Daniel J. Jakubisin

Iterative joint detection, decoding, and synchronization with a focus on frame timing

The concept of an iterative receiver has gained attention as a means of performing reliable synchronization, especially at the low signal-to-noise ratios enabled by error correction codes. In this paper, we consider joint detection of the information bits and estimation of the channel gain, carrier phase, symbol timing, frame timing, and noise power. Our particular focus is on the frame timing where we evaluate the complexity of the iterative receiver by characterizing the frame offset distribution. A method for dynamically choosing the set of frame offsets processed by the iterative receiver is presented. The receiver utilizes the expectation-maximization algorithm to perform estimation and the sum-product algorithm to perform soft demodulation and decoding. Numerical results are presented to characterize the frame offset distribution and to demonstrate the receivers performance.

Approximate joint MAP detection of co-channel signals

Detection of co-channel signals is important as wireless communication systems become increasingly dense. A particularly challenging case is single antenna reception in both the presence of inter-symbol interference and co-channel interference. Optimal joint maximum a posteriori probability (MAP) detection of the co-channel signals is prohibitively complex. Therefore, in this paper, we propose a factor graph-based iterative receiver which approximates joint MAP detection. In the receiver, noise is modeled with a Gaussian mixture distribution since studies have shown that the noise affecting wireless communication systems is often impulsive. Furthermore, the parameters of the factor graph model (channel and noise parameters) are iteratively estimated within the receiver. The proposed receiver is shown to the outperform state-of-the-art receiver algorithms while having a lower complexity in both Gaussian and impulsive noise. We also show significant gains from iterative parameter estimation, especially in non-Gaussian noise.

Performance, Complexity, and Receiver Design for Code-Aided Frame Synchronization in Multipath Channels

Next generation wireless communications systems are pushing the limits of both energy efficiency and spectral efficiency. This presents a challenge at the receiver when it comes to accomplishing tasks such as synchronization, channel estimation, and equalization and has motivated the development of code-aided iterative receiver algorithms in the technical literature. In this paper, we focus on the task of frame synchronization. While previous work has predominately assumed an additive white Gaussian noise channel, we develop code-aided frame synchronization algorithms for multipath channels. An iterative receiver is presented which integrates frame synchronization with iterative channel estimation, equalization, demodulation, and decoding. The receiver design includes a novel frame pre-processing stage to reduce the complexity of the proposed receiver. The complexity and performance of the proposed receiver is compared with that of a receiver based on conventional synchronization. The results demonstrate that the proposed receiver is capable of achieving a gain of up to 3 dB while increasing complexity by only 20%.

Approximate Joint MAP Detection of Co-Channel Signals in Non-Gaussian Noise

We consider joint detection of co-channel signals---specifically, signals which do not possess a natural separability due to, for example, the multiple access technique or the use of multiple antennas. Iterative joint detection and decoding is a well known approach for utilizing the error correction code to improve detection performance. However, the joint maximum a posteriori probability (MAP) detector may be prohibitively complex, especially in a multipath channel. In this paper, we present an approximation to the joint MAP detector motivated by a factor graph model of the received signal. The proposed algorithm is designed to approximate the joint MAP detector as closely as possible within the computational capability of the receiver.

On the complexity-performance trade-off in code-aided frame synchronization

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.

Feasibility Study of Outdoor Wireless Communication in the 60 GHz Band

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.

Improved modulation classification using a factor-graph-based iterative receiver

We bring together two research topics which have been the focus of significant research individually: modulation classification and iterative receiver design. In this work, these topics are joined within the framework of factor graphs which provide a unified approach to representing a variety of algorithms, especially iterative algorithms. Specifically, in this paper we present a factor graph which incorporates modulation classification into the iterative receiver structure. The proposed iterative receiver applies message passing on the factor graph to approximate the optimal solution to joint modulation classification, demodulation, and decoding. This results in a classifier which treats feedback from the decoder as a priori probabilities for the coded bits. We show that the proposed receiver is able to achieve significant performance gains over a receiver which performs maximum likelihood classification separately from demodulation and decoding.

BP, MF, and EP for Joint Channel Estimation and Detection of MIMO-OFDM Signals

Receiver algorithms which combine belief propagation (BP) with the mean field (MF) approximation are well-suited for inference of both continuous and discrete random variables. In wireless scenarios involving detection of multiple signals, the standard construction of the combined BP-MF framework includes the equalization or multi-user detection functions within the MF subgraph. However, the MF approximation is not particularly effective for multi-signal detection. For this reason, we propose a new factor graph construction for application of the BP-MF framework to problems involving the detection of multiple signals. We also developed a low-complexity variation to the proposed construction in which Gaussian BP is applied to detection and expectation propagation links the discrete BP and Gaussian BP subgraphs. The result is a probabilistic receiver architecture with strong theoretical justification which can be applied to multi-signal detection and, in general, detection in the presence of interference.

Asynchronous signal detection in frequency-selective non-Gaussian channels

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.