Cross-layer schemes for performance optimization in wireless networks

Wireless networks are undergoing rapid progress and inspiring numerous applications. As the application of wireless networks becomes broader, they are expected to not only provide ubiquitous connectivity, but also support end users with certain service guarantees. End-to-end delay is an important Quality of Service (QoS) metric in multihop wireless networks. This dissertation addresses how to minimize end-to-end delay through joint optimization of network layer routing and link layer scheduling. Two cross-layer schemes, a loosely coupled cross-layer scheme and a tightly coupled cross-layer scheme, are proposed. The two cross-layer schemes involve interference modeling in multihop wireless networks with omnidirectional antenna. In addition, based on the interference model, multicast schedules are optimized to minimize the total end-to-end delay. Throughput is another important QoS metric in wireless networks. This dissertation addresses how to leverage the spatial multiplexing function of MIMO links to improve wireless network throughput. Wireless interference modeling of a half-duplex MIMO node is presented. Based on the interference model, routing, spatial multiplexing, and scheduling are jointly considered in one optimization model. The throughput optimization problem is first addressed in constant bit rate networks and then in variable bit rate networks. In a variable data rate network, transmitters can use adaptive coding and modulation schemes to change their data rates so that the data rates are supported by the Signal to Noise and Interference Ratio (SINR). The problem of achieving maximum throughput in a millimeter-wave wireless personal area network is studied --Abstract, page iv

Experimental analysis of power control and element spacing for unobtrusive MIMO antenna systems

With ever-increasing demand for wireless communications, spectral efficiency and power management are of great importance. Mobile nodes in an ad hoc network are limited by the available power, interference, and shared communication resources. Research shows that multiple-input multiple-output (MIMO) communication systems can increase capacity and mitigate interference by exploiting the multi-path nature of wireless energy. This increase in capacity is realized with an array of antennas that can transmit multiple uncorrelated streams. In order to achieve theoretical gains in capacity, several practical problems must be considered. This dissertation presents solutions to create higher quality communication systems in MIMO ad hoc networks through power management, antenna array spacing, and unobtrusive conductive polymer antennas.To show how co-channel interference can be managed in ad hoc networks, the experimental performance of several power control methods are demonstrated. These experiments were made with a multiple antenna software defined radio (SDR) testbed and verified with electro-magnetic ray tracing. In addition, the spacing between antenna array elements directly impacts the wireless channel. An analysis of the wireless channel is presented to show the impact of the antenna spacing and cochannel interference on the network capacity. A method for selecting the best antenna spacing is also described based upon the channel analysis. Finally, due to the size of mobile devices, it is difficult to incorporate MIMO systems into small form factors. A transparent, conformal antenna array was fabricated to demonstrate that antennas can be developed to fit into small form factors and perform at a high level.Ph.D., Electrical Engineering -- Drexel University, 200

Computation of Approximate Welfare-Maximizing Correlated Equilibria and Pareto-Optima with Applications to Wireless Communication

In a wireless application with multiple communication links, the data rate of each link is subject to degradation due to transmitting interference from other links. A competitive wireless game then arises as each link acts as a player maximizing its own data rate. The game outcome can be evaluated using the solution concept of game equilibria. However, when significant interference among the links arises, uniqueness of equilibrium is not guaranteed. To select among multiple equilibria, the sum of network rate or social welfare is used as the selection criterion. This thesis aims to offer the theoretical foundation and the computational tool for determining approximate correlated equilibria with global maximum expected social welfare in polynomial games. Using sum of utilities as the global objective, we give two theoretical and two wireless-specific contributions. 1. We give a problem formulation for computing near-exact ε -correlated equilibria with highest possible expected social welfare. We then give a sequential Semidefinite Programming (SDP) algorithm that computes the solution. The solution consists of bounds information on the social welfare. 2. We give a novel reformulation to arrive at a leaner problem for computing near-exact ε -correlated equilibria using Kantorovich polynomials with sparsity. 3. Forgoing near-exactness, we consider approximate correlated equilibria. To account for the loss in precision, we introduce the notion of regret. We give theoretical bounds on the regrets at any iteration of the sequential SDP algorithm. Moreover, we give a heuristic procedure for extracting a discrete probability distribution. Subject to players’ acceptance of the regrets, the computed distributions can be used to implement central arbitrators to facilitate real-life implementation of the correlated equilibrium concept. 4. We demonstrate how to compute Pareto-optimal solutions by dropping the correlated equilibria constraints. For demonstration purpose, we focus only on Pareto-optima with equal weights among the players