TUTCRIS

TY - GEN

T1 - An efficient GPU implementation of an arbitrary resampling polyphase channelizer

AU - Kim, Scott C.

AU - Plishker, William L.

AU - Bhattacharyya, Shuvra S.

PY - 2013

Y1 - 2013

N2 - A channelizer is a part of a receiver front-end subsystem, commonly found in various communication systems, that separates different users or channels. A modern channelizer uses advantages of polyphase filter banks to process multiple channels at the same time, allowing down conversion, downsampling, and filtering all at the same time. However, due to limitations imposed by the structure and requirements of channelizers, their usage is limited and poses significant challenges due to inflexibility using conventional implementation techniques, which are intensively hardware-based. However, with advances in graphics processing unit (GPU) technology, we now have the potential to deliver high computational throughput along with the flexibility of software-based implementation. In this paper, we demonstrate how this potential can be exploited by presenting a novel GPU-based channelizer implementation. Our implementation incorporates methods for eliminating complex buffer managements and performing arbitrary resampling on all channels simultaneously. We also introduce the notion of simultaneously processing many channels as a high data rate parallel receiver system using blocks of threads in the GPU. The multi-channel, flexible, high-throughput, and arbitrary resampling characteristics of our GPU-based channelizer make it attractive for a variety of communication receiver applications.

AB - A channelizer is a part of a receiver front-end subsystem, commonly found in various communication systems, that separates different users or channels. A modern channelizer uses advantages of polyphase filter banks to process multiple channels at the same time, allowing down conversion, downsampling, and filtering all at the same time. However, due to limitations imposed by the structure and requirements of channelizers, their usage is limited and poses significant challenges due to inflexibility using conventional implementation techniques, which are intensively hardware-based. However, with advances in graphics processing unit (GPU) technology, we now have the potential to deliver high computational throughput along with the flexibility of software-based implementation. In this paper, we demonstrate how this potential can be exploited by presenting a novel GPU-based channelizer implementation. Our implementation incorporates methods for eliminating complex buffer managements and performing arbitrary resampling on all channels simultaneously. We also introduce the notion of simultaneously processing many channels as a high data rate parallel receiver system using blocks of threads in the GPU. The multi-channel, flexible, high-throughput, and arbitrary resampling characteristics of our GPU-based channelizer make it attractive for a variety of communication receiver applications.

KW - Arbitrary resampling

KW - DSP accelerator

KW - Front-end receiver

KW - Polyphase channelizer

KW - Sample rate conversion

UR - http://www.scopus.com/inward/record.url?scp=84892642738&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9791092279016

SP - 231

EP - 238

BT - DASIP 2013 - Proceedings of the 2013 Conference on Design and Architectures for Signal and Image Processing

ER -