E.N. Onggosanusi

Bio: E.N. Onggosanusi is an academic researcher from University of Wisconsin-Madison. The author has contributed to research in topics: Communication channel & Multipath propagation. The author has an hindex of 4, co-authored 10 publications receiving 66 citations.

Canonical space-time processing for wireless communications

Abstract: A canonical space-time characterization of mobile wireless channels is introduced in terms of a fixed basis that is independent of the true channel parameters The basis captures the essential degrees of freedom in the received signal using discrete multipath delays, Doppler shifts, and directions of arrival (DOA). The canonical representation provides a robust representation of the propagation dynamics and eliminates the need for estimating delay, Doppler and DOA parameters of different multipaths, Furthermore, it furnishes a natural framework for designing low-complexity space-time receivers. Single-user receivers based on the canonical channel representation are developed and analyzed, It is demonstrated that the resulting canonical space-time receivers deliver near-optimal performance at substantially reduced complexity compared to existing designs.

A canonical space-time characterization of mobile wireless channels

Abstract: A canonical space-time characterization of mobile wireless channels is introduced in terms of a fixed basis that is independent of the true channel parameters. The basis captures the essential degrees of freedom in the received signal using discrete multipath delays, Doppler shifts, and directions of arrival. This provides a robust representation of the propagation dynamics and dramatically reduces the number of channel parameters to be estimated. The resulting canonical space-time receivers deliver optimal performance at substantially reduced complexity compared to existing designs.

Canonical space-time coordinates for multiuser wireless communications

Abstract: We propose a space-time multiuser detection scheme for wireless communications that projects the received signal onto a fixed set of basis signals. The basis signals are dictated by a canonical characterization of channel propagation dynamics in terms of discrete multipath delays, Doppler shifts, and directions of arrival. They capture the essential degrees of freedom in the received signal. The canonical space-time coordinates induced by the underlying basis provide a natural framework for multi-access interference (MAI) suppression and diversity processing. The signal of the desired user is concentrated in a subset of coordinates, while the interference generally occupies the entire space-time coordinate system. It is demonstrated that MAI suppression can be improved by incorporating a subset of coordinates where the desired user is absent.

Spatio-temporal polarization signaling for multipath spread-spectrum channels

Abstract: A spread-spectrum spatio-temporal signaling scheme based on electric field polarization is proposed. The information symbol is transmitted via two perpendicular transverse electric field components, each with a unique signature sequence. At the receiver, all three electric field components are measured. It is demonstrated that polarization signaling provides another degree of freedom for increasing spatial diversity to improve the performance of the wireless link.

Space-time polarization signaling for wireless communications

Abstract: A polarization-based spread-spectrum spatio-temporal signaling scheme is proposed in this paper for transmitters consisting of an array of vector radiators. Each vector radiator consists of two closely spaced perpendicular antennas and each antenna is assigned a unique signature sequence. At the receiver, all three electric field components of the scattered signal are measured using an array of vector sensors. Each vector sensor consists of three closely spaced perpendicular antennas. The proposed polarization signaling scheme is cast in the framework of a general multiple antenna system. The distinguishing feature of polarization signaling lies within the resulting channel statistics. In particular, polarization signaling can be exploited to achieve diversity gain using less physical space than conventional antenna array approaches. We identify the key parameters controlling system performance and evaluate the relative advantages of polarization signaling under constraints of aperture size and number of antenna elements for given spatial scattering statistics.

Detection, classification, and tracking of targets

Abstract: Networks of small, densely distributed wireless sensor nodes are being envisioned and developed for a variety of applications involving monitoring and the physical world in a tetherless fashion. Typically, each individual node can sense in multiple modalities but has limited communication and computation capabilities. Many challenges must be overcome before the concept of sensor networks In particular, there are two critical problems underlying successful operation of sensor networks: (1) efficient methods for exchanging information between the nodes and (2) collaborative signal processing (CSP) between the nodes to gather useful information about the physical world. This article describes the key ideas behind the CSP algorithms for distributed sensor networks being developed at the University of Wisconsin (UW). We also describe the basic ideas on how the CSP algorithms interface with the networking/routing algorithms being developed at Wisconsin (UW-API). We motivate the framework via the problem of detecting and tracking a single maneuvering target. This example illustrates the essential ideas behind the integration between UW-API and UW-CSP algorithms and also highlights the key aspects of detection and localization algorithms. We then build on these ideas to present our approach to tracking multiple targets that necessarily requires classification techniques becomes a reality.

Detection, Classification and Tracking of Targets in Distributed Sensor Networks

Abstract: We outline a framework for collaborative signal processing in distributed sensor networks. The ideas are presented in the context of tracking multiple moving objects in a sensor field. The key steps involved in the tracking procedure include event detection, target classification, and estimation and prediction of target location. Algorithms for various tasks are discussed with an emphasis on classification. Results based on experiments with real data are reported which provide useful insights into the essential nature of the problems. Issues, challenges and directions for future research are identified.

Space-time coded transmissions within a wireless communication network

Abstract: Techniques are described for space-time block coding for single-carrier block transmissions over frequency selective multipath fading channels Techniques are described that achieve a maximum diversity of order NtNr(L + 1) in rich scattering environments, where Nt(Nr) is the number of transmit (receive) antennas, and L is the order of the finite impulse responde (FIR) channels. The techniques may include parsing a stream of information-bearing symbols to form blocks of K symbols, precoding the symbols to form blocks having J symbols, and collecting consecutive Ns blocks, generating a space-time block coded matrix having Nt rows that are communicated through a wireless communication medium. The receiver complexity is comparable to single antenna transmissions, and the exact Viterbi's algorithm can be applied for maximum-likelihood (ML) optimal decoding.

Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI

Abstract: This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimization criteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed, and their relationship with existing algorithms is indicated. As with other previously proposed solutions, the minimum bit error rate algorithm converges to the open-loop transmission scheme for very poor CSI estimates.

Orthogonal multiple access over time- and frequency-selective channels

Abstract: Suppression of multiuser interference (MUI) and mitigation of time- and frequency-selective (doubly selective) channel effects constitute major challenges in the design of third-generation wireless mobile systems. Relying on a basis expansion model (BEM) for doubly selective channels, we develop a channel-independent block spreading scheme that preserves mutual orthogonality among single-cell users at the receiver. This alleviates the need for complex multiuser detection, and enables separation of the desired user by a simple code-matched channel-independent block despreading scheme that is maximum-likelihood (ML) optimal under the BEM plus white Gaussian noise assumption on the channel. In addition, each user achieves the maximum delay-Doppler diversity for Gaussian distributed BEM coefficients. Issues like links with existing multiuser transceivers, existence, user efficiency, special cases, backward compatibility with direct-sequence code-division multiple access (DS-CDMA), and error control coding, are briefly discussed.