Electrical and Electronic Engineering - Theses
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ItemEnergy efficient wireless system design( 2015)The demand for telecommunication networks is increasing rapidly. Wireless access is a major contributor to this trend. On the other hand, wireless is considered as a least energy efficient transmission medium mainly due to its unguided nature. The general focus of increasing wireless system energy efficiency is on reduction of the transmit power. However, this strategy may not save energy in short distance communication systems as the processing energy in hardware becomes more significant compared to the transmit radio energy. This thesis focuses on looking at the energy consumption of wireless systems by modeling the energy consumption as a function of several parameters such as receiver SNR, RF bandwidth, information rate, modulation scheme and code rate. We propose energy models for synchronization systems and other digital signal processing modules by considering the computational complexity of the algorithm and the required circuitry. Initially we focus on the synchronization aspects of wireless receivers. We study various algorithms on symbol timing recovery, carrier frequency recovery and carrier phase recovery and compare the performance in order to identify the suitable algorithms to operate at different SNR regions. We then develop energy models for those synchronization sub-systems by analyzing the computational complexity of circuitries based on a number of arithmetic, logic and memory operations. We define a new metric - energy consumption to achieve a given performance as a function of SNR - in order to compare the energy efficiency of different estimation algorithms. Next, we investigate the energy-efficiency trade-offs of a point-to-point wireless system by developing energy models of both the transmitter and receiver that include practical aspects such as error control coding, synchronization and channel equalization. In our system, a multipath Rayleigh-fading channel model and a low-density parity check (LDPC) coding scheme are chosen. We then develop a closed-form approximation for the total energy consumption as a function of receiver SNR and use it to find a minimum-energy transmission configuration. The results reveal that low SNR operation (i.e. low transmit power) is not always the most energy efficient strategy, especially in short distance communication. We present an optimal-SNR concept which can save a significant amount of energy mainly in short-range transmission systems. We then focus on cooperative relay systems. We investigate the energy efficiency trade-offs of single--relay networks by developing energy models for two relay strategies: amplify-and-forward (AF) and detect-and-forward (DF). We then optimize the location and power allocation of the relay to minimize the total energy consumption. The optimum location is found in two-dimensional space for constrained and unconstrained scenarios. We then optimize the total energy consumption over the spectral efficiency and derive expressions for the optimal spectral efficiency values. We use numerical simulations to verify our results. Finally, we focus on energy efficiency of multi-relay systems by considering a dual-relay cooperative system using DF protocol with full diversity. We propose a location-and-power-optimization approach for the relays to minimize the transmit radio energy. We then minimize the total system energy from spectral efficiency perspective for two scenarios: throughput-constrained and bandwidth-constrained configurations. Our proposed approach reduces the transmit energy consumption compared to an equal-power allocated and equidistant-located relay system. Finally, we present an optimal transmission scheme as a function of distance by considering single-hop and multi-hop schemes. The overall results imply that more relays are required as the transmission distance increases in order to maintain a higher energy efficiency.
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ItemFundamental energy requirements of information processing and transmission( 2015)This thesis investigates fundamental limits on the energy required to process and transmit information. By combining physical laws, such as the second law of thermodynamics, with information theory, we present novel limits on the efficiency of systems that track objects, perform stochastic control, switch communication systems and communicate information. This approach yields results that apply regardless of how the system is constructed. While the energy required to perform an ideal measurement of a static state has no known lower bound, this thesis demonstrates that this is not true for noisy measurements or if the state is evolving stochastically. We derive new lower bounds on the energy required to perform such tracking tasks, including Kalman filtering. The goal of stochastic control is usually to reduce the entropy of the controlled system. This is also the task of a Maxwell demon, a thought experiment in which a device or being reduces the thermodynamic entropy of a closed system, violating the second law of thermodynamics. We demonstrate that the same arguments that `exorcise' Maxwell's demon can be used to find lower bounds on the energy consumption of stochastic controllers. We show that the configuration of a switching system in communications, that directs input signals to the desired outputs, can be used to store information. Reconfiguring the switch therefore erases information, and must have an energy cost of at least $k_B T \ln(2)$ per bit due to Landauer's principle. We then calculate lower bounds on the energy required to perform finite-time switching in a one-input, two-output MEMS (microelectromechanical system) mirror switch subject to Brownian motion, demonstrating that the shape of the potential that the switch is subject to affects both the steady-state noise and the energy required to change the configuration. Finally, by modifying Feynman's ratchet and pawl heat engine in order to perform communication instead of doing work, we investigate the efficiency of communication systems that operate solely using the temperature difference between two thermal reservoirs. The lower bound for the energy consumption of any communication system operating between two thermal reservoirs, with no channel noise and using equiprobable partitions of heat energy taken from these reservoirs, is found to be $\frac{T_H T_C}{T_H-T_C} k_B \ln(2)$, where $T_H$ and $T_C$ are the temperatures of the hot and cold reservoir, and $k_B$ is Boltzmann's constant.