Adaptive switching detection algorithm for iterative-MIMO systems to enable power savings

This paper attempts to tackle one of the challenges faced in soft input soft output Multiple Input Multiple Output (MIMO) detection systems, which is to achieve optimal error rate performance with minimal power consumption. This is realized by proposing a new algorithm design that comprises multiple...

Full description

Saved in:
Bibliographic Details
Published in:Radio science Vol. 49; no. 11; pp. 1065 - 1079
Main Authors: Tadza, N., Laurenson, D., Thompson, J. S.
Format: Journal Article
Language:English
Published: Washington Blackwell Publishing Ltd 01.11.2014
Subjects:
Adaptive algorithms
Algorithms
Channels
DVFS
dynamic static power
Dynamical systems
Dynamics
Electrical engineering
Energy conservation
FSD
iterative-MIMO
Mean square errors
mutual information
Receivers
Thresholds
V-BLAST/ZF
ISSN:0048-6604, 1944-799X
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper attempts to tackle one of the challenges faced in soft input soft output Multiple Input Multiple Output (MIMO) detection systems, which is to achieve optimal error rate performance with minimal power consumption. This is realized by proposing a new algorithm design that comprises multiple thresholds within the detector that, in real time, specify the receiver behavior according to the current channel in both slow and fast fading conditions, giving it adaptivity. This adaptivity enables energy savings within the system since the receiver chooses whether to accept or to reject the transmission, according to the success rate of detecting thresholds. The thresholds are calculated using the mutual information of the instantaneous channel conditions between the transmitting and receiving antennas of iterative‐MIMO systems. In addition, the power saving technique, Dynamic Voltage and Frequency Scaling, helps to reduce the circuit power demands of the adaptive algorithm. This adaptivity has the potential to save up to 30% of the total energy when it is implemented on Xilinx®Virtex‐5 simulation hardware. Results indicate the benefits of having this “intelligence” in the adaptive algorithm due to the promising performance‐complexity tradeoff parameters in both software and hardware codesign simulation. Key Points Adaptivity achieves optimal error rate performance with minimal powerReceiver adapts to conditions according to the mutual information thresholdsDVFS technique reduces the circuit power demands of the adaptive algorithm
Bibliography:ark:/67375/WNG-4B9NZKNF-S
University of Tun Hussein Onn Malaysia
istex:579A39C0CD0D7A0AD1EF977AC89CE17DBD114ACC
ArticleID:RDS20164
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0048-6604
1944-799X
DOI:10.1002/2013RS005323