FPGA implementation of adaptive filters

  • Michael Hanson

Student thesis: Master's Thesis


Adaptive signal processing is an important topic of research covering many application areas such as audio signal processing, radar, wireless communications and control systems. In the context of wireless communications, the impulse response of the channel can vary rapidly with respect to time. Fast adaptive filtering algorithms are required in order to perform equalization of such channels. The two algorithms predominantly used in practice are variants of Least Mean Squares (LMS) and Recursive Least Squares (RLS) algorithms. LMS algorithms are more straightforward to implement however, RLS algorithms offer increased performance at the expense of greater complexity. For very high throughput operation, dedicated hardware is required to keep up with the incoming sampling rate. Field Programmable Gate Arrays (FPGAs) can provide superior performance both in terms of power utilization and throughput, when compared to Graphic Processor Unit (GPU) or Digital Signal Processor (DSP) implementation. However, despite the potential performance advantage, FPGA implementation progress has been limited by the difficulty of programming such devices. This motivates the development of software allowing the user to program FPGAs in a more straightforward manner than direct low-level programming. The first part of the following work seeks to alleviate this via means of a high abstraction level Intellectual Property (IP) core for both the classic LMS algorithm, and the Normalized LMS (NLMS) algorithm. High level parameters allow the user to trade resource utilization against throughput, choosing fully parallel, serial or partly-serial architectures. In the second part of this work, a survey is presented on the implementation of the QR Decomposition RLS (QRD-RLS) algorithm. Discussion is given on the numerical performance, cost and throughput of different architectures, with particular detail presented on the Givens based systolic array architecture.
Date of Award26 May 2016
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SponsorsUniversity of Strathclyde
SupervisorRobert Stewart (Supervisor) & Stephan Weiss (Supervisor)

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