Transmit beamforming in Rayleigh product MIMO channels: Ergodic mutual information and symbol error rate

2016 ◽  
Author(s):  
Zhong Zheng ◽  
Lu Wei ◽  
Zygmunt J. Haas ◽  
Vahid Tarokh
Keyword(s):  
Mutual Information ◽  
Error Rate ◽  
Symbol Error Rate ◽  
Mimo Channels ◽  
Transmit Beamforming

scholarly journals Average Vector-Symbol Error Rate Closed-Form Expression for ML Group Detection Receivers in Large MU-MIMO Channels With Transmit Correlation

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 45653-45663
Author(s):  
Byron P. Maza ◽  
Ghassan Dahman ◽  
Georges Kaddoum ◽  
Francois Gagnon
Keyword(s):  
Closed Form ◽  
Error Rate ◽  
Symbol Error Rate ◽  
Closed Form Expression ◽  
Form Expression ◽  
Mimo Channels ◽  
Group Detection

Symbol error rate analysis of transmit beamforming systems under delayed and limited feedback

2014 ◽  
Vol 50 (4) ◽  
pp. 321-323 ◽  
Author(s):  
Donghun Lee ◽  
Byung Jang Jeong
Keyword(s):  
Error Rate ◽  
Limited Feedback ◽  
Symbol Error Rate ◽  
Transmit Beamforming ◽  
Rate Analysis

Capacity Analysis for Correlated Multi-Hop MIMO Channels under Colored Noise

2015 ◽  
Vol 1 ◽  
pp. 41
Author(s):  
Nguyen N. Tran ◽  
Ha X. Nguyen
Keyword(s):  
Computational Complexity ◽  
Mutual Information ◽  
Closed Form Solution ◽  
Optimal Solution ◽  
Form Solution ◽  
Maximization Problem ◽  
Capacity Analysis ◽  
Mimo Channels ◽  
Average Mutual Information ◽  
Channel Output

A capacity analysis for generally correlated wireless multi-hop multi-input multi-output (MIMO) channels is presented in this paper. The channel at each hop is spatially correlated, the source symbols are mutually correlated, and the additive Gaussian noises are colored. First, by invoking Karush-Kuhn-Tucker condition for the optimality of convex programming, we derive the optimal source symbol covariance for the maximum mutual information between the channel input and the channel output when having the full knowledge of channel at the transmitter. Secondly, we formulate the average mutual information maximization problem when having only the channel statistics at the transmitter. Since this problem is almost impossible to be solved analytically, the numerical interior-point-method is employed to obtain the optimal solution. Furthermore, to reduce the computational complexity, an asymptotic closed-form solution is derived by maximizing an upper bound of the objective function. Simulation results show that the average mutual information obtained by the asymptotic design is very closed to that obtained by the optimal design, while saving a huge computational complexity.

Symbol error rate analysis of non-orthogonal multiple access systems

2021 ◽  
Vol 46 ◽  
pp. 101295
Author(s):  
Ali Mohammed A. Alkhazzar ◽  
Hassan Aghaeinia
Keyword(s):  
Error Rate ◽  
Multiple Access ◽  
Symbol Error Rate ◽  
Rate Analysis

Performance Analysis of OQPSK Signals with Bi-Kappa Noise for Wireless Sensor Networks

2013 ◽  
Vol 330 ◽  
pp. 957-960
Author(s):  
Qiao Ling Du ◽  
Zhi Rui Wang ◽  
Yu Pei ◽  
Yi Ding Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Performance Analysis ◽  
Error Rate ◽  
Fading Channel ◽  
Rayleigh Fading ◽  
Symbol Error Rate ◽  
Wireless Sensor ◽  
Channel Simulation ◽  
Simulation Results

This paper investigates the performance analysis of OQPSK in HF band for wireless sensor networks. An analytical model for getting symbol error rate (SER) is given in presence of Bi-Kappa noise in HF band. And the SER of OQPSK is given in AWGN and Rayleigh fading channel. Simulation results HF noise as Bi-Kappa noise should be investigated in HF band for WSN.

Corrections to “Symbol Error Rate Model for Communication Using Femtosecond Pulses for Space Applications”

2017 ◽  
Vol 29 (15) ◽  
pp. 1277-1277
Author(s):  
Ehud Weiss ◽  
Dima Bykhovsky ◽  
Shlomi Arnon
Keyword(s):  
Error Rate ◽  
Symbol Error Rate ◽  
Femtosecond Pulses ◽  
Rate Model ◽  
Space Applications
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