Keith M. Chugg

Adaptive soft-input soft-output algorithms for iterative detection with parametric uncertainty

The soft-input soft-output (SISO) module is the basic building block for established iterative detection (ID) algorithms for a system consisting of a network of finite state machines. The problem of performing ID for systems having parametric uncertainty has received relatively little attention in the open literature. Previously proposed adaptive SISO (A-SISO) algorithms are either based on an oversimplified channel model, or have a complexity that grows exponentially with the observation length N (or the smoothing lag D). In this paper, the exact expressions for the soft metrics in the presence of parametric uncertainty modeled as a Gauss-Markov process are derived in a novel way that enables the decoupling of complexity and observation length. Starting from these expressions, a family of suboptimal (practical) algorithms is motivated, based on forward/backward adaptive processing with linear complexity in N. Previously proposed A-SISO algorithms, as well as existing adaptive hard decision algorithms are interpreted as special cases within this framework. Using a representative application-joint iterative equalization-decoding for trellis-based codes over frequency-selective channels-several design options are compared and the impact of parametric uncertainty on previously established results for ID with perfect channel state information is assessed.

Adaptive iterative detection for phase tracking in turbo-coded systems

The problem of performing iterative detection (ID)-a technique originally introduced for the decoding of turbo codes-for systems having parametric uncertainty has received relatively little attention in the open literature. In this paper, the problem of adaptive ID (AID) for serial and parallel concatenated convolutional codes (SCCCs and PCCCs or turbo codes) in the presence of carrier-phase uncertainty is examined. Based on the theoretical framework of Anastasopoulos and Chugg, (see Proc. Int. Conf. Communications, p.177-181, 1999). and Colavolpe, Ferrari and Raheli (see IEEE Trans. Commun., vol.48, p.1488-98, 2000), adaptive soft inverse (ASI) algorithms are developed for two commonly used blocks in turbo codes, leading to the adaptive soft-input soft-output (A-SISO) and the adaptive soft demodulator (A-SODEM) algorithms. Based on these algorithms, practical AID receivers are presented. Several design options are proposed and compared and the impact of parametric uncertainty on previously established results for iterative detection with perfect channel state information (CSI) is assessed.

A theoretical study on the effects of interference UWB multiple access impulse radio

Ultra wide bandwidth impulse radio occupies huge bandwidth from near DC to up to a few GHz. This suggests that many coexisting communication systems working simultaneously at different regions of impulse radios bandwidth cause interference. The effects of an arbitrary external interference as SNR and bit error rate degradation of multiple access UWB radio versus interference frequency is theoretically evaluated and pulse shape design for narrow band interference rejection is presented. Using doublet pulses, it is shown how narrow bandwidth interference is mitigated significantly. Effects of amplitude mismatches and gap time offset from the nominal value in a doublet pulse are investigated.

Remarks on space-time codes including a new lower bound and an improved code

This article presents a new asymptotically exact lower bound on pairwise error probability of a space-time code as well as an example code that outperforms the comparable orthogonal-design-based space-time (ODST) code. Also contained in the article are an exact expression for pairwise error probability (PEP), signal design guidelines, and some observations relating to the reception of ODST codes.

A new approach to rapid PN code acquisition using iterative message passing techniques

Iterative message passing algorithms on graphs, which are generalized from the well-known turbo decoding algorithm, have been studied intensively in recent years because they can provide near-optimal performance and significant complexity reduction. In this paper, we demonstrate that this technique can be applied to pseudorandom code acquisition problems as well. To do this, we represent good pseudonoise (PN) patterns using sparse graphical models, then apply the standard iterative message passing algorithms over these graphs to approximate maximum-likelihood synchronization. Simulation results show that the proposed algorithm achieves better performance than both serial and hybrid search strategies in that it works at low signal-to-noise ratios and is much faster. Compared with full parallel search, this approach typically provides significant complexity reduction.

An algorithm for counting short cycles in bipartite graphs

Let G=(U/spl cup/W, E) be a bipartite graph with disjoint vertex sets U and W, edge set E, and girth g. This correspondence presents an algorithm for counting the number of cycles of length g, g+2, and g+4 incident upon every vertex in U/spl cup/W. The proposed cycle counting algorithm consists of integer matrix operations and its complexity grows as O(gn/sup 3/) where n=max(|U|,|W|).

Further results in likelihood classification of QAM signals

Maximum likelihood decision theory is applied to the problem of classification of quadrature-modulated digital communication signals. Several aspects of the existing low signal-to-noise ratio (SNR) results are extended to the moderate and high SNR environments. An approximate probability density function (PDF) for the single-term approximation to the average log-likelihood-ratio (ALLR) which is valid at all SNR values is presented and its superior accuracy, compared to the low SNR pdf, is verified via computer simulation. Computer simulation is also used to show that multiple-term approximations to the ALLR may provide significant performance gains relative to their individual terms. A simple, practical method for setting the threshold of the ALLR test is presented and it is shown, through simulation, that little performance degradation is suffered relative to the optimal setting, which is difficult to determine analytically in most cases. True signal pre-processing techniques are also presented, and it is demonstrated that their use significantly improves the robustness of the classification algorithms for phase-shift-keying signals in frequency-uncertain environments.<<ETX>>

Barrage Relay Networks

A receiver-oriented perspective on capacity scaling in mobile ad hoc networks (MANETs) suggests that broadcast and multicast may be more natural traffic models for these systems than the random unicast pairs typically considered. Furthermore, traffic loads for the most promising near-term application for MANET technology — namely, networking at the tactical edge — are largely broadcast. The development of novel MANET approaches targeting broadcast first and foremost, however, has not been reported. Instead, existing system designs largely rely on fundamentally link-based, layered architectures, which are best suited to unicast traffic. In response to the demands of tactical edge communications, TrellisWare Technologies, Inc. developed a MANET system based on Barrage Relay Networks (BRNs). BRNs utilize an autonomous cooperative communication scheme that eliminates the need for link-level collision avoidance. The fundamental physical layer resource in BRNs is not a link, but a portion in space and time of a cooperative, multihop transport fabric. While initial hardware prototypes of BRNs were being refined into products by TrellisWare, a number of concepts similar to those that underlie BRNs were reported independently in the literature. That TrellisWares tactical edge MANET system design and academic research reconsidering the standard networking approach for MANETs arrived at similar design concepts lends credence to the value of these emerging wireless network approaches.

New class of turbo-like codes with universally good performance and high-speed decoding

Modern turbo-like codes (TLCs), including concatenated convolutional codes and low density parity check (LDPC) codes, have been shown to approach the Shannon limit on the additive white Gaussian noise (AWGN) channel Many design aspects remain relatively unexplored, however, including TLC design for maximum flexibility, very low error rate performance, and amenability to simple or very high-speed hardware codecs. In this paper we address these design issues by suggesting a new class of TLCs that we call systematic with serially concatenated parity (S-SCP) codes. One example member of this family is the Generalized (or Systematic) repeat accumulate code. We describe two other members of this family that both exhibit good performance over a wide range of block sizes, code rates, modulation, and target error probability. One of these provides error floor performance not previously demonstrated with any other TLC construction and the other is shown to offer very low complexity decoding with good performance. These two codes have been implemented in high-speed hardware codecs and performance curves based on these down to bit error rates below 10-10 are provided.

Tactical Mobile Mesh Network System Design

Tactical mobile mesh systems are wireless communication networks characterized by: harsh propagation channels and interference, frequent and rapid changes in the network topology, the requirement for very robust, low latency multimedia information decimation, and no centralized network control. In this paper we describe a technology testbed designed to address these challenges. The testbed is based on advanced waveform technologies, modern digital likelihood receiver processing, and robust ad-hoc networking strategies. A technology testbed was assembled to evaluate the cumulative benefits of this integrated system design. Field tests are presented demonstrating low-latency voice and multimedia IP traffic over multiple hop, cooperative routes.