm can significantly improve the detection performance, and is more robust to noise uncertainty than the existing algorithms. Furthermore, the performance of this algorithm is not sensitive to the local target false alarm probability at low SNR. Under sufficiently high SNR condition, this algorithm reduces to the improved one-out-of-N rule. As noise uncertainty is unavoidable, this algorithm is highly practical.

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Cognitive Radio (CR) is aimed at increasing the efficiency of spectrum utilization by allowing unlicensed users to access, in an opportunistic and non-interfering manner, some licensed bands temporarily and/or spatially unoccupied by the licensed users. The analysis of CR systems usually requires the spectral activity of the licensed system to be represented and characterized in a simple and tractable, yet accurate manner, which is accomplished by means of spectrum models. In order to guarantee the realism and accuracy of such models, the use of empirical spectrum occupancy data is essential. In this context, this paper explains the complete process of spectrum modeling, from the realization of field measurements to the obtainment of the final validated model, and highlights the main relevant aspects to be taken into account when developing spectrum usage models for their application in the context of the CR technology.

In this paper, we investigate how to achieve call admission control (CAC) for guaranteeing call dropping probability QoS which is caused by handoff timeout in cognitive radio (CR) networks. When primary user (PU) appears, spectrum handoff should be initiated to maintain secondary user (SU)'s link. We propose a novel virtual queuing (VQ) scheme to schedule spectrum handoff requests sent by multiple SUs. Unlike the conventional first-come-first-served (FCFS) scheduling, resuming transmission in the original channel has higher priority than switching to another channel. It costs less because it avoids the cost of signaling frequent spectrum switches. We characterize the handoff delay on the effect of PU's behavior and the number of SUs in CR networks. And user capacity under certain QoS requirement is derived as a guideline for CAC. The analytical results show that call dropping performance can be greatly improved by CAC when a large amount of SUs arrives fast as well as the VQ scheme is verified to reduce handoff cost compared to existing methods.

In cognitive radio networks, the dynamic traffic of the primary user can lead to not only the spectrum sensing performance degradation, but also co-channel interference between primary user and secondary user, and, furthermore, the secondary system throughput can be decreased. Taking into account the impact of the dynamic primary-user traffic on spectrum sensing performance and the secondary throughput, we study the optimization problem of maximizing the secondary throughput under the constraints of probability of detection, average interference and transmit power budget, and derive its optimal solution. The optimal power allocation scheme and the algorithm that can find the optimal sensing time are also proposed. The proposed algorithm is of great practical significance in the scenario where primary-user traffic varies very quickly, for example, in public safety spectrum band.

We consider two methods for constructing high rate punctured convolutional codes. First, we present the best high rate R=(n-1)/n punctured convolutional codes, for n=5,6,…,16, which are obtained by exhaustive searches. To obtain the best code, we use a regular convolutional code whose weight spectrum is equivalent to that of each punctured convolutional code. We search these equivalent codes for the best one. Next, we present a method that searches for good punctured convolutional codes by partial searches. This method searches the codes that are derived from rate 1/2 original codes obtained in the first method. By this method, we obtain some good punctured convolutional codes relatively faster than the case in which we search for the best codes.

This paper studies channel sounding for selfish dynamic spectrum control (S-DSC) in which each link dynamically maps its spectral components onto a necessary amount of discrete frequencies having the highest channel gain of the common system band. In S-DSC, it is compulsory to conduct channel sounding for the entire system band by using a reference signal whose spectral components are sparsely allocated by S-DSC. Using nonuniform sampling theory, this paper exploits the finite impulse response characteristic of frequency selective fading channels to carry out the channel sounding. However, when the number of spectral components is relatively small compared to the number of discrete frequencies of the system band, reliability of the channel sounding deteriorates severely due to the ill-conditioned problem and degradation in channel capacity of the next frame occurs as a result. Aiming at balancing frequency selection diversity effect and reliability of channel sounding, this paper proposes an S-DSC which allocates an appropriate number of spectral components onto discrete frequencies with low predicted channel gain besides mapping the rest onto those with high predicted channel gain. A numerical analysis confirms that the proposed S-DSC gives significant enhancement in channel capacity performance.

In this paper we consider fixed-to-fixed length (FF) coding of a general source X with vanishing error probability and define two kinds of optimalities with respect to the coding rate and the redundancy, where the redundancy is defined as the difference between the coding rate and the symbolwise ideal codeword length. We first show that the infimum achievable redundancy coincides with the asymptotic width W(X) of the entropy spectrum. Next, we consider the two sets $mCH(X)$ and $mCW(X)$ and investigate relationships between them, where $mCH(X)$ and $mCW(X)$ denote the sets of all the optimal FF codes with respect to the coding rate and the redundancy, respectively. We give two necessary and sufficient conditions corresponding to $mCH(X) subseteq mCW(X)$ and $mCW(X) subseteq mCH(X)$, respectively. We can also show the existence of an FF code that is optimal with respect to both the redundancy and the coding rate.

In this letter, we first introduce a stronger notion of the optimistic achievable coding rate and discuss a coding theorem. Next, we give a necessary and sufficient condition under which the coding rates of all the optimal FF codes asymptotically converge to a constant.

In this letter, we present a novel cooperative spectrum sensing scheme for cognitive radio systems. The proposed approach is based on a consensus algorithm. Using the received signals, we set up a formula for the consensus algorithm, which guarantees a convergence to an agreement value. The simulation results exhibit that the performance of the consensus-based cooperative scheme is much better than that of the conventional cooperative technique in the case that the cooperative nodes for spectrum sensing are sparsely distributed in cognitive radio systems.

Conventional CPM signals employ information sequence with time-unlimited phase shaping pulse (PSP) to achieve power and bandwidth efficient transmission. On the contrary, information sequence using time-limited PSP was believed to produce power-wasting data-independent discrete spectral lines in CPM spectra, and was suggested to be avoided. In this paper, we revisit this problem and adopt the time-limited PSP to replace the one with time-unlimited, it turns out to have an alternative solution to the CPM scheme. We first modify the spectral computing formula for the CPM with time-limited PSP (or CPM-TL) from conventional CPM formula and show that the discrete spectral lines appeared in the power density spectrum of CPM-TL signals can be diminished or become negligible by appropriately choosing PSP. We also show that this class of CPM can use any real number modulation index (h) and the resultant trellis structure of CPM guarantees the maximum constraint length allowed by the number of states in the MLSD receiver. Finally, the energy-bandwidth performance of CPM using time-limited PSP is investigated and compared with conventional CPM with time-unlimited PSP. From numerical results we show that, under the same number of states in the MLSD receiver and bandwidth occupancy, this subclass of CPM could outperform the conventional CPM up to 6dB coding gain, for h<1, in many cases.

Spectrum sensing is one of the main functions in cognitive radio networks. To improve the sensing performance and increase spectrum efficiency, a number of cooperative spectrum sensing methods have been proposed. However, most of these methods focused on a single-channel environment. In this letter, we present a novel cooperative spectrum sensing method based on cooperator selection in a multi-channel cognitive radio network. Using reinforcement learning, a cognitive radio user can select reliable and robust cooperators, without any a priori knowledge. Using the proposed method, a cognitive radio user can achieve better sensing capability and overcome performance degradation problems due to malicious users or erratic user behavior. Numerical results show that the proposed method can achieve excellent performance.

In cognitive radio networks, the primary user (PU) can lease a fraction of its licensed spectrum to the secondary users (SUs) in exchange for their cooperative transmission if it has a minimum transmission rate requirement and is experiencing a bad channel condition. However, due to the selfish nature of the SUs, they may not cooperate to meet the PU's Quality of Service (QoS) requirement. On the other hand, the SUs may not exploit efficiently the benefit from cooperation if they compete with each other and collaborate with the PU independently. Therefore, when SUs belong to the same organization and can work as a group, how to stimulate them to cooperate with the PU and thus guarantee the PU's QoS requirement, and how to coordinate the usage of rewarded spectrum among these SUs after cooperation are critical challenges. In this paper, we propose a two-level bargaining framework to address the aforementioned problems. In the proposed framework, the interactions between the PU and the SUs are modeled as the upper level bargaining game while the lower level bargaining game is used to formulate the SUs' decision making process on spectrum sharing. We analyze the optimal actions of the users and derive the theoretic results for the one-PU one-SU scenario. To find the solutions for the one-PU multi-SU scenario, we put forward a revised numerical searching algorithm and prove its convergence. Finally, we demonstrate the effectiveness and efficiency of the proposed scheme through simulations.

A technique that enables a SSCG to fine-tune an output signal frequency and a spread ratio is presented. Proposed SSCG achieves the output signal frequency from 1.2 GHz to 3.0 GHz and the spread ratio from 0 to 30000 ppm. The fine-tuning technique achieves 30 ppm adjustment of the output signal frequency and 200 ppm adjustment of the spread ratio. This technique is achieved by controlling a triangular modulation signal characteristics generated by a proposed digital controlled wave generator. A proposed multi-modulus divider can have a divide ratio of 4/5 and 8/9. This SSCG has been fabricated in a 0.13-µm CMOS process. The output signal frequency-range and the spread ratio are achieved fluently from 0.1 to 3.0 GHz and from 0 to 30000 ppm, respectively. EMI noise is suppressed at less than 17.1 dB at the output signal frequency of 3.0 GHz and spread ratio of 30000 ppm.

Dynamic spectrum leasing (DSL) is regarded as a promising dynamic spectrum sharing (DSS) scheme both to improve the spectrum revenue of primary users (PUs) and to guarantee the QoS of secondary users (SUs). A pricing-based DSL termed PBDSL is formulated as a Stackelberg DSL game model, where PUs as players entering the interacting game with multiple SUs. The strategic design contains both optimal spectrum pricing schemes (including unit spectrum/interference price and interference sensitivity distributed adjustments) of PUs for the specific shared/leased spectrum and optimal transmission strategies (e.g., transmit power and bandwidth) of SUs. To capture two types of competition relationships among multiple SUs and between SUs and PUs, we investigate two intra-game models of multiple PUs and SUs, respectively, which interact with each other to constitute the final Stackelberg DSL game. The existence and uniqueness of Stackelberg equilibrium solution (SES) are analyzed and proved for presented games, based on which a joint multi-stage PBDSL algorithm is presented to approximate the optimal equilibrium strategies. Numerical results demonstrate the convergence property of the interactive decision-making process, and verify the effectiveness of the proposed algorithm, in a comparison with the Nash equilibrium solution (NES)-based approach.

In this article, we propose a method to reduce the impact of primary traffic on spectrum sensing performance. In practice, the sensing performance is degraded by noise-only sample in the spectrum sensing time. Therefore, we employ a time of primary user (PU) signal arrival detector in order to remove the noise-only portion. Then, we employ equal-weight-based energy detection (EWED) to provide the detection decision. The analysis and simulation results show that there exists an optimal early time of arrival (ToA) false alarm which provides better performance compared to the use of a single EWED scheme.

In order to evaluate the goodness of frequency hopping (FH) sequence design, the periodic Hamming correlation function is used as an important measure. But aperiodic Hamming correlation of FH sequences matters in real applications, while it received little attraction in the literature compared with periodic Hamming correlation. In this paper, the new aperiodic Hamming correlation lower bounds for FH sequences, with respect to the size of the frequency slot set, the sequence length, the family size, the maximum aperiodic Hamming autocorrelation and the maximum aperiodic Hamming crosscorrelation are established. The new aperiodic bounds are tighter than the Peng-Fan bounds. In addition, the new bounds include the second powers of the maximum aperiodic Hamming autocorrelation and the maximum aperiodic Hamming crosscorrelation but the Peng-Fan bounds do not include them. For the given sequence length, the family size and the frequency slot set size, the values of the maximum aperiodic Hamming autocorrelation and the maximum aperiodic Hamming crosscorrelation are inside of an ellipse which is given by the new aperiodic bounds.

A wireless emergency communication network with a fixed allocation of spectrum resources cannot meet the tremendous demand for spectrum access when a crisis occurs. It is necessary to develop an effective spectrum access scheme to improve the performance of emergency communication systems. In this paper, we study a new emergency communication system combines cognitive radio technology and an emergency communication network. Emergency users can utility resources in a general network when traffic becomes congested in an emergency network. Non-reciprocal spectrum access scheme (NRA) and reciprocal spectrum access scheme (RA) for two heterogeneous cognitive networks, namely emergency network and general network are proposed to compare with traditional spectrum access scheme (TA). User behavior with each scheme is modeled by continuous-time Markov chains. Moreover, the blocking and dropping probabilities of users in two heterogeneous cognitive networks are derived as the performance metrics. In addition, the throughput and the spectrum utilization rate of the system are evaluated. Finally, we compare the performance of three dynamic spectrum access schemes. The simulation results show that the RA scheme is an effective scheme to enhance the performance of emergency systems.