Contributions On Theory And Practice For Multi-Mission Wireless Systems

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\u27s non-naive frequency division. The achievable region is shown to be equivalent to that of Costa\u27s 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 \u27staircase-climbing\u27 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

On the Corner Points of the Capacity Region of a Two-User Gaussian Interference Channel

This work considers the corner points of the capacity region of a two-user Gaussian interference channel (GIC). In a two-user GIC, the rate pairs where one user transmits its data at the single-user capacity (without interference), and the other at the largest rate for which reliable communication is still possible are called corner points. This paper relies on existing outer bounds on the capacity region of a two-user GIC that are used to derive informative bounds on the corner points of the capacity region. The new bounds refer to a weak two-user GIC (i.e., when both cross-link gains in standard form are positive and below 1), and a refinement of these bounds is obtained for the case where the transmission rate of one user is within $\varepsilon > 0$ of the single-user capacity. The bounds on the corner points are asymptotically tight as the transmitted powers tend to infinity, and they are also useful for the case of moderate SNR and INR. Upper and lower bounds on the gap (denoted by $\Delta$) between the sum-rate and the maximal achievable total rate at the two corner points are derived. This is followed by an asymptotic analysis analogous to the study of the generalized degrees of freedom (where the SNR and INR scalings are coupled such that $\frac{\log(\text{INR})}{\log(\text{SNR})} = \alpha \geq 0$), leading to an asymptotic characterization of this gap which is exact for the whole range of $\alpha$. The upper and lower bounds on $\Delta$ are asymptotically tight in the sense that they achieve the exact asymptotic characterization. Improved bounds on $\Delta$ are derived for finite SNR and INR, and their improved tightness is exemplified numerically.Comment: Submitted to the IEEE Trans. on Information Theory in July 17, 2014, and revised in April 5, 2015. Presented in part at Allerton 2013, and also presented in part with improved results at ISIT 201

Capacity Regions and Sum-Rate Capacities of Vector Gaussian Interference Channels

The capacity regions of vector, or multiple-input multiple-output, Gaussian interference channels are established for very strong interference and aligned strong interference. Furthermore, the sum-rate capacities are established for Z interference, noisy interference, and mixed (aligned weak/intermediate and aligned strong) interference. These results generalize known results for scalar Gaussian interference channels.Comment: 33 pages, 1 figure, submitted to IEEE trans. on Information theor

Coordination and Bargaining over the Gaussian Interference Channel

This work considers coordination and bargaining between two selfish users over a Gaussian interference channel using game theory. The usual information theoretic approach assumes full cooperation among users for codebook and rate selection. In the scenario investigated here, each selfish user is willing to coordinate its actions only when an incentive exists and benefits of cooperation are fairly allocated. To improve communication rates, the two users are allowed to negotiate for the use of a simple Han-Kobayashi type scheme with fixed power split and conditions for which users have incentives to cooperate are identified. The Nash bargaining solution (NBS) is used as a tool to get fair information rates. The operating point is obtained as a result of an optimization problem and compared with a TDM-based one in the literature.Comment: 5 pages, 4 figures, to appear in Proceedings of IEEE ISIT201

A Game-Theoretic View of the Interference Channel: Impact of Coordination and Bargaining

This work considers coordination and bargaining between two selfish users over a Gaussian interference channel. The usual information theoretic approach assumes full cooperation among users for codebook and rate selection. In the scenario investigated here, each user is willing to coordinate its actions only when an incentive exists and benefits of cooperation are fairly allocated. The users are first allowed to negotiate for the use of a simple Han-Kobayashi type scheme with fixed power split. Conditions for which users have incentives to cooperate are identified. Then, two different approaches are used to solve the associated bargaining problem. First, the Nash Bargaining Solution (NBS) is used as a tool to get fair information rates and the operating point is obtained as a result of an optimization problem. Next, a dynamic alternating-offer bargaining game (AOBG) from bargaining theory is introduced to model the bargaining process and the rates resulting from negotiation are characterized. The relationship between the NBS and the equilibrium outcome of the AOBG is studied and factors that may affect the bargaining outcome are discussed. Finally, under certain high signal-to-noise ratio regimes, the bargaining problem for the generalized degrees of freedom is studied.Comment: 43 pages, 11 figures, to appear on Special Issue of the IEEE Transactions on Information Theory on Interference Networks, 201