Covert communication refers to the process of communicating data through a channel that is neither designed, nor intended to transfer information. Traditionally, covert channels are considered as security threats in computer systems and a great deal of attention has been given to countermeasures for covert communication schemes. The evolution of computer networks led the communication community to revisit the concept of covert communication not only as a security threat but also as an alternative way of providing security and privacy to communication networks. In fact, the heterogeneous structure of computer networks and the diversity of communication protocols provide an appealing setting for covert channels. This dissertation is an exploration on a novel design methodology for undetectable and robust covert channels in communication networks. Our new design methodology is based on the concept of behavioral mimicry in computer systems. The objective is to design a covert transmitter that has enough degrees of freedom to behave like an ordinary transmitter and react normally to unpredictable network events, yet it has the ability to modulate a covert message over its behavioral fingerprints in the network. To this end, we argue that the inherent randomness in communication protocols and network environments is the key in finding the proper medium for network covert channels. We present a few examples on how random behaviors in communication protocols lead to discovery of suitable shared resources for covert channels. The proposed design methodology is tested on two new covert communication schemes, one is designed for wireless networks and the other one is optimized for public communication networks (e.g., Internet). Each design is accompanied by a comprehensive analysis from undetectability, achievable covert rate and reliability perspectives. In particular, we introduced turbo covert channels, a family of extremely robust model-based timing covert channels that achieve provable polynomial undetectability in public communication networks. This means that the covert channel is undetectable against any polynomial-time statistical test that analyzes samples of the covert traffic and the legitimate traffic of the network. Target applications for the proposed covert communication schemes are discussed including detailed practical scenarios in which the proposed channels can be implemented.

We construct polar codes for binary relay channels with orthogonal receiver components. We show that polar codes achieve the cut-set bound when the channels are symmetric and the relay-destination link supports compress-and-forward relaying based on Slepian-Wolf coding. More generally, we show that a particular version of the compress-and-forward rate is achievable using polar codes for Wyner-Ziv coding. In both cases the block error probability can be bounded as O(2-Nβ) for 0 &lt; β &lt; 1/2 and sufficiently large block length N. / <p>© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. QC 20111207</p>

In general, ultra wideband (UWB) signals are transmitted using ~'eIYshort pulses m tiIae domain, thus promising very high data rates. In this thesis, a recei'ler structure is proposed for decoding multiuser information data in a convolutionally coded UWB system. The proposed iterative receiver has three stages: a pulse detector, a symbol detector, and a channel decoder. Each of these stages outputs soft values, which are used as a priori information in the next iteration. Simulation results show that the proposed system can provide performance very close to a single-user system. / Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and Computer Engineering. / "July 2006." / Incluldes bibliographic references (leaves 29-31)

Recently, the transmission of vector quantization (VQ) over a code-division multiple access (CDMA) channel has received a considerable attention in research community. The complexity of the optimal decoding for VQ in CDMA communications is prohibitive for implementation, especially for systems with a medium or large number of users. A suboptimal approach to VQ decoding over a CDMA channel, disturbed by additive white Gaussian noise (AWGN), was recently developed. Such a suboptimal decoder is built from a soft-output multiuser detector (MUD), a soft bit estimator and the optimal soft VQ decoders of individual users. <p>Due to its lower complexity and good performance, such a decoding scheme is an attractive alternative to the complicated optimal decoder. It is necessary to extend this decoding scheme for a frequency-selective Rayleigh fading CDMA channel, a channel model typically seen in mobile wireless communications. This is precisely the objective of this thesis. <p>Furthermore, the suboptimal decoders are obtained not only for binary phase shift keying (BPSK), but also for M-ary pulse amplitude modulation (M-PAM). This extension offers a flexible trade-off between spectrum efficiency and performance of the systems. In addition, two algorithms based on distance measure and reliability processing are introduced as other alternatives to the suboptimal decoder. <p>Simulation results indicate that the suboptimal decoders studied in this thesis also performs very well over a frequency-selective Rayleigh fading CDMA channel.

The paradigm of separate source-channel coding is inspired by Shannon's separation result, which implies the asymptotic optimality of designing source and channel coding independently from each other. The result exploits the fact that channel error probabilities can be made arbitrarily small, as long as the block length of the channel code can be made arbitrarily large. However, this is not possible in practice, where the block length is either fixed or restricted to a range of finite values. As a result, the optimality of source and channel coding separation becomes unknown, leading researchers to consider joint source-channel coding (JSCC) to further improve the performance of practical systems that must operate in the finite block length regime. With this motivation, this thesis investigates the application of JSCC principles for multimedia communications over point-to-point, broadcast, and relay channels. All analyses are conducted from the perspective of end-to-end distortion (EED) for results that are applicable to channel codes with finite block lengths in pursuing insights into practical design. The thesis first revisits the fundamental open problem of the separation of source and channel coding in the finite block length regime. Derived formulations and numerical analyses for a source-channel coding system reveal many scenarios where the EED reduction is positive when pairing the channel-optimized source quantizer (COSQ) with an optimal channel code, hence establishing the invalidity of the separation theorem in the finite block length regime. With this, further improvements to JSCC systems are considered by augmenting error detection codes with the COSQ. Closed-form EED expressions for such system are derived, from which necessary optimality conditions are identified and used in proposed algorithms for system design. Results for both the point-to-point and broadcast channels demonstrate significant reductions to the EED without sacrificing bandwidth when considering a tradeoff between quantization and error detection coding rates. Lastly, the JSCC system is considered under relay channels, for which a computable measure of the EED is derived for any relay channel conditions with nonzero channel error probabilities. To emphasize the importance of analyzing JSCC systems under finite block lengths, the large sub-optimality in performance is demonstrated when solving the power allocation configuration problem according to capacity-based formulations that disregard channel errors, as opposed to those based on the EED. Although this thesis only considers one JSCC setup of many, it is concluded that consideration of JSCC systems from a non-asymptotic perspective not only is more meaningful, but also reveals more relevant insight into practical system design. This thesis accomplishes such by maintaining the EED as a measure of system performance in each of the considered point-to-point, broadcast, and relay cases.

Shannon's classical separation result holds only in the limit of infinite source code dimension and infinite channel code block length. In addition, Shannon theory does not address the design of good source codes when the probability of channel error is nonzero, which is inevitable for finite-length channel codes. Thus, for practical systems, a joint source and channel code design could improve performance for finite dimension source code and finite block length channel code, as well as complexity and delay. Consider a multicast system over a broadcast channel, where different end users typically have different capacities. To support such user or capacity diversity, it is desirable to encode the source to be broadcasted into a scalable bit stream along which multiple resolutions of the source can be reconstructed progressively from left to right. Such source coding technique is called multiresolution source coding. In wireless communications, joint source channel coding (JSCC) has attracted wide attention due to its adaptivity to time-varying channels. However, there are few works on joint source channel coding for network multicast, especially for the optimal source coding over broadcast channels. In this work, we aim at designing and analyzing the optimal multiresolution vector quantization (MRVQ) in conjunction with the subsequent broadcast channel over which the coded scalable bit stream would be transmitted. By adopting random index assignment (RIA) to link MRVQ for the source with superposition coding for the broadcast channel, we establish a closed-form formula of end-to-end distortion for a tandem system of MRVQ and a broadcast channel. From this formula we analyze the intrinsic structure of end-to-end distortion (EED) in a communication system and derive two necessary conditions for optimal multiresolution vector quantization over broadcast channels with random index assignment. According to the two necessary conditions, we propose a greedy iterative algorithm for jointly designed MRVQ with channel conditions, which depends on the channel only through several types of average channel error probabilities rather than the complete knowledge of the channel. Experiments show that MRVQ designed by the proposed algorithm significantly outperforms conventional MRVQ designed without channel information. By building an closed-form formula for the weighted EED with RIA, it also makes the computational complexity incurred during the performance analysis feasible. In comparison with MRVQ design for a fixed index assignment, the computation complexity for quantization design is significantly reduced by using random index assignment. In addition, simulations indicate that our proposed algorithm shows better robustness against channel mismatch than MRVQ design with a fixed index assignment, simply due to the nature of using only the average channel information. Therefore, we conclude that our proposed algorithm is more appropriate in both wireless communications and applications where the complete knowledge of the channel is hard to obtain. Furthermore, we propose two novel algorithms for MRVQ over broadcast channels. One aims to optimize the two corresponding quantizers at two layers alternatively and iteratively, and the other applies under the constraint that each encoding cell is convex and contains the reconstruction point. Finally, we analyze the asymptotic performance of weighted EED for the optimal joint MRVQ. The asymptotic result provides a theoretically achievable quantizer performance level and sheds light on the design of the optimal MRVQ over broadcast channel from a different aspect.

Recently, the transmission of vector quantization (VQ) over a code-division multiple access (CDMA) channel has received a considerable attention in research community. The complexity of the optimal decoding for VQ in CDMA communications is prohibitive for implementation, especially for systems with a medium or large number of users. A suboptimal approach to VQ decoding over a CDMA channel, disturbed by additive white Gaussian noise (AWGN), was recently developed. Such a suboptimal decoder is built from a soft-output multiuser detector (MUD), a soft bit estimator and the optimal soft VQ decoders of individual users. <p>Due to its lower complexity and good performance, such a decoding scheme is an attractive alternative to the complicated optimal decoder. It is necessary to extend this decoding scheme for a frequency-selective Rayleigh fading CDMA channel, a channel model typically seen in mobile wireless communications. This is precisely the objective of this thesis. <p>Furthermore, the suboptimal decoders are obtained not only for binary phase shift keying (BPSK), but also for M-ary pulse amplitude modulation (M-PAM). This extension offers a flexible trade-off between spectrum efficiency and performance of the systems. In addition, two algorithms based on distance measure and reliability processing are introduced as other alternatives to the suboptimal decoder. <p>Simulation results indicate that the suboptimal decoders studied in this thesis also performs very well over a frequency-selective Rayleigh fading CDMA channel.

Distributed three-dimensional (3D) graphics applications exhibit both resemblance and uniqueness in comparison with conventional streaming media applications. The resemblance relates to the large data volume and the bandwidth-limited and error-prone transmission channel. The uniqueness is due to the polygon-based representation of 3D geometric meshes and their accompanying attributes such as textures. This specific data format introduces sophisticated rendering computation to display graphics models and therefore places an additional constraint on the streaming application. The objective of this research is to provide scalable, error-resilient, and time-efficient solutions for high-quality 3D graphics applications in distributed and resource-constrained environments. Resource constraints range from rate-limited and error-prone channels to insufficient data-reception, computing, and display capabilities of client devices. Optimal resource treatment with transmission and rendering scalability is important under such circumstances. The proposed research consists of three milestones. In the first milestone, we develop a joint mesh and texture optimization framework for scalable transmission and rendering of textured 3D models. Then, we address network behaviors and develop a hybrid retransmission and error protection mechanism for the on-demand delivery of 3D models. Next, we advance from individual 3D models to 3D scene databases, which contain numerous objects interacting in one geometric space, and study joint application and transport approaches. By properly addressing the properties of 3D scenes represented in multi-resolution hierarchies, we develop a joint source and channel coding method and a multi-streaming framework for streaming the content-rich 3D scene databases toward optimized transmission and rendering scalability under resource constraints.

Cooperative communication has been shown that it is an effective way to combat the outage caused by channel fading; that is, it provides the spatial diversity for communication. Except for amplify-and-forward (AF) and decode-and-forward (DF), compressed-and-forward (CF) is also an efficient forwarding strategy. In this thesis, we proposed a new CF scheme. In the existing CF protocol, the relay will switch to the DF mode when the source transmitted signal can be recovered by the relay completely; no further compression is made in this scheme. In our proposed, the relay will estimate if the codeword in a block is succeeded decoded, choose the corresponding forwarding methods with LDPC coding; those are based on joint source-channel coding or compressive sensing. At the decode side, a joint decoder with side information that performs sum-product algorithm (SPA) to decode the source message. Simulation results show that the proposed CF scheme can acquire the spatial diversity and outperform AF and DF schemes.

In orthogonal frequency division multiplexing (OFDM) system, blind estimator was proposed which can obtain high bandwidth efficiently. There is a serious ambiguity problem in blind data detector structure. Solution methods can divide into three cases: pilot signal, superimposed training, and channel coding. In order to achieve totally blind estimate, we use channel coding to solve ambiguity in this thesis. In previous study, it had been use low-density-parity-check code (LDPC) to solve ambiguity, and proposed an encoding method to avoid ambiguity for BPSK. However, we consider generic linear block code (LBC) and want to extend BPSK modulation to higher modulation scheme, including QPSK, 16QAM, and 64QAM. For any constellation follows grey coding, we induct a difference of inner product for ambiguity and derive some sufficient conditions for LBC. If LBC satisfy some conditions, then it could avoid ambiguity between valid code words and it can achieve totally blind estimate. In simulation section, for data estimate, we respectively use two LBC cases, which exist ambiguity or not. In order to be fair, we insert a pilot to solve ambiguity in LBC, which exist ambiguity. In simulation results, the performance of two cases is similar in high signal to noise ratio (SNR). In other words, if we use proper channel code which it satisfy sufficient conditions, then we can increase bandwidth efficiently.