Modulation Diversity in Fading Channels with Quantized Receiver

In this paper, we address the design of codes which achieve modulation diversity in block fading single-input single-output (SISO) channels with signal quantization at receiver and low-complexity decoding. With an unquantized receiver, coding based on algebraic rotations is known to achieve modulation coding diversity. On the other hand, with a quantized receiver, algebraic rotations may not guarantee diversity. Through analysis, we propose specific rotations which result in the codewords having equidistant component-wise projections. We show that the proposed coding scheme achieves maximum modulation diversity with a low-complexity minimum distance decoder and perfect channel knowledge. Relaxing the perfect channel knowledge assumption we propose a novel training/estimation and receiver control technique to estimate the channel. We show that our coding/training/estimation scheme and minimum distance decoding achieve an error probability performance similar to that achieved with perfect channel knowledge

Constellation Shaping for Communication Channels with Quantized Outputs

Channel capacity is an important aspect of every digital communication system. Capacity can be defined as the highest rate of information that can be transmitted over the channel with low error probability. The purpose of this research is to study the effect of the input symbol distribution on the information rate when the signal is transmitted over an Additive White Gaussian Noise (AWGN) channel with a quantized output. The channel was analyzed by transforming it into a Discrete Memoryless Channel (DMC), which is a discrete-input and discrete-output channel. Given the quantizer resolution and Signal-to-Noise Ratio (SNR), this thesis proposes a strategy for achieving the capacity of a certain shaping technique previously proposed by Le Goff, et al. Under the constraints of the modulation, the shaping technique, and the quantizer resolution, the capacity is found by jointly optimizing the input distribution and quantizer spacing. The optimization is implemented by exhaustively searching over all feasible input distributions and a finely-spaced set of candidate quantizer spacings. The constrained capacity for 16-QAM modulation is found using the proposed technique

Quantum key distribution protocols with high rates and low costs

In the age of information explosion, there is huge amount of information generated every second. Some of the information generated, for example news, is supposed to be shared by public and anyone in the world can get a copy of it. However, sometimes, information is only supposed to be maintain private or only shared by a given group of people. In the latter case, information protection becomes very important. There are various ways to protect information. One of the technical ways is cryptography, which is an area of interest for mathematicians, computer scientists and physicists. As a new area in cryptography, physical layer security has been paid great attention recently. Quantum key distribution is a hot research topic for physical layer security in the two decades. This thesis focuses on two quantum key distribution protocols that can potentially increase the key generation rate and lower the cost. On protocol is based on amplified spontaneous emission as signal source and the other one is based on discretely signaled continuous variable quantum communication. The security analysis and experimental implementation issues for both protocols are discussed.M.S.Committee Chair: Paul Voss; Committee Member: Abdallah Ougazzaden; Committee Member: David Citri

MAP Joint Source-Channel Arithmetic Decoding for Compressed Video

In order to have robust video transmission over error prone telecommunication channels several mechanisms are introduced. These mechanisms try to detect, correct or conceal the errors in the received video stream. In this thesis, the performance of the video codec is improved in terms of error rates without increasing overhead in terms of data bit rate. This is done by exploiting the residual syntactic/semantic redundancy inside compressed video along with optimizing the configuration of the state-of-the art entropy coding, i.e., binary arithmetic coding, and optimizing the quantization of the channel output. The thesis is divided into four phases. In the first phase, a breadth-first suboptimal sequential maximum a posteriori (MAP) decoder is employed for joint source-channel arithmetic decoding of H.264 symbols. The proposed decoder uses not only the intentional redundancy inserted via a forbidden symbol (FS) but also exploits residual redundancy by a syntax checker. In contrast to previous methods this is done as each channel bit is decoded. Simulations using intra prediction modes show improvements in error rates, e.g., syntax element error rate reduction by an order of magnitude for channel SNR of 7.33dB. The cost of this improvement is more computational complexity spent on the syntax checking. In the second phase, the configuration of the FS in the symbol set is studied. The delay probability function, i.e., the probability of the number of bits required to detect an error, is calculated for various FS configurations. The probability of missed error detection is calculated as a figure of merit for optimizing the FS configuration. The simulation results show the effectiveness of the proposed figure of merit, and support the FS configuration in which the FS lies entirely between the other information carrying symbols to be the best. In the third phase, a new method for estimating the a priori probability of particular syntax elements is proposed. This estimation is based on the interdependency among the syntax elements that were previously decoded. This estimation is categorized as either reliable or unreliable. The decoder uses this prior information when they are reliable, otherwise the MAP decoder considers that the syntax elements are equiprobable and in turn uses maximum likelihood (ML) decoding. The reliability detection is carried out using a threshold on the local entropy of syntax elements in the neighboring macroblocks. In the last phase, a new measure to assess performance of the channel quantizer is proposed. This measure is based on the statistics of the rank of true candidate among the sorted list of candidates in the MAP decoder. Simulation results shows that a quantizer designed based on the proposed measure is superior to the quantizers designed based on maximum mutual information and minimum mean square error