Steepest descent algorithm implementation for multichannel blind signal recovery

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© The Institution of Engineering and Technology
Published 10/01/2013

Abstract

In the literature, there exists a number of blind signal recovery algorithms that are implemented as stochastic gradient descent (SGD)-based adaptive schemes. SGD typically has low complexity at the expense of slower convergence. On the other hand, packet-based data transmission in many practical digital communication systems makes it attractive to develop steepest descent (SD) implementation in order to speed-up convergence. This work aims at developing SD implementation of several well-known blind signal recovery algorithms for multi-channel equalisation and source separation. The authors SD formulation is more amenable to additional parametric and signal subspace constraint for faster convergence and superior performance.

Inspec keywords: blind equalisers; equalisers; stochastic processes; MIMO communication; blind source separation; gradient methods

Other keywords: digital communication systems; stochastic gradient descent-based adaptive schemes; steepest descent algorithm implementation; multichannel equalisation; packet-based data transmission; multichannel blind signal recovery; signal subspace constraint; source separation

Subjects: Radio links and equipment; Signal processing and detection; Interpolation and function approximation (numerical analysis); Linear algebra (numerical analysis); Other topics in statistics; Optimisation techniques; Communication channel equalisation and identification

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