Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

It is shown that, particularly for terrestrial cellular telephony, the interference-suppression feature of CDMA (code division multiple access) can result in a many-fold increase in capacity over analog and even over competing digital techniques. A single-cell system, such as a hubbed satellite network, is addressed, and the basic expression for capacity is developed. The corresponding expressions for a multiple-cell system are derived. and the distribution on the number of users supportable per cell is determined. It is concluded that properly augmented and power-controlled multiple-cell CDMA promises a quantum increase in current cellular capacity. >

On the capacity of a cellular CDMA system

Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified by the definition of a cognitive radio as an intelligent wireless communication device that exploits side information about its environment to improve spectrum utilization. This side information typically comprises knowledge about the activity, channels, codebooks, and/or messages of other nodes with which the cognitive node shares the spectrum. Based on the nature of the available side information as well as a priori rules about spectrum usage, cognitive radio systems seek to underlay, overlay, or interweave the cognitive radios' signals with the transmissions of noncognitive nodes. We provide a comprehensive summary of the known capacity characterizations in terms of upper and lower bounds for each of these three approaches. The increase in system degrees of freedom obtained through cognitive radios is also illuminated. This information-theoretic survey provides guidelines for the spectral efficiency gains possible through cognitive radios, as well as practical design ideas to mitigate the coexistence challenges in today's crowded spectrum.

Breaking Spectrum Gridlock With Cognitive Radios: An Information Theoretic Perspective

Information Theory and Reliable Communication

Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

http://ieeexplore.ieee.org/iel5/5/31307/01456462.pdf

Linear systems

Vehicular wireless channels have a high degree of variability, presenting a challenge for vehicles and infrastructure to remain connected. The emergence of the white space bands for data usage enables increased flexibility for vehicular networks with distinct propagation characteristics across frequency bands from 450 MHz to 6 GHz. Since wireless propagation largely depends on the environment in operation, a historical understanding of the frequency bands' performance in a given environment could expedite band selection as vehicles transition across diverse scenarios. In this paper, we leverage knowledge of in-situ operation across frequency bands with real-time measurements of the activity level to select the the band with the highest throughput. To do so, we perform a number of experiments in typical vehicular topologies. With two models based on machine learning algorithms and an in-situ training set, we predict the throughput based on: (i.) prior performance for similar context information (e.g., SNR, GPS, relative speed, and link distance), and (ii.) real-time activity level and relative channel quality per band. In the field, we show that training on a repeatable route with these machine learning techniques can yield vast performance improvements from prior schemes.

/pdf/leveraging-diverse-propagation-and-context-for-multi-modal-1fufpc948x.pdf

Leveraging diverse propagation and context for multi-modal vehicular applications

The packet outage probability for fading channels can be significantly reduced by exploiting queuing delay and transmitter channel information is demonstrated in this paper. Queuing delay gain is conceptually similar to delay diversity, but at a packet time-scale instead of symbol time-scale. First, a lower bound on outage probability assuming full channel state information at the transmitter (CSIT) is computed and then simple outage minimizing transmission policies which adapt the rate and power of the transmitted signal based jointly on buffer occupancy and channel conditions is constructed . We demonstrate that the rate of decrease of outage with increasing transmitter channel information is higher for larger delays. We also address the closely coupled problem of designing a practical feedback channel which supplies the CSIT.

/pdf/outage-behavior-with-delay-and-csit-4bbfe3724p.pdf

Outage behavior with delay and CSIT

The current and future wireless systems need to support a multitude of services with a wide range of data rates and reliability requirements. The limited battery resource at a mobile terminal coupled with the hostile multipath fading channel makes the problem of providing reliable high data rate services challenging. In this thesis we develop a new framework for the design of power efficient transmission mechanisms that support multimedia traffic having different delay constraints. First, we present optimal design techniques that substantially reduce the transmission power (exceeding 60% in certain cases) for small increases in average communication delays for a single user scenario thereby providing another avenue for mobile devices to save on battery power. The power minimizing schedulers adapt the transmission rate and power based on the queue and channel state. We also construct a variable rate modulation scheme to show the benefits of the proposed formulation in a practical system. Power optimal schedulers with absolute packet delay constraints are also studied and their performance is evaluated via simulations. Second, we design power efficient schedulers that satisfy average delay bounds for multiple users in a broadcast channel. Optimal schedulers that jointly allocate rate and power to the different users based on the different buffer and channel conditions are presented in code-division multiple access (CDMA) and time-division multiple access (TDMA) regimes used commonly in current cellular standards. We show that joint scheduling gains over non-cooperative single user schedulers are largest when the users belong to different delay classes. We also show the superiority of CDMA over TDMA in terms of a larger set of achievable delays and at consistently lower powers. Near optimal low complexity schedulers are introduced in which computational complexity increases gracefully with increasing number of users. We also compute achievable power regions under average delay constraints in a multiple access channel with global and local queue state information. Finally, we develop a framework for designing power limited delay bounded transmission schemes that minimize the outage probability in fading channels with feedback. We explicitly construct schemes that quantitatively demonstrates the outage reduction with increasing delays and amounts of feedback information.

Power efficient transmission policies for multimedia traffic over wireless channels

Structural impairments can be detected by monitoring and analyzing dynamic structural responses. In this paper, accurate dynamic deformations of multiple vibrating structures are estimated using one off-the-shelf CCD (Charge-coupled Device) camera and a novel target configuration and computation algorithm. In this method, a CCD camera, which can be mounted on either an adjacent vibrating structure or stationary support, is used to track global movements of a vibrating structure. The method utilizes subpixel feature extraction, Zhang’s camera calibration-based method, and a novel approach for target configuration which eliminates the need of having a stationary support for the recording camera. Two scaled models of a traffic signal structure were designed and constructed to implement the proposed method in laboratory conditions. The camera is mounted on one of the structures while facing targets on the other structure. The image data from the camera is processed to extract the structural response of both the structures in the field-of-view (FOV) of the camera as well as the structure on which the camera is mounted. Data from strain gages mounted on these structures provide measurement benchmarks for the dynamic structural responses. Experimental results indicate that one CCD camera and the presented method adequately capture displacements with similar accuracy and precision of strain gages. In practice, a camerabased method may be less expensive and more easily installed

Accurate Structural Dynamic Response Monitoring of Multiple Structures using One CCD Camera and a Novel Targets Configuration

While many metropolitan areas sought to deploy city-wide WiFi networks, the densest urban areas were not able to broadly leverage the technology for large-scale Internet access. Ultimately, the small spatial separation required for effective 802.11 links in these areas resulted in prohibitively large up-front costs. The FCC has reapportioned spectrum from TV white spaces for the purposes of large-scale Internet connectivity via wireless topologies of all kinds. The far greater range of these lower carrier frequencies are especially critical in rural areas, where high levels of aggregation could dramatically lower the cost of deployment and is in direct contrast to dense urban areas in which networks are built to maximize spatial reuse. Thus, leveraging a broad range of spectrum across diverse population densities becomes a critical issue for the deployment of data networks with WiFi and white space bands. In this paper, we measure the spectrum utility in the Dallas-Fort Worth metropolitan and surrounding areas and propose a measurement-driven band selection framework, Multiband Access Point Estimation (MAPE). In particular, we study the white space and WiFi bands with in-field spectrum utility measurements, revealing the number of access points required for an area with channels in multiple bands. In doing so, we find that networks with white space bands reduce the number of access points by up to 1650% in sparse rural areas over similar WiFi-only solutions. In more populated rural areas and sparse urban areas, we find an access point reduction of 660% and 412%, respectively. However, due to the heavy use of white space bands in dense urban areas, the cost reductions invert (an increase in required access points of 6%). Finally, we numerically analyze band combinations in typical rural and urban areas and show the critical factor that leads to cost reduction: considering the same total number of channels, as more channels are available in the white space bands, less access points are required for a given area.

/pdf/a-measurement-study-of-white-spaces-across-diverse-6odc01z4gh.pdf

Dinesh Rajan

Papers

Leveraging diverse propagation and context for multi-modal vehicular applications

Outage behavior with delay and CSIT

Power efficient transmission policies for multimedia traffic over wireless channels

Accurate Structural Dynamic Response Monitoring of Multiple Structures using One CCD Camera and a Novel Targets Configuration

A measurement study of white spaces across diverse population densities