Information-theoretic Studies and Capacity Bounds: Group Network Codes and Energy Harvesting Communication Systems

Network information theory and channels with memory are two important but difficult frontiers of information theory. In this two-parted dissertation, we study these two areas, each comprising one part. For the first area we study the so-called entropy vectors via finite group theory, and the network codes constructed from finite groups. In particular, we identify the smallest finite group that violates the Ingleton inequality, an inequality respected by all linear network codes, but not satisfied by all entropy vectors. Based on the analysis of this group we generalize it to several families of Ingleton-violating groups, which may be used to design good network codes. Regarding that aspect, we study the network codes constructed with finite groups, and especially show that linear network codes are embedded in the group network codes constructed with these Ingleton-violating families. Furthermore, such codes are strictly more powerful than linear network codes, as they are able to violate the Ingleton inequality while linear network codes cannot. For the second area, we study the impact of memory to the channel capacity through a novel communication system: the energy harvesting channel. Different from traditional communication systems, the transmitter of an energy harvesting channel is powered by an exogenous energy harvesting device and a finite-sized battery. As a consequence, each time the system can only transmit a symbol whose energy consumption is no more than the energy currently available. This new type of power supply introduces an unprecedented input constraint for the channel, which is random, instantaneous, and has memory. Furthermore, naturally, the energy harvesting process is observed causally at the transmitter, but no such information is provided to the receiver. Both of these features pose great challenges for the analysis of the channel capacity. In this work we use techniques from channels with side information, and finite state channels, to obtain lower and upper bounds of the energy harvesting channel. In particular, we study the stationarity and ergodicity conditions of a surrogate channel to compute and optimize the achievable rates for the original channel. In addition, for practical code design of the system we study the pairwise error probabilities of the input sequences.

Métodos espectronodais para cálculos de transporte de partículas neutras com fonte fixa na formulação de ordenadas discretas e multigrupo de energia

Um método espectronodal é desenvolvido para problemas de transporte de partículas neutras de fonte fixa, multigrupo de energia em geometria cartesiana na formulação de ordenadas discretas (SN). Para geometria unidimensional o método espectronodal multigrupo denomina-se método spectral Greens function (SGF) com o esquema de inversão nodal (NBI) que converge solução numérica para problemas SN multigrupo em geometria unidimensional, que são completamente livre de erros de truncamento espacial para ordem L de anisotropia de espalhamento desde que L < N. Para geometria X; Y o método espectronodal multigrupo baseia-se em integrações transversais das equações SN no interior dos nodos de discretização espacial, separadamente nas direções coordenadas x e y. Já que os termos de fuga transversal são aproximados por constantes, o método nodal resultante denomina-se SGF-constant nodal (SGF-CN), que é aplicado a problemas SN multigrupo de fonte fixa em geometria X; Y com espalhamento isotrópico. Resultados numéricos são apresentados para ilustrar a eficiência dos códigos SGF e SGF-CN e a precisão das soluções numéricas convergidas em cálculos de malha grossa.