Reduced complexity short-block data detection techniques for fading time-dispersive channels

1992 ◽  
Vol 41 (3) ◽  
pp. 255-265 ◽  
Author(s):  
S.N. Crozier ◽  
D.D. Falconer ◽  
S.A. Mahmoud
Keyword(s):  
Data Detection ◽  
Detection Techniques ◽  
Dispersive Channels ◽  
Block Data ◽  
Reduced Complexity ◽  
Fading Time

scholarly journals Improved Surprise Adequacy Tools for Corner Case Data Description and Detection

2021 ◽  
Vol 11 (15) ◽  
pp. 6826
Author(s):  
Tinghui Ouyang ◽  
Vicent Sanz Marco ◽  
Yoshinao Isobe ◽  
Hideki Asoh ◽  
Yutaka Oiwa ◽  
...  
Keyword(s):  
Data Detection ◽  
Design Phase ◽  
Critical Systems ◽  
Classification Problems ◽  
Data Description ◽  
Detection Techniques ◽  
Qualitative And Quantitative ◽  
Improved Performance ◽  
Case Data ◽  
Experiment Analysis

Facing the increasing quantity of AI models applications, especially in life- and property-related fields, it is crucial for designers to construct safety- and security-critical systems. As a major factor affecting the safety of AI models, corner case data and its related description/detection techniques are important in the AI design phase and quality assurance. In this paper, inspired by surprise adequacy (SA), a tool having advantages on capture data behaviors, we developed three modified versions of distance-based-SA (DSA) for detecting corner cases in classification problems. Through the experiment analysis on MNIST, CIFAR, and industrial example data, the feasibility and usefulness of the proposed tools on corner case data detection are verified. Moreover, Qualitative and quantitative experiments validated that the developed DSA tools can achieve improved performance in describing corner cases’ behaviors.

scholarly journals Reduced complexity optimum detector for Block Data Transmission Systems

2009 ◽  
Vol 6 (23) ◽  
pp. 1649-1655 ◽  
Author(s):  
SPK. Babu ◽  
M. F. M. Salleh ◽  
Farid Ghani
Keyword(s):  
Data Transmission ◽  
Transmission Systems ◽  
Block Data ◽  
Reduced Complexity

scholarly journals Large Scale MIMO Analysis Using Enhanced LAMA

2021 ◽  
Author(s):  
Hanumantharao Bitra ◽  
Palanisamy Ponnusamy
Keyword(s):  
Message Passing ◽  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Research Work ◽  
Base Station ◽  
Superior Performance ◽  
Gram Matrix ◽  
Data Detection ◽  
Detection Techniques

Abstract In this research work, a novel enhanced large scale multi-input multi-output (MIMO) approximate message passing (LAMA) based optimal data detection is proposed for large scale MIMO systems. Existing LAMA and sub-optimal detection techniques suffer from iteration complexity and performance loss in finite dimensional systems due to large scale user fading. To over come these, Gram matrix and message damping techniques are incorporated in the traditional LAMA. The effectiveness of the proposed enhanced LAMA and existing techniques are analyzed with 64, 32 and 16 user antennas, 256, 128, 64 and 16 base station elements with 64QAM, 16QAM, QPSK and BPSK. The simulation results show that the proposed enhanced LAMA gives superior performance when compared to existing matrix inversion methods such as Gauss sidle and Neumann, box techniques such as optimal co-ordinate descent and alternating direction method of multipliers based on the infinity norm, minimum mean square error and LAMA.

scholarly journals False Data Detection in Wireless Sensor Network with Secure communication

2011 ◽  
pp. 66-71
Author(s):  
Priyanka S. Fulare ◽  
Nikita Chavhan
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Data Aggregation ◽  
Wireless Sensor ◽  
Data Detection ◽  
Data Forwarding ◽  
Detection Techniques ◽  
False Data Detection

The security of wireless sensor networks is a challenging problem in the process of data aggregation. As data are send though sensor network confidentiality plays and important role between sink and destination. An efficient secure data aggregation is proposed to enhance the data security of wireless sensor networks. In wireless sensor networks, compromised sensor nodes can inject false data during both data aggregation and data forwarding. The existing false data detection techniques consider false data injections during data forwarding only and do not allow any change on the data by data aggregation. However, In this paper we can see how the data is being remain confidential between sink and destination by using Data authentication method for securing the data in wireless sensor network.

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