In our previous paper, we presented a concept of “Baseband Radio” as an ideal of future wireless communication scheme. Furthermore, for enhancing the adaptability of baseband radio, the adaptive baseband radio was discussed as the ultimate communication system; it integrates the functions of cognitive radio and software-defined radio. In this paper, two transmission schemes that take advantage of adaptive baseband radio are introduced and the results of a performance evaluation are presented. The first one is a scheme based on DSFBC for realizing higher reliability; it allows the flexible use of frequency bands over a wide range of white space. The second one is a low-power-density communication scheme with spectrum-spreading by means of frequency-domain differential coding so that the secondary system does not seriously interfere with primary-user systems that have been assigned the same frequency band.

Cognitive radio (CR) is an important technology to provide high-efficiency data communication for the IoT (Internet of Things) era. Signal detection is a key technology of CR to detect communication opportunities. Energy detection (ED) is a signal detection method that does not have high computational complexity. It, however, can only estimate the presence or absence of signal(s) in the observed band. Cyclostationarity detection (CS) is an alternative signal detection method. This method detects some signal features like periodicity. It can estimate the symbol rate of a signal if present. It, however, incurs high computational complexity. In addition, it cannot estimate the symbol rate precisely in the case of single carrier signal with a low Roll-Off factor (ROF). This paper proposes a method to estimate coarsely a signal's bandwidth and carrier frequency from its power spectrum with lower computational complexity than the CS. The proposed method can estimate the bandwidth and carrier frequency of even a low ROF signal. This paper evaluates the proposed method's performance by numerical simulations. The numerical results show that in all cases the proposed coarse bandwidth and carrier frequency estimation is almost comparable to the performance of CS with lower computational complexity and even outperforms in the case of single carrier signal with a low ROF. The proposed method is generally effective for unidentified classification of the signal i.e. single carrier, OFDM etc.

This paper investigates a signal area (SA) estimation method for wideband and long time duration spectrum measurements for dynamic spectrum access. SA denotes the area (in time/frequency domain) occupied by the primary user's signal. The traditional approach, which utilizes only Fourier transform (FT) and energy detector (ED) for SA estimation, can achieve low complexity, but its estimation performance is not very high. Against this issue, we apply post-processing to improve the performance of the FT-based ED. Our proposed method, simple SA (S-SA) estimation, exploits the correlation of the spectrum states among the neighboring tiles and the fact that SA typically has a rectangular shape to estimate SA with high accuracy and relatively low complexity compared to a conventional method, contour tracing SA (CT-SA) estimation. Numerical results will show that the S-SA estimation method can achieve better detection performance. The SA estimation and processing can reduce the number of bits needed to store/transmit the observed information compared to the FT-based ED. Thus, in addition to improved detection performance it also compresses the data.

This study explored the question of how to minimize older drivers' accidents and to identify at-risk drivers by analyzing their driving performance. Previous traffic research reported that there were two factors involved in risky driving, namely driving risk perception and risky driving attitude. We investigated these two factors as indicators of an at-risk driver by using large-scale test data from license renewal tests that are obligatory for Japanese drivers who are 70 years of age or older. The tests include a driving simulator test, an on-road test, and a cognitive screening test. By using these assessments and predictions made with renewal driving tests, we were able to indicate the possibility of identifying at-risk drivers.

In many movies, social conditions and awareness of the issues of the times are depicted in any form. Even if fantasy and science fiction are works far from reality, the character relationship does mirror the real world. Therefore, we try to understand social conditions of the real world by analyzing the movie. As a way to analyze the movies, we propose a method of estimating interpersonal relationships of the characters, using a machine learning technique called Markov Logic Network (MLN) from movie script databases on the Web. The MLN is a probabilistic logic network that can describe the relationships between characters, which are not necessarily satisfied on every line. In experiments, we confirmed that our proposed method can estimate favors between the characters in a movie with F-measure of 58.7%. Finally, by comparing the relationships with social indicators, we discussed the relevance of the movies to the real world.

In this paper, we propose the novel concept of a spectrum database for improving the efficiency of spectrum utilization. In the current design of TV white space spectrum databases, a propagation model is utilized to determine the spectrum availability. However, this propagation model has poor accuracy for radio environment estimation because it requires a large interference margin for the PU coverage area to ensure protection of primary users (PUs); thus, it decreases the spectrum sharing efficiency. The proposed spectrum database consists of radio environment measurement results from sensors on mobile terminals such as vehicles and smart phones. In the proposed database, actual measurements of radio signals are used to estimate radio information regarding PUs. Because the sensors on mobile terminals can gather a large amount of data, accurate propagation information can be obtained, including information regarding propagation loss and shadowing. In this paper, we first introduce the architecture of the proposed spectrum database. Then, we present experimental results for the database construction using actual TV broadcast signals. Additionally, from the evaluation results, we discuss the extent to which the proposed database can mitigate the excess interference margin.

The problem of power allocation for the secondary user (SU) in a cognitive radio (CR) network is investigated in this paper. The primary user (PU) is protected by the average interference power constraint. Besides the average interference power constraint at the PU, the transmit power of the SU is also subject to the peak or average transmit power constraint. The aim is to balance between the goal of maximizing the ergodic capacity and the goal of minimizing the outage probability of the SU. Power allocation schemes are then proposed under the aforementioned setups. It is shown that the proposed power allocation schemes can achieve high ergodic capacity while maintaining low outage probability, whereas existing schemes achieve either high ergodic capacity with high outage probability or low outage probability with low ergodic capacity.

A cognitive radio user (CU) can get assistance from sensor nodes (SN) to perform spectrum sensing. However, the SNs are often powered by a finite-capacity battery, which can maintain operations of the SNs over a short time. Therefore, energy-efficiency of the SNs becomes a crucial problem. In this paper, an SN is considered to be a device with an energy harvester that can harvest energy from a non-radio frequency (non-RF) energy resource while performing other actions concurrently. In any one time slot, in order to maintain the required sensing accuracy of the CR network and to conserve energy in the SNs, only a small number of SNs are required to sense the primary user (PU) signal, and other SNs are kept silent to save energy. For this, an algorithm to divide all SNs into groups that can satisfy the required sensing accuracy of the network, is proposed. In a time slot, each SN group can be assigned one of two actions: stay silent, or be active to perform sensing. The problem of determining the optimal action for all SN groups to maximize throughput of the CR network is formulated as a framework of a partially observable Markov decision process (POMDP), in which the effect of the current time slot's action on the throughput of future time slots is considered. The solution to the problem, that is the decision mode of the SN groups (i.e., active or silent), depends on the residual energy and belief of absence probability of the PU signal. The simulation results show that the proposed scheme can improve energy efficiency of CR networks compared with other conventional schemes.

In cognitive radar systems (CRSs), target scattering coefficients (TSC) can be utilized to improve the performance of target identification and classification. This work considers the problem of TSC estimation for temporally correlated target. Multiple receive antennas are adopted to receive the echo waveforms, which are interfered by the signal-dependent clutter. Unlike existing estimation methods in time domain, a novel estimation method based on Kalman filtering (KF) is proposed in frequency domain to exploit the temporal TSC correlation, and reduce the complexity of subsequent waveform optimization. Additionally, to minimize the mean square error of estimated TSC at each KF iteration, in contrary to existing works, we directly model the design process as an optimization problem, which is non-convex and cannot be solved efficiently. Therefore, we propose a novel method, similar in some way to semi-definite programming (SDP), to convert the non-convex problem into a convex one. Simulation results demonstrate that the estimation performance can be significantly improved by the KF estimation with optimized waveform.

We propose a joint channel, power and rate allocation scheme to minimize the weighted group outage probability of the secondary users (SUs) in a downlink cognitive radio (CR) multicast network coexisting with a primary network, subject to the service outage constraint as well as the interference power constraint and the transmit power constraint. It is validated by simulation results that, compared to the existing schemes, the proposed scheme achieves lower group outage probability.

This paper investigates the detection performance of an improved energy detector for a secondary user with spatially correlated multiple antennas. In an improved energy detector, an arbitrary positive power operation p replaces the squaring operation in a conventional energy detector, and the optimum value of p that gives the best detection performance may be different from 2. Firstly, for a given value of p, we derive closed-form expressions for the probability of detection and the probability of false alarm when antennas at the secondary user are exponentially correlated. We then find the optimum value of p for two different detection criteria-maximizing the probability of detection for a target probability of false alarm, and minimizing the probability of false alarm for a target probability of detection. We show that the optimum p is strongly dependent on system parameters like number of antennas, antenna correlation coefficient among multiple antennas, and average received signal-to-noise ratio (SNR). From results, we infer that, in low SNR regime, the effect of antenna correlation is less pronounced on the optimum p. Finally, we find the optimum values of p and threshold jointly that minimize the total error rate.

This paper studies the energy-saving problem in cognitive multicast orthogonal frequency-division multiplexing (OFDM) systems, for which a time-frequency two-dimensional model is established to enable the system energy conservation through joint temporal and spectral adaptations. The formulated two-dimensional problem, minimizing the total power consumption whilst guaranteeing the minimal-rate requirement for each multicast session and constraining the maximal perceived interference in each timeslot for the active primary user, is categorized as mixed integer non-convex programming, whose optimal solution is intractable in general. However, based on the time-sharing property, an asymptotically optimal algorithm is proposed by jointly iterating spectrum element (SE) assignment and power allocation. Moreover, a suboptimal algorithm, which carries out SE assignment and power allocation sequentially, is presented as well to reduce the computation complexity. Simulation results show the proposed joint algorithm can achieve the near-optimal solution, and the proposed sequential algorithm approximates to the joint one very well with a gap of less than 3%. Compared with the existing slot-by-slot energy-saving algorithms, the total power consumption is considerably decreased due to the combined exploitation of time and frequency dimensions.

In cognitive radio (CR), superposition cooperative spectrum sensing (SPCSS) is able to offer a much improved sensing reliability compared to individual sensing. Because of the differences in sensing channel condition, the reporting order for each cognitive radio user (CU) will highly affect the sensing performance of the network. In this paper, we propose an algorithm to assign the best reporting order to each CU in order to maximize sensing performance under SPCSS. The numerical results show that the proposed scheme can obtain the same performance as the optimal scheme.

TV white space (TVWS) brings potential opportunities to relieve the growing spectrum scarcity. Therefore organizations like the FCC have suggested the co-channel deployment of cellular networks (CNs) on condition that a keep-out distance from the protected region of TV receivers is maintained. However the consequent CN interference has not been described. In addition, considering the wide range of TV coverage, it is also inefficient and wasteful not applying the vacant spectra for secondary user (SU) communication by opportunistic access inside the TV coverage zone. In this paper, we first investigate the aggregate interference from CNs outside the protected area to find out how the interference is generated, and then research the available spectrum resource distribution for SUs inside the TV coverage zone under aggregate interference constraints to utilize TVWS more efficiently. Specifically, we model CN in three aspects. A close-form interference probability distribution function (PDF) is proposed. Since the PDF is too complex to analyze, we approximate it as Gaussian and prove the accuracy of our approximation with Kolmogorov-Smirnov test. Then, available spectra maximization is formulated as an optimization problem under both TV and SU receiver outage probability constraints. We find that available spectra demonstrate a volcano-shaped geographical distribution and optimal network-status-aware SU transmit power exists to maximize the spectra. Our analysis reveals the characteristics of interference in TVWS and contributes to the utilization improvement of white space.

In this paper, an energy harvesting architecture in an Underlay Cooperative Cognitive Network (UCCN) is investigated, in which power constrained Decode-and-Forward relays harvest energy from radio-frequency signals received from a source, and then consume the harvested energy by forwarding the recoded signals to their destination. These recoded signals are launched by a transmitting power which is the harvested energy per a time interval. Based on the energy harvesting architectures that have been studied, two operation protocols are proposed: UCCN with Power Splitting architecture (UCCN-PS), and UCCN with Time Switching architecture (UCCN-TS). The best cooperative relay in both protocols is taken to be the one that satisfies the following conditions: maximum harvested energy, and maximum decoding capacity. As a result of the best relay selection, the signal quality of the selected link from the best relay to the destination is enhanced by the maximum harvested energy. The system performance of the secondary network in the UCCN-PS and UCCN-TS protocols is analyzed and evaluated by the exact closed-form outage probabilities and throughput analyses over Rayleigh fading channels. The Monte Carlo simulation method is performed to verify the theoretical expressions. Evaluations based on outage probability and throughput show that the system performance of the secondary network in the UCCN-PS and UCCN-TS protocols improves when the number of cooperative relays and the interference constraint increase as well as when the primary receiver is farther from the transmitting nodes such as the source and relays of the secondary network. In addition, the throughput performance of the UCCN-PS protocol outperforms that of the UCCN-TS protocol. Finally, the effects of the power splitting ratio, energy harvesting time, energy conversion efficiency, target Signal-to-Noise Ratio (SNR), and location of cooperative relays on the system performance of the secondary network are presented and discussed.

In this paper, a novel synchronization method is proposed for a heterogeneous cognitive radio that combines public safety mobile communication systems (PMCSs) with commercial mobile wireless communication systems (CMWCSs). The proposed method enables self-synchronization of the PMCSs as well as co-synchronization of PMCSs and CMWCSs. In this paper, the self-synchronization indicates that each system obtains own timing synchronization. The co-synchronization indicates that a system recognizes data transmitted from other systems correctly. In our research, we especially focus on PMCS self-synchronization because it is one of the most difficult parts of our proposed cognitive radio that improves PMCS's communication quality. The proposed method is utilized for systems employing differentially encoded π/4 shift QPSK modulation. The synchronization can be achieved by correlating envelopes calculated from a PMCS's received signals with subsidiary information (SI) sent via a CMWCS. In this paper, the performance of the proposed synchronization method is evaluated by computer simulation. Moreover, because this SI can also be used to improve the bit error rate (BER) of PMCSs, BER improvement and efficient SI sending methods are derived, after which their performance is evaluated.

Accessing a geo-location database is one of the approaches for a secondary user (SU) to obtain the list of available channels for its operation. Channel availability is calculated based on information stored in the geo-location database and information submitted by the SU so that primary users (PU) are protected from harmful interference. The available channel checking process is modeled as a number of intersection tests between the protected contours of PUs and the operation area of the SU regarding to all potential channels. Existing studies indicated that these intersection tests consume time and introduce overhead to the database, especially when the contours or the operation areas are represented by n-polygons and the number of vertices n is a large number. This paper presents a novel method of determining available channels which reduces the number of intersection tests. By submitting SU's preferred channels or the number of channels to be checked to the database, the calculation time and database's load will be reduced significantly. This paper also presents analysis and simulation results of the database workload and the average number of channels obtained per query on different query methods. Suitable query method can be selected based on the number of similar channels in neighbor areas and the maximum number of intersection tests.

Overlapped FFT based energy detection has been proposed as a signal detection scheme in dynamic spectrum access. The overlapped FFT scheme increases the number of FFT frames to reduce the variance of squared noise and improves the detection performance. As the FFT frames are overlapped, correlation values between the frames affect to the detection performance. This paper proposes the window functions which decrease the correlation values between adjacent FFT bins. Numerical results obtained through computer simulation show that novel window functions generated by upsampling a Hamming window improves the detection performance by 0.09. However, this window function suffers more from adjacent channel interference than a conventional window. Therefore, this paper also proposes a two step detection scheme to achieve higher detection performance and to avoid the influence of the adjacent channel signal. Numerical results also indicate that the proposed scheme improves the detection performance and reduces the effect from the adjacent channel signal.

This paper presents a downlink interference mitigation framework for two-tier heterogeneous networks, that consist of spectrum-sharing macrocells and femtocells*. This framework establishes cooperation between the two tiers through two algorithms, namely, the restricted waterfilling (RWF) algorithm and iterative reweighted least squares interference alignment (IRLS-IA) algorithm. The proposed framework models the macrocell-femtocell two-tier cellular system as an overlay cognitive radio system in which the macrocell system plays the role of the primary user (PU) while the femtocell networks play the role of the cognitive secondary users (SUs). Through the RWF algorithm, the macrocell basestation (MBS) cooperates with the femtocell basestations (FBSs) by releasing some of its eigenmodes to the FBSs to do their transmissions even if the traffic is heavy and the MBS's signal to noise power ratio (SNR) is high. Then, the FBSs are expected to achieve a near optimum sum rate through employing the IRLS-IA algorithm to mitigate both the co-tier and cross-tier interference at the femtocell users' (FUs) receivers. Simulation results show that the proposed IRLS-IA approach provides an improved sum rate for the femtocell users compared to the conventional IA techniques, such as the leakage minimization approach and the nuclear norm based rank constraint rank minimization approach. Additionally, the proposed framework involving both IRLS-IA and RWF algorithms provides an improved total system sum rate compared with the legacy approaches for the case of multiple femtocell networks.

This paper studies the problem of power allocation for a two-way orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) network to maximize the ergodic capacities of the secondary users (SUs). Under the assumption that the SUs know the channel state information (CSI) of the interference links between the SUs and the primary user (PU) perfectly, the optimal power allocation algorithm under the interference and transmit power constraints is derived. In addition, we further assume that the SUs only know the channel distribution information (CDI) of the interference links and propose a heuristic algorithm under the interference outage and transmit power constraints based on Gaussian approximation. It is shown that the ergodic capacity with CDI is not degraded compared to that with perfect CSI under tight transmit power constraint. Moreover, it is shown that the interference outage constraint is satisfied even for very small number of subcarriers if an interference power margin is adopted for Gaussian approximation.