Date of Award

August 2016

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Electrical Engineering and Computer Science

Advisor(s)

Biao Chen

Subject Categories

Engineering

Abstract

The field of wireless systems has long been an active research area with various applications. Recently much attention has been given to multi-mission wireless systems that combine capabilities including information sensing, data processing, energy harvesting as well as the traditional data communication. This dissertation describes our endeavor in addressing some of the research challenges in multi-mission wireless systems, including the development of fundamental limits of such multi-mission wireless systems and effective technologies for improved performance.

The first challenge addressed in this dissertation is how to handle interference, which is encountered in almost all wireless systems involving multiple nodes, an attribute shared by most multi-mission systems. To deepen our understanding on the impact of interference, we study a class of Gaussian interference channels (GICs) with mixed interference. A simple coding scheme is proposed based on Sato's non-naive frequency division. The achievable region is shown to be equivalent to that of Costa's noiseberg region for the one-sided Gaussian interference channel. This allows for an indirect proof that this simple achievable rate region is indeed equivalent to the Han-Kobayashi (HK) region with Gaussian input and with time sharing for this class of Gaussian interference channels with mixed interference.

Optimal power management strategies are then investigated for a remote estimation system with an energy harvesting sensor. We first establish the asymptotic optimality of uncoded transmission for such a system under Gaussian assumption. With the aim of minimizing the mean squared error (MSE) at the receiver, optimal power allocation policies are proposed under various assumptions with regard to the knowledge at the transmitter and the receiver as well as battery storage capacity. For the case where non-causal side information (SI) of future harvested energy is available and battery storage is unlimited, it is shown that the optimal power allocation amounts to a simple 'staircase-climbing' procedure, where the power level follows a non-decreasing staircase function. For the case where battery storage has a finite capacity, the optimal power allocation policy can also be obtained via standard convex optimization techniques. Dynamic programming is used to optimize the allocation policy when causal SI is available. The issue of unknown transmit power at the receiver is also addressed. Finally, to make the proposed solutions practically more meaningful, two heuristic schemes are proposed to reduce computational complexity.

Related to the above remote sensing problem, we provide an information theoretic formulation of a multi-functioning radio where communication between nodes involves transmission of both messages and source sequences. The objective is to study the optimal coding trade-off between the rate for message transmission and the distortion for source sequence estimation. For point-to-point systems, it is optimal to simply split total capacity into two components, one for message transmission and one for source transmission. For the multi-user case, we show that such separation-based scheme leads to a strictly suboptimal rate-distortion trade-off by examining the simple problem of sending a common source sequence and two independent messages through a Gaussian broadcast channel.

Finally we study the design of a practical multi-mission wireless system - the dual-use of airborne radio frequency (RF) systems. Specifically, airborne multiple-input-multiple-output (MIMO) communication systems are leveraged for the detection of moving targets in a typical airborne environment that is characterized by the lack of scatterers. With uniform linear arrays (ULAs), angular domain decomposition of channel matrices is utilized and target detection can be accomplished by detection of change in the resolvable paths in the angular domain. For both linear and nonlinear arrays, Doppler frequency analysis can also be applied and the change in frequency components indicates the presence of potential airborne targets. Nonparametric detection of distribution changes is utilized in both approaches.

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Open Access

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