A new form of multi-waveform space-time adaptive processing (MuW-STAP) is presented. The formulation provides additional training data for adaptive clutter cancellation for ground moving target indication after pulse compression. The pulse compression response is homogenized using stochastic phase filters to produce a smeared response that approximates identically distribution assumed by covariance estimation. Post pulse compression MuW-STAP (PMuW-STAP) is proposed to address clutter heterogeneity that causes degradation in detection performance of STAP similar to single-input multi-output MuW-STAP. Furthermore, the family of MuW-STAP algorithms are computationally expensive due to estimation of multiple covariance matrices and inversion of a single covariance for every range sample. Well-known partially adaptive techniques, previously implemented in STAP, are implemented with PMuW-STAP. Partial adaptation in element-space post-Doppler, beam-space pre-Doppler, and beam-space post-Doppler are presented. Each of these are examined on several simulated, controlled clutter scenarios. Fully adaptive PMuW-STAP is further evaluated on the high-fidelity knowledge aided adaptive radar architecture: knowledge-aided sensor signal processing and expert reasoning (KASSPER) dataset.

Owning to the ever-increasing data traffic in today’s optical network, how to utilize the optical bandwidth more efficiently has become a critical issue. Optical wavelength division multiplexing (WDM) multiplexes multiple optical carrier signals into a single fiber by using different wavelengths of laser light. Optical cross-connect (OXC) and switches based on optical WDM can greatly improves the performance of optical networks, which results in reduced complexity, signal transparency, and significant electrical energy saving. However, OXC alone cannot fully exploit the availability of optical bandwidth due to its coarse bandwidth granularity imposed by optical filtering. Thus, OXC may not meet the requirements of some applications when the sub-band has a small bandwidth. In order to achieve smaller bandwidth granularities, electrical digital cross-connect (DXC) could be added to the current optical network.

In this work, we proposed a scheme of real-time digital signal processing (DSP) enabled multi-carrier cross-connect which can dynamically assign bandwidth and allocates power to each individual subcarrier channel. This cross-connect is based on digital sub-carrier multiplexing (DSCM), which is a frequency division multiplexing (FDM) technique. Either Nyquist WDM (N-WDM) or orthogonal frequency division multiplexing (OFDM) can be used to implement real-time enabled DSCM. DSCM multiplexes the digital created subcarriers on each optical wavelength. Compared with optical WDM, DSCM has a smaller bandwidth granularity because it multiplexes sub-carriers in electrical domain. DSCM also provides more flexibility since operations such as distortion compensation and signal regeneration could be conducted by using DSP algorithms.

We built a real-time DSP platform based on a Virtex7 FPGA, which allows the test of real-time DSP algorithms for multi-carrier cross-connect in optical systems. We have implemented a real-time DSP enabled multi-carrier cross-connect based on up/down sampling and filtering. This technique can save the DSP resources since local oscillators (LO) are not needed in spectral translation. We got some preliminary results from theoretical analysis, simulation and experiment. The performance and resource cost of this cross-connect has been analyzed. This real-time DSP enabled cross-connect also has the potential to reduce the cost in applications such as the mobile Fronthaul in 5G next-generation wireless networks.

In real world environments, the speech signals received by our ears are usually a combination of different sounds that include not only the target speech, but also acoustic interference like music, background noise, and competing speakers. This interference has negative effect on speech perception and degrades the performance of speech processing applications such as automatic speech recognition (ASR), and hearing aid devices. One way to solve this problem is using source separation algorithms to separate the desired speech from the interfering sounds. Many source separation algorithms have been proposed to improve the performance of ASR systems and hearing aid devices, but it is still challenging for these systems to work efficiently in noisy and reverberant environments. On the other hand, humans have a remarkable ability to separate desired sounds and listen to a specific talker among noise and other talkers. Inspired by the capabilities of human auditory system, a popular method known as auditory scene analysis (ASA) was proposed to separate different sources in a two stage process of segmentation and grouping. The main goal of source separation in ASA is to estimate time frequency masks that optimally match and separate noise signals from a mixture of speech and noise. Three major aims are proposed to improve upon source separation in noisy and reverberant acoustic signals. First, a simple and novel algorithm is proposed to increase the discriminability between two sound sources by magnifying the head-related transfer function of the interfering source. Experimental results show a significant increase in the quality of the recovered target speech. Second, a time frequency masking-based source separation algorithm is proposed that can separate a male speaker from a female speaker in reverberant conditions by using the spatial cues of the sources. Furthermore, the proposed algorithm also has the ability to preserve the location of the sources after separation.

Finally, a supervised speech separation algorithm is proposed based on deep neural networks to estimate the time frequency masks. Initial experiments show promising results for separating sources in noisy and reverberant condition. Continued work is focused on identifying the best network training features and network structure that are robust to different types of noise, speakers, and reverberation. The main goal of the proposed algorithm is to increase the intelligibility and quality of the recovered speech from noisy environments, which has the potential to improve both speech processing applications and signal processing strategies for hearing aid technology.

Time and again, fiber optic medium has proved to be the best means for transporting global data traffic which is following an exponential growth trajectory. High bandwidth applications based on cloud, virtual reality and big data, necessitates maximum effective utilization of available fiber bandwidth. To this end, multicarrier superchannel transmission systems, aided by robust digital signal processing both at transmitter and receiver, have proved to enhance spectral efficiency and achieve multi tera-bit per second data rates.

With respect to transmission sources, laser technology too has made significant strides, especially in the domain of multiwavelength sources such as quantum dot passive mode-locked laser (QD-PMLL) based optical frequency combs. In the present research work, we characterize the phase dynamics of comb lines from a QD-PMLL based on a novel multiheterodyne coherent detection technique. The inherently broad linewidth of comb lines which is in the order of tens of MHz, make it difficult for conventional digital phase noise compensation algorithms to track the large phase noise especially for low baud rate subcarriers using higher cardinality modulation formats. In the context of multi-subcarrier Nyquist pulse shaped superchannel transmission system with coherent detection, we demonstrate through measurements, an efficient phase noise compensation technique called “Digital Mixing” which exploits the mutual phase coherence among the comb lines. For QPSK and 16 QAM modulation formats, digital mixing provided significant improvement in bit error rate (BER) performance.  For short reach data center and passive optical network-based applications, which adopt direct detection, a single optical amplifier is generally used meet the power budget requirements to achieve the desired BER.  Semiconductor Optical Amplifier (SOA) with its small form factor, is a low-cost power booster that can be designed to operate in any desired wavelength and most importantly can be integrated with the transmitter. However, saturated SOAs introduce nonlinear distortions on the amplified signal. Alongside SOA, the photodiode also introduces nonlinear mixing in the form of Signal-Signal Beat Interference (SSBI). In this research, we study the impact of SOA nonlinearity on the effectiveness of SSBI compensation in a direct detection OFDM based transmission system. We experimentally demonstrate a digital compensation technique to undo the SOA nonlinearity effect by digitally back-propagating the received signal through a virtual SOA, thereby effectively eliminating the SSBI. ​

Many online social networks are increasingly being used as information sharing platforms. With a massive increase in the number of users participating in information sharing, an enormous amount of information becomes available on such sites. It is vital to preserve user’s privacy, without preventing them from socialization. Unfortunately, many existing models overlooked a very important fact, that is, a user may want different information boundary preference for different information. To address this short coming, in this paper, I will introduce a ‘social circle’ model, which follows the concepts of ‘private information boundaries’ and ‘restricted access and limited control’. While facilitating socialization, the social circle model also provides some privacy protection capabilities. I then utilize this model to analyze the most popular social networks (such as Facebook, Google+, VKontakte, Flickr, and Instagram) and demonstrate the potential privacy vulnerabilities in some of these networking sites. Lastly, I discuss the implication of the analysis and possible future directions. 

The non-ending growth of data traffic resulting from the continuing emergence of high-data-rate-demanding applications sets huge capacity requirements on optical interconnects and transport networks. This requires optical communication schemes in these networks to make the best possible use of the available optical spectrum per a single optical channel to enable transmission of multiple tens of tera-bits per second per a single fiber core in high capacity transport networks. Therefore, advanced modulation formats are required to be used in conjunction with energy-efficient and robust transceiver schemes. Important challenges facing these goals are the stringent requirements on the characteristics of optical components comprising these systems. Especially the laser sources. Laser phase noise is one of the most important performance-limiting factors in systems with high spectral efficiency. In this research work, we study the effects of different laser phase noise characteristics on the performance of different optical communication schemes. A novel, simple and accurate phase noise characterization technique is proposed. Experimental results show that the proposed technique is very accurate in estimating the performance of lasers in coherent systems employing digital phase recovery techniques. A novel multi-heterodyne scheme for characterizing the phase noise of laser frequency comb sources is also proposed and validated by experimental results. This proposed scheme is the first one of its type capable of measuring the differential phase noise between multiple spectral lines instantaneously by a single measurement. Moreover, extended relations between system performance and detailed characteristics of laser phase noise are also analyzed and modeled. The results of this study show that the commonly-used metric to estimate the performance of lasers with a specific phase recovery scheme, linewidth-symbol-period product, is not necessarily accurate for all types of lasers, and description of FM-noise power spectral profile is required for accurate performance estimation. We also propose an energy- and cost-efficient transmission scheme suitable for metro and long-reach data-center-interconnect links based on direct detection of field-modulated optical signals with advanced modulation formats, allowing for higher spectral efficiency. The proposed system combines the Kramers-Kronig coherent receiver technique, with the use of quantum-dot multi-mode laser sources, to generate and transmit multi-channel optical signals using a single diode laser source. Experimental results of the proposed system show that high modulation formats can be employed, with high robustness against laser phase noise and frequency drifting.