The Low Complexity Multi-user Detection Algorithms for Uplink SCMA System

2019 ◽  
pp. 562-575
Author(s):  
Jingjing Wu ◽  
Shaochuan Wu ◽  
Rundong Zuo ◽  
Wenbin Zhang
Keyword(s):  
Low Complexity ◽  
Detection Algorithms

scholarly journals Low-Complexity Detection Algorithms for Spatial Modulation MIMO Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Xinhe Zhang ◽  
Yuehua Zhang ◽  
Chang Liu ◽  
Hanzhong Jia
Keyword(s):  
Computational Complexity ◽  
Mimo Systems ◽  
Optimal Solution ◽  
Low Complexity ◽  
Search Tree ◽  
Spatial Modulation ◽  
Algorithm Analysis ◽  
Detection Algorithms ◽  
Search Order ◽  
Ber Performance

In this paper, the authors propose three low-complexity detection schemes for spatial modulation (SM) systems based on the modified beam search (MBS) detection. The MBS detector, which splits the search tree into some subtrees, can reduce the computational complexity by decreasing the nodes retained in each layer. However, the MBS detector does not take into account the effect of subtree search order on computational complexity, and it does not consider the effect of layers search order on the bit-error-rate (BER) performance. The ost-MBS detector starts the search from the subtree where the optimal solution is most likely to be located, which can reduce total searches of nodes in the subsequent subtrees. Thus, it can decrease the computational complexity. When the number of the retained nodes is fixed, which nodes are retained is very important. That is, the different search orders of layers have a direct influence on BER. Based on this, we propose the oy-MBS detector. The ost-oy-MBS detector combines the detection order of ost-MBS and oy-MBS together. The algorithm analysis and experimental results show that the proposed detectors outstrip MBS with respect to the BER performance and the computational complexity.

scholarly journals A SIMPLE PATTERN RECOGNITION-BASED METHOD FOR POWER QUALITY DISTURBANCE DETECTION

2021 ◽  
Vol 5 (3) ◽  
pp. 1-10
Author(s):  
Robson Rosserrani De Lima ◽  
Danton Diego Ferreira ◽  
José Manoel de Seixas ◽  
Leonardo Silveira Paiva
Keyword(s):  
Power Systems ◽  
Power Quality ◽  
Low Complexity ◽  
Mean Value ◽  
Computational Effort ◽  
Detection Rates ◽  
Detection Algorithms ◽  
Power Quality Disturbance ◽  
Simple Detection ◽  
Disturbance Detection

Voltage disturbances are the most frequent cause of a large range of disruption in industrial, commercial, and residential power supply systems. These disturbances are often referred to as power quality problems and affect the Power Systems causing substantial losses. To avoid the storage of a large amount of data, the first task in monitoring the power quality is the realtime detection of disturbances, which must be performed by an accurate and low-complexity system. This paper proposes a low-complexity system for power quality disturbance detection. The method makes innovative use of simple features extracted from reduced segments of the monitored voltage waveform. The extract features (the mean value, variance, energy, and the maximum and minimum values of the filtered voltage signals) require low computational effort and allow a considerable dimensional reduction of the signals, leading to simple detection algorithms. The proposed method achieves high detection rates on both simulated and real signals.

scholarly journals Low-Complexity Super-Resolution Detection for Range-Vital Doppler Estimation FMCW Radar

2021 ◽  
Vol 21 (3) ◽  
pp. 236-245
Author(s):  
Bongseok Kim ◽  
Youngseok Jin ◽  
Youngdoo Choi ◽  
Jonghun Lee ◽  
Sangdong Kim
Keyword(s):  
Continuous Wave ◽  
Low Cost ◽  
Phase Variation ◽  
Super Resolution ◽  
Estimation Algorithm ◽  
Low Complexity ◽  
Music Algorithm ◽  
Fmcw Radar ◽  
Detection Algorithms ◽  
Simulation And Experiment

This paper proposes low-complexity super-resolution detection for range-vital Doppler estimation frequency-modulated continuous wave (FMCW) radar. In regards to vital radar, and in order to estimate joint range and vital Doppler information such as the human heartbeat and respiration, two-dimensional (2D) detection algorithms such as 2D-FFT (fast Fourier transform) and 2D-MUSIC (multiple signal classification) are required. However, due to the high complexity of 2D full-search algorithms, it is difficult to apply this process to low-cost vital FMCW systems. In this paper, we propose a method to estimate the range and vital Doppler parameters by using 1D-FFT and 1D-MUSIC algorithms, respectively. Among 1D-FFT outputs for range detection, we extract 1D-FFT results based solely on human target information with phase variation of respiration for each chirp; subsequently, the 1D-MUSIC algorithm is employed to obtain accurate vital Doppler results. By reducing the dimensions of the estimation algorithm from 2D to 1D, the computational burden is reduced. In order to verify the performance of the proposed algorithm, we compare the Monte Carlo simulation and root-mean-square error results. The simulation and experiment results show that the complexity of the proposed algorithm is significantly lower than that of an algorithm detecting signals in several regions.

Advanced Space-Time Block Codes and Low Complexity Near Optimal Detection for Future Wireless Networks

2009 ◽  
pp. 107-129
Author(s):  
W. H. Chin ◽  
C. Yuen
Keyword(s):  
Maximum Likelihood ◽  
Low Complexity ◽  
Block Codes ◽  
Space Time ◽  
Time Block ◽  
Block Coding ◽  
Detection Algorithms ◽  
Space Time Block Codes ◽  
Space Time Block Coding ◽  
Almost All

Space-time block coding is a way of introducing multiplexing and diversity gain in wireless systems equipped with multiple antennas. There are several classes of codes tailored for different channel conditions. However, in almost all the cases, maximum likelihood detection is required to fully realize the diversity introduced. In this chapter, we present the fundamentals of space-time block coding, as well as introduce new codes with better performance. Additionally, we introduce the basic detection algorithms which can be used for detecting space-time block codes. Several low complexity pseudo-maximum likelihood algorithms will also be introduced and discussed.

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