Low-complexity large-scale multiple-input multiple-output channel estimation using affine combination of sparse least mean square filters

2015 ◽  
Vol 9 (17) ◽  
pp. 2168-2175 ◽  
Author(s):  
Guan Gui ◽  
Ning Liu ◽  
Fumiyuki Adachi ◽  
Li Xu
Keyword(s):  
Channel Estimation ◽  
Large Scale ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Output Channel ◽  
Mean Square ◽  
Least Mean Square ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Affine Combination

scholarly journals Channel Estimation for MIMO Systems

2022 ◽  
Vol 10 (1) ◽  
pp. 201-204
Author(s):  
Sonti Swapna
Keyword(s):  
Channel Estimation ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Least Square ◽  
Spectrum Efficiency ◽  
Mean Square ◽  
Multiple Input ◽  
Input Multiple Output

Abstract: A combination of multiple-input multiple-output (MIMO) systems and orthogonal frequency division multiplexing (OFDM) technologies can be employed in modern wireless communication systems to achieve high data rates and improved spectrum efficiency. For multiple input multiple output (MIMO) systems, this paper provides a Rayleigh fading channel estimation technique based on pilot carriers. The channel is estimated using traditional Least Square (LS) and Minimum Mean Square (MMSE) estimation techniques. The MIMO-OFDM system's performance is measured using the Bit Error Rate (BER) and Mean Square Error (MSE) levels. Keywords: MIMO, MMSE, Channel estimation, BER, OFDM

scholarly journals A Low Complexity Channel Estimation and Detection for Massive MIMO Using SC-FDE

Telecom ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 3-17
Author(s):  
Mário Marques da Silva ◽  
Rui Dinis ◽  
João Guerreiro
Keyword(s):  
Channel Estimation ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Data Detection ◽  
Pilot Symbols ◽  
Multiple Input ◽  
Input Multiple Output

5G Communications will support millimeter waves (mm-Wave), alongside the conventional centimeter waves, which will enable much higher throughputs and facilitate the employment of hundreds or thousands of antenna elements, commonly referred to as massive Multiple Input–Multiple Output (MIMO) systems. This article proposes and studies an efficient low complexity receiver that jointly performs channel estimation based on superimposed pilots, and data detection, optimized for massive MIMO (m-MIMO). Superimposed pilots suppress the overheads associated with channel estimation based on conventional pilot symbols, which tends to be more demanding in the case of m-MIMO, leading to a reduction in spectral efficiency. On the other hand, MIMO systems tend to be associated with an increase of complexity and increase of signal processing, with an exponential increase with the number of transmit and receive antennas. A reduction of complexity is obtained with the use of the two proposed algorithms. These algorithms reduce the complexity but present the disadvantage that they generate a certain level of interference. In this article, we consider an iterative receiver that performs the channel estimation using superimposed pilots and data detection, while mitigating the interference associated with the proposed algorithms, leading to a performance very close to that obtained with conventional pilots, but without the corresponding loss in the spectral efficiency.

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