Wilaiporn Lee

Two-stage spectrum sensing for cognitive radio under noise uncertainty

The robustness to uncertainty of noise power is one of main challenges to spectrum sensing technique. Since the occurrence of noise power uncertainty causes the detection performance of spectrum sensing techniques significantly degrade. In this paper, we propose two novel schemes of two-stage spectrum sensing for cognitive radio under environment as noise power uncertainty. The two-stage spectrum sensing technique combines two conventional spectrum sensing techniques to perform spectrum sensing by exploiting their individual advantages. The proposed two-stage spectrum sensing scheme exploits the merits of ED, MME and CAV techniques to determine the existence of the primary user. The ED performs spectrum sensing within a short time and offers a reliable detection at high SNRs condition. MME and CAV are robust to noise power uncertainty. Due to the combination of these techniques, the proposed schemes offer much more reliable detection when the uncertainty of noise power occurs. Even though the proposed technique takes the longest time in sensing period among two-stage spectrum sensing techniques, it is worth using this period of time to protect the primary user from harmful interference caused by the secondary user.

Two hybrid RSS/TOA localization techniques in cognitive radio system

In this paper, we proposed two hybrid RSS/TOA localization techniques in cognitive radio system including serial and parallel schemes. The proposed methods joint two location estimation techniques such as received signal strength (RSS) and time of arrival (TOA). First, we divide the consideration area into two cases: inner area and outer area using convex hull algorithm. We can conclude that the RSS is suitable for using in inner area and TOA should be chosen to use in outer area. Second, we enhance accuracy of RSS technique by applying the improved best linear unbiased estimation (iBLUE) method. In simulation results, we compare the performance and time duration of the RSS, TOA estimation and the two proposed methods: serial scheme and parallel scheme with iBLUE. Our simulation shows that the proposed method in serial scheme with iBLUE has better performance than RSS and TOA. Moreover, it is faster than TOA about 60%.

Performance Evaluation of TOA Estimation for Ultra-wideband System under AWGN and IEEE 802.13a Channel Model

This paper proposes the performance evaluation of seven Time-of-Arrival (TOA) estimation techniques in Ultra-wideband (UWB) systems. The TOA estimation schemes can be classified 2 types such as one-step and two-step TOA estimation. One-step TOA estimations include the maximum energy selection (MES) and the maximum energy selection based-on block (MES -- Block). For two-step TOA estimations, we consider 3 techniques including the separated signal TOA estimations that have 3 types: 1 Cut, 2 Cut and 3 Cut, the threshold-based TOA estimation and the window-based TOA estimation. Additional, we consider three UWB pulses that have power spectral density comply with Federal Communications Commission (FCC) mask. Moreover, we consider two environment types that are Additive White Gaussian Noise (AWGN) channel and UWB channel model based-on IEEE 802.13a (CM2). We use the root mean square error (RMSE) for evaluating and comparing the performance of TOA estimation schemes. The simulation results show that the window-based TOA estimation outperforms than other methods under both channel models. The threshold-based TOA estimation is very sensitive to multipath channel because its performance rapidly decreases when these techniques are applied on UWB channel model.

An experimental performance analysis of image reconstruction techniques under both Gaussian and non-Gaussian noise models

Recently, the images reconstruction approaches are very essential in digital image processing (DIP), especially in terms of removing the noise contaminations and recovering the content of images. Each image reconstruction approach has different mathematical models. Therefore a performance of individual reconstruction approach is varied depending on several factors such as image characteristic, reconstruction mathematical model, noise model and noise intensity. Thus, this paper presents comprehensive experiments based on the comparisons of various reconstruction approaches under Gaussian and non-Gaussian noise models. The employing reconstruction approaches in this experiment are Inverse Filter, Wiener Filter, Regularized approach, Lucy-Richardson (L-R) approach, and Bayesian approach applied on mean, median, myriad, meridian filters together with several regularization techniques (such as non-regularization, Laplacian regularized, Markov Random Field (MRF) regularization, and one-side Bi-Total Variation (OS-BTV) regularization). Three standard images of Lena, Resolution Chart, and Susie (40th) are used for testing in this experiment. Noise models of Additive White Gaussian Noise (AWGN), Poisson, Salt&Pepper, and Speckle of various intensities are used to contaminate all these images. The comparison is done by varying the parameters of each approach until the best peak-signal-to-noise ratio (PSNR) is obtained. Therefore, PSNR plays a vital parameter for comparisons all the results of individual approaches.

Double constraints adaptive energy detection for spectrum sensing in cognitive radio networks

In this paper, we propose double constraints adaptive energy detection (DCAED) for spectrum sensing. DCAED adapts the threshold by exploiting the interdependent between Pfa and Pd. DCAED overcomes a demerit of ED and AED in tradeoff between Pfa and Pd. The simulation results show that DCAED gives the highest detection rate, therefore the PU has the maximum protection from harmful interference. The DCAED consumes short sensing time and gives the low of false alarm rate, the SU accordingly has more opportunities to use the channel and also maintain the throughput nearly at the same rate as the other ED techniques.

Packet transfer of DLMS/COSEM standards for smart grid

In this paper, we review packet transfer from DCU to meter by using DLMS/COSEM protocol. We descript the kind of book of DLMS/COSEM and explain the combination of DLMS/COSEM such as COSEM application process, COSEM application layer and connection manager. We show some example of packet transfer from application layer of DLMS/COSEM to data link layer and summary the size of packet of each command and response of DLSM/COSEM. Additionally, we will descript the ZigBee basic knowledge that used to physical layer of DLMS/COSEM protocol.

Multi-slot double constraints adaptive energy detection for spectrum sensing in Cognitive radio networks

In this paper, we propose a new scheme of an adaptive energy detection, multi-slot double constraints adaptive energy detection (MDCAED), with an objective to improve the detection performance of our previous work, double constraints adaptive energy detection (DCAED). MDCAED exploits multiple mini-slot technique, which achieves the diversity reception concept, to increase the ability to distinguish noise from the PU since the effect of diversity reception increases the received SNR. MDCAED performs spectrum sensing by spitting a sensing slot into a multiple mini-slot. Each mini-slot is performed spectrum sensing using DCAED and the final decision is made by using K-of-N rule. The decision threshold is adapted on the SNR of each mini-slot using DCAED. Therefore, by exploiting the multiple mini-slot concept together with DCAED, Pfa is reduced while Pd is improved. Although, the detection performance is improved, the average sensing time of MDCAED slightly increases compared to DCAED since the system threshold needs to adapt more than once. Nevertheless, the average sensing time of MDCAED still achieves the spectrum sensing requirement.

Multicriteria Parent Selection Using Cognitive Radio for RPL in Smart Grid Network

To maintain reliability of advanced metering infrastructure network in smart grid, data sent from a smart meter must reach a data concentrator unit efficiently. Parent selecting mechanism in routing protocol for low-power and lossy (RPL) is a key to maintain the reliability by balancing workload of meters in the network. In this paper, a parent selecting mechanism with three criteria including expected transmission count, residual energy, and expected transmission time is proposed to improve workload balancing and lifetime differences of all meters. A meter selects an immediate parent based on three factors. From simulation results, parents’ workload is better balanced and the lifetime of all meters in the network is depleted nearly at the same time. Moreover, a simulation with cognitive radio enabled meters, where data can be transmitted on a licensed channel opportunistically when the channel is not utilized, shows an improvement in the packet delivery ratio.

An Optimal Performance Investigation for Bilateral Filter under Four Different Image Types

The merit of bilateral filter is that it preserves the edges of the image and smooth the image at the same time. This can be done by controlling two important parameters -- spatial domain parameter and range domain parameter. The contribution of this paper is two-fold. First, we investigate the optimal parameters of the bilateral filter under four different types of images -- aerial, face, object and texture. The simulation results show that the parameters -- spatial domain parameter and range parameter -- should be changed depending on the noise power and the details of image. If the noise power is high, the parameters should be set at high levels. These values should be decreased on the increasing in an SNR. Second, we determine the appropriate types of image that the bilateral filter can be applied to perform filtering. Then, we compare bilateral filters performance to Gaussian filter and switching bilateral filter. The simulation results show that the bilateral filter gives the best performance when perform de-nosing of aerial, face and object image where the detail of these images are less than texture image.

An experimental comparision of vector quantization techniques for Thai text image

This paper presents the experimental comparison of vector quantization (VQ) methods for Thai text image. The compared methods include of Linde-Buzo-Gray (LBG), Enhanced LBG (ELBG) and Genetic algorithm (GA). The performance of VQ over gray image is measured with peak signal-to-noise ratio (PSNR) and processing time. The studied parameter are including of codebook number, cluster size, training image type, number of training image and noise. In addition, the results are shown in the verities aspects which are conducted to the appropriate approach in compression of Thai text image.