scholarly journals Statistical Analysis of MIMO Beamforming With Co-Channel Unequal-Power MIMO Interferers Under Path-Loss and Rayleigh Fading

2011 ◽  
Vol 59 (8) ◽  
pp. 3738-3748 ◽  
Author(s):  
Yongzhao Li ◽  
Lu Zhang ◽  
Leonard J. Cimini ◽  
Hailin Zhang
Keyword(s):  
Statistical Analysis ◽  
Rayleigh Fading ◽  
Path Loss ◽  
Mimo Beamforming

scholarly journals Capacity Analysis of Distributed Antenna Systems with Beamforming

2018 ◽  
Vol 232 ◽  
pp. 04039
Author(s):  
Meiyan Ju ◽  
Chao Chen ◽  
Yueheng Li ◽  
Guoping Tan
Keyword(s):  
Rayleigh Fading ◽  
Path Loss ◽  
Mathematical Expression ◽  
System Capacity ◽  
Capacity Analysis ◽  
Multiple Antenna ◽  
Distributed Antenna Systems ◽  
Multiple Antenna Systems ◽  
Distributed Antenna ◽  
Antenna Systems

Distributed antenna systems (DASs) can reduce the access distance, increase system capacity and improve system performance compared with conventional centralized multiple antenna systems. In this paper, the system capacity of downlink DAS with beamforming is investigated. The mathematical expression of system capacity is derived over the composite channel including Rayleigh fading, shadowing and path loss. At the same time, the interference from other APs is also considered for the studied AP. Numerical methods including Gauss-Hermite integral and composite Simpson’s rule are used to compute the system capacity of DAS under different MS distributions. Numerical results verify the precision of the mathematical analysis of system capacity by comparing Monte-Carlo simulation results. The results also show interference among APs shouldn’t be ignored when APs are close to each other or there are many APs.

scholarly journals Factorial Design Analysis for Localization Algorithms

2018 ◽  
Vol 8 (12) ◽  
pp. 2654
Author(s):  
Joaquin Mass-Sanchez ◽  
Erica Ruiz-Ibarra ◽  
Ana Gonzalez-Sanchez ◽  
Adolfo Espinoza-Ruiz ◽  
Joaquin Cortez-Gonzalez
Keyword(s):  
Statistical Analysis ◽  
Noise Level ◽  
Performance Metrics ◽  
Extreme Values ◽  
Path Loss ◽  
Propagation Model ◽  
Path Loss Exponent ◽  
Localization Algorithms ◽  
Accuracy And Precision ◽  
The Impact

Localization is a fundamental problem in Wireless Sensor Networks, as it provides useful information regarding the detection of an event. There are different localization algorithms applied in single-hop or multi-hop networks; in both cases their performance depends on several factors involved in the evaluation scenario such as node density, the number of reference nodes and the log-normal shadowing propagation model, determined by the path-loss exponent (η) and the noise level (σdB) which impact on the accuracy and precision performance metrics of localization techniques. In this paper, we present a statistical analysis based on the 2k factorial methodology to determine the key factors affecting the performance metrics of localization techniques in a single-hop network to concentrate on such parameters, thus reducing the amount of simulation time required. For this proposal, MATLAB simulations are carried out in different scenarios, i.e., extreme values are used for each of the factors of interest and the impact of the interaction among them in the performance metrics is observed. The simulation results show that the path-loss exponent (η) and noise level (σdB) factors have the greatest impact on the accuracy and precision metrics evaluated in this study. Based on this statistical analysis, we recommend estimating the propagation model as close to reality as possible to consider it in the design of new localization techniques and thus improve their accuracy and precision metrics.

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