Performance Evaluation of Non-coherent DPSK Signal Detection Algorithms in Massive MIMO Systems

Author(s):  
Omnia Mahmoud ◽  
Ahmed El-Mahdy
Author(s):  
М.Г. БАКУЛИН ◽  
Т.Б.К. БЕН РАЖЕБ ◽  
В.Б. КРЕЙНДЕЛИН ◽  
А.Э. СМИРНОВ

С развитием технологии MIMO и появлением технологии massive MIMO возросла сложность обработки сигнала на приемной стороне. Применение известных алгоритмов детектирования сигнала на приемной стороне становится трудно реализуемым из-за высокой вычислительной сложности. Предлагается новая реализация известного алгоритма МСКО, которая позволяет снизить вычислительную сложность детектирования без потерь в помехоустойчивости в системах беспроводной связи, использующих технологию massive MIMO. With the development of MIMO technology and the appearance of the massive MIMO technology, the computational complexity of signal processing on the receiving side has increased. The application of known signal detection algorithms used in MIMO systems becomes difficult or even impossible to implement in massive MIMO systems because of computational complexity. We offer a new realization technique of the well-known MMSE detection algorithm with less computational complexity and without any loss in noise immunity in wireless communication systems using massive MIMO technology.


Information ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 301
Author(s):  
Samarendra Nath Sur ◽  
Rabindranath Bera ◽  
Akash Kumar Bhoi ◽  
Mahaboob Shaik ◽  
Gonçalo Marques

Massive multi-input-multi-output (MIMO) systems are the future of the communication system. The proper design of the MIMO system needs an appropriate choice of detection algorithms. At the same time, Lattice reduction (LR)-aided equalizers have been well investigated for MIMO systems. Many studies have been carried out over the Korkine–Zolotareff (KZ) and Lenstra–Lenstra–Lovász (LLL) algorithms. This paper presents an analysis of the channel capacity of the massive MIMO system. The mathematical calculations included in this paper correspond to the channel correlation effect on the channel capacity. Besides, the achievable gain over the linear receiver is also highlighted. In this study, all the calculations were further verified through the simulated results. The simulated results show the performance comparison between zero forcing (ZF), minimum mean squared error (MMSE), integer forcing (IF) receivers with log-likelihood ratio (LLR)-ZF, LLR-MMSE, KZ-ZF, and KZ-MMSE. The main objective of this work is to show that, when a lattice reduction algorithm is combined with the convention linear MIMO receiver, it improves the capacity tremendously. The same is proven here, as the KZ-MMSE receiver outperforms its counterparts in a significant margin.


2014 ◽  
Vol 1049-1050 ◽  
pp. 2063-2068
Author(s):  
Xiao Tian Wang ◽  
Long Xiang Yang

massive MIMO (also known as Large-Scale Antenna Systems),which is one of the key technologies for the fifth generation (5G) mobile systems, brings huge improvements in spectral efficiency and energy efficiency through the use of a large excess of antennas for base station. This paper analyses and simulates the performances of several signal detection algorithms under the massive MIMO system model. The results show that when the number of base station antennas is considerably larger than the number of users, even the simple signal detection algorithms can achieve good system performance.


2015 ◽  
pp. 357-385
Author(s):  
Rodrigo de Lamare ◽  
Raimundo Sampaio-Neto

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