This letter proposes an intra-cell partial spectrum reuse (PSR) scheme for cellular OFDM-relay networks. The proposed method aims to increase the system throughput, while the SINR of the cell edge users can be also promoted by utilizing the PSR scheme. The novel pre-allocation factor γ not only indicates the flexibility of PSR, but also decreases the complexity of the reuse mechanism. Through simulations, the proposed scheme is shown to offer superior performances in terms of system throughput and SINR of last 5% users.

Dynamic spectrum access has become a focal issue recently, in which identifying the available spectrum plays a rather important role. Lots of work has been done concerning secondary user (SU) synchronously accessing primary user's (PU's) network. However, on one hand, SU may have no idea about PU's communication protocols; on the other, it is possible that communications among PU are not based on synchronous scheme at all. In order to address such problems, this paper advances a strategy for SU to search available spectrums with asynchronous MAC-layer sensing. With this method, SUs need not know the communication mechanisms in PU's network when dynamically accessing. We will focus on four aspects: 1) strategy for searching available channels; 2) vacating strategy when PUs come back; 3) estimation of channel parameters; 4) impact of SUs' interference on PU's data rate. The simulations show that our search strategy not only can achieve nearly 50% less interference probability than equal allocation of total search time, but also well adapts to time-varying channels. Moreover, access by our strategies can attain 150% more access time than random access. The moment matching estimator shows good performance in estimating and tracing time-varying channels.

Cooperation is an attractive approach to improving the spectrum sensing performance of cognitive systems experiencing deep shadowing and fading. In this letter, an efficient weight-based cooperative spectrum sensing scheme is proposed. Simulation results show that the proposed scheme has better accuracy than "AND," "OR," and "half-voting" combination schemes and has similar spectrum sensing accuracy but with lower computational and communication complexity in comparison to the "optimal data fusion" rule.

The error diffusion filter in this paper is optimized with respect to the ideal blue noise pattern corresponding to a single tone level. The filter coefficients are optimized by the minimization of the squared error norm between the Fourier power spectra of the resulting halftone and the blue noise pattern. During the process of optimization, the binary pattern power spectrum matching algorithm is applied with the aid of a new blue noise model. The number of the optimum filters is equal to that of different tones. The visual fidelity of the bilevel halftones generated by the error diffusion filters is evaluated in terms of a weighted signal-to-noise ratio, Fourier power spectra, and others. Experimental results have demonstrated that the proposed filter set generates satisfactory bilevel halftones of grayscale images.

Free probability theory, which has become a main branch of random matrix theory, is a valuable tool for describing the asymptotic behavior of multiple systems, especially for large matrices. In this paper, using asymptotic free probability theory, a new cooperative scheme for spectrum sensing is proposed, which shows how the asymptotic free behavior of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for cognitive radio. Simulations over Rayleigh fading and AWGN channels demonstrate the proposed scheme has better detection performance than the energy detection techniques and the Maximum-minimum eigenvalue (MME) scheme even for the case of a small sample of observations.

A new estimation algorithm of clock drift in symbol duration for high precision ranging, based on multiple symbols of chirp spread spectrum (CSS) is proposed. Since the permissible error of a crystal oscillator in CSS is relatively high given the need to lower device costs, ranging results are perturbed by clock drift. We establish the phenomenon of clock drift in multiple symbols of CSS, and estimate the clock drift in symbol duration based on phase difference between adjacent symbols. The proposed algorithm is analyzed, and verified by Monte Carlo simulations.

An improved bidirectional search algorithm for computing the weight spectrum of convolutional codes is presented. This algorithm does not employ the column distance function of a code which plays an important role in the original bidirectional search algorithm. We show the proposed algorithm can reduce computaion time for obtaining the weigth spectrum of convolutional codes significantly compared with that of the bidirectional search algorithm.

Network monitoring systems that detect and analyze malicious activities as well as respond against them, are becoming increasingly important. As malwares, such as worms, viruses, and bots, can inflict significant damages on both infrastructure and end user, technologies for identifying such propagating malwares are in great demand. In the large-scale darknet monitoring operation, we can see that malwares have various kinds of scan patterns that involves choosing destination IP addresses. Since many of those oscillations seemed to have a natural periodicity, as if they were signal waveforms, we considered to apply a spectrum analysis methodology so as to extract a feature of malware. With a focus on such scan patterns, this paper proposes a novel concept of malware feature extraction and a distinct analysis method named "SPectrum Analysis for Distinction and Extraction of malware features (SPADE)". Through several evaluations using real scan traffic, we show that SPADE has the significant advantage of recognizing the similarities and dissimilarities between the same and different types of malwares.

This paper investigates dynamic spectrum access based on MAC-Layer spectrum sensing and prior channel pre-allocation strategy. We first combine channel utilization with channel state transition probability from idle to busy to reflect the channel opportunity quality in cognitive radio systems. Then a MAC-Layer spectrum sensing algorithm based on Channel Opportunity Quality Descending Order (COQDO) is proposed for the single secondary user scenario, so that the single secondary user can be provided with dynamic spectrum access. For the multi-secondary users scenario, in order to solve the channel collision problem among secondary users in dynamic spectrum access, a joint MAC-Layer spectrum sensing and prior channel pre-allocation algorithm is proposed and analyzed. Channel collision problem occurs when more than one secondary users detect the channel as idle and access it at the same time. Furthermore, the prior channel pre-allocation is optimized by using the conventional Color Sensitive Graph Coloring (CSGC) algorithm. Extensive simulation results are presented to compare our proposed algorithms with existing algorithms in terms of idle channel search delay and accumulated channel handoff delay.

In this letter, the performance improvement by the deployment of multiple antennas in cognitive radio systems is studied from a system-level view. The term opportunistic spectrum efficiency (OSE) is defined as the performance metric to evaluate the spectrum opportunities that can actually be exploited by the secondary user (SU). By applying a simple energy combining detector, we show that deploying multiple antennas at the SU transceiver can improve the maximum achievable OSE significantly. Numerical results also reveal that the improvement comes from the reduction of both the detection overhead and the false alarm probability.

Based on Free Probability Theory (FPT), which has become an important branch of Random Matrix Theory (RMT), a new scheme of frequency band sensing for Cognitive Radio (CR) in Direct-Sequence Code-Division Multiple-Access (DS-CDMA) multiuser network is proposed. Unlike previous studies in the field, the new scheme does not require the knowledge of the spreading sequences of users and is related to the behavior of the asymptotic free behavior of random matrices. Simulation results show that the asymptotic claims hold true even for a small number of observations (which makes it convenient for time-varying topologies) outperforming classical energy detection scheme and another scheme based on random matrix theory.

This paper is concerned with the estimation of radio communication distance when both the transmitter and receiver are arbitrarily distributed on a random rough surface such as desert, terrain, sea surface and so on. First, we simulate electromagnetic wave propagation along the rough surface by using the discrete ray tracing method (DRTM) proposed by authors recently. Second, we determine three parameters by conjugate gradient method (CGM) combined with the method of least-squares. Finally, we derive an analytical expression which can estimate the maximum communication distance when the input power of a transmitter and the minimum detectable electric intensity of a receiver are specified. Random rough surfaces are assumed to be Gaussian, pn-th order power law or exponential distributions.

This paper reviews applications of fuzzy logic to telecommunications and proposes a novel fuzzy combining scheme for cooperative spectrum sensing in cognitive radio systems. A summary of previous applications of fuzzy logic to telecommunications is given outlining also potential applications of fuzzy logic in future cognitive radio systems. In complex and dynamic operational environments, future cognitive radio systems will need sophisticated decision making and environment awareness techniques that are capable of handling multidimensional, conflicting and usually non-predictable decision making problems where optimal solutions can not be necessarily found. The results indicate that fuzzy logic can be used in cooperative spectrum sensing to provide additional flexibility to existing combining methods.

In this paper, we propose a novel method for gathering sensing information by using an orthogonal narrowband signal for cooperative sensing in cognitive radio. It is desirable to improve the spectrum sensing performance by countering the locality effect of a wireless channel; cooperative sensing by using multiple inputs of sensing information from the surrounding sensing nodes has attracted attention. Cooperative sensing requires that sensing information be gathered at the master node for determining the existence of a primary signal. If the used information gathering method leads to redundancies, the total capacity of the secondary networks is not improved. In this paper, we propose a novel method for gathering sensing information that maps the sensing information to the orthogonal narrowband signal to achieve simultaneous sensing information gathering at the master node. In this method, the sensing information is mapped to an orthogonal subcarrier signal of an orthogonal frequency division multiplexing (OFDM) structure to reduce the frequency resource required for sensing information gathering. The orthogonal signals are transmitted simultaneously from multiple sensing nodes. This paper evaluates the performance of the proposed information gathering method and confirms its effectiveness.

Spectrum sensing is a key technology within Cognitive Radio (CR) systems. Cooperative spectrum sensing using a distributed model provides improved detection for the primary user, which opens the CR system to a new security threat. This threat is the decrease of the cooperative sensing performance due to the spectrum sensing data falsification which is generated from malicious users. Our proposed scheme, based on robust statistics, utilizes only available past sensing nodes' received power data for estimating the distribution parameters of the primary signal presence and absence hypotheses. These estimated parameters are used to perform the Dempster-Shafer theory of evidence data fusion which causes the elimination of malicious users. Furthermore, in order to enhance performance, a node's reliability weight is supplemented along with the data fusion scheme. Simulation results indicate that our proposed scheme can provide a powerful capability in eliminating malicious users as well as a high gain of data fusion under various cases of channel condition.

When cognitive radio (CR) systems dynamically use the frequency band, a control signal is necessary to indicate which carrier frequencies are currently available in the network. In order to keep efficient spectrum utilization, this control signal also should be transmitted based on the channel conditions. If transmitters dynamically select carrier frequencies, receivers have to receive control signals without knowledge of their carrier frequencies. To enable such transmission and reception, this paper proposes a novel scheme called DCPT (Differential Code Parallel Transmission). With DCPT, receivers can receive low-rate information with no knowledge of the carrier frequencies. The transmitter transmits two signals whose carrier frequencies are spaced by a predefined value. The absolute values of the carrier frequencies can be varied. When the receiver acquires the DCPT signal, it multiplies the signal by a frequency-shifted version of the signal; this yields a DC component that represents the data signal which is then demodulated. The performance was evaluated by means of numerical analysis and computer simulation. We confirmed that DCPT operates successfully even under severe interference if its parameters are appropriately configured.

An OFDMA based channel access scheme is proposed for dynamic spectrum access to utilize frequency spectrum efficiently. Though the OFDMA based scheme is flexible enough to change the bandwidth and channel of the transmitted signals, the OFDMA signal has large PAPR (Peak to Average Power Ratio). In addition, if the OFDMA receiver does not use a filter to extract sub-carriers before FFT (Fast Fourier Transform) processing, the designated sub-carriers suffer large interference from the adjacent channel signals in the FFT processing on the receiving side. To solve the problems such as PAPR and adjacent channel interference encountered in the OFDMA based scheme, this paper proposes a novel dynamic channel access scheme using overlap FFT filter-bank based on single carrier modulation. It also shows performance evaluation results of the proposed scheme by computer simulation.

To realize dynamic spectrum access (DSA), spectrum sensing is performed to detect the presence or absence of primary users (PUs). This paper proposes a sensing architecture. This architecture enables use cases such as DSA with PU detection using a single spectrum sensor and DSA with distributed sensing, such as cooperative sensing, collaborative sensing, and selective sensing. In this paper we focus on distributed sensing. These sensing schemes employ distributed spectrum sensors (DSSs) where each sensor uses energy detection (ED) in Rayleigh fading environment. To theoretically analyze the performance of the three sensing schemes, a closed-form expression for the probability of detection by ED with selective combining (SC) in Rayleigh fading environment is derived. Applying this expression to the PU detection problem, we obtain analytical models of the three sensing schemes. Analysis shows that at 5-dB signal-to-noise ratio (SNR) and with a false alarm rate of 0.004, the probability of detection is increased from 0.02 to 0.3 and 0.4, respectively, by cooperative sensing and collaborative sensing schemes using using three DSSs. Results also show that the selected sensing scheme matches the performance of the collaborative sensing scheme. Moreover, it provides a low false alarm rate.

A simple distributed Medium Access Control (MAC) protocol for cognitive wireless networks is proposed. It is assumed that the network is slotted, the spectrum is divided into a number of channels, and the primary network statistical aggregate traffic model on each channel is given by independent Bernoulli random variables. The objective of the cognitive MAC is to maximize the exploitation of the channels idle time slots. The cognitive users can achieve this aim by appropriate hopping between the channels at each decision stage. The proposed protocol is based on the rule of least failures that is deployed by each user independently. Using this rule, at each decision stage, a channel with the least number of recorded collisions with the primary and other cognitive users is selected for exploitation. The performance of the proposed protocol for multiple cognitive users is investigated analytically and verified by simulation. It is shown that as the number of users increases the user decision under this protocol comes close to the optimum decision to maximize its own utilization. In addition, to improve opportunity utilization in the case of a large number of cognitive users, an extension to the proposed MAC protocol is presented and evaluated by simulation.

Spectrum sensing is an important function for dynamic spectrum access (DSA) type cognitive radio systems to detect opportunities for sharing the spectrum with a primary system. The key requirements for spectrum sensing are stability in controlling the probability of false alarm as well as detection performance of the primary signals. However, false alarms can be triggered by noise uncertainty at the secondary devices or unknown interference signals from other secondary systems in realistic radio environments. This paper proposes a robust spectrum sensing method against such uncertainties; it is a kind of cyclostationary feature detection (CFD) approaches. Our proposed method, referred to as maximum cyclic autocorrelation selection (MCAS), compares the peak and non-peak values of the cyclic autocorrelation function (CAF) to detect primary signals, where the non-peak value is the CAF value calculated at cyclic frequencies between the peaks. In MCAS, the desired probability of false alarm can be obtained by setting the number of the non-peak values. In addition, the multiple peak values are combined in MCAS to obtain noise reduction effect and coherent combining gain. Through computer simulations, we show that MCAS can control the probability of false alarm under the condition of noise uncertainty and interference. Furthermore, our method achieves better performance with much less computational complexity in comparison to conventional CFD methods.