Thesis (M.S. in Information Systems and Operations)--Naval Postgraduate School, December 2008. / Thesis Advisor(s): Bordetsky, Alex. "December 2008." Description based on title screen as viewed on January 29, 2009. Includes bibliographical references (p. 83-86). Also available in print.

Thesis (Ph. D.) University of Missouri-Columbia, 2006. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on August 3, 2007) Vita. Includes bibliographical references.

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In network information theory, the relay channel models a communication scenario where there is one or more relay nodes that can help the information transmission between the source and the destination. Although the capacity of the relay channel is still unknown even in the single-relay case, two fundamentally different relay schemes have been developed by (Cover and El Gamal, 1979) for such channels, which, depending on whether the relay decodes the information or not, are generally known as Decode-and-Forward (D-F) and Compress-and-Forward (C-F). In the D-F relay scheme, the relay first decodes the message sent by the source and then forwards it to the destination, and the destination decodes the message taking into account the inputs of both the source and the relay. In contrast, the C-F relay scheme is used when the relay cannot decode the message sent by the source, but still can help by compressing its observation into some compressed version, and forwarding this compression into the destination; the destination then either successively or jointly decodes the compression of the relay's observation and the original message of the source. For the single-relay case, it is known that joint compression-message decoding, although providing more freedom in choosing the compression at the relay, cannot achieve higher rates for the original message than successive decoding. This thesis addresses some fundamental issues in generalizing and unifying the above D-F and C-F relay schemes to the multiple-relay case. We first generalize the C-F scheme to multiple-relay channels, and investigate the question of whether compression-message joint decoding can improve the achievable rate compared to successive decoding in the multiple-relay case. It is demonstrated that in the case of multiple relays, there is no improvement on the achievable rate by joint decoding either. More interestingly, it is discovered that any compressions not supporting successive decoding will actually lead to strictly lower achievable rates for the original message. Therefore, to maximize the achievable rate for the original message, the compressions should always be chosen to support successive decoding. Furthermore, it is shown that any compressions not completely decodable even with joint decoding will not provide any contribution to the decoding of the original message. We also develop a new C-F relay scheme with block-by-block backward decoding. This new scheme improves the original C-F relay scheme to achieve higher rates in the multiple-relay case as the recently proposed noisy network coding scheme. However, compared to noisy network coding which uses repetitive encoding/all blocks united decoding, our new coding scheme is not only simpler, but also reveals the essential reason for the improvement of the achievable rate, that is, delayed decoding until all the blocks have been finished. Finally, to allow each relay node the freedom of choosing either the D-F or C-F relay strategy, we propose a unified relay framework, where both the D-F and C-F strategies can be employed simultaneously in the network. This framework employs nested blocks combined with backward decoding to allow for the full incorporation of the best known D-F and C-F relay strategies. The achievable rates under our unified relay framework are found to combine both the best known D-F and C-F achievable rates and include them as special cases. It is also demonstrated through a Gaussian network example that our achievable rates are generally better than the rates obtained with existing unified schemes and with D-F or C-F alone.

Smart phones and tablet computers have greatly boosted the demand for services via wireless access points, keeping constant pressure on the network providers to deliver vast amounts of data over the wireless infrastructure. To enlarge coverage and enhance throughput, relaying has been adopted in the new generation of wireless communication systems, such as in the Long-Term Evolution Advanced standard,  and will continue to play an important role in the next generation wireless infrastructure. Depending on functionality, relaying can be characterizing into three main categories: amplify-and-forward (AF), compression-and-forward (CF), and decode-and-forward (DF).  In this thesis, we investigate different cooperative strategies in wireless networks when relaying is in use. We first investigate  the capacity outer and inner bounds for a wireless multicast relay network where two sources, connected by error-free backhaul, multicast to two destinations with the help of a full-duplex relay node.  For high-rate backhaul scenarios, we find the exact cut-set bound of the capacity region by extending the proof of the converse for the Gaussian relay channel. For low-rate backhaul scenarios, we present two genie-aided outer bounds by extending the previous proof and introducing two lemmas on conditional (co-)variance. Our inner bounds are derived from various cooperative strategies by combining DF/CF/AF relaying with network coding schemes. We also extend the noisy network coding scheme and the short-message noisy network coding approach to correlated sources. For low-rate backhaul, we propose a new coding scheme, partial-decode-and-forward based linear network coding. We derive the achievable rate regions  for these schemes and measure the performance in term of achievable rates over Gaussian channels. By numerical investigation we observe significant gains over benchmark schemes and demonstrate that the gap between upper and lower bounds is in general not large. We also show that for high-rate backhaul, the cut-set bound can be achieved  when the signal-to-noise ratios lie in the sphere defined by the source-relay and relay-destination channel gains. For wireless networks with independent noise, we propose a simple framework to get capacity outer and inner bounds based on the ``one-shot'' bounding models. We first extend the models for two-user broadcast channels to many-user scenarios and then establish the gap between upper and lower bounding models. For networks with coupled links, we propose  a channel decoupling method which can decompose the network into overlapping multiple-access channels and broadcast channels.  We then apply the one-shot models and create an upper bounding network with only  bit-pipe connections. When developing the lower bounding network, we propose a  two-step update of these models for each coupled broadcast and multiple-access channels. We demonstrate by some examples that the resulting upper bound is in general very good and the gap between the upper and lower bounds is usually not large. For relay-aided downlink scenarios, we propose a cooperation scheme by cancelling interference at the transmitter. It is indeed a symbol-by-symbol approach to one-dimension dirty paper coding (DPC). For finite-alphabet signaling and interference, we derive the optimal (in terms of maximum mutual information) modulator under a given power constraint. A sub-optimal modulator is also proposed by formulating an optimization problem that maximizes the minimum distance of the signal constellation, and this non-convex optimization problem is approximately solved by semi-definite relaxation.  Bit-level simulation shows that the optimal and sub-optimal modulators can achieve significant gains over the Tomlinson-Harashima precoder (THP) benchmark and over non-DPC reference schemes, especially when the power of the interference is larger than the power of the noise. / <p>QC 20121015</p>

Despite much research on the throughput of relaying networks under idealized interference models, many practical wireless networks rely on physical-layer protocols that preclude the concurrent reception of multiple transmissions. In this work, we develop analytical frameworks for the uplink of a multi-source single-channel relay-aided wireless system where transmissions are scheduled to avoid collisions. We study amplify-and-forward and decode-and-forward strategies, in both time-sharing and network-coded variants, and provide mathematical models to investigate their achievable rate regions. Both general and optimal power allocations are considered. We also find the cut-set outer bounds for the rate regions. Moreover, we present a comparison between these methods with the simple time sharing scheme. Our numerical results reveal that optimizing power allocation favors the time sharing scheme significantly more than it does the relaying schemes. The proposed analysis provides means to quantitatively evaluate the efficacy of relaying under the collision model, leading to pragmatic design guidelines.

Despite much research on the throughput of relaying networks under idealized interference models, many practical wireless networks rely on physical-layer protocols that preclude the concurrent reception of multiple transmissions. In this work, we develop analytical frameworks for the uplink of a multi-source single-channel relay-aided wireless system where transmissions are scheduled to avoid collisions. We study amplify-and-forward and decode-and-forward strategies, in both time-sharing and network-coded variants, and provide mathematical models to investigate their achievable rate regions. Both general and optimal power allocations are considered. We also find the cut-set outer bounds for the rate regions. Moreover, we present a comparison between these methods with the simple time sharing scheme. Our numerical results reveal that optimizing power allocation favors the time sharing scheme significantly more than it does the relaying schemes. The proposed analysis provides means to quantitatively evaluate the efficacy of relaying under the collision model, leading to pragmatic design guidelines.

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An Information Theoretic approach is used for studying the effect of noise on various spiking neural systems. Detailed statistical analyses of neural behaviour under the influence of stochasticity are carried out and their results related to other work and also biological neural networks. The neurocomputational capabilities of the neural systems under study are put on an absolute scale. This approach was also used in order to develop an optimisation framework. A proof-of-concept algorithm is designed, based on information theory and the coding fraction, which optimises noise through maximising information throughput. The algorithm is applied with success to a single neuron and then generalised to an entire neural population with various structural characteristics (feedforward, lateral, recurrent connections). It is shown that there are certain positive and persistent phenomena due to noise in spiking neural networks and that these phenomena can be observed even under simplified conditions and therefore exploited. The transition is made from detailed and computationally expensive tools to efficient approximations. These phenomena are shown to be persistent and exploitable under a variety of circumstances. The results of this work provide evidence that noise can be optimised online in both single neurons and neural populations of varying structures.