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In this paper, indoor passive localization and tracking using a multiple-input multiple-output (MIMO) radar are studied. Indoor localization suffers from severe multipath propagation. We propose two novel clustering-based algorithms for multi-target tracking in such environments. These techniques aim to exploit either the delay-Doppler diversity offered by spread spectrum signals or the delay-angle diversity of received signals using successive beamforming. The targets are tracked using a bank of extended Kalman filters and the filters' predicted future locations of all targets are intelligently utilized to solve the data association problem. Finally, the feasibility of both techniques is analyzed and discussed in light of two common indoor tracking layouts.

Next generation wireless communication systems are pushing the limits of both energy efficiency and spectral efficiency. This presents a challenge to other functions in the receiver such as frame synchronization. In this paper we examine the trade-off between increased complexity and the improvement in energy and spectral efficiency of code-aided frame synchronization. Parallel and serial approaches to the frame synchronization problem are considered as well as methods for minimizing their complexity. We identify regions over which code-aided frame synchronization improves performance, with respect to a conventional receiver, while maintaining reasonable complexity.

In 2001, the Federal Communications Commission made available a large block of spectrum known as the 60 GHz band. The 60 GHz band is attractive because it provides the opportunity of multi-Gbps data rates with unlicensed commercial use. One of the main challenges facing the use of this band is poor propagation characteristics including high path loss and strong attenuation due to oxygen absorption. Antenna arrays have been proposed as a means of combating these effects. In this paper we study the feasibility of outdoor communication in the 60 GHz band. Because arrays are required for antenna gain and adaptability, we explore the use of arrays as a form of equalization in the presence of channel-induced intersymbol interference. A site-specific study is conducted using ray tracing to model an outdoor environment on the Virginia Tech campus. The performance of outdoor links is evaluated through simulation of the bit error probability.

We present a signal detection algorithm for digital amplitude-phase modulated signals in frequency-selective fading channels with non-Gaussian noise. We consider an asynchronous scenario in which the timing (symbol transition epochs) is unknown and a symbol rate offset is present due to clock drift. A Gibbs sampling-based algorithm is proposed to estimate the unknown parameters and signal detection is performed using a maximum-likelihood procedure. The additive noise is modeled by a Gaussian mixture distribution, a well-known model for man-made and natural noise. Numerical results are presented to characterize the performance of the proposed algorithm.