Real-time Communication Applications Research Articles

Fast algorithms for updating signal subspaces

In various real-time signal processing and communication applications, it is often required to track a low-dimensional signal subspace that slowly varies with time. Conventional methods of updating the signal subspace rely on eigendecomposition or singular value decomposition, which is computationally expensive and difficult to implement in parallel. Recently, Xu and Kailath proposed fast and parallelizable Lanczos-based algorithms for estimating the signal subspace based on the data matrices or the covariance matrices. In this paper, we shall extend these algorithms to achieve fast tracking of the signal subspace. The computational complexity of the new methods is O(M/sup 2/d) per update, where M is the size of the data vectors and d is the dimension of the signal subspace. Unlike most tracking methods that assume d is fixed and/or known a priori, the new methods also update the signal subspace dimension. More importantly, under certain stationarity conditions, we can show that the Lanczos-based methods are asymptotically equivalent to the more costly SVD or eigendecomposition based methods and that the estimation of d is strongly consistent. Knowledge of the previous signal subspace estimate is incorporated to achieve better numerical properties for the current signal subspace estimate. Numerical simulations for some signal scenarios are also presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Tools for real-time signal-processing research

The use of digital signal processing (DSP) devices for real-time communication applications is discussed. The authors comment on distinguishing aspects of DSP architecture, describing not so much individual processors as those features common to DSPs and distinct from modern general-purpose processors. They describe three DSP32xx-based machines that support DSP algorithm implementation: SURF-board, HoBo, and DSP3. They also described rtpi, a source-code debugger for workstations and for the AT&T DSP32C signal-processor integrated circuit, and dspx, a collection of subroutines and host programs that provides an execution environment for DSPs akin to the UNIX environment. These tools facilitate the transfer of algorithms from mainframes or workstations to DSP hardware. Included are case studies of two real-time implementations: the low-delay CELP (LD-CELP) speech coder and the decoder side of the perceptual audio coder (PAC), an algorithm that compresses CD-quality audio into a 128-kb/s stream without perceptible distortion. >

A two-step bilinear filtering approximation

A new approximation technique to a certain class of non-linear filtering (signal processing) problems is considered here. The method is based on an approximation of a nonlinear, partially observable system by a bilinear model with fully observable states. The filter development proceeds from the assumption that the unobservable states are conditionally Gaussian with respect to the observation initially. The method is shown to be promising for real-time communication and sonar applications as demonstrated by computer simulations. Moreover, some of the traditional techniques evolve as special cases of this methodology.

Fast decryption algorithm for the knapsack cipher

A fast decryption algorithm is described which permits use of the knapsack cipher (a public-key cryptosystem) at data rates in the neighborhood of 10 Mbit/sec. This high-speed capability can be used to incorporate the security and flexibility of public-key cryptosystems into a wide variety of real-time communications applications. Implementation of the algorithm using Very Large Scale Integration appears attractive: The circuit functions required are approximately 56 kilobits of memory and a small amount of arithmetic logic.