A Novel Data-Aided Channel Estimation with Reduced Complexity for TDS-OFDM Systems

In contrast to the classical cyclic prefix (CP)-OFDM, the time domain synchronous (TDS)-OFDM employs a known pseudo noise (PN) sequence as guard interval (GI). Conventional channel estimation methods for TDS-OFDM are based on the exploitation of the PN sequence and consequently suffer from intersymbol interference (ISI). This paper proposes a novel dataaided channel estimation method which combines the channel estimates obtained from the PN sequence and, most importantly, additional channel estimates extracted from OFDM data symbols. Data-aided channel estimation is carried out using the rebuilt OFDM data symbols as virtual training sequences. In contrast to the classical turbo channel estimation, interleaving and decoding functions are not included in the feedback loop when rebuilding OFDM data symbols thereby reducing the complexity. Several improved techniques are proposed to refine the data-aided channel estimates, namely one-dimensional (1-D)/two-dimensional (2-D) moving average and Wiener filtering. Finally, the MMSE criteria is used to obtain the best combination results and an iterative process is proposed to progressively refine the estimation. Both MSE and BER simulations using specifications of the DTMB system are carried out to prove the effectiveness of the proposed algorithm even in very harsh channel conditions such as in the single frequency network (SFN) case

Convolutional Coded Generalized Direct Sequence Spread Spectrum

In this thesis we investigate the worst-case performance of coded ordinary and coded generalized direct sequence spread spectrum (DSSS) systems in a communication channel corrupted by an unknown and arbitrary interfering signal of bounded power. We consider convolutional codes with Viterbi decoding in order to compare the performance of coded ordinary and coded generalized DSSS systems. For the generalized DSSS system, we use a pulse stream of +1,-1 and 0 as the spreading sequence, which is different from ordinary DSSS system which uses the typical sequence with pulse values of +1 and -1. A C program for performing Monte-Carlo simulations is written in order to evaluate and compare the performance of coded ordinary and coded generalized DSSS systems. Plots of the worst-case error probability versus signal-to-interference ratio are presented for different code rates and constraint lengths of the convolutional code. Simulation results of the worst-case performance of ordinary and generalized DSSS show that generalized DSSS consistently performs appreciably better than ordinary DSSS. Simulation is performed for various code rates, various constraint lengths of the convolutional code and various lengths of the convolutional interleaver. Over all these simulations, it is observed that the difference between ordinary and generalized DSSS gets more pronounced as the channel gets wors

Convolutional Coded Generalized Direct Sequence Spread Spectrum

In this thesis we investigate the worst-case performance of coded ordinary and coded generalized direct sequence spread spectrum (DSSS) systems in a communication channel corrupted by an unknown and arbitrary interfering signal of bounded power. We consider convolutional codes with Viterbi decoding in order to compare the performance of coded ordinary and coded generalized DSSS systems. For the generalized DSSS system, we use a pulse stream of +1,-1 and 0 as the spreading sequence, which is different from ordinary DSSS system which uses the typical sequence with pulse values of +1 and -1. A C program for performing Monte-Carlo simulations is written in order to evaluate and compare the performance of coded ordinary and coded generalized DSSS systems. Plots of the worst-case error probability versus signal-to-interference ratio are presented for different code rates and constraint lengths of the convolutional code. Simulation results of the worst-case performance of ordinary and generalized DSSS show that generalized DSSS consistently performs appreciably better than ordinary DSSS. Simulation is performed for various code rates, various constraint lengths of the convolutional code and various lengths of the convolutional interleaver. Over all these simulations, it is observed that the difference between ordinary and generalized DSSS gets more pronounced as the channel gets wors

Cross-layer Optimized Wireless Video Surveillance

A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

Cross-layer Optimized Wireless Video Surveillance

A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

Error-Correction in Flash Memories via Codes in the Ulam Metric

We consider rank modulation codes for flash memories that allow for handling arbitrary charge-drop errors. Unlike classical rank modulation codes used for correcting errors that manifest themselves as swaps of two adjacently ranked elements, the proposed \emph{translocation rank codes} account for more general forms of errors that arise in storage systems. Translocations represent a natural extension of the notion of adjacent transpositions and as such may be analyzed using related concepts in combinatorics and rank modulation coding. Our results include derivation of the asymptotic capacity of translocation rank codes, construction techniques for asymptotically good codes, as well as simple decoding methods for one class of constructed codes. As part of our exposition, we also highlight the close connections between the new code family and permutations with short common subsequences, deletion and insertion error-correcting codes for permutations, and permutation codes in the Hamming distance

Convolutional Coded Generalized Direct Sequence Spread Spectrum

In this thesis we investigate the worst-case performance of coded ordinary and coded generalized direct sequence spread spectrum (DSSS) systems in a communication channel corrupted by an unknown and arbitrary interfering signal of bounded power. We consider convolutional codes with Viterbi decoding in order to compare the performance of coded ordinary and coded generalized DSSS systems. For the generalized DSSS system, we use a pulse stream of +1,-1 and 0 as the spreading sequence, which is different from ordinary DSSS system which uses the typical sequence with pulse values of +1 and -1. A C program for performing Monte-Carlo simulations is written in order to evaluate and compare the performance of coded ordinary and coded generalized DSSS systems. Plots of the worst-case error probability versus signal-to-interference ratio are presented for different code rates and constraint lengths of the convolutional code. Simulation results of the worst-case performance of ordinary and generalized DSSS show that generalized DSSS consistently performs appreciably better than ordinary DSSS. Simulation is performed for various code rates, various constraint lengths of the convolutional code and various lengths of the convolutional interleaver. Over all these simulations, it is observed that the difference between ordinary and generalized DSSS gets more pronounced as the channel gets wors

Capacity, coding and interference cancellation in multiuser multicarrier wireless communications systems

Multicarrier modulation and multiuser systems have generated a great deal of research during the last decade. Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier modulation generated with the inverse Discrete Fourier Transform, which has been adopted for standards in wireless and wire-line communications. Multiuser wireless systems using multicarrier modulation suffer from the effects of dispersive fading channels, which create multi-access, inter-symbol, and inter-carrier interference (MAI, ISI, ICI). Nevertheless, channel dispersion also provides diversity, which can be exploited and has the potential to increase robustness against fading. Multiuser multi-carrier systems can be implemented using Orthogonal Frequency Division Multiple Access (OFDMA), a flexible orthogonal multiplexing scheme that can implement time and frequency division multiplexing, and using multicarrier code division multiple access (MC-CDMA). Coding, interference cancellation, and resource sharing schemes to improve the performance of multiuser multicarrier systems on wireless channels were addressed in this dissertation. Performance of multiple access schemes applied to a downlink multiuser wireless system was studied from an information theory perspective and from a more practical perspective. For time, frequency, and code division, implemented using OFDMA and MC-CDMA, the system outage capacity region was calculated for a correlated fading channel. It was found that receiver complexity determines which scheme offers larger capacity regions, and that OFDMA results in a better compromise between complexity and performance than MC-CDMA. From the more practical perspective of bit error rate, the effects of channel coding and interleaving were investigated. Results in terms of coding bounds as well as simulation were obtained, showing that OFDMAbased orthogonal multiple access schemes are more sensitive to the effectiveness of the code to provide diversity than non-orthogonal, MC-CDMA-based schemes. While cellular multiuser schemes suffer mainly from MAI, OFDM-based broadcasting systems suffer from ICI, in particular when operating as a single frequency network (SFN). It was found that for SFN the performance of a conventional OFDM receiver rapidly degrades when transmitters have frequency synchronization errors. Several methods based on linear and decision-feedback ICI cancellation were proposed and evaluated, showing improved robustness against ICI. System function characterization of time-variant dispersive channels is important for understanding their effects on single carrier and multicarrier modulation. Using time-frequency duality it was shown that MC-CDMA and DS-CDMA are strictly dual on dispersive channels. This property was used to derive optimal matched filter structures, and to determine a criterion for the selection of spreading sequences for both DS and MC CDMA. The analysis of multiple antenna systems provided a unified framework for the study of DS-CDMA and MC-CDMA on time and frequency dispersive channels, which can also be used to compare their performance