In this paper, we propose a novel censor-based cooperative spectrum sensing strategy, called adaptive energy-efficient sensing (AES), in which both sequential sensing and censoring report mechanism are employed, aiming to reduce the sensing energy consumption of secondary user relays (SRs). In AES, an anchor secondary user (SU) requires cooperative sensing only when it does not detect the presence of PU by itself, and the cooperative SR adopts decision censoring report only if the sensing result differs from its previous one. We derive the generalized-form expressions false alarm and detection probabilities over Rayleigh fading channels for AES. The sensing energy consumption is also analyzed. Then, we study sensing energy overhead minimization problem and show that the sensing time allocation can be optimized to minimize the miss detection probability and sensing energy overhead. Finally, numerical results show that the proposed strategy can remarkably reduce the sensing energy consumption while only slightly degrading the detection performance compared with traditional scheme.

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.

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.

In the dynamic heterogeneous cellular network, spectrum allocation deeply impacts the quality of service and performance of network. In this paper, spectrum allocation is formulated as a dynamic programming problem. A two-level framework is proposed by jointly considering users' dynamic service selection and provider's spectrum allocation. In the first level, the users' service selection is modeled as an evolutionary game, and an evolutionary equilibrium is obtained. In the second level, the service provider allocates the spectral resources to macrocells and femtocells according to the users' strategies, so as to maximize its profits. By jointly considering the service selection and spectrum allocation, the equilibriums of the dynamic network are found. The stability of the equilibriums is analyzed and proven. The proposed two-level framework is validated by the numerical simulation.

This paper shows accuracy of using azimuth-variable path-loss fitting in white-space (WS) boundary-estimation. We perform experiments to evaluate this method, and demonstrate that the required number of sensors can be significantly reduced. We have proposed a WS boundary-estimation framework that utilizes sensors to not only obtain spectrum sensing data, but also to estimate the boundaries of the incumbent radio system (IRS) coverage. The framework utilizes the transmitter position information and pathloss fitting. The pathloss fitting describes the IRS coverage by approximating the well-known pathloss prediction formula from the received signal power data, which is measured using sensors, and sensor-transmitter separation distances. To enhance its accuracy, we have further proposed a pathloss-fitting method that employs azimuth variables to reflect the azimuth dependency of the IRS coverage, including the antenna directivity of the transmitter and propagation characteristics.

In this article, we investigate the depth distribution and the depth spectra of linear codes over the ring R=F2+uF2+u2F2, where u3=1. By using homomorphism of abelian groups from R to F2 and the generator matrices of linear codes over R, the depth spectra of linear codes of type 8k14k22k3 are obtained. We also give the depth distribution of a linear code C over R. Finally, some examples are presented to illustrate our obtained results.

Based upon the Kerckhoffs' principle, illegal users can get to know the embedding and detection algorithms except for a secret key. Then, it is possible to access to a host signal which may be selected from frequency components of a digital content for embedding watermark signal. Especially for a fingerprinting scheme which embeds user's information as a watermark, the selected components can be easily found by the observation of differently watermarked copies of a same content. In this scenario, it is reported that some non-linear collusion attacks will be able to remove/modify the embedded signal. In this paper, we study the security analysis of our previously proposed spread-spectrum (SS) fingerprinting scheme[1], [2] under the Kerckhoffs' principle, and reveal its drawback when an SS sequence is embedded in a color image. If non-linear collusion attacks are performed only to the components selected for embedding, the traceability is greatly degraded while the pirated copy keeps high quality after the attacks. We also propose a simple countermeasure to enhance the robustness against non-linear collusion attacks as well as possible signal processing attacks for the underlying watermarking method.

A major challenge in wideband spectrum sensing, in cognitive radio system for example, is the requirement of a high sampling rate which may exceed today's best analog-to-digital converters (ADCs) front-end bandwidths. Compressive sampling is an attractive way to reduce the sampling rate. The modulated wideband converter (MWC) proposed recently is one of the most successful compressive sampling hardware architectures, but it has high hardware complexity owing to its parallel channels structure. In this paper, we design a single channel sub-Nyquist sampling scheme to bring substantial savings in terms of not only sampling rate but also hardware complexity, and we also present a wideband power spectrum sensing and reconstruction method for bandlimited wide-sense stationary (WSS) signals. The total sampling rate is only one channel rate of the MWC's. We evaluate the performance of the sensing model by computing the probability of detecting signal occupancy in terms of the signal-to-noise ratio (SNR) and other practical parameters. Simulation results underline the promising performance of proposed approach.

This letter investigates the circularity of fractional Fourier transform (FRFT) coefficients containing noise only, and proves that all coefficients coming from white Gaussian noise are circular via the discrete FRFT. In order to use the spectrum kurtosis (SK) as a Gaussian test to check if linear frequency modulation (LFM) signals are present in a set of FRFT points, the effect of the noncircularity of Gaussian variables upon the SK of FRFT coefficients is studied. The SK of the α th-order FRFT coefficients for LFM signals embedded in a white Gaussian noise is also derived in this letter. Finally the signal detection algorithm based on FRFT and SK is proposed. The effectiveness and robustness of this algorithm are evaluated via simulations under lower SNR and weaker components.

A wide-bandwidth fundamental mixer operating at a frequency above 110GHz for precise spectrum analysis was developed using the InP HEMT technology. A single-ended resistive mixer was adopted for the mixer circuit. An IF amplifier and LO buffer amplifier were also developed and integrated into the mixer chip. As for packaging into a metal block module, a flip-chip bonding technique was introduced. Compared to face-up mounting with wire connections, flip-chip bonding exhibited good frequency flatness in signal loss. The mixer module with a built-in IF amplifier achieved a conversion gain of 5dB at an RF frequency of 135GHz and a 3-dB bandwidth of 35GHz. The mixer module with an LO buffer amplifier operated well even at an LO power of -20dBm.

In the study of the capacity problem for multiple access channels (MACs), a lower bound on the error probability obtained by Han plays a crucial role in the converse parts of several kinds of channel coding theorems in the information-spectrum framework. Recently, Yagi and Oohama showed a tighter bound than the Han bound by means of Polyanskiy's converse. In this paper, we give a new bound which generalizes and strengthens the Yagi-Oohama bound, and demonstrate that the bound plays a fundamental role in deriving extensions of several known bounds. In particular, the Yagi-Oohama bound is generalized to two different directions; i.e, to general input distributions and to general encoders. In addition we extend these bounds to the quantum MACs and apply them to the converse problems for several information-spectrum settings.

Combining heterogeneous wireless networks that cross licensed and unlicensed spectra is a promising way of supporting the surge in mobile traffic. The unlicensed band is mostly used by wireless LAN (WLAN) nodes which employ carrier sense multiple access/collision avoidance (CSMA/CA). Since the number of WLAN devices and their traffic are increasing, the wireless resource of the unlicensed band is expected be more depleted in 2020s. In such a wireless environment, the throughput could be extremely low and unstable due to the hidden terminal problem and exposed terminal problem despite of the large resources of the allocated frequency band and high peak PHY rate. In this paper, we propose user equipment (UE) centric access in the unlicensed band, with support by licensed band access in the mobile network. The proposed access enables robust downlink transmission from the access point (AP) to the UEs by mitigating the hidden terminal problem. The licensed spectrum access passes information on the user data waiting at the AP to the UEs and triggers UE reception opportunity (RXOP) acquisition. Furthermore, the adaptive use of UE centric downlink access is presented by using the channel utilization measured at the AP. Computer simulations confirm that licensed access assistance enhances the robustness of the unlicensed band access against the hidden terminal problem.

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.

We propose a method of spread spectrum digital watermarking with quantization index modulation (QIM) and evaluate the method on the basis of IHC evaluation criteria. The spread spectrum technique can make watermarks robust by using spread codes. Since watermarks can have redundancy, messages can be decoded from a degraded stego-image. Under IHC evaluation criteria, it is necessary to decode the messages without the original image. To do so, we propose a method in which watermarks are generated by using the spread spectrum technique and are embedded by QIM. QIM is an embedding method that can decode without an original image. The IHC evaluation criteria include JPEG compression and cropping as attacks. JPEG compression is lossy compression. Therefore, errors occur in watermarks. Since watermarks in stego-images are out of synchronization due to cropping, the position of embedded watermarks may be unclear. Detecting this position is needed while decoding. Therefore, both error correction and synchronization are required for digital watermarking methods. As countermeasures against cropping, the original image is divided into segments to embed watermarks. Moreover, each segment is divided into 8×8 pixel blocks. A watermark is embedded into a DCT coefficient in a block by QIM. To synchronize in decoding, the proposed method uses the correlation between watermarks and spread codes. After synchronization, watermarks are extracted by QIM, and then, messages are estimated from the watermarks. The proposed method was evaluated on the basis of the IHC evaluation criteria. The PSNR had to be higher than 30 dB. Ten 1920×1080 rectangular regions were cropped from each stego-image, and 200-bit messages were decoded from these regions. Their BERs were calculated to assess the tolerance. As a result, the BERs were less than 1.0%, and the average PSNR was 46.70 dB. Therefore, our method achieved a high image quality when using the IHC evaluation criteria. In addition, the proposed method was also evaluated by using StirMark 4.0. As a result, we found that our method has robustness for not only JPEG compression and cropping but also additional noise and Gaussian filtering. Moreover, the method has an advantage in that detection time is small since the synchronization is processed in 8×8 pixel blocks.

This paper considers a method for constructing good high-rate punctured convolutional codes through dual codes. A low-rate R=1/n convolutional code has a dual code identical to a punctured convolutional code with rate R=(n-1)/n. This implies that a low-rate R=1/n convolutional code encoder can help the search of punctured convolutional code encoders. This paper provides the procedures that obtain all the useful dual code encoders to a given CC with rate R=1/n easily, and the best PCC encoder with rate R=(n-1)/n among the encoders we derive from all the obtained dual code encoders. This paper also shows an example of the PCC the procedures obtain from some CC.

Delayed correlation has been used to detect orthogonal frequency division multiplexing symbols with cyclic prefix in spectrum sensing. Because of the frequency offset, the outputs of the delayed correlation do not lie only on the real axis of a complex plane. Therefore, the absolute value of the outputs of the delayed correlation is employed. Furthermore, with the use of a filter bank, the number of the outputs of the delayed correlators increases and the averaging over the outputs decreases the noise variance. This paper proposes a new delayed correlation scheme that uses a filter bank and employs the absolute of the outputs of delayed correlation. The proposed scheme improves the probability of detection as the number of the branches of the delayed correlators increases. In the case of 6 branches, the proposed scheme reduces the required sample energy by 1dB the probability of detection of 0.9.

This paper proposes a novel blind adaptive array scheme with subcarrier transmission power assignment (STPA) for spectrum superposing in cognitive radio networks. The Eigenvector Beamspace Adaptive Array (EBAA) is known to be one of the blind adaptive array algorithms that can suppress inter-system interference without any channel state information (CSI). However, EBAA has difficulty in suppressing interference signals whose Signal to Interference power Ratio (SIR) values at the receiver are around 0dB. With the proposed scheme, the ST intentionally provides a level difference between subcarriers. At the receiver side, the 1st eigenvector of EBAA is applied to the received signals of the subcarrier assigned higher power and the 2nd eigenvector is applied to those assigned lower power. In order to improve interference suppression performance, we incorporate Beamspace Constant Modulus Algorithm (BSCMA) into EBAA (E-BSCMA). Additionally, STPA is effective in reducing the interference experienced by the primary system. Computer simulation results show that the proposed scheme can suppress interference signals received with SIR values of around 0dB while improving operational SIR for the primary system. It can enhance the co-existing region of 2 systems that share a spectrum.

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.

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.

A serial ATA PHY fabricated in a 0.15-µm CMOS process performs the serial ATA operation in an asynchronous transition by using large variation in the reference clock. This technique calibrates a transmission signal frequency by utilizing the received signal. This is achieved by calibrating the divide ratio of a spread-spectrum clock generator (SSCG). This technique enables a serial ATA PHY to use reference oscillators with a production-frequency tolerance of less than 400ppm, i.e., higher than the permissible TX frequency variations (i.e., 350ppm). The calibrated transmission signal achieved a total jitter of 3.9ps.