Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/412554
Title: Mimo channel modeling using a class of soft computational techniques
Researcher: Sarma, Kandarpa Kumar
Guide(s): A. Mitra
Keywords: Architecture
Arts and Humanities
Arts and Recreation
University: Indian Institute of Technology Guwahati
Completed Date: 2011
Abstract: The key challenge faced by up coming wireless communication systems is to provide high data rate wireless access at better quality of service QoS In such a situation Multiple Input Multiple Output MIMO wireless technology seems to be able to meet these demands by offering increased spectral efficiency A very common form of uncer tainty and stochastic behaviour is observed in MIMO wireless communication due to interference and correlation among channel coefficients which makes channel estimation a challenging area There are several statistical methods of channel estimation that have provided satisfactory performance while modeling the MIMO wireless systems Soft computational approaches are recent additions to the list of channel estimation methods of which most of the works have primarily focused on the training learning aspects of ANN fuzzy systems etc Till now no recorded efforts have been observed regarding expansion of the abilities of such architectures beyond the training testing realm which includes certain architectural challenges These challenges include i incorporating tem poral behaviour in the Multi Layer Perceptron MLP a feedforward ANN enabling it to track time variations in the input signal ii ensuring stability to the system by append ing a feedback path along with the usual feedforward structure of the ANN iii retaining only the contextual portion of the information with the above structure iv properly capturing the fast time varying nature of the channels v combining ANN and fuzzy based systems to obtain the capability of expert level decision making while modeling uncertainty observed in the MIMO channel and vi realization of a suitable system with lower implementation and time complexity Taking these challenges into consideration a class of soft computational tools based on ANN in feedforward layout called MLP and feedback form called Recurrent Neural Network RNN and fuzzy based composite sys tems are explored with stress on architectural expansion so as to improve performance and precision th newline
Pagination: Not Available
URI: http://hdl.handle.net/10603/412554
Appears in Departments:DEPARTMENT OF ELECTRONICS AND ELECTRICAL ENGINEERING

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