Authors: Md Abdul Latif Sarker Moon Ho Lee Jin Gyun Chung
Publish Date: 2015/04/19
Volume: 83, Issue: 4, Pages: 2899-2923
Abstract
This article presents the concept of future 5th generation 5G wireless communications as an existing beyond 4G systems like long term evolution LTE which means the indicate of 5G scenarios can be introduced in near future Therefore this paper deals of a future 5G mobile terminal for applications to uplink transmission in a multiuser LTE scheme Unfortunately LTEuplink inherently generates significant intersymbol interference especially high bandwidth scenarios The result is a rise to mutual interference among active users with an increased error rate This incidence eventually causes nonorthogonal user spreading codes Moreover this drawback is known as the multiple access interference episodes which demonstrate high computational complexity and enhances symbol error rate at the receiving end and degrades the communication quality Most of the related work has been claimed iterative linear minimum mean square error LMMSE detection requires a matrix inversion role which has a high computational complexity and contains a combinatorial optimization problem Consequently the LMMSE does not meet the requirement to implement realtime detection with low complexity and thus limiting its application Therefore we propose an acceptable bioinspired neural network NN in the case of single and multilayer NNs with supervised learning particularly Levenberg–Marquardt backpropagation learning algorithm to improve the convergence speed Simulation results performed with highest approaches highlights a better act for the proposed system
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