Analysis about MIMO Detection Algorithms

2012 ◽  
pp. 157-162
Author(s):  
Xueyun Zhu ◽  
Xinyu Mao
Keyword(s):  
Mimo Detection ◽  
Detection Algorithms

Performance analysis of various massive MIMO detection algorithms in 5G Wireless technologies

2019 ◽  
Vol 10 ◽  
Author(s):  
Shihab Jimaa ◽  
Jawahir Al-Ali
Keyword(s):  
Massive Mimo ◽  
Spectrum Efficiency ◽  
System Capacity ◽  
Network Coverage ◽  
Mimo Detection ◽  
Infinity Norm ◽  
Detection Algorithms ◽  
Alternating Direction ◽  
5G Systems ◽  
Efficient Power

Background: The 5G will lead to a great transformation in the mobile telecommunications sector. Objective: The huge challenges being faced by wireless communications such as the increased number of users have given a chance for 5G systems to be developed and considered as an alternative solution. The 5G technology will provide a higher data rate, reduced latency, more efficient power than the previous generations, higher system capacity, and more connected devices. Method: It will offer new different technologies and enhanced versions of the existing ones, as well as new features. 5G systems are going to use massive MIMO (mMIMO), which is a promising technology in the development of these systems. Furthermore, mMIMO will increase the wireless spectrum efficiency and improve the network coverage. Result: In this paper we present a brief survey on 5G and its technologies, discuss the mMIMO technology with its features and advantages, review the mMIMO capacity and energy efficiency and also presents the recent beamforming techniques. Conclusion: Finally, simulation of adopting different mMIMO detection algorithms are presented, which shows the alternating direction method of multipliers (ADMM)-based infinity-norm (ADMIN) detector has the best performance.

scholarly journals An energy efficient weakly programmable MIMO detector architecture

2013 ◽  
Vol 11 ◽  
pp. 131-136 ◽  
Author(s):  
C. Gimmler-Dumont ◽  
N. Wehn
Keyword(s):  
Energy Efficient ◽  
Detection Algorithm ◽  
Multiple Antenna ◽  
Mimo Detection ◽  
Current Channel ◽  
Multiple Antenna Systems ◽  
Detection Algorithms ◽  
Programmable Architecture ◽  
Channel Conditions ◽  
Efficient Processing

Abstract. Energy efficient processing is mandatory in todays' mobile devices. For the upcoming multiple-antenna systems, algorithmic flexibility enables the dynamic reaction to changing channel conditions. We show that most of the tree search based MIMO detection algorithms are based on the same algorithmic kernels and present a weakly-programmable architecture based on these observations. In this way, the detection algorithm can be chosen and parameterized during runtime according to the current channel conditions and QoS requirements leading to a highly energy efficient implementation. The architecture has been implemented and synthesized on a 65 nm technology, resulting in an area of 0.26 mm2 and a power consumption of only 15 mW.

Reducing Computational Complexity and Enhancing Performance of IKSD Algorithm for Encoded MIMO Systems

2016 ◽  
Vol 2 (3) ◽  
pp. 636 ◽  
Author(s):  
Mohammed Qasim Sulttan
Keyword(s):  
Computational Complexity ◽  
Maximum Likelihood ◽  
High Performance ◽  
Mimo Systems ◽  
Practical Implementation ◽  
Mimo Detection ◽  
Detection Algorithms ◽  
Sphere Detection ◽  
Manhattan Metric ◽  
Main Challenge

<p>The main challenge in MIMO systems is how to design the MIMO detection algorithms with lowest computational complexity and high performance that capable of accurately detecting the transmitted signals. In last valuable research results, it had been proved the Maximum Likelihood Detection (MLD) as the optimum one, but this algorithm has an exponential complexity especially with increasing of a number of transmit antennas and constellation size making it an impractical for implementation. However, there are alternative algorithms such as the K-best sphere detection (KSD) and Improved K-best sphere detection (IKSD) which can achieve a close to Maximum Likelihood (ML) performance and less computational complexity. In this paper, we have proposed an enhancing IKSD algorithm by adding the combining of column norm ordering (channel ordering) with Manhattan metric to enhance the performance and reduce the computational complexity. The simulation results show us that the channel ordering approach enhances the performance and reduces the complexity, and Manhattan metric alone can reduce the complexity. Therefore, the combined channel ordering approach with Manhattan metric enhances the performance and much reduces the complexity more than if we used the channel ordering approach alone. So our proposed algorithm can be considered a feasible complexity reduction scheme and suitable for practical implementation.</p>

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