Hongting Zhang

Novel Energy-Based Localization Technique for Multiple Sources

Source localization using acoustic sensor networks has been drawing a lot of research interest recently. In a sensor network, there are a large number of inexpensive sensors which are densely deployed in a region of interest (ROI). This dense deployment enables accurate intensity (energy) based target localization. The maximum-likelihood is the predominant objective which leads to a variety of source localization approaches. However, the investigation on the energy-based localization for multiple sources has been very rare. The corresponding robust and efficient algorithms are still being pursuit by researchers nowadays. In this paper, we would like to combat the energy-based multiple-source localization problem. We propose two new algorithms, namely alternating projection (AP) algorithm and expectation maximization (EM) algorithm, which can combat the energy-based localization problem for multiple sources.

Adaptive cooperative spectrum sensing based on a novel robust detection algorithm

The optimal data fusion rule for multiple sensor detection systems based on the Bayesian criterion has been derived by Chair and Varshney in 1986. However, most of the following works are focused on how to implement such a fusion rule, since the probability of false alarm and the probability of miss detection are hard to evaluate in practice. Till now, although more and more satisfactory data-fusion implementation schemes are available, most of the cooperative spectrum sensing techniques are based on the simple energy-detection algorithm, which only relies on the energy of the received signal. However, when noise is relatively large or the time-varying characteristics of the signal are conspicuous, the energy-detection spectrum sensing algorithm is more prone to fail. Thus, in this paper, we propose a new adaptive cooperative spectrum sensing scheme, which is based on a novel detection algorithm involving JB (Jarque-Bera) statistic. The ROC (receiver-operating characteristic) curves show that our new cooperative spectrum sensing scheme is more robust than that based on the energy-detection spectrum sensing algorithm. Besides, the performance comparison also implies that the optimal data-fusion rule in our new cooperative spectrum sensing scheme is superior to the commonly adopted “OR” and “AND” rules in the existing literature.

A New Approach for Optimal Multiple Watermarks Injection

The digital imaging technology has grown explosively for multimedia applications in recent years. The need for the copyrighted digitalized media becomes urgent nowadays. An approach for the digital copyright protection is to employ advanced watermarking techniques, where watermarks can reveal the ownership identities. Generally speaking, the watermarks are embedded into image or video signals. In this paper, we will investigate digital watermarking techniques and propose a new optimal watermarking scheme. When multiple embedded watermarks are considered, a new analysis for the signal-to-interference-plus-noise-ratios (SINRs) with respect to the subject signal and the watermark signals is carried out. The objective quality measure for the digital watermarking applications should essentially consist of both signal-to-interference-plus-noise-ratio for the subject signal and similarity coefficients for the watermarks. In order to optimize the aforementioned objective measure, we design a novel efficient scale-factor optimization scheme, which can lead to the maximum overall SINR for both subject signal and watermarks. Simulation results are also demonstrated to illustrate the effectiveness of our proposed method.

Robust Pilot Detection Techniques for Channel Estimation and Symbol Detection in OFDM Systems

In this letter, we propose new frequency-domain pilot-multiplexing techniques (FDPMTs) for the channel estimation and equalization in orthogonal frequency-division multiplexing (OFDM) systems. A robust and effective pilot insertion and detection scheme is devised thereby. These pilot positions are optimally selected to minimize the distortion of the transmitted time-domain signal caused by the subcarrier-removal at the corresponding pilot positions. Besides, three different blind pilot-detection techniques are designed at the receiver without any a priori knowledge of the pilot positions, and the distorted data symbols can thus be iteratively reconstructed. Rigorous theoretical analysis and Monte Carlo simulation results both demonstrate that our proposed new OFDM system using dynamical pilot positions is more robust than the conventional OFDM system using the fixed pilot positions over multipath fading channels.

Analysis and Algorithm for Robust Adaptive Cooperative Spectrum-Sensing

The optimal data-fusion rule was first established for multiple-sensor detection systems in 1986. Most subsequent works have been focused on the corresponding implementation aspects. The probability of false alarm and the probability of miss detection used in this data-fusion rule are quite difficult to precisely enumerate in practice. Although the improved data-fusion implementation techniques are now available, most existing cooperative spectrum-sensing techniques are still based on the simple energy-detection algorithm, which is prone to failure in many scenarios. In this paper, we propose a novel adaptive cooperative spectrum-sensing scheme based on our recently proposed single-reception spectrum-sensing technique. We also found that the commonly-used sample-average estimator for the cumulative weights in the data-fusion rule becomes unreliable in time-varying environments. To overcome this drawback, we adopt a temporal discount factor, which is crucial to the probability estimators. New theoretical analysis to justify the advantage of our proposed new estimators over the conventional sample-average estimators and to determine the optimal numerical value of the proposed discount factor is presented. The Monte Carlo simulation results are also provided to demonstrate the superiority of our proposed adaptive cooperative spectrum-sensing method in both stationary and time-varying environments.

A new approach for optimal multiple watermarks injection

The digital imaging technology has grown explosively for multimedia applications in recent years. The need for the copyrighted digitalized media becomes urgent nowadays. An approach for the digital copyright protection is to employ advanced watermarking techniques, where watermarks can reveal the ownership identities. Generally speaking, the watermarks are embedded into an image or video signals. In this paper, we will investigate digital watermarking techniques and propose a new optimal watermarking scheme. When multiple watermarks are considered, a new analysis for the signal-to-interference-plus-noise-ratios (SINRs) with respect to the subject signal and the watermark signals is carried out. The objective quality measure for the digital watermarking applications should essentially consist of both signal-to-interference-plus-noise-ratio for the subject signal and similarity coefficients for the watermarks. In order to optimize the aforementioned objective measure, we design a novel efficient scale-factor optimization scheme, which can lead to the maximum overall SINR for both subject signal and watermarks. Simulation results are also demonstrated to illustrate the effectiveness of our proposed new method.

Robust optimization for home-load scheduling under price uncertainty in smart grids

In this paper, the emerging problem of residential energy scheduling for smart grid under the energy-price uncertainty is investigated, where the prices randomly vary around nominal values with a known underlying distribution. The objective of the focused optimization problem is to minimize the users cost of energy consumption. The robust optimization methodology will be used to deal with the uncertainty programming. We schedule the amounts of charged/discharged energy of the energy storage devices varied continuously within each time slot, which is more realistic and cost-effective. In addition, the mathematical model we adopts here is more practical because we consider the linear dynamical model of the temperature-related appliances. The involvement of the price uncertainty makes our devised algorithm more robust. Simulation results illustrate that our proposed new scheme is more effective than the conventional method without smart grid in terms of total energy cost.

Novel blind encoder identification of Reed-Solomon codes with low computational complexity

Adaptive modulation and coding (AMC) is commonly used in wireless systems to dynamically change the modulation and coding schemes (MCSs) in subsequent frames such that the spectral efficiency can be adapted to various channel conditions. The spectrum and energy efficiency would decrease if the adopted MCS option at the transmitter needs to be dynamically transmitted to the receiver through a secure control channel. To combat this problem, in this paper, we would like to propose a novel blind channel-encoder identification scheme with low computational complexity for Reed-Solomon (RS) codes over Galois field GF(q), which could also be applied to other similar non-binary channel codes as well. Our proposed new scheme involves the estimation of the channel parameters using the expectation-maximization (EM) algorithm, the calculation of the log-likelihood ratio vectors (LLRVs) of the syndrome a posteriori probabilities over GF(q), and the identification of the non-binary RS encoder in use subject to the maximum average log-likelihood ratio (LLR) over the pre-selected candidate encoder set. Simulation results justify the effectiveness of this new mechanism.

Novel fast MUSIC algorithm for spectral estimation with high subspace dimension

Multiple signal classification (MUSIC) algorithm has been employed for many applications of frequency estimation, emitter localization, direction-of-arrival (DOA) estimation, etc. However, when the MUSIC algorithm is applied, a lot of computational resource is required to carry out the eigen-decomposition in order to extract the subspace information. In this paper, we would like to present a novel fast MUSIC algorithm. Since the data storage devices become less and less costly, spectral estimation of large dimensions appears crucial in modern telecommunication and signal processing applications. Our proposed computationally-efficient MUSIC algorithm, which can be facilitated in real time, would be very useful in the future. Our scheme is based on the fast eigen-decomposition method, and the computational complexity of our new technique is O (ρM2) (ρ ≪ M) compared to O (M3) of the conventional MUSIC algorithm when the size of the autocorrelation matrix of the received signal is M × M.

Multimedia services scheduling optimization using femtocell on high-speed trains

Nowadays, it is well-known that the LTE (Long Term Evolution) networks have greatly tackled the Doppler effect problem at the physical layer since they are capable of achieving a 100 Mbps data throughput on a high-speed moving vehicle up to 350 km/h within the same cell (i.e. no handover is allowed). However, there are still cases where vehicles are moving at very high speeds and thus frequent handovers across cells are inevitable, such as high-speed trains, which have been constructed rapidly all over the world in recent years. Therefore, how to maintain good link quality and schedule multimedia services optimally on high-speed trains remains challenging. In this paper, we propose a novel optimal LTE-based multimedia-service-scheduling and resource-allocation mechanism for highspeed trains, which could maximize the service rate and maintain a good service quality at the same time. This new scheme makes use of the seamless handover mechanism by carefully organizing the cell array along the railroad and aggregating the data (at the femtocell) from different users within the train cabins. Besides, we also project to schedule the multimedia services and allocate the network resources as fair as possible for all the users on the train. The simulation results justify the effectiveness of our proposed new scheme.