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Implementation of Low-latency Signal Processing and Data Shuffling for TDD massive MIMO Systems

Malkowsky, Steffen LU ; Vieira, Joao LU ; Nieman, Karl; Kundargi, Nikhil; Wong, Ian; Öwall, Viktor LU ; Edfors, Ove LU ; Tufvesson, Fredrik LU and Liu, Liang LU (2016) IEEE International Workshop on Signal Processing Systems
Abstract
Low latency signal processing and high throughput implementations are required in order to realize real-time TDD massive MIMO communications, especially in high mobility scenarios. One of the main challenges is that the up-link and down-link turnaround time has to be within the coherence time of the wireless channel to enable efficient use of reciprocity. This paper presents a hardware architecture and implementation of this critical signal processing path, including channel estimation, QRD-based MMSE decoder/precoder and distributed reciprocity calibration. Furthermore, we detail a switch-based router implementation to tackle the stringent throughput and latency requirements on the data shuffling network. The proposed architecture was... (More)
Low latency signal processing and high throughput implementations are required in order to realize real-time TDD massive MIMO communications, especially in high mobility scenarios. One of the main challenges is that the up-link and down-link turnaround time has to be within the coherence time of the wireless channel to enable efficient use of reciprocity. This paper presents a hardware architecture and implementation of this critical signal processing path, including channel estimation, QRD-based MMSE decoder/precoder and distributed reciprocity calibration. Furthermore, we detail a switch-based router implementation to tackle the stringent throughput and latency requirements on the data shuffling network. The proposed architecture was verified on the LuMaMi testbed, based on the NI SDR platform. The implementation supports real-time TDD transmission in a 128x12 massive MIMO setup using 20 MHz channel bandwidth. The processing latency in the critical path is less than 0.15 ms, enabling reciprocity-based TDD massive MIMO for high-mobility scenarios. (Less)
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author
organization
publishing date
type
Contribution to conference
publication status
in press
subject
keywords
Massive MIMO, TDD, Low-latency, SDR
pages
6 pages
conference name
IEEE International Workshop on Signal Processing Systems
language
English
LU publication?
yes
id
baac6069-af2a-4591-87fd-26995b125743
date added to LUP
2016-09-13 16:54:28
date last changed
2016-11-22 09:36:51
@misc{baac6069-af2a-4591-87fd-26995b125743,
  abstract     = {Low latency signal processing and high throughput implementations are required in order to realize real-time TDD massive MIMO communications, especially in high mobility scenarios. One of the main challenges is that the up-link and down-link turnaround time has to be within the coherence time of the wireless channel to enable efficient use of reciprocity. This paper presents a hardware architecture and implementation of this critical signal processing path, including channel estimation, QRD-based MMSE decoder/precoder and distributed reciprocity calibration. Furthermore, we detail a switch-based router implementation to tackle the stringent throughput and latency requirements on the data shuffling network. The proposed architecture was verified on the LuMaMi testbed, based on the NI SDR platform. The implementation supports real-time TDD transmission in a 128x12 massive MIMO setup using 20 MHz channel bandwidth. The processing latency in the critical path is less than 0.15 ms, enabling reciprocity-based TDD massive MIMO for high-mobility scenarios.},
  author       = {Malkowsky, Steffen and Vieira, Joao and Nieman, Karl and Kundargi, Nikhil and Wong, Ian and Öwall, Viktor and Edfors, Ove and Tufvesson, Fredrik and Liu, Liang},
  keyword      = {Massive MIMO,TDD,Low-latency,SDR},
  language     = {eng},
  month        = {08},
  pages        = {6},
  title        = {Implementation of Low-latency Signal Processing and Data Shuffling for TDD massive MIMO Systems},
  year         = {2016},
}