Impact of Quantization in Decentralized Processing for Large Multi-Antenna Architectures

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

The demand for an increased number of antennas at base stations is driving research on decentralized processing schemes aimed at reducing the information volume that has to be transferred to, and processed at, a central processing unit (CPU). Some of these schemes can reduce the dimensions of the data while achieving information-lossless processing with respect to centralized architectures. However, little is known about the impact of quantization in these decentralized schemes. Moreover, it is unclear if an information-lossless reduction of dimensions directly corresponds to a reduction in the bit-rate that has to be transmitted to the CPU after quantization. This paper studies how quantization affects the performance of decentralized processing. Bit rates after quantization of a received vector (in a centralized scheme) are contrasted with bit rates after quantization of post-processed vectors using various information-lossless dimension reductions that can potentially be applied in decentralized schemes.

Original languageEnglish
Title of host publication2022 56th Asilomar Conference on Signals, Systems, and Computers
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1351-1356
Number of pages6
ISBN (Electronic)9781665459068
DOIs
Publication statusPublished - 2022
Event56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022 - Virtual, Online, United States
Duration: 2022 Oct 312022 Nov 2

Conference

Conference56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
Country/TerritoryUnited States
CityVirtual, Online
Period2022/10/312022/11/02

Subject classification (UKÄ)

  • Telecommunications

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